Financial Stability Review (FSR) -...

This Financial Stability Review (FSR) is presented as part of Bank Indonesia»s

mission ≈to achieve and maintain rupiah value stability through maintenance of monetary stability

and development of financial system stability for the achievement of sustainable long-term national

development∆.

Published:

Bank Indonesia

Jl. MH Thamrin No.2, Jakarta

Indonesia

Information and Order :

This FSR document is based on data and information as of September 2003, except when otherwise indicated.

This FSR document is also available in pdf format at Bank Indonesia»s web site at http://www.bi.go.id

Inquiries, comments, and recommendations may be addressed to :

Bank Indonesia

Directorate for Banking Research and Development

Financial System Stability Bureau

Jl. MH Thamrin No.2, Jakarta, Indonesia

Telephone : (+62-21) 381 7779, 7990

Fax : (+62-21) 2311672

Email : Tim SSK √ [email protected]

The FSR is published biannually with the following objectives:

• To foster public understanding of financial system stability, both domestically and

internationally;

• To analyze potential risks to financial system stability; and,

• To analyze developments and problems in the financial market and recommend policies to

boost and maintain a stable financial system.

fsrFinancial Stability Review

No. 2, December 2003

iii

FFFFForeword vii

EEEEExecutive Summary xi

CCCCChapter 1 Overview 3

CCCCChapter 2 Development of Domestic and Interna-

tional Economies 7

2.1. External Influences 7 7 7 7 7

2.2. Domestic Economic Conditions 9

Boks II.1 Will Property Become a Nightmare Again? 13

Boks II.2 Rocketing China : Threat or Opportunity? 15

CCCCChapter 3 Development of Banking Industry 19

3.1. Commercial Banks 19

3.1.1. Credit Risk 19

3.1.2. Liquidity Risk 31

3.1.3. Profitability 36

3.1.4. Capital 38

3.1.5. Market Risk 40

3.1.6. Operational Risk 42

3.2. Development of Sharia Banking 44

3.3. Development of Bank 45

3.4. Law Enforcement 46

Boks III.1 Indonesian Banking Architecture, Blue Print

and Strategic Directions in the Future? 20

Boks III.2 Rigidity of Loan Interest Rates 22

Boks III.3 Undisbursed Loans 24

Boks III.4 Capital»s Resilience To Credit Expansion 27

Boks III.5 Stress Test of NPLs Impact on Capital 29

Boks III.6 Provisions for Earning Assets Losses (PEAL) 29

Boks III.7 Implications of Implementation of The New

Guarantee Scheme 35

Boks III.8 Impact of IBRA»s Dissolution 43

TABLE OF CONTENTS

CCCCChapter 4 Non-bank Financial Institutions 58

4.1. The Insurance Industry 58

2.2. The Pension Funds Industry 64

Boks IV.1 Bancassurance - Advantageous

for All Parties? 59

Boks IV.2 Implementation of the Regulation on Fit &

Proper Tests in the Insurance Industry 63

CCCCChapter 5 Capital and Money Markets 69

5.1. Development of Indonesia»s Capital Market 69

5.2. Development of Indonesia»s Money Markets 75

Boks V.1 Mutual Fund 71

Boks V.2 Prospects for Issuance of Government

International Securities (SUN) (the Yankee Bond) 76

Boks V.3 Corporate Bond 78

Chapter 6 Payment System 81

Articles 85

I. Study on the Cost of Intermediation At Several

Large Banks in Indonesia:Are Commercial

Banks» Interest Rates on Credits Overpriced? 87

II. Early Indicators of Banking Crises 97

III. Company Failure Indicators in Indonesia : As An

Additional Early Warning Tool On Financial System

Stability 109

iv

List Charts and Tables

Tables

Chart I.1 Asset Composition of Financial

Institutions 3

Chart II.1 Developments of International Interest

Rates 7

Chart II.2 Developments of 5 Major Trading Partner

Countries» Economies 7

Chart II.3 Development of Inflation In 5 Major Trading

Partner Countries 8

Chart II.4 Foreign Investments and Portfolio Invest-

ments (Net) 8

Chart II.5 Developments of Composite

Stock Price Index and Rupiah Exchange

Rate 9

Chart II. 6 Inflation and Consumer Loan 10

Chart II.7 2002 Supply and Demand for Logs 11

Chart II. 8 Developments of Average Leverage and

ROE of Several Textile Companies 14

Chart III.1 Number of Banks and Total Assets 19

Chart III.2 Development of LDR 21

Chart III.3 Loan Growth by Bank Group 23

Table II.1 Indonesia»s Balance of Payments (Million of

USD) 9

Table II.2 Government Financial Statistics 10

Table II.3 Number of Workers in Indonesia»s Textiles

and Related Products Industry 12

Table III.1 NPLs by Bank Group 30

Table III.2 Loans Concentration on 25 Largest Debtors

(LD) 30

Table III.3 Development of Third Party Funds and NAV

32

Table III.4 Rural Bank Major Indicators 46

Table III.5 STR Reported to Police

Table V.1 Rating of Default Probability of Large

Corporate Bonds 75

Charts

Chart III.4 Outstanding Credit by Bank Group 23

Chart III.5 Growth of Credits & Funds 23

Chart III.6 Credit Growth by Debtor Group 23

Chart III.7 Credit Growth by Certain Economic

Sectors (%) 23

Chart III.8 Credit Development by Economic Sector 25

Chart III.9 Loan Development of Credit by Usage 25

Chart III.10 Loan Growth by Usage 25

Chart III.11 NPLs of Consumer Loans 25

Chart III.12 New Loans by Economic Sector 26

Chart III.13 2003 New Credits 26

Chart III.14 Development of Property Loan 26

Chart III.15 Growth (y to y) of Property Sector (%) 26

Chart III.16 Non Performing Loans 28

Chart III.17 Growth of Loans Classification 28

Chart III.18 Development of Outstanding NPLs 28

Chart III.19 2003 Ratio of NPLs to Capital 30

Chart III.20 Gross NPLs of Asian Countries 30

Chart III.21 Ratio of 25 Largest Debtors» to

Capital √ August 2003 31

Chart III.22 Banks» Funding Structure 32

Chart III.23 Structure of Third Party Funds 32

Chart III.24 Composition of Time Deposits by Tenor 33

Chart III.25 Ownership of Third Party Funds by Core

Depositors 33

Chart III.26 Third Party Funds Ownership at 15 Big Banks

33

Chart III.27 Composition of Time Deposits by Amount 34

Chart III.28 Liquid Asset Ratio 34

Chart III.29 Ratio of Funds Channelled Over to Funds

Sources 34

Chart III.30 Ratio of Liquid Assets to Short-Term Liabilities

at 15 Big Banks 36

Chart III.31 Non-Core Deposits to Liquid Assets 36

Chart III.32 Development of Net Interest Income 37

Chart III.33 Composition of Interest Income at 15 Big

Banks 37

Chart III.34 Composition of Interest Income 37

Chart III.35 Efficiency Ratio 38

Chart III.36 CER Comparison 38

Chart III.37 Development of ROA in 5 Asian Countries 38

Chart III.38 Risk-weighted Asset and ROA 39

v

Chart III.39 Development of Banks» Earning Assets 39

Chart III.40 Ratio Tier 1 To Total Assets 40

Chart III.41 CARs of Several Asian Countries 40

Chart III.42 Stress Test on Interest Rates 41

Chart III.43 Stress Test on Exchange Rates

at Bank ≈X∆ 41

Chart III.44 Total Assets 44

Chart III.45 Capital 44

Chart III.46 Deposits 44

Chart III.47 Financing 44

Chart III.48 Non Performing Loans 45

Chart III.49 ROA & ROE 45

Chart III.50 Development of Banking Cases Received by

UKIP (in number of banks) 47

Chart III.51 Development of Banking Cases, Where

Investigations Have been Stopped (in

number of banks) 47

Chart III.52 Development of Banking Cases Transferred

to Law Enforcement Body (in number of

banks) 47

Chart III.53 Completion of Banking Cases (cumulative)

47

Chart III.54 Types of Banking Violation Cases Followed-

Up During 2003 (by number of cases) 48

Grafik III.55 STR reported to Police by Numbers of

Reports 49

Chart IV.1 Developments of Shares, Bonds, Mutual

Funds 57

Chart IV. 2 Asset Composition of Financial Institutions

58

Chart IV. 3 Total Non-Bank Financial Institutions 2000 √

June 2003 58

Chart IV. 4 ROA Value - Life and General Insurance

Companies 61

Chart IV. 5 ROE - Life and General Insurance Compa-

nies 61

Chart IV. 6 ROI Value √ Life and General Insurance

Companies 61

Chart IV. 7 Investment Composition of Insurance

Industry √ 2002 61

Chart IV. 8 Investment Composition of Insurance

Industry √ Quarter II/2003 61

Chart IV. 9 ROA & ROI Values - Pension Funds 65

Chart V.1 A Shift in The Role of Bank Loans Versus

Capitalization of Stock and Bond Markets

69

Chart V.2 Ratings of Indonesia and Other Developing

Countries 70

Chart V.3 Composite Stock Price Index and Volatility72

Chart V. 4 Trend of Jakarta Financial Index (JFI) 73

Chart V. 5 Price Earning Ratio»s of Listed Bank 73

Chart V.6 Yield Curve of Indonesia Goverment Bond

73

Chart V.7 Maturity Profile of Goverment Bond 74

Chart V.8 Market Liquidity of Corporate Bond 74

Chart V.9 Development of SBI, Deposit, Interbank

Money Market Interest Rates 75

Chart V.10 Development of Interbank Money Market

Interest Rates and Transaction Volumes 77

Chart VI.1 Clearing Transaction 81

Chart VI.2 Unsetled RTGS Transaction 82

Chart VI.3 Average Clearing Cycle 83

vii

This financial system stability review provides a picture of the current state of financial system stability in

Indonesia and its outlook as of end-2003.

As of the end of 2003, the condition of our financial system was stable with quite encouraging developments.

It is expected that this will continue in 2004. However, there are still several problems that need close attention to

prevent them from becoming constraints in the future.

Important developments during 2003 included rising international confidence as indicated by an upgrade in

Indonesia»s debt rating as well as high foreign investors» interest in the sales of corporate shares and bonds. These

were possible largely due to rupiah exchange rate stability, lower interest rates and inflation, as well as improving

banking conditions. However, in the same year, the banking sector was strained for a time by several cases of

fraud, which caused considerable losses for the banks concerned. This shows how implementation of good

corporate governance needs to be stepped up by all parties, particularly those involved in financial systems

management.

There were several other problems originating internally to the financial system, such as continuing high

NPLs of banks, slow recovery of bank intermediation, and rigidity of interest rates on credits. Problems from the

external side of the financial system, such as slow real sector recovery more competitive global markets, have also

put pressure on our financial system development.

The downward trend in interest rates has prompted the public to shift some funds to the capital market,

which has boosted the composite stock price index and the bond index in the capital market, up 63% and 66%,

respectively from the previous year. Such growth has also boosted the mutual funds industry, which is up 56%

from the year before. These are, of course, encouraging developments. However, there is a need to emphasize

that rapid capital market expansion also has the potential to create new problems if it is not followed by improvements

in infrastructure, such as better accounting systems, regulations and market discipline on market players.

This Financial Stability Review is the second issue written in two languages (the first was in June 2003). It

disseminates educational information to the public, who are key stakeholders in financial system stability. Although

this document is issued biannually, monitoring of financial system stability is conducted routinely by Bank Indonesia,

and results are contained in weekly internal reports.

Foreword

viii

Bank Indonesia»s determined efforts in building and maintaining stability of the financial system cannot be

done properly without the support of related parties and institutions. For this, we express our appreciation and

thanks to all contributors and participants in the hope that this document will assist the general public and related

supervisory institutions in building a sense of joint concern and responsibility.

In closing, we welcome any suggestions, comments, and even critiques to enhance the the quality of this

review in the future.

Jakarta, January 2004Jakarta, January 2004Jakarta, January 2004Jakarta, January 2004Jakarta, January 2004

Maman H.SomantriMaman H.SomantriMaman H.SomantriMaman H.SomantriMaman H.Somantri

Deputy Governor

ix

Executive Summary

ExecutiveSummary

x

Executive Summary

xi

Executive Summary

In general, stability was maintained in the banking and

financial systems during 2003, as indicated by continuous

improvements in several banking and financial system

performance indicators. This condition was supported by

macroeconomic stability and relatively conducive

monetary conditions during the year, as indicated, for

example, by economic growth that reached its target and

by improved macroeconomic indicators that strengthened

domestic and international public confidence in the

Indonesian economy.

However, banks» dependence on income from

recapitalization bonds, continuing weak governance, and

limited risk management, could pose a threat to the

banking industry and financial system in the future. Also,

the real sector has not fully recovered and several business

sectors are susceptible to tough competition from other

countries. Both have the potential to cause banks» NPLs

to rise. Meanwhile, short-term foreign capital inflows are

on the rise; these tend to be volatile and could have a

negative impact on financial system stability and the overall

economy.

1. MACROECONOMIC STABILITY

Stable macroeconomic conditions that tended to

improve during 2003 have supported financial system

stability. The balance of payments, rupiah exchange rate,

and inflation rate all performed better than expected at

the beginning of the year, while economic growth achieved

the figure originally projected.

Improved economic indicators were greatly assisted

by consistent implementation of monetary and fiscal

policies. Relatively loose monetary policy during 2003

provided room for the real sector to recover without

reducing the purchasing power of the public. Meanwhile,

the implementation of a conservative and cautious fiscal

policy has helped to strengthen confidence in

macroeconomic stability which leaded to hold down

inflation, which in turn helped with the maintenance of

financial system stability.

On the external side, declining international interest

rates helped provide room for domestic interest rates to

fall without undermining the exchange rate. These

conditions contributed to strengthening economic players»

confidence, and no damaging shocks occurred. In the

future, if fiscal policy remains conservative and is adjusted

to the needs of economic growth, it would further benefit

financial system stability.

Nevertheless, economic and non-economic

fundamental conditions are worrisome. Economic growth

of around 4.55% during 2003 was within the range of

original projections, but it was not able to make any

progress on Indonesia»s unemployment problem. Open

unemployment is estimated at 10.1 million people or 9.8%

of the whole work force in 2003. Also, the growth to date

has not been able to lift per capita income back to its pre-

crisis level. In addition, the major factor behind economic

growth during 2003 was consumption growth of 5.1%.

In the long-term, high unemployment and economic

growth dependent upon consumption pose risks for the

economy.

Investment expanded by 1.6%. However, this

expansion was more for construction than machinery, and

consequently it did not have any meaningful impact on

production capacity. Manufacturing grew by only 2.4%,

Executive Summary

xii

Executive Summary

down from 4% in the previous year. However, this did not

push up prices due to smooth flows of imported goods

that suppressed inflation. On the downside, this could pose

difficulty for banks and other financial institutions in

determining interest rates on credits to be channeled to

the real sector. In the long-term, businesses that are not

able to compete with imported products have the potential

to go bankrupt, which could cause economic instability, if

it were to happen on a large scale.

For its part, the balance of payment»s structure was

less encouraging. Non-oil/gas exports were dependent

upon demand from several countries (mainly the US, Japan,

and Singapore), but remained dominated by five main

commodities (textiles, wood products, electrical appliances,

and footwear), which have many international competitors

(except for paper products). Nonetheless, repayment

capacity of exporting companies generally seemed not to

have been disrupted because free trade regulations have

not yet been fully enacted. On capital account, inflows

were dominated by short-term portfolio investment, which

is susceptible to reversals. Foreign direct investment, which

is more stable, was on the decline.

A policy of low interest rates, which was successfully

implemented during 2003, is expected to be continued

cautiously. The large gap in maturity profiles between

banking assets and liabilities would raise banking instability

if interest rates were changed suddenly and with violent

fluctuations. But, because exchange rate stability could

be maintained, exchange rate risk was relatively low, which

added to stability in the financial industry in 2003.

2. FINANCIAL SYSTEM STABILITY

Macroeconomic stability supported banking and

financial stability in 2003. The banking industry»s stability

was reflected in several performance indicators, which

continued to improve during the year, despite several

potential problems concerning banking credit, assets and

capital. Meanwhile, Indonesia»s capital markets experienced

extraordinary development during 2003, with the stock

market»s performance ranking as the second best in the

world. The bond market also recorded rapid growth with

a tendency towards oversubscription at each new issuance.

For its part, the money market did not fluctuate in any

way that could have endangered financial stability, while

conditions at non-bank financial institutions were also

relatively stable. This was further supported by policy on

the non-cash payment system that has successfully reduced

systemic risk and increased the efficiency of payment

transactions. Nonetheless, in order to maintain financial

system stability, there are several matters that warrant close

attention such as bank intermediation that has not fully

recovered; weak corporate governance that leads to large

operational risk in the banking industry; the possibility of

rising NPLs; and a reduction in the coverage of the blanket

guarantee program.

2.1. Banking Industry

In general, stability of the banking industry during

2003 was bolstered by banks» control of credit risk. At the

same time, market risk was quite moderate, being

supported by adequate banking capital, a stable exchange

rate, lower interest rates, and a relatively small net foreign

currency position of banks (which, for example, averaged

4.70% of banking capital in quarter III-2003). During 2003,

banks still experienced excess liquidity, which was mostly

placed in SBIs and the interbank money market. The large

size of interbank borrowings could have a systemic risk.

However, no banks experienced a liquidity crisis during

2003. Nevertheless, the large size of maturity mismatches

at several recapitalization banks could have created

instability if interest rates were to fluctuate excessively.

Operational risk remained high as evidenced by various

cases of fraud at several banks due to weak

implementation of good corporate governance.

xiii

Executive Summary

The banking industry»s stability was further bolstered

by growing public confidence in the Indonesian banking

sector as indicated by confidence index surveys.

Improved banking conditions were generally reflected

in a rising rate of return on assets (ROA) during 2003,

from 1.9% (Dec«02) to 2.3% (y-t-d, Oct»03). This mainly

stemmed from banks» success in preventing a drop in their

net interest margins (NIM) in the face of declining interest

rates. During 2003, banks» NIM narrowed only modestly,

from 4.2% (Dec»02) to 3.8% (y-t-d, Oct»03). Also, banks»

CAR remained above the 20% level, which turned out to

be more than adequate to absorb business risks, particularly

credit risk, during 2003.

Rural Banks also did well during 2003, with asset

growth of 38.8%, reaching Rp10.4 trillion (June 2003).

Another indicator of improved performance was a rise in

the percentage of Rural Banks categorized as «sound» from

61.9% (June 2002) to 63.9% (June 2003). Sharia banks

had a similar experience, with strong growth in assets

(60%), third party funds (60%), and financing (50%) with

Capital Adequacy Ratio (CAR) reached 17%. In addition,

the quality of earning assets in the sharia banking industry

were in a sound condition as indicated by the level of non-

current financing, which was below 5%. In general, the

sharia banking industry also had a good level of earnings,

although in 2003 it did record a sizable drop due to large

expansion, which incurred sizable infrastructure costs.

However, several matters that arose during 2003

warrant close review, particularly concerning bank loan

and capital. As regards development of bank loan, growth

in outstanding loan and new loan extensions during 2003

were down from the year before. Also, there was a rise in

undisbursed banking loans to Rp25.6 trillion (Jan - Oct

»03), up from the previous year»s Rp19.1 trillion (Jan-Oct

«02). The slowdown in credit channeling was partly related

to on-going rigidity in interest rates on credit, which did

serve to protect banks» profitability. Excess liquidity and

limited lending have prompted banks to depend on SBIs

and bonds for interest income. Unfortunately, this does

not boost economic growth, which in the long run could

disrupt financial stability.

During 2003, credit channeling continued to be

dominated by consumer credit. In line with the downward

trend of interest rates, consumer credit channeling was

on a rising trend (33.8%, y-o-y), far larger than the rises

of working capital and investment credits of 16.9% and

7.4%, respectively. This rapid expansion of consumer

credits risks higher NPLs, if economic growth were to

decline.

Meanwhile, outstanding property credit reached

Rp43.9 trillion (Oct »03) or 10.3% of total banking credits,

up Rp35.0 trillion from its position at December 2002.

This rapid increase is also susceptible to rising NPLs if

unemployment were to rise due to layoffs.

The aggregate CAR during 2003 ranged between

20% - 26%, with 17 (out of 138 banks) having CARs

between 8% √ 10%; of these, one was a large bank. Six

banks had CARs at between 10% √ 15%. This figure was

quite susceptible to changes in the quality of earning assets

and in the method of calculation to includes risk

components in addition to credit risk.

2.2. Non-Bank Financial Institutions

The downward trend in interest rates prompted

several insurance and pension funds industries to shift their

fund placements from deposits to capital market products

in order to minimize income declines.

During 2003, the insurance industry experienced

some restructuring to enable it to face rising competition,

fulfillment of minimum risk-based capital, and new

regulations, such as fit and proper tests. Still, lower interest

rates impacted directly on the earnings of funds managed

by the insurance and pension funds industries. To tackle

this, these industries started to shift their earning assets

xiv

Executive Summary

structures from placements in banking products (deposits)

to capital market products (shares, bonds, and mutual

funds). However, this shift has not prevented a decline in

returns (ROA, ROI, and ROE). This was due to high

operational costs resulting from competition on premiums

and commissions as well as still inefficient business

activities.

2.3. Capital and Money Markets

Rapid growth of the stock market has the potential

to cause an overpriced situation. This could spur instability

in the future if it is not followed by implementation of

good governance, among others in the form of adequate

transparency. The extraordinary development that occurred

in Indonesia»s stock market during 2003 resulted in this

market having the second best record in the world after

Thailand. Several developments that boosted the capital

market»s performance were the downward trend in global

interest rates, improvements in several macroeconomic

indicators, and stable political and security conditions.

Despite a sell-off for a time in the wake of the bomb

incident at the JW Marriot Hotel, positive developments

(such as continued declines in SBI rates and improvements

in the quality of issuers) soon prompted a recovery. The

composite stock price index was at a low of 379.351 on

11 March 2003, but recovered very well, closing the year

at 691.90, the highest level in 2003. This rise of 82% was

only exceeded by Thailand»s bourse, which soared by

115.6% (Jan-Dec 2003). The stock market in 2003 also

benefited from the successful initial public offerings of

three large state-owned companies (Bank Mandiri, BRI,

and Perusahaan Gas Negara), which received an

enthusiastic response from domestic and foreign investors.

Meanwhile, the bond market also experienced rapid

growth with a trend toward oversubscription with each

issuance. Investor interest was also apparent in secondary

market trading for both corporate and government bonds.

One of the factors encouraging bond issuance was

continuing high credit rates at banks and the rising demand

for mutual funds with bonds as assets. Rapid development

of the bond market was further indicated by bond

issuances, which reached Rp24.7 trillion in 2003 out of

total bonds traded at the Surabaya Stock Exchange of

Rp46.2 trillion (November 2003). The 2003 issuance was

the largest in the history of Indonesia»s capital market. In

the secondary market, bond trading during 2003 was

active with prices increasing to an average of 99.4% of

nominal values (November 2003), compared to 95.31%

at the beginning of 2003). These developments warrants

close attention because if the bond issuers use these funds

for high-risk business activities, it would heighten credit

risk, including risk of systemic default.

Rapid expansion in the mutual funds marketƒ

without implementation of adequate accounting

standardsƒrisk a loss of customer confidence. Mutual

funds» NAV rose by 482.4% to Rp46.6 trillion in 2002

followed by a further rise of 70% to Rp79.2 trillion during

2003 (Jan-Oct). One of the reasons for the rise in mutual

funds» NAV was vigorous tradings of corporate and

government bonds in the secondary market. Most mutual

funds (85.2% in October 2003) were of the fixed-income

type with bonds as their major asset. This rapid growth

ended in October 2003, when there were large-scale

redemptions due to rumors of a change (to marked-to-

market) in the method for calculating mutual funds» NAV.

Consequently, there was a drop in mutual funds» NAV from

Rp85.9 trillion (September 2003) to Rp79.2 trillion (October

2003) because investors withdrew their funds.

During 2003 in the interbank money market, interest

rates trended downward in line with declines in SBI interest

rates. Interest rates in the morning and afternoon money

market sessions dropped from 12.3% and 9.6% (January

2003) to 8.3% and 5.8% (December 2003), respectively.

This was related to overliquid banking conditions, because

xv

Executive Summary

funds could not be quickly channeled to credits.

Nonetheless, lower interest rates in the money market did

not boost bank intermediation.

Turning to the payment system, credit and settlement

risk have eased considerably with implementation of the

real time gross settlement (BI-RTGS) system, whose

coverage now reaches over all of Indonesia. But despite a

major shift in transactions to the BI-RTGS system, the older

clearing system still has an important role in executing

payment transactions.

3. 2004 OUTLOOK

Macroeconomic and financial system stability are

expected to be maintained in 2004. With a stable rupiah

exchange rate, low inflation, and a downward trend of

interest rates, economic growth is projected to rise, although

it would still not be able to absorb all additions to the work

force. The main factor boosting growth is expected to be

domestic demand, particularly consumption. Global

economic conditions are forecast to improve in 2004, and

this would give a boost to the financial system, particularly

as regards credit extensions. However, several constraints

would remain due to difficulties in improving economic and

non-economic fundamentals, which in turn would cause

risk to remain high.

Based on developments in 2003 and economic

prospects for 2004, commercial banks» are expected to

remain stable in 2004. However, several conditions warrant

close review due to their potential for hampering

improvement of NPLs and banking performance, which

could disrupt banking stability.

Banking credits are projected to expand in line with

improving economic performance. In particular, improved

prospects for international commodity prices (especially

primary non-oil/gas commodities) and manufacturing due

to rising demand in export markets would have a positive

impact on the domestic business climate, which would

raise demand for bank credits. However, there would be

several factors that could pose problems on the supply

side, including: (i) weak implementation of risk

management by banks remaining high risk perceptions

from the banking system towards credit; and (ii) high credit

interest rates due to declining interest income from SBIs

and bonds, as well as banks» inefficient business operations.

Meanwhile, on the demand side, demand for credits would

be limited by more attractive alternative funding sources

outside banking credits such as the issuance of bonds and

shares.

Banks» NPLs are estimated to remain below the

indicative target of 5% because banks are expected to

provision against (gross) NPLs through adequate Provisions

for Earning Assets Losses (PEAL). Another factor would be

banks» very conservative behavior in extending credits due

to perceptions of high risk. Consequently, NPLs (gross)

would tend to rise in 2004. Several conditions would

prompt this rise, such as ex-IBRA and restructured credits.

Furthermore, structural problems such as legal uncertainty

related to regulations and their enforcement would pose

constraints on banks» attempts to improve their NPLs.

The composition of banks» income is estimated to

continue improving during 2004 in line with rising credit

volume and credit»s share in banks» earning assets.

However, this rise would not significantly boost banks»

profitability due to several remaining problems, such as (i)

relatively large components of banks» income whose

sustainablity is doubtful, i.e. non-interest income, which

mostly comes from fluctuanting trading activities as well

as write backs provisioning coming from credit

restructuring and sales of NPLs; and (ii) rising costs due to

deterioration in the quality of banks» credits that require

more provisioning (PEAL).

On the capital side, banks» overall CAR is estimated

to remain well above 8%. However, there could be

pressures due to several factors, namely: (i) a rise in Risk

xvi

Executive Summary

Weighted Assets due to higher credits, (ii) difficulty in

building up capital from profits because several banks tend

to distribute dividends despite low profitability, and (iii) a

potential rise in NPLs (gross).

However, on the bank liquidity side, growth of third

party funds is expected to come under pressure, due to

factors such as: (i) a downward trend in interest rates; (ii)

a decline in the guarantee interest rate, which limits banks»

flexibility in setting interest rates on deposits; as well as

(iii) competition from mutual funds and corporate bonds,

which offer more attractive returns for fund owners.

Based on current growth trends, the sharia banking

industry is estimated to reach asset values of Rp12 - 13

trillion by end-2004 compared to Rp7 trillion at present.

As such, the percentage of sharia banking operations could

exceed 1% of the national banking industry»s total

business. Even higher asset growth is possible because of

plans by one conventional bank to change to a sharia bank

and by several conventional banks to open sharia units.

However, if expansion continues this rapidly, challenges

sharia banking will face increasing challenges, particularly

on the sides of risk management and capital.

Continuing previous years» developments, the Rural

Bank industry is also expected to expand rapidly. This will

be assisted in part by its captive market comprising

customers from communities in urban suburbs and villages

that are not served by commercial banks. However, several

constraints could hamper growth, among others: (i) a

relatively low quality of Rural Bank human resources; (ii)

insufficient numbers of Rural Bank supervisors; and (iii)

relatively inefficient business activities as indicated by

extremely high credit rates charged by Rural Banks.

As was the case in 2003, the insurance and pension

funds industries would continue to face problems with

funds management due to a continuing downward trend

in interest rates. Tough competition in the insurance

industry will force insurance companies to enhance their

efficiency and capital in preparation for merger or

acquisition. Meanwhile, the pension funds industry, which

been extremely conservative to date in its investment

strategy (as indicated by a large share of bank deposits),

will need to implement adequate risk management in

support of its desire for higher-yielding, long-term

placements.

Many analysts expect that the capital market will not

grow as rapidly in 2004 as it did in 2003. Investors that

have aggressively placed funds during 2003 are pulling

back somewhat, adopting a wait- and-see attitude.

Similarly, several businesses that have used the opportunity

to raise funds in the capital market during 2003 will wait

for indications that the market will accept new issuances

of their debt at better prices. However, if the national

general election agenda proceeds smoothly, investors √

domestic and international√ might rush to invest in

Indonesia.

Meanwhile, the money market is not expected to

experience any meaningful change in line with continued

trends towards lower interest rates and excess liquidity.

Concerning implementation of the payment system,

it is necessary to step up monitoring and supervision of

the system in accordance with international standards

(Core Principles for Systemically Important Payment

Systems √ CP-SIPS set the BIS). In addition, it is necessary

to make efforts to further develop that system in terms of

capacity and to mitigate operational risk.

4. POLICY DIRECTIONS FOR THE FUTURE

In line with continued accommodative monetary

policy and closer coordination between monetary and fiscal

policy, rehabilitation and enhancement of the banking

system»s resilience needs to be continued. Within the

framework of this policy, and along with rising risks facing

the banks, there is need for banks to implement better

risk management and for the establishment of a credit

xvii

Executive Summary

bureau. Meanwhile, in order to safeguard stability,

elimination of the blanket deposit guarantee needs to be

undertaken gradually and cautiously. In this regard, the

implementation of prudential banking principles in

accordance with international standards need to be

continued.

Implementation of good risk management by banks

is vital. Risk management that is incorporated into bank»s

operations will support the creation of good governance

and minimize criminal banking practices. This ranges from

making misrepresentation to the public, through window

dressing of balance sheets and incorrect reporting, up to

fraud, such as has occurred recently. If these problems are

not seriously addressed by the supervisory authority and

other players in the banking industry, such cases will recur.

This will further undermine public confidence, which has

still not recovered fully.

One of the ways to implement good risk

management is by banks knowing their customers well.

This can be achieved by information sharing between banks

through a credit bureau, which is one effective way to

prevent fraud. Several recent cases of fraud were

undertaken by the same people and companies with the

same modus operandi.

The government plan to phase out the deposit

guarantee program could have a wide impact on the

banking industry. If thorough preparations and calculations

are not made at an early stage, this could result in public

funds shifting from one bank to another (a flight-to-quality)

or to outside the banking industry, particularly on the part

of depositors.

In order to minimize this risk, reduction of the

guarantee needs to be done gradually. In addition,

reduction of the guarantee program needs to executed in

parallel with elements of the financial safety net, especially

the lender of last resort (LOLR) facility from Bank Indonesia.

LOLR can function as a contingency plan in anticipating

the negative impact of a decline of public confidence in

the banking industry while the guarantee program is being

narrowed.

As was the case in 2003, Bank Indonesia plans to

enhance several regulations during 2004, particularly those

related to prudential principles. The plan is to issue

regulations concerning several matters, including the

quality of earning assets, provisions for earning assets

losses, credit restructuring, and a limit on credit extensions.

In addition, BI will issue new guidelines for bank soundness

(CAMELS), which is planned to be effective in December

2004. This is intended more as a supervisory tool for BI

and for determination of action plans in the framework of

problem identification and problem resolution of certain

aspects of banks» operations. Meanwhile, in order for

implementation of the guidelines to function well, a trial

run will be undertaken on the June 2004 position for all

banks. In line with enhancement of the regulation on

bank»s soundness level, BI plans to enhance regulations

concerning banks» business plans.

As regards the end of the tenure of the Indonesian

Banking Restructuring Agency»s (IBRA) in February 2004,

BI plans to adjust BI regulation number 3/25/PBI/2001

dated 26 December 2001 concerning «Determination of

Bank»s Status and Transfer to IBRA».

xviii

Executive Summary

1

Overview

Chapter 1:Overview

2

Overview

3

Overview

With the financial industry»s ownership, organization,

operations, and products becoming more integrated,

instability in one type of institution can have an impact on

other financial institutions, with increasing systemic risk.

Within the financial industry, banking is still very important

in determining financial system stability, as it accounts for

some 91% of total assets of the financial system. However,

this does not mean that other types of financial institutions

can be ignored in the maintenance of financial system

stability. Recently, non-bank product innovation and non-

bank financial institutions have developed rapidly, in line

with heightening competition and customers» increasing

understanding of financial products.

In general, macroeconomic conditions were stable

and tended to improve during 2003, which has raised

public and investor confidence in Indonesia»s economy.

These conditions made a positive contribution to financial

system stability. Improvements of economic development

indicators were largely supported by consistent

implementation of monetary and fiscal policies. However,

economic growth that is largely dependent upon

consumption is quite susceptible to rising banks» NPLs, if

economic activity were to deteriorate.

On the external side, the downward trend in

international interest rates has helped in lowering domestic

interest rates without weakening the exchange rate. This

stability is expected to continue in 2004. However, rising

competition and protectionism by certain countries could

disrupt export performance. In the long-term, domestic

businesses that are not able to compete with imported

products will likely go bankrupt, which could generate

economic instability.

Macroeconomic stability in 2003 was bolstered by

the maintenance of banking and financial system stability.

Despite several potential problems, the banking industry»s

stability continued to improve during 2003, as evidenced

by several performance indicators. In addition, credit,

liquidity, and market risks were relatively controlled, while

implementation of operational risk needs to be closely

watched.

Meanwhile, Indonesia»s capital market experienced

relatively rapid development during 2003. Indeed, the stock

market»s performance was the second best in the world.

The bond market also experienced rapid growth with a

trend towards oversubscription with each new issuance.

The money market also did not show any fluctuations,

which could endanger financial stability, since banking

tended to be overliquid.

The downward trend in interest rates has forced the

insurance and pension funds industries to shift the

composition of their investment portfolios from deposits

to capital market products in order to minimize loss of

revenues. Nevertheless, performance of these two

industries did deteriorate in 2003.

The generally stable condition of the financial system

was assisted by the policy on the non-cash payment

Chapter 1:Overview

Chart I.1Asset Composition of Financial Institutions

Banking91%

Pension Fund3%

InsuranceCorporation

3%

LeasingCompany

2%

SecuritiesCompany

1%

Pawn Shop0%

4

Overview

system, which has been successful in reducing systemic

risk and enhancing the efficiency of payment

transactions.

Looking ahead to 2004, in line with economic

growth and conducive macroeconomic conditions, the

capital market»s performance is expected to continue on

a strengthening trend. However, many parties see the

potential for a decline in market activity. This would be

due to market players adopting a wait-and-see attitude

because of the socio-political agenda for that year,

although this would not entail any meaningful fluctuations.

If the general election proceeds smoothly, investors, both

domestic and international, are expected to rush to invest

their funds in Indonesia. For their part, money market

conditions are not expected to experience any meaningful

change.

5

Chapter 2 Development of Domestic and International Economies

Chapter 2Development of Domesticand International Economies

6

Chapter 2 Development of Domestic and International Economies Development Of Domestic

7


Generally speaking, macroeconomic conditions during

2003 were stable and trended to improve, as indicated

by several improved macroeconomic indicators. This

situation had a positive impact on public and investors»

confidence in the Indonesian economy, which was

already on the mend. An improving national economy

was largely supported by consistent implementation of

monetary and fiscal policies. However, economic

growth, which is still largely dependent on consumption,

is susceptible to many potential shocks. The immediate

impact on the financial system, particularly the banking

sector, would be higher NPLs and a lower quality of

earning assets. On the external side, the downward

trend in global interest rates has helped to reduce

domestic interest rates without a negative impact on

the exchange rate (Chart II.1), and it is expected that

this stability will be maintained in 2004. However, rising

competition and the imposition of limits on imports by

certain countries could disrupt performance of the

domestic business sector, partly because Indonesia»s

products are uncompetitive in world markets.

2.1 External Influences

World economic growth has not fully recovered due

to several large countries» economies that remain sluggish.

(Chart II.2). This was marked by continuing low GDP

growth in the US, Japan, and Singapore, which were

Indonesia»s major trading partners in 2003. Development

of the world economy in semester I/2003 tended to

weaken due to the Iraqi war involving the US, which is a

superpower with major economic influence. In addition,

the outbreak of severe acute respiratory syndrome (SARS)

in several Asian countries and Canada weakened the global

economy. In this regard, in April 2003, the IMF

downgraded its projection on global economic

performance by 0.5% (from its September 2002 projection)

to 3.2%. Still, this figure is slightly higher than 2002 real

growth of 3%.

In order to stimulate domestic economies and to

revive capital markets, several countries have lowered

interests rates (Chart II.2). On 3 June 2003, the European

Central Bank lowered its refinancing interest rate by 0.5%

to an historical low of 2%. On 25 June 2003, the US

Chapter 2Development of Domestic and International Economies

Chart II.1Developments of International Interest Rates

Chart II.2 Developments of 5 MajorTrading Partner Countries» Economies

Percentage

0

1

2

3

4

5

6

7

19981997 1999 2000 2001 2002 Q.1/03 Q.2/03 Q.3/03 Q.4/03

LIBOR (1 Month) SIBOR (1 Month) Fed Funds Rate

Percentage

USA Japan

Singapore China South Korea-8

-6

-4

-2

0

2

4

6

8

10

12

1997 1998 1999 2000 2001 2002 Q.1/03 Q.2/03

8


Federal Reserve lowered the Fed Funds rate by 0.25% to

1%, its lowest since 1958. The Bank of England reduced

its cut-base rate by 0.25% to 3.75%, its lowest since 1955.

Low world inflation, particularly in several advanced

countries, and rupiah appreciation have helped to lower

Indonesia»s inflation rate (Chart II.3). During 2003, the non-

oil/gas commodity price index rose sharply in international

markets, from 2.6 as of December 2002 to 12.8 as of

December 2003 . This rise in non-oil/gas commodity prices,

which is partly a result of the USD depreciation, and a rise

in world oil prices have boosted Indonesia»s exports by an

estimated 4.4% in 2003, despite limited recovery in the

economies of Indonesia»s trading partner countries. Higher

exports would increase exporters» incomes, which would

improve the quality of earning assets in the financial system.

The downtrend in international interest rates during

2003 along with growing worries over the enormous US

current account deficit have spurred investors to shift their

capital to developing countries in Asia and Latin America,

which offered more attractive yields. This was supported

by improving Asian countries» ratings. For example,

Indonesia»s rating was upgraded one level by international

rating institutions (Moody»s, Standard & Poor, Fitch) to the

equivalent of BB with stable prospects (Moody»s). In Asia,

foreign investment mostly came into countries with

economies that were considered to be stronger, such as

China, Vietnam and Thailand. In Indonesia, the investment

climate remains troublesome, causing foreign capital

inflows to be dominated by portfolio investment (Chart

II.4), such as purchases of shares and bonds. During 2003,

inflows of portfolio investment totaled USD1.4 billion, up

from the previous year (USD1.2 billion). Although these

short-term capital inflows are supportive of the

development of Indonesia»s capital market, they have the

potential to put pressure on the financial system due to

their short-term nature and therefore, potential quick

reversals. Also, these short-term capital inflows do little

to help with the real sector»s recovery.

Improving macroeconomic indicators and the

government»s plan to remain conservative as regards fiscal

policy in 2004 are the main factors promoting financial

system stability. Supported by a stable rupiah exchange

rate, low inflation, and a downward trend in interest rates,

domestic demand, particularly consumption, is boosting

economic growth.

In addition, global economic conditions are expected

to improve in 2004, triggered by rising economic growth

in several advanced countries and within the Asian region.

The IMF has forecast (November 2003) that world

economic growth in 2004 would reach 4.3%. This growth

Chart II.3 Development of Inflationin 5 Major Trading Partner Countries

Chart II.4Foreign Investments and Portfolio Investments (Net)

Percentage

1998 1999 2000 2001 2002 Q.1/03 Q.2/03 Q.3/03-2

-1

0

1

2

3

4

5

South Korea China SingaporeJapanUSA

(Million of USD)

-9,000

-8,000

-7,000

-6,000

-5,000

-4,000

-3,000

-2,000

-1,000

0

1,000

2,000

FDI (net) Portfolio Investment (net) Others (net) Total

2001 2002 2003

9


would largely stem from advanced countries, such as the

US, Japan, and those in the European region of 4.3%,

1.5% and 2.2%, respectively, higher than the previous

projection (September 2003) of 3.9%, 1.4% and 1.9%.

This situation has the potential to lift export growth

appreciably. If this opportunity is seized by Indonesian

exporters, it will make a sizable contribution to the

maintenance of financial sector stability.

2.2 Domestic Economic Conditions

During 2003, domestic macroeconomic conditions

tended to improve and this has contributed significantly

to financial system stability.

The balance of payments, particularly the current

account, strengthened in 2003 as evidenced by a rise in

foreign currency revenues from exports, which were up

from USD59,165 million in 2002 to USD62,891 million

in 2003 (Table II.1). Capital flows also bolstered the

financial system. This was marked by rising inflows of

portfolio investment, which boosted the composite stock

price index to the level of 691.90 at end of 2003, up

266.955 points compared to end of 2002 (Chart II.5).

The rise in capital flows also triggered vigorous bond

trading, as indicated by increased trading frequency

during 2003, from 308 units in 2002 to 1,023 units in

2003 (source: CCIC).

The rupiah exchange rate was quite stable in 2003,

with a strengthening trend from Rp8,940 at end- 2002 to

Rp8,420 at the end of 2003. This was due to Indonesia»s

Improved balance of payments, declining domestic interest

rates and the USD depreciation against several world

currencies. This strengthening trend of the rupiah had

mixed benefits. On one side, it could reduce business

players» foreign currency risk exposure, but it could also

reduce exports, if not complemented by improved exporter

competitiveness. Lower exports have the potential to

reduce exporters» repayment capacity, which could impact

on the quality of bank credit.

The inflation rate dropped from 10.0% during 2002

to 5.06% during 2003 (Chart II.6). The downward trend

in inflation along with lower interest rates on credits, have

boosted consumer credit, from Rp79.99 trillion as of end-

2002 to Rp101.60 trillion as of October 2003. This rise

needs to be watched closely, due its potential for putting

pressure on the quality of bank credit, if a decline in

economic growth were to occur.

In the future, improved international developments

and relatively easy domestic monetary policy are expected

Table II.1Indonesia»s Balance of Payments (Million of USD)

Curren AccountCurren AccountCurren AccountCurren AccountCurren Account 7,8227,8227,8227,8227,822 7,8007,8007,8007,8007,800 5,020 5,020 5,020 5,020 5,020

Export 59,165 62,891 62,630

Import -35,653 -39,509 -40,945

Services -15,690 -15,582 -16,665

Capital AccountCapital AccountCapital AccountCapital AccountCapital Account -1,102-1,102-1,102-1,102-1,102 -2,554-2,554-2,554-2,554-2,554 -6,413-6,413-6,413-6,413-6,413

Goverment (Net) -190 -779 -1,641

Private (Net) -913 -1,774 -4,772

TotalTotalTotalTotalTotal 6,7206,7206,7206,7206,720 5,2465,2465,2465,2465,246 -1,393-1,393-1,393-1,393-1,393

Monetary MovementMonetary MovementMonetary MovementMonetary MovementMonetary Movement -4,021-4,021-4,021-4,021-4,021 -4,209-4,209-4,209-4,209-4,209 2,3282,3282,3282,3282,328

Memorandum ItemsMemorandum ItemsMemorandum ItemsMemorandum ItemsMemorandum Items

International ReserveInternational ReserveInternational ReserveInternational ReserveInternational Reserve 32,03732,03732,03732,03732,037 36,24636,24636,24636,24636,246 33,91833,91833,91833,91833,918

(Import month &(Import month &(Import month &(Import month &(Import month &

Govt» Foreign Debt) Govt» Foreign Debt) Govt» Foreign Debt) Govt» Foreign Debt) Govt» Foreign Debt) 6.66.66.66.66.6 7.1 7.1 7.1 7.1 7.1 6.1 6.1 6.1 6.1 6.1

ComponentComponentComponentComponentComponent 2004**2004**2004**2004**2004**2003*2003*2003*2003*2003*20022002200220022002

* Realization Estimate** EstimateSource : Bank Indonesia

Chart II. 5 Developments of CompositeStock Price Index and Rupiah Exchange Rate

JCI USD/IDR

Source : JCI, Bank Indonesia

Rupiah Exchange Rate (Rigth axis)

JCI(Left axis )

1996 19981997 1999 2001 2002 20032000

0

2000

4000

6000

8000

10000

12000

14000

16000

0

100

200

300

400

500

600

700

800Index IDR/USD

Jan May Sep Jan May Sep Jan May SepJan May Sep Jan May SepJan May Sep Jan May Sep Jan May Sep

10


development. In particular, manufacturing grew by only

2.4%, down from 4% the year before. Nonetheless, this

did not disrupt the smooth flow of goods supply due to

imported goods, which dampened price increases.

However, in the long-term, business sectors whose

products cannot compete with imported products will have

difficulty surviving, which could create economic stagnation

or instability.

Meanwhile, implementation of a conservative and

cautious fiscal policy helped to lower inflation, which

greatly assisted with the maintenance of financial system

stability. In light of large payments of principal and interest

on the national debt, and to safeguard fiscal sustainability,

the government targeted its fiscal deficit within the

framework of accelerating the economic recovery. The

fiscal deficit in 2003 edged up compared to last year, from

1.7% of GDP in 2002 to 1.9% in 2003 (Table II.2). To

achieve a fiscal deficit 1.9% of GDP, the government took

a series of conducive policies, such as postponement of

Chart II. 6Inflation and Consumer Loan

to bolster the recovery of business activity in Indonesia»s

real sector. However, this needs to be followed by

conducive investment climate such as improved

infrastructure, secure security conditions, and elimination

of unofficial charges.

The modest rise in investment activity (1.6%) in 2003

had no meaningful impact on the economy»s production

capacity, because it was concentrated in property

Trillions of Rp Percentage

Inflation rate (Rigth axis) Consumer loan (Left axis)

Sources : Bank Indonesia, BPS

0

20

40

60

80

100

120

-10

0

10

20

30

40

50

60

70

80

90

1998 1999 2000 2001 2002 2003Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct Jan Apr Jul Oct

1. Government Revenues and Grants1. Government Revenues and Grants1. Government Revenues and Grants1. Government Revenues and Grants1. Government Revenues and Grants 301,874301,874301,874301,874301,874 300,188300,188300,188300,188300,188 336,156336,156336,156336,156336,156 17,317,317,317,317,3 342,812342,812342,812342,812342,812 137,204137,204137,204137,204137,204 343,876343,876343,876343,876343,876 17.217.217.217.217.2a. Domestic Revenues 301,874 299,887 336,156 17,3 342,472 136,964 343,242 17.1

- Tax Revenues 219,628 210,954 254,140 13,1 248,470 108,807 271,023 13.5 - Non Tax Revenues 82,247 88,933 82,016 4,2 94,001 28,157 72,219 3.6

b. Grants 0 301 0 340 240 634 0.0

2. Government Expenditures2. Government Expenditures2. Government Expenditures2. Government Expenditures2. Government Expenditures 344,009344,009344,009344,009344,009 327,865327,865327,865327,865327,865 370,592370,592370,592370,592370,592 19,119,119,119,119,1 377,248377,248377,248377,248377,248 139,703139,703139,703139,703139,703 368,800368,800368,800368,800368,800 18.418.418.418.418.4a. Central Government Expenditures 246,040 229,343 253,714 13,1 257,934 85,203 253,943 12.7

- Current Expenditure 193,741 189,072 188,584 9,7 191,788 70,993 185,842 9.3 - Development Expenditure 52,299 40,271 65,130 3,4 66,146 14,210 68,101 3.4

b. Regional Government Expenditures 97,969 98,522 116,878 6,0 119,314 54,499 114,856 5.7 - Balanced Budget 94,532 94,763 107,491 5,5 109,927 49,966 108,243 5.4- Special Autonomy 3,437 3,759 9,387 0,5 9,387 4,533 6,613 0.3

3. Surplus/Deficit ( 1 - 2 )3. Surplus/Deficit ( 1 - 2 )3. Surplus/Deficit ( 1 - 2 )3. Surplus/Deficit ( 1 - 2 )3. Surplus/Deficit ( 1 - 2 ) -42,135-42,135-42,135-42,135-42,135 -27,677-27,677-27,677-27,677-27,677 -34,436-34,436-34,436-34,436-34,436 (1,9)(1,9)(1,9)(1,9)(1,9) -34,436-34,436-34,436-34,436-34,436 -2,498-2,498-2,498-2,498-2,498 -24,923-24,923-24,923-24,923-24,923 (1.2)(1.2)(1.2)(1.2)(1.2)

4. Financing4. Financing4. Financing4. Financing4. Financing 42,13542,13542,13542,13542,135 27,67727,67727,67727,67727,677 34,43634,43634,43634,43634,436 1,91,91,91,91,9 34,43634,43634,43634,43634,436 -2,498-2,498-2,498-2,498-2,498 24,92324,92324,92324,92324,923 1.21.21.21.21.2a. Domestic Financing 23,501 20,562 22,450 1,2 31,530 2,229 39,844 2.0b. Foreign Financing 18,634 7,115 11,986 0,7 2,906 -4,727 -14,921 (0.7)

Budget 1)Budget 1)Budget 1)Budget 1)Budget 1) Actual 2)Actual 2)Actual 2)Actual 2)Actual 2)

20022002200220022002

%%%%%

of GDPof GDPof GDPof GDPof GDP

Budget-R 4)Budget-R 4)Budget-R 4)Budget-R 4)Budget-R 4)Budget 3)Budget 3)Budget 3)Budget 3)Budget 3) Actual 2)Actual 2)Actual 2)Actual 2)Actual 2)

Semester ISemester ISemester ISemester ISemester I

Budget 3)Budget 3)Budget 3)Budget 3)Budget 3) %%%%%

of GDPof GDPof GDPof GDPof GDP

Notes:1) Parliament approved budget. October 2001

Basic Assumptions : GDP growth = 3.5%, Inflation rate = 9.3%, exchange rate = Rp.9,600/US$, 3 month-SBI rate = 15%, oil price = US$24/barel2) Preliminary figure3) Budget approved by parliament

Basic Assumptions : GDP growth = 4%, Inflation rate = 9%, exchange rate = Rp.9,000/US$, 3 month-SBI rate = 13%, oil price = US$22/barel4) 2003 revised budget approved by parliament, 24 September 2003

Basic Assumptions : GDP growth = 4%, Inflation rate = 6%, exchange rate = Rp.8,000/US$, 3 month-SBI rate = 10.1%, oil price = US$27.9/barelSource: Ministry of Finance

20022002200220022002 20032003200320032003 20032003200320032003

(Billion Rp)

Table II.2Government Financial Statistics

11


fuel price hike increasing excise taxes. Looking ahead, it

will be very important to closely watch for pressures on

the state finances originating in the refinancing of domestic

indebtedness because maturing bonds will total Rp36.3

trillion in 2004. Also, repayments of foreign debt and

interest will rise by around 50% compared with 2003,

because the Paris Club rescheduling facility is no longer

available after the end of the IMF program. Financing of

the 2004 state budget deficit will rely upon domestic

sources, whereas heavy servicing of the foreign debt could

reduce Indonesia»s official foreign exchange reserves.

2.3 Development of the Real Sector

During 2003, the real sector did not recover much

despite various efforts, including a policy to reduce interest

rates. Indeed, there was a worrisome trend of business

relocations to other countries. This could boost the

unemployment rate and increase banks» NPLs, particularly

for consumer credits.

Several recent cases illustrate how investors will pull

back in the face of legal uncertainty. For example, the

divestment of Kaltim Prima Coal (KPC) and the Cemex

investment in Semen Gresik. In the KPC case, the

divestment of that mining company from the old foreign

investor (Rio Tinto and British Petroleum) to the domestic

investor was prolonged. This was caused by court decisions

as well as regional and central governments» reactions to

the ownership change, which was believed to conflict with

the original agreement.

Such cases cause investors to reconsider placing their

capital in Indonesia. During 2003, the amount of long-

term foreign investment √which is very important to

boosting economic recovery√ actually declined (as

mentioned, capital inflows were dominated by short-term

portfolio investment). This is one of the reasons why real

sector growth was limited, and unable to absorb additions

to the work force. Indeed, many workers were laid off as

companies cut back operations, closed, or relocated to

other countries. For example, at PT Dirgantara Indonesia

and Texmaco. In 2003, the unemployment rate rose to

9.8% of the overall work force. Such high unemployment

could disrupt economic stability, including in the financial

sector. Settlement of cases like those mentioned above

will be difficult without enhanced legal instruments.

Equally serious, it will be difficult to prevent similar cases

from occurring in the future. However, it will necessary to

continue making efforts in this direction in order to improve

Indonesia»s investment climate, as it continues to

deteriorate in investors» eyes.

Meanwhile, several business sectors experienced

disappointing growth and have uncertain prospects. These

sectors need to be closely monitored in order not to create

problems in the financial sector in the future. These sectors

include wood and wood products, property, textiles and

textile related industry.

Wood and forestry products are one of Indonesia»s

major exports. During 2003, a number of companies in

this industry experienced operational disruptions and many

closed down. The main reason for closure was limited raw

materials due to license tightening by the Ministry of

Forestry and increased illegal logging, much of which is

smuggled out of the country (Chart II.7). Also, many

charges imposed by governments (central and regional)

Chart II. 72002 Supply and Demand for Logs

2 0 0 2

Supply Demand Gap

Source: Ministry of Forestry

Thousands of mm3

0

20,000

40,000

60,000

80,000

100,000

12


Table II.3 Number of Workers in Indonesia»sTextiles and Related Products Industry

Fibers 24.415 25.524 26.076 26.762 29.324 29.682

Yarns 170.275 175.337 186.450 189.785 193.361 207.871

Fabrics 317.191 329.377 337.971 341.400 349.392 355.566

Garments 329.440 346.167 348.419 355.236 372.716 376.584

Others 241.486 243.884 244.525 246.710 247.372 249.622

TotalTotalTotalTotalTotal 1.082.8071.082.8071.082.8071.082.8071.082.807 1.120.2891.120.2891.120.2891.120.2891.120.289 1.143.4411.143.4411.143.4411.143.4411.143.441 1.159.8931.159.8931.159.8931.159.8931.159.893 1.192.1651.192.1651.192.1651.192.1651.192.165 1.219.3251.219.3251.219.3251.219.3251.219.325

ComodityComodityComodityComodityComodity 2000200020002000200019971997199719971997

Source: Asosiasi Pertekstilan Indonesia (API)

19961996199619961996 2001200120012001200119981998199819981998 19991999199919991999

1 Source : Ministry of Industry and Trade.2 People that do not have jobs and are looking for jobs.

burden the wood industry. In the banking sector, credit

exposure to the wood and forestry industry is currently far

less than in the pre-crisis period, because large amounts

of banking credits to this industry were transferred to IBRA

during the crisis. Nonetheless, the condition of the wood

and forestry industry still has an influence on financial

stability, because credit exposure is still quite large and

many companies in the forestry and related industry have

issued shares and bonds in domestic and foreign markets.

One example is the Asia Pulp & Paper (APP) group, which

issued bonds amounting to USD12 billion. These have been

categorized as «default», and APP has been undertaking a

long restructuring process with its creditors.

Prospects for industries that use raw materials from

forestry are deteriorating. For 2004, it is estimated that 1

million workers will be laid off because of wood companies»

shutdowns, which would add to the large number of

unemployment in this country. International pressure on

Indonesia concerning compliance with proper

environmental rules (such as comprehensive logging plans,

including regreening) will raise operational costs of

domestic wood manufacturing, which will make them less

competitive in international markets. Therefore, it is

important for banks and financial institutions to prudently

and thoroughly calculate credit risk when channeling funds

to this industry.

Meanwhile, the property industry has experienced

very rapid growth, with the potential to generate an

oversupply, particularly in the commercial property sector

(Box II.1 : Will Property Become a Nightmare Again?).

In the textile area, China»s exports of textiles and

related products are very competitive due to conducive

economic policies, which include a low value of the Yuan

pegged to the USD; textile industry restructuring that has

reduced production costs; low interest rates on credits

(5%); and cheap labor due to an excess supply of workers

(Box II.2 : Rocketing China : Threat or Opportunity?). By

contrast, Indonesia»s production costs are high due to,

among others, high loading and unloading costs at ports;

illegal charges; high interest rates on credits; and a rising

cost of labor that has not been offset by improved

productivity. These developments represent a significant

challenge for the textiles industry (Table II.3).

Competition from China, (including products that are

either imported legally or smuggled) threaten to shutdown

some 3,250 small-to-medium scale businesses in the textile

and related products industry.1 In the future, with the plan

to end textile quotas by the US, European Union, and

Canada in 2005 as part of WTO agreements, Indonesian

exporters of textiles (which have been indirectly protected

to date by the quotas) will be in direct competition with

low-cost competitors such as China and Vietnam.

Based on the outlook for business in several of the

sectors mentioned above, it is necessary to review the

potential for rising unemployment due to layoffs and the

impact on banking credit, particularly consumer credits to

workers in these sectors.

Data of the Central Statistics Agency (BPS) indicate

that 4.13 million people were (openly)2 unemployed in

1996. By 2003, this number had more than doubled to

10.13 million people. The chairman of the Indonesian

Businessmen Association predicts mass layoffs in the

forestry and textile sectors in 2004, each involving around

13


Chart Box 2.1.1Development of Property Loan in Total Credits

Chart Box 2.1.2Development of Property Sector»s Contribution

to GDP

BoX II. 1 Will Property Become a Nightmare Again?

During 2003, the property business grew by

78%. This is an exceptionally high figure, especially

considering that after the 1997 crisis, the property

sector seemed to stall for several years. Such high

growth needs to be closely watched because

experience indicates that the property sector is risky

for the financial system.

In developing countries, the property sector plays

an important role, particularly in developing state

infrastructure. During the pre-crisis period, the

property sector in Indonesia contributed 7 √ 8% of

GDP, boosted by both government and private sector

spending. However, after the crisis, its contribution

dropped to 5 √ 6%.

Revival of the property sector since 2000 and its

rapid growth during 2003 are positive developments,

considering that property is a very cyclical business.

An interesting new development in the property area

is a shift in the financing structure, from mostly bank

loans to developers» equity and consumers» down

payment and installment payments. Banking credit

for the property sector in total has dropped, and now

is dominated by housing-ownership credits (KPR) and

apartment-ownership credits (KPA).

High NPLs in the property sector when the crisis

struck has made banks more cautious in channeling

credit to the property sector. Meanwhile, latest

developments show that leverage of the property

sector has tended to rise. This is indicated by the high

proportion of property industry financing coming from

outside the companies, particularly from individuals

or non-bank institutions. However, borrowing more

funds from non-bank sources does not mean that risk

is significantly less for the financial system, because

these funds are still suspected to end up in the financial

sector. Bit it does show that there is quite large

potential for banking funds to be channeled to the

property industry. On the other hand, this potential

could be a risk for financial stability should an over-

supply or a price bubble develop in this sector.

Symptoms of oversupply are already apparent in

several office buildings, on which construction is

complete but the space looks empty and there is

intense competition for tenants. The same is the case

in industrial areas where several tenants might relocate

to other countries, following indications that the

business climate has not improved to the standard

2001 2002 20030

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

8.5

9

9.5

10

10.5

11

11.5

12

Total Loan Share of Property Loan to Total Loan

Poly. (Share of Property Loan to Total Loan)

GDP Share of Property Sector to GDP

0

1

2

3

4

5

6

7

8

9

10

1996 1997 1998 1999 2000 2001 2002 20030

20,000

40,000

60,000

80,000

100,000

120,000

14


Chart Box 2.1.3Developments of Average Leverage and ROE at

Several Property Companies

Chart Box 2.1.4Average Supply and Occupancy Levels in Office

Buildings in Jakarta and Surrounding Areas

being set by competitor countries. If oversupply in the

property sector continues to rise next year, a price

bubble could develop, which could eventually trigger

a rise in NPLs such as occurred during the 1997 crisis.

Leverage (DER)-% ROE (%)

leverage ROE

Source : SIC

-8000

-7000

-6000

-5000

-4000

-3000

-2000

-1000

0

1000

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002-10

0

10

20

30

40

50

60M 2 Percentage

Supply (semi gross) Occupancy Level (%)

2,400,000

2,450,000

2,500,000

2,550,000

2,600,000

2,650,000

2,700,000

2,750,000

2,800,000

2,850,000

71

72

73

74

75

76

77

78

79

80

81

82

99 00 2001 2002 2003

1 million workers. With the addition of 2.5 million new

members to the work force every year, unemployment will

almost certainly rise in 2004, possibly to 3 times its pre-

crisis level.

The high level of open unemployment and its upward

trend constitute one of Indonesia»s critical social problems,

which could ultimately undermine stability of the financial

system. When part of the upward trend of unemployment

rate comes from layoffs, it can be a signal of declines in

borrowers» repayment capacity, which would eventually

worsen the quality of banks» consumer credit. This point

is particularly notable because banks have been increasing

the share of consumer credits in their lending portfolios.

Those increased share of consumer credits were triggerd

by banks continuing perceptions of high credit risk,

especially towards industries marked by relatively high

average Debt-Equity Ratios and relatively low Rate of

Return on Equity (Chart II.8).

The unemployment problem is not easily solved.

One important effort is government cooperation with the

Malaysian government through a Memo of

Understanding concerning recruitment of Indonesian

workers to Malaysia. Also, the government is expected

to be able to continuously increase work opportunities

through capital investments by investors and labor-

intensive projects to anticipate short-term needs for the

2004 general election activities. In addition, tight

monitoring needs to be undertaken of the rise in

unemployment and its impact on the banking sector.

Also, banks should be urged to include unemployment

in their calculation of credit channeling targets in their

business plans.

Chart II. 8Developments of Average

Leverage and ROE of Several Textile Companies

Leverage (DER) (%) ROE (%)

leverage ROE

Source: Jakarta Composite Index (processed)

0

100

200

300

400

500

600

-350

-300

-250

-200

-150

-100

-50

0

50

1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

15


Box II. 2

Chart Box 2.2.1Indonesia»s Non-Oil/Gas Exports to China &Indonesia»s Non-Oil/Gas Imports from China

During 2003, the world economy began to

improve as reflected in the GDP growth of Indonesia»s

5 major trading partner countries. This recovery is

expected to have a positive impact on Indonesia,

particularly exports. The prices of non-oil/gas

commodities in international markets rose sharply

during 2003. This was due to, among others, a slow

recovery in production; producers» attempts to improve

prices after their sharp plunge in the period 1998 √

2001; and the USD depreciation. However, the growth

of world trade volume fell a bit compared to 2002 due

to the Iraqi war, the outbreak of SARS, and rising

protectionism in several advanced countries.

However, improved international trade is

accompanied by tougher competition. Competing

countries that previously were not taken into

consideration, have now improved their

competitiveness. China is a particular case in point;

this country experienced a high growth (on average at

around 8%) since the 1997 when many Asia countries

were hot hard by crisis. That country»s expanding

exports have contributed so much to official foreign

currency reserves that they reached USD346.5 billion

at end of quarter II/2003, up USD60.1 billion compared

to end of 2002.

Rapid expansion of China»s economy √with

increasing export competitiveness√ has become a worry

for advanced countries and other competing countries.

The trade account deficits of advanced countries with

China are getting wider. The US, which has been

continuously experiencing a widening trade account

deficit with China, has threatened to increase tariffs

on products imported from China. In addition, believing

Rocketing China : Threat or Opportunity ?

that the Renminbi is undervalued, the US continues

to urge China to revalue its currency, which has been

pegged within a narrow range at RMB8.2774 per

USD1 since 1994.

Rising competitiveness of China»s products poses

a threat to other exporting countries, particularly in

the Asian region including Indonesia. China may

takeover export markets that were previously

dominated by other countries.

For Indonesia, the worst-case impact on

producers would be closing down their business. This

could trigger a rise in unemployment and undermine

businessmen»s ability to fulfill their financial obligations

to creditors and investors, which could upset financial

system stability. In addition, the poor investment

climate in Indonesia has diverted foreign investors to

China, thus hampering real sector recovery.

However, China is also an enormous potential

market. In addition to its amazing economic growth,

China accounts for more than 15% of world

population, far exceeding for instance, the European

Union (335 million). This potentially makes China a

1998 1999 2000 2001 2002 Jan-Aug '03

Export Import (Export-Import)

thousands of USD

0

500

1,000

1,500

2,000

2,500

3,000

3,500

16


major new trading partner for Indonesia. Just when

the US and Japan economies are sluggish, China could

rescue Indonesia»s exporters. However, this requires

improvement in Indonesia»s competitiveness, in terms

of quality and price. In this regard, the government of

Indonesia must be able to build the economic and

legal infrastructure that will invigorate Indonesia»s

exports and attract foreign investors.

17

Chapter 3 Development of The Banking Industry

Chapter 3Development ofThe Banking Industry

18


19


Stability of the banking industry during 2003 was

maintained largely due to the firm risks control faced by

banks during the year. Credit risk was under control, while

such problems that did occur had no significant impact

on financial system stability. Meanwhile, market risk was

quite moderate due to adequate capital, banks» relatively

small net foreign currency position, as well as stability of

the rupiah exchange rate and interest rates. The banking

industry still experienced excess liquidity, which was

primarily invested in SBIs and the interbank money market,

resulted in optimum interest income. At the same time,

maturity mismatches at several recapitalization banks could

have created instability, if interest rates had fluctuated

excessively. In addition, operational risk was still considered

relatively high, due to quite weak implementation of risk

management and good governance within the banks,

which caused several incidents of fraud. In view of previous

year developments and the economic prospects for 2004,

banks» condition is expected to remain stable.

Nevertheless, several conditions warrant close review due

to their potential for hampering NPLs improvement.

Likewise, relatively high operational risk could disrupt

banking industry stability that is currently improving

through, among others, the Indonesian Banking

Architecture program √ IBA (Box III.1 : Indonesian Banking

Architecture, Blue Print and Strategic Directions in the

Future).

Since the crisis of 1997/98, the number of banks

has declined drastically. However, total assets of the

banking industry have expanded due to mergers between

several banks and the entry of one new foreign bank.

Within the Indonesian financial system, the banking

Chapter 3Development of The Banking Industry

Chart III.1 Number of Banks and Total Assets

industry still dominates, with total assets amounting to

91% of the financial system»s total assets.

As of October 2003, the number of banks stood at

139 with total assets of Rp1,126.1 trillion. Of these banks,

15 banks accounted for 75.0% of total bank assets. Of

these total assets, 91.5% comprised earning assets that

were extremely sensitive to risks, particularly credit risk,

market risk, and liquidity risk. As the Indonesian banking

industry has not yet moved to universal banking, the largest

risk was still credit risk. The share of credits in earning

assets reached 41.5%; the shares of marketable securities,

placements in SBIs, placements in other banks, and

participations were 35.2%, 12.7%, 10.0%, and 0.6%,

respectively. Some 91.1% (Rp362.5 trillion) of total

marketable securities comprised recapitalization bonds.

3.1. COMMERCIAL BANKS

3.1.1. Credit Risk

In general, credit risk remained under control. Several

problems arose, but none had any meaningful impact on

banking system stability. However, credit risk is expected

Trillions

0

50

100

150

200

250

300Unit

0

200

400

600

800

1000

1200

1995 1996 1997 1998 1999 2000 2001 2002 Oct-03

Total Asset (left axis) Number of Bank (right axis)

20


Box III. 1

The Indonesian Banking Architecture (IBA), which

Bank Indonesia started to develop two years ago, is

finally completed. The development process has

involved large resources and has taken into account

inputs and recommendations from various

stakeholders. On 9 January 2004, the BI Governor

announced that implementation will begin in 2004.

Indonesian Banking Architecture, Blue Print and StrategicDirections in the Future

The IBA is a blue print for future national banking

with six pillars that constitute important elements

related to banks» operational activities. These six pillars

are formulated into recommendations that can be

grouped into 19 initiatives or work programs that are

to be achieved.

The IBA itself has a clear vision as regards the

banking industry»s direction and structure within the

next ten to fifteen years. The national banking

structure in the long-term is expected to comprise

from 2 to 3 international-quality banks (international

champions), which have the capacity and ability to

operate regionally as well as internationally. In

addition, it is expected that within the next 10 √ 15

years there will be around 3 to 5 national banks

(national champions), which will have business

coverage all over Indonesia. Furthermore, in the long-

run it is also expected that there will be around 30-50

The completion of IBA opens a new page in the

history of Indonesian banking. The IBA itself constitutes

policy directions as well as policy recommendations for

the national banking industry and is a follow-up to the

bank restructuring program that started in 1998. The

IBA has one very fundamental goal, which is to create

sound, strong, and efficient national banking industry

in support of financial system stability within the

framework of promoting national economic growth.

The IBA enables Indonesia to have a banking

industry that is strong in the short- and long-term, so

that the industry will be able to prevent or to absorb

internal and external shocks, such as the 1997/98

monetary crisis.

Healthybankingstructure

Effective andindependentsupervisory

system

Adequateinfrastructure

Effectiveregulatory

system

Strongbankingindustry

Robustcustomerprotection

Sound, strong, and efficient banking systemto create financial system stability for

promotion of national economic growth

Pillar 2 Pillar 3 Pillar 4 Pillar 5 Pillar 6Pillar 1

Capital(Trillions Rp)

Rural Banks

InternationalBank

National Bank

Regional Corporate Retail Others

Bank withlimited scope of

activities

50

10

0.1

Banks with focuses on:

21


banks that are focused players. They would have

narrow business activities, such as retail, corporate,

or banks that are focused on fixed business segments

(such as agriculture banks, banks for hajj pilgrimage,

to remain high in 2004 due to pressures on banks from

both internal and external sources.

On one hand, the Indonesian banking industry

seemed to be overly prudent in extending loans as reflected

in extremely slow loan growth and wide interest spreads.

In addition, alternative fund placements that were safer

and more profitable (such as SBIs) reduced banks»

motivation in loan extension. On the other hand, the real

sector»s demand for bank financing seemed subdued with

high undisbursed loans (90% in 25 banks) and declining

extensions of new loans. In addition, alternative funding

sources (bond and share issuance) have proven popular

with large corporations, which are mainly potential debtors

of banks.

On the external side, the economies of Indonesia»s

major trading partners (such as the US and Japan) have

been sluggish, and only early signs of recovery appeared

during much of 2003. However, it will take time for the

recovery to have much influence on demand for goods

exported from Indonesia. Moreover, if the available

opportunities are not well utilized, low competitiveness of

Indonesian producers will cause their business to

deteriorate, which in turn will weaken demand for

investment and working capital loans for exports.

Development of Bank Loan

Loan expansion was largely boosted by an increase

in consumer loans and performance by the national private

commercial banks and the Regional Government banks

(RGB).

During 2003, bank credits1 rose by Rp53.4

trillion, from Rp410.3 trillion (at the end of 2002) to

Rp463.7 trillion (October 2003). During this period,

new loans amounted to Rp53.6 trillion. Compared to

funds accumulation, banks» loan to deposit ratio

(LDR) was only 42.4%, far below its pre-crisis position

that averaged 75% (Chart III.2). However, growth in

loans was higher than in third-party funds, due in

large part to declining SBI and deposit rates (Box III.2

: Interest Rate Rigidity). These lower rates prompted

fund owners to shift their money from deposits to

other, more profitable investments such as mutual

funds. Meanwhile, on the loans side, growth was

quite slow as reflected in declining new loan

extensions and rising undisbursed loans (Box III.3 :

Undisbursed Loans).

Growth of loans during 2003 was largely bolstered

by performance of the national private commercial banks

1 Including channelling.

Chart III.2Development of LDR

Trillion Rp

Loan (left axis)

Deposits (left axis)LDR (right axis)

1996 1997 1998 1999 2000 2001 2002 2003

Percentage

0

100,000

200,000

300,000

400,000

500,000

600,000

700,000

800,000

900,000

1,000,000

0

10

20

30

40

50

60

70

80

90

100

or regional banks). In addition to commercial banks,

described above, the national banking industry of the

future will be complemented by BPRs and banks with

limited business activities.

22


Box III. 2

Chart Box 3.2.1Interest Rates of Guarantees, SBIs & Deposits

Chart Box 3.2.2Loan Interest Rates (Average)

Rigidity of Loan Interest Rates

Interest rates on SBIs and the guarantee ceiling

have fallen sharply in recent quarters. By November

2003, they were down to 8.38% (3 months) and

7.28% (3-month deposits), respectively, and they have

continued to fall. The banks followed this development

with adjustments to interest rates paid on third party

funds for all tenors. As of October, the average interest

rates on savings, 1-month deposit, and 3-month

deposit stood at 5.71%, 7.47% and 7.96%,

respectively.

By contrast, banks have been slow to lower their

loan interest rates as shown by the accompanying

graph. Interest rates on working capital, investment,

and consumer loans were on average quite high at

15.77%, 16.27% and 19.0%. Quite significant

declines only occurred for certain consumer loans such

as KPM (motor-vehicle loans) and KPR (housing loans).

For example, interest rates on KPR and KPM at certain

banks were lowered to around 13% and 6.5% (for

the first year).

Credit interest rate rigidity was caused by several

factors:

a. Banks» perceptions that loan risk remained high.

This was related to various constraints faced by

banks in improving their loan quality, particularly

in lowering their NPLs.

b. Banks, particularly recapitalization banks, have

profit targets (RoE) set in their recapitalization

agreements with the government. Declines in their

incomes from SBI and recapitalization bonds put

pressure on banks to maintain high loan rates in

order to maintain their incomes.

c. The operational efficiency of Indonesian banks,

particularly recapitalization banks, was still

relatively low. In addition, these banks were still

in recovery and thus did not want to significantly

accelerate loan rate declines.

d. Demand for loans, particularly from the corporate

sector, was low as reflected, among others, in

quite large unused loan facilities (undisbursed

loans) and limited growth of investment and

working capital loans.

Therefore, there is a need for stimulus coming

from real sector policies, so that declines in loan rates

can bolster a rise in demand for loans.

2001 2002 2003

Percentage

0

2

4

6

8

10

12

14

16

18

20

Interest Rate on Guarantee (3 Month)

BI Certificates (3 Month)

Deposit (3 Month)

Percentage

2001 2002 2003

Working Capital Loan

Investment Loan

Consumer Loan0

2

4

6

8

10

12

14

16

18

20

22

23


1997 1998 1999 2000 2001 2002 Jan Feb Mar Apr May Jun Jul Aug Sep Oct

Percentage

Individual Private Corporate-80

-60

-40

-20

0

20

40

60

2003

Percentage

Deposits Loan

1997 1998 1999 2000 2001 2002 Jun Jul Aug Sep Oct

-80

-60

-40

-20

0

20

40

60

80

2003

State Bank Private National BankForeign & Joint Venture Regional Gov’t Bank

0

50,000

100,000

150,000

200,000

250,000

300,000

1996 20011997 1998 1999 2000 2002 2003

2 0 0 3

Percentage

State Owned Bank Private BankForeign & Joint Venture Regional Gov’t Bank

-80

-60

-40

-20

0

20

40

60

80

100


and the RGB (Chart III.3). By sector, the main sources of

growth were consumer loans, particularly KPR (housing

loan) and KPM (motor-vehicle loan), with the largest

demand coming from individual borrowers.

Another factor that contributed to slow growth in

bank credits was the business strategy of foreign and joint

venture banks that did not focus their expansion on credit

channeling.

By economic sector, there was potential for further

deterioration in credits to the industrial sector, brought

on by worsening conditions in the textile and wood-

processing industries. Nearly half of banks» NPLs originate

in these sectors.

During 2003, there was no significant change in the

distribution of credit by economic sector. As of October

2003, banks» credits were still dominated by industry

(28.9%), other (24.1%), trade (19.5%) and business

services (9.8%). The business services and other sectors

experienced quite significant growth recently, resulting

from quite high growth in consumer credits (Chart III.8).

Meanwhile, the main «engines of economic growth»,

Chart III.3Loan Growth by Bank Group

Chart III.4Outstanding Credit by Bank Group

Chart III.5Growth of Credits & Funds

Chart III.6Credit Growth by Debtor Group

Industry Trading Services Others

1997 1998 1999 2000 2001 2002 Jan

2003

Feb Mar Apr May Jun Jul Aug Sep Oct-80

-60

-40

-20

0

20

40

60

80

100Percentage

Chart III. 7Credit Growth by Certain Economic Sectors (%)

24


Box III. 3

Chart Box III.3.1New Loan Growth and Undisbursed Loans

Chart Box III.3.2Undisbursed Loans √ By Usage

Chart Box III.3.3Banks» Outstanding Credits, Undisbursed Loans &

New Loans (Trillion)

Banks» outstanding credits continued to rise, and

so did undisbursed loans. By percentage, undisbursed

loans increased even faster than outstanding credits.

During 2003 (January √ October), undisbursed

loans rose by 28.6%, while credits increased by only

13.6%. Total undisbursed loans reached 47.8% of

2003 total new credits. Total undisbursed loans for

2003 reached Rp25.6 trillion compared to Rp19.1

trillion (Jan-Oct 2002). By usage, working capital credit

was the largest (73.9%).

The largest undisbursed loans were owned by

the national private commercial bank group (38.8%),

followed by the state banks (26.8%) and the foreign

banks (26.7%). For information, 90.25% of total

undisbursed loans belonged to 25 banks. Meanwhile,

by economic sector, the largest undisbursed loans were

for industry and trade. The large size of undisbursed

loans for the industrial sector showed that the economy

has not developed in a robust manner, especially

considering that industry is the main engine for

economic growth and absorbs the largest number of

workers.

Debtors» main reason for not utilizing more of

the available credit is that business or economic

conditions are not conducive. Other factors are high

credit rates (see Box : Rigidity of Credit Interest Rates);

issues of continuous declines of interest rates; and

cheaper alternative sources of funds (e.g. issuance of

corporate bonds).

Undisbursed Loans

4.9% 2.9%

2.9%23.5% 0.4%

3.1%

10.4% 34.8%

16.4%

0.7%

Agriculture MiningElectricity Construction Trading

Transportation Services Social Services Others

Industry

Working Capital Loan

Investment Loan Consumer Loan

73.9%

9.6%

16.4%

Trillion Rp

New Loan Loan

-8

-6

-4

-2

0

2

4

6

8

10

12

2 0 0 2 2 0 0 3Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct

25


Trillion Rp

Investment

Working Capital

Consumer

1996 20031997 1998 1999 2000 2001 20020

50,000

100,000

150,000

200,000

250,000

300,000

350,000

400,000

450,000

1996 1997 1998 1999 2000 2001 2002 2003

Trillion Rp

Industry

Trading

Services

Others

-

50.0

100.0

150.0

200.0

250.0

namely industry and agriculture, recorded the smallest

expansions in credit.

Credit risk in the industrial sector was the highest

with 10.5% of its credits being NPLs (total NPLs were only

7.8% of total assets). NPLs in this sector constituted 44.8%

of the banking industry»s total NPLs. In the future, this

figure could rise and become the trigger for systemic risk,

particularly with potentially deteriorating conditions in the

textile and wood & forestry industries.

On the side of uses of credit, the rapid expansion of

consumer credit has the potential to raise banks» NPLs in

the future should the economy deteriorate. Meanwhile,

although working capital NPLs were quite small, its share

in banks» total NPLs was the largest (45%) among uses of

credit.

Through October 2003, the composition of credit

by uses has not changed much. Banks» credits were still

dominated by working capital (54.0%), followed by

consumer (23.8%) and investment loans (22.2%).

Consumer loan had the highest rate of expansion, at

33.5% (y-o-y).

The large share of working capital in total credit is a

matter of concern because a failure in this type of credit

would have a major impact on overall credit performance.

Although working capital NPLs were only 6.7% of total

working capital credits (total NPLs were 7.8%), by value

they were 54.4% of total NPLs.

Meanwhile, investment credit NPLs were highest, at

10.9% of total investment credit. By contrast, consumer

credits were only 2.7%.

Chart III. 8Credit Development by Economic Sector

Chart III. 9Loan Development by Usage

Percentage

Investment Capital Working Consumer

1997 1998 1999 2000 2001 2002 Jan-80

-60

-40

-20

0

20

40

60

80

Feb Mar Apr May Jun Jul Aug Sep Oct

2 0 0 2

Chart III. 10Loan Growth by Usage

Chart III. 11NPLs of Consumer Loans

Trillion

Sub standard Doubtfull Loss0.0

0.2

0.4

0.6

0.8

1.0

1.2

1.4

12/01 2/02 4/02 6/02 8/02 10/02 12/02 2/03 4/03 6/03 8/03 10/03

26


Billion Rp

0

1,000

2,000

3,000

4,000

5,000

6,000

7,000

Jan Feb Mar Apr May Jun Jul Aug Sep Oct

Working Capital Loans

Investment Loans

Consumer Loans

As credit growth illustrates, economic growth has

been concentrated in areas boosted by consumer credit.

On the other hand, investment and working capital credits,

which were supposed to support engines of economic

growth (investment and exports), have performed poorly.

The large share of consumer credits and the recent

downward trend in new credits suggest that the Indonesian

economy has not fully recovered to its pre-crisis condition.

New credit extensions during 2003 tended to decline

after mid-year. During 2003 (up to October 2003), new

credit extensions were Rp53.6 trillion with the shares of KI

(investment credits), KMK (working capital credits) and KK

(consumption credits) at 27.4%, 54.3% and 18.3%,

respectively. This total was considerably smaller than during

the comparable period in 2002 (Rp63.5 trillion). During

2004, the general election is expected to boost money-in-

Chart III.12New Loans by Economic Sector

Chart III.132003 New Loans by Usage

Billion

Agriculture

Mining

Construction

Transportation

0

100

200

300

400

500

600

700

800

900

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

circulation and consumption, which points towards

consumer credits as the continuing leader in banks» credit

growth.

As regards property credit, the relatively large increase

in housing credits warrants close monitoring. Based on

experience, the quality of housing credits is sensitive to

the cycle in economic growth.

Although housing credit NPLs averaged less than 5%

in 2003, the rising trend in housing credits needs to be

monitored carefully. Company shutdowns and factory

relocations to other countries are a few examples of events

that can result in significant employee layoffs. In such

circumstances, employees would have difficulty in making

on-time repayments on housing credits. As is the case for

consumer credits, deteriorating economic conditions could

raise housing credit NPLs.

Trillion Rp

Property

Construction

Real Estate

Housing

1996 1997 1998 1999 2000 2001 2002 20030

10

20

30

40

50

60

70

80

90

Chart III.14Development of Property Loans

PropertyConstruction

Real EstateHousing

2 0 0 3

Percentage (y-oy)

-80

-60

-40

-20

0

20

40


Chart III.15Growth (y to y) of Property Sector (%)

27


Boks III. 4

Chart Box 3.4.1CAR with 20% Credit Increase

On the assumption that total credits at 15 large

banks will rise 20% (Rp92.6 trillion) from its position

as of October 2003 (Rp463.7 trillion), the average CAR

of these banks would drop by 2.8% (the highest being

5.2%, the lowest 1.8%). However, no bank would

have a CAR below 8% (Chart).

Capital’s Resilience To Credit Expansion

This analysis indicates that when there is a 20%

rise in credits, large banks» CARs will decline, but

remain at a safe level. This is supported by these 15

banks» fund placements in SBIs are quite large, i.e.

Rp86.3 trillion; trade portfolio bonds amounting to

Rp65.1 trillion; and their excess provisioning in the

amount of Rp11.3 trillion (a total of Rp162.7 trillion).

All have the potential to be converted to credits

quickly.

From this illustration, there is no problem on the

supply side if banks channel significantly more credits.

However, on the demand side, there is a difficulty in

relation to uncertainty about potential debtors»

capacity to absorb more credit. In this regard, it should

be noted that new credit extensions were declining

during 2003 while undisbursed loans were rising.

0

5

10

15

20

25

30

35

40Percentage

A B C D E F G H I J K L M N O

New CARCAR

Judging from developments during 2003, the

property industry grew rapidly, marked by vigorous

construction of malls, house-shop buildings and offices in

the Jabotabek area as well as in several provincial cities.

Nonetheless, the share of property credits remained

relatively small. Funds used by construction developers

mostly come from non-bank sources, such as own funds,

issuance of bonds or foreign loans.

However, property credits (construction, real estate,

and housing credits) expanded rapidly during 2003,

largely spurred by the high demand for housing. As of

October 2003, total property credit reached Rp43.9 trillion

or 9.5% of banks» total credits. Of total property credit,

the share of housing was 63.8%; construction and real-

estate credits accounted for 22.0% and 14.3%,

respectively.

Non-Performing Loans (NPLs)

Concerning the quality of credit, banks» NPLs declined

during 2003. However, 2004 could be quite different,

based upon the following considerations: (i) the quality of

credits could decline due to (restructured and

unrestructured) credits purchased from IBRA; (ii) the rising

trend of (gross and net) NPLs owned by state banks in the

last several months; and (iii) indications that NPLs are higher

than reported, as suggested by higher-than-required

Provisions for Earning Assets Losses (PEAL).

This NPL problem has the potential to generate

systemic risk, because CARs are sensitive to changes in

NPLs. In addition, pressures from credit concentration are

also quite high, considering that: (i) credit concentrated2

2 Credit concentration to 25 large debtors at large banks was 26.1%, with NPLs averaging9.1% (industry-wide NPLs were 7.8%). Total credits extended to these debtors reached98.9% of the capital of these banks.

28


Current (left axis)Special Mention (right axis)

Sub Standard (right axis)

Doubtfull (right axis)

Loss (right axis)

0

20

40

60

80

100

120

140

160

1996 1997 1998 1999 2000 2001 2002 2003

Trillion Trillion

-100

0

100

200

300

400

500

Percentage

Current Special Mention Sub Standard

Doubtfull Loss

2003

-80

-60

-40

-20

0

20

40

60

80


Percentage Trillion Rp

NPLs Gross NPLs Net NPLs Nominal Loan

0

2

4

6

8

10

12

14

16

18

20

0

50

100

150

200

250

300

350

400

450

500

2000 2001Dec Jun Dec Jun Dec Jun Oct

2003 2003

banks» and auditors» calculations of collectibility,

provisioning that exceeds requirements, and the

classification of ex-IBRA restructured credits as being

≈current∆. Analysis using more conservative ratios

presents a different picture. For example, the ratios of

NPLs to total capital and to core capital average of

33.0% and 42.0%, respectively. Although there are no

well-defined benchmarks for these ratios, Indonesian

banks» NPLs are clearly high compared to capital (Box

III.5 NPL Stress Test). However, in the short term, banks»

capital ratio (CAR) is not expected to be influenced much

by these NPLs, because banks have generally provisioned

(PEAL) in larger amounts than required (Box III.6

Provisions for Earning Asset Losses).

By bank group, the joint venture banks had the

highest NPL ratio of 13.4%. This was due to these banks»

3 The industrial sector»s NPLs reached 10.5% (average NPLs were 7.8%); its credit sharewas 28.9% (the largest).

in the 25 largest debtors at large banks had NPLs higher

than banks» average for NPLs; and (ii) NPLs of the industrial

sector (which has the largest share of credits) were also

higher than banks» average for NPLs 3 .

NPLs were relatively high in 2003, as the economy

has not fully recovered from the crisis of 1997/98. The

banking industry adjusted to this situation with large

amounts of provisioning (PEAL). However, credit risk was

lower in 2003 (with a slight downward trend in the last

few months) compared to the previous year. Banks» NPLs

in gross and net terms averaged 8.1% and 1.1%,

respectively compared with 11.5% and 3.8%, respectively,

in 2002.

In 2004, NPLs are expected to be on an upward trend,

primarily due to a weakening trend in the quality of

restructured credits and an end to the grace period on

classification of credits purchased from IBRA. In addition,

structural problems (such as legal uncertainty, regulations

and their enforcement, and a disappointing economic

recovery to date) will continue to hinder banks from

improving their NPLs.

Currently, banks» NPLs are believed to be higher

than reported. This is supported by the number of

occasions when discrepancies have arisen between

Chart III. 16Non Performing Loans

Chart III.17Growth of Loans Classification

Chart III.18Development of Outstanding NPLs

29


Box III. 5

Chart Box 3.5.1 Stress Test of NPLs Impact on CAR

Results of stress tests indicate that two banks are

relatively sensitive to rising NPLs. Considering that these

two are large banks, rising NPLs would have quite an

influence on the financial system stability.

To access the impact of a decline in credit quality

on capital (CAR), a stress test was conducted on 15

large banks using a number of hypothetical scenarios

(rises of NPLs from 5% up to 50%) from a base CAR

as of October 2003. Results of the stress test using

rises in NPLs of 10% and 30% indicated that 2 banks

Stress Test of NPLs Impact on Capital

NPL Decreasing Scenario (percentage)

CAR (%)

-5

0

5

10

15

20

Start 10 15 20 25 30 35 40 45 50

B D H N 15 BB

Box III. 6

Chart Box III.6.1Development of NPLs & PEAL

Chart Box III.6.2PEAL for Loans & Channeling

Although gross NPLs are relatively high, in the

short-term this will not have a negative impact on

financial system stability, considering that reserves are

high enough to cover potential losses.

Overall provisions (PEAL) at Indonesian banks are

quite high, 127.8% of requirements, indicating that

banks are very conservative in anticipating credit risk.

However, this also reflects banks» lack of confidence

in the quality and prospects of their credits, including

in Indonesia»s economic prospects. In addition, this

suggests that the credit performance of banks in

Indonesia is not yet optimal because excessive PEAL is

substituting for efforts to reduce NPLs (net). On the

other hand, this situation also shows the opportunities

for banks to channel more credits.

The high PEAL ratio is due to the provisioning at

15 large banks, where the average provisioning against

credits reached 147.8%, with a very large range (the

lowest being 58.4%, the highest 269.5%).

Provisions for Earning Assets Losses (PEAL)

Trillion Rp

1996 1997 1998 1999 2000 2001 2002 20030

Loan NPL Provision

100

200

300

400

500

600

700

800

Percentage

A B C D E F G H I J K L M N O0

50

100

150

200

250

300

Provision made by bank/Required PEAL

Provision for NPL/NPL

(1 state bank and 1 national private commercial bank)

would have CARs below 8%.

30


NPLs having undergone credit restructuring by the banks

themselves during the crisis period because their capital

was quite large. Low NPLs of other bank groups were

due to the transfer of these banks» NPLs to IBRA during

recapitalization.

NPLs at the state banks need to be monitored closely.

In gross and net terms, their NPLs rose markedly from end-

2002 through October 2003, from 6.83% and 1.47% to

8.68% and 2.01%, respectively. Credits increased by

10.5% and NPLs by 40.5%.

In general, Indonesian banks» NPLs are lower than

those of several other Asian countries, such as Malaysia,

Thailand, and the Philippines (October 2003). However,

this further supports suspicions that NPLs in Indonesia

are under-reported, considering that economic

conditions of those countries are generally better than

Indonesia»s, as reflected in their stronger ratings and

lower sovereign risk.

Loan concentration in the 25 largest debtors is quite

high and needs to be closely watched; when the quality

of their credit deteriorates, it will directly lower banks»

capital.

Credit concentration in the 25 largest debtors at 14

large banks was quite high, on average reaching 26.1%

of total credits with NPLs at an average of 9.1% of total

credits extended to those debtors. In general, those 25

largest debtors» NPLs were in the manufacturing sector

(plastics, paper, shoes, wood, cement, gas, and textiles)

and plantations.

Chart III. 20Gross NPLs of Asian Countries

Source: ADB - personal website

State Owned Bank 8.52 1.90 6.83 1.47 8.68 2.01

Recapitalization Bank 24.31 9.81 8.36 3.74 7.00 -0.47

Bank A Category 5.18 1.29 5.20 2.33 4.36 0.82

Taken Over Bank 4.87 0.10 6.53 0.79 6.08 -2.30

Regional Gov» Bank 6.38 4.72 5.24 4.14 4.67 3.72

Joint Venture Bank 22.91 10.191 8.62 6.481 3.45 3.92

Foreign Bank 19.8 12.76 16.14 2.12 11.89 1.07

GroupGroupGroupGroupGroup

GrossGrossGrossGrossGross NetNetNetNetNet GrossGrossGrossGrossGross NetNetNetNetNet GrossGrossGrossGrossGross NetNetNetNetNetOctoberOctoberOctoberOctoberOctober DecemberDecemberDecemberDecemberDecember OctoberOctoberOctoberOctoberOctober

20022002200220022002 20032003200320032003

Table III. 1NPLs by Bank Group

PercentagePercentagePercentagePercentagePercentage

NPL/Capital

NPL/Tier I25

27

29

31

33

35

37

39

41

43

45

Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct

2 0 0 2 2 0 0 3

Percentage

Chart III. 19 2003 Ratio of NPLs to Capital

Asian Countries NPL Gross

China

Philippines

Thailand

Malaysia

India

Indonesia

Japan

Singapore

Taiwan

Hong Kong

South Korea

New Zealand

Percentage

0 5 10 15 20 25

A 24.4 8.5 0.0 0.0B 32.8 2.2 4.7 1.5C 25.3 5.2 22.1 5.6D 1.6 3.8 25.8 0.4E 12.5 12.7 21.3 2.7F 48.6 11.9 19.1 9.3G 32.8 3.7 0.0 0.0H 24.2 16.4 27.0 6.5I 41.7 17.1 34.7 14.5J 86.0 6.1 0.0 0.0K 11.9 1.0 0.0 0.0L 22.2 4.5 5.5 1.2M 24.4 4.4 5.4 1.3N 28.2 2.0 5.5 1.6

AVERAGEAVERAGEAVERAGEAVERAGEAVERAGE 26.126.126.126.126.1 7.67.67.67.67.6 9.19.19.19.19.1 2.42.42.42.42.4

BankBankBankBankBankBankBankBankBankBank

25 largest25 largest25 largest25 largest25 largestdebtors todebtors todebtors todebtors todebtors to

total loan (%)total loan (%)total loan (%)total loan (%)total loan (%)

NPLs GrossNPLs GrossNPLs GrossNPLs GrossNPLs Gross

Table III. 2Loans Concentration on 25 Largest Debtors (LD)

PercentagePercentagePercentagePercentagePercentage

NPL of 25 LD toNPL of 25 LD toNPL of 25 LD toNPL of 25 LD toNPL of 25 LD tototal loans oftotal loans oftotal loans oftotal loans oftotal loans of

25 LD25 LD25 LD25 LD25 LD

NPL of 25 LD toNPL of 25 LD toNPL of 25 LD toNPL of 25 LD toNPL of 25 LD tototaltotaltotaltotaltotal

Banks LoansBanks LoansBanks LoansBanks LoansBanks Loans

31


25 Largest debtors to Capital

25 Largest debtors to Tier I

0

50

100

150

200

250

300

A B C D E F G H I K L M N

Percentage

As of August 2002, restructured credits held by

26 banks reached Rp14.5 trillion (12.0% of banks» total

credits), comprising performing loans of Rp10.3 trillion

and NPLs of Rp4.2 trillion. This total amount is quite

sizable and could have a significant impact on these

banks» condition should the quality of restructured

credits deteriorate again. This has been demonstrated

through a stress test under a worst-case scenario, where

all performing loans were changed to non-performing.

The result showed 2 banks would have CARs below 8%,

while 2 other banks would have negative CARs. This

result is worrisome because of the condition of the

restructured credits, particularly those coming from IBRA.

These credits are scheduled to have their quality re-

evaluated at the end of a 1-year grace period, because

they were originally automatically categorized as

performing loans.

3.1.2. Liquidity Risk

During 2003, bank liquidity condition was generally

adequate, as reflected in the upward trend in ratios of

liquid assets to short-term liabilities and to total assets.

Indeed, banks still experience excess liquidity, which has

largely been invested in interbank placements and

marketable securities, particularly SBIs. Several problems

could develop and put pressures on banks» liquidity,

including: a funding structure that concentrates on short-

term funds; large deposits and core depositors; banks»

medium-term payment obligations; and the development

of mutual funds. Meanwhile, banks need to anticipate

the possibility of funds migration as the blanket guarantee

program is removed, as it is planned to cover up to a

maximum of Rp100 million for each bank customer at

each bank.

With declining interest rates, there is potential for

the shifting of deposits from banks to the capital market.

This could endanger banks» liquidity considering that bank

Credits extended to these 25 large debtors averaged

98.9% of these banks» total capital with quite a wide range

between the lowest of 16.6% (bank D) and the highest of

1,304.7% (bank J). Compared to core capital, this ratio

was 137.7% (the lowest at 20.5% and the highest at

1,447.2%).

These high ratios indicate that bank credit risk is

still quite high. Should credits extended to these large

debtors become non-performing, the entire capital of

these banks will be consumed and could become

negative. Results of stress tests indicate that, if all credits

extended to large debtors at these 14 banks become non-

performing, only 3 banks would maintain a CAR above

8%. Among the others, 2 banks would have CARs

between 0-8% and 9 banks would have negative CARs.

These results warrant close attention, because the average

performance of the large debtors at these 14 banks is

less satisfactory than those of other debtors; NPLs of the

largest 25 debtors (9.1%) are higher than the banking

industry»s average NPLs (7.8%).

Quality of Restructured Loans

There is potential for a decline in the quality of

restructured credits, which would raise NPLs significantly

due to the large amounts involved.

Chart III. 21 Ratio of 25 Largest Debtors» to

Capital √ August 2003

32


Chart III. 22 Banks» Funding Structure

Rp Trillion

44 4 4 7 7 7 9 11

1112

836 825 832 833 838 838 847 852 858

863 879

14 12 9 9 8 66 7 7 7

781

84 82 81 79 80 76 72 6771

66


2002 2003

750

800

850

900

950

1,000Interbank Liabilities

Borrowed funds Deposits

Marketable Securities

Chart III. 23Structure of Third Party Funds

2002

Trillion of Rp

20

25

30

35

40

45

50

55

60

100

150

200

250

300

350

400

450

500Percentage

2003Jan Feb Mar Apr May Jun Jul Aug Sep OctDec

Checking Accounts (IDR) Time Deposit (IDR) Saving Accounts (IDR)

Saving Accounts (%)Checking Accounts (%) Time Deposit (%)

assets are dominated by loans, which cannot be liquidated

quickly.

In 2003, bank»s funding structure was still dominated

by third-party funds4 , particularly deposits. As of October

2003, third party funds reached 91.2% of total funding,

followed by interbank placements (6.8%), marketable

securities (1.3%), and borrowed funds (0.7%). The shares

of third party funds and marketable securities have

increased since end-2002 (Chart III.22).

Banks» third party funds, which are dominated by

deposits, trended upwards during much of 2003, after

having dropped in the first month in the year. However,

since July 2003, the share of deposits has dropped

continuously partly mirroring rising shares of current

accounts and savings in total third party funds (Chart III.23).

This development is also related to the rapid expansion of

mutual funds through September 2003. These attracted

large amounts of banks» third party funds, particularly

deposits (Table III.3).

Rapid development of mutual funds is reflected in

their continuous, rapid rise in net asset value (NAV), which

has indirectly affected banks» deposits. With the downward

trend in SBI interest rates (which influences deposit interest

rates), customers have sought alternative placements with

higher returns.

The structure of banks» funding source is relatively

unbalanced, as reflected in: (i) banks» high dependence

on short-term deposits (up to 3 months); (ii) relatively large

amount deposits owned by certain depositors; and (iii) a

high concentration in large depositors.

As of October 2003, 3-month deposits reached

81.4% of total deposits or 40.5% of total third party funds4 Comprising current accounts, deposits, and savings accounts.

Trillion Rp

Table III.3Development of Third Party Funds and NAV

NAV 2.78 4.92 2.99 4.97 5.52 8.00 46.6 51.1 54.7 58.4 61.3 65.3 68.4 76.9 81.3 85.9 79.2

Deposits 303.21 400.35 625.33 617.64 699.11 797.36 835.8 824.6 832.0 833.4 837.8 838.1 846.8 852.2 858.0 863.5 879.4

- Checking

Account 59.49 86.40 99.78 111.83 161.47 186.15 197.0 186.2 188.3 189.9 191.9 194.8 202.0 203.8 208.0 217.6 222.8

- Saving

Account 61.57 67.99 68.69 122.98 152.94 171.30 192.6 188.7 189.1 189.4 192.9 196.9 201.6 204.0 209.7 213.2 219.3

- Time

Deposits 182.15 245.96 456.86 382.83 384.70 439.91 446.2 449.8 454.5 454.1 453.1 446.4 443.2 444.4 440.4 432.7 437.3

19961996199619961996 19971997199719971997 19981998199819981998 19991999199919991999 20002000200020002000 20012001200120012001 20022002200220022002 Jan»03Jan»03Jan»03Jan»03Jan»03 Feb»03Feb»03Feb»03Feb»03Feb»03 Mar»03Mar»03Mar»03Mar»03Mar»03 Apr»03Apr»03Apr»03Apr»03Apr»03 May»03May»03May»03May»03May»03 Jun»03Jun»03Jun»03Jun»03Jun»03 Jul»03Jul»03Jul»03Jul»03Jul»03 Aug»03Aug»03Aug»03Aug»03Aug»03 Sep»03Sep»03Sep»03Sep»03Sep»03 Oct»03Oct»03Oct»03Oct»03Oct»03

33


(Chart III.24). Most of these funds were denominated in

rupiah (65.6% of total deposits); those denominated in

foreign currencies amounted to 15.8% of total deposits.

Of total short-term deposits, 74.3% was placed at 15 large

banks.

Despite such conditions, banks are expected to

stop their maturity profile structure gaps from becoming

too wide, which will give banks adequate time to

anticipate possible migration of deposits to the capital

market.

Large depositors and certain other depositors are

generally market-sensitive. They tend to withdraw their

funds quickly when conditions are considered

unprofitable.

Banks» dependence on certain depositorsƒnamely

state-owned companies, insurance companies, and

pension fundsƒhas remained quite significant despite a

downward trend. As of October 2003, the share of these

depositors accounted for 10.3% of total third party funds

(Chart III.25). Similarly, the shares of State-owned

Comapnies, Insurance Companies and Pension Funds at

15 large banks and state banks was quite significant,

reaching 11.1% and 16.6%, respectively. At 5 banks,

these depositors exceeded the average for the banking

industry; at 1 bank, they represented 40.5% of that bank»s

third party funds (Chart III.26).

Concentration of banks» fund sources in large

deposits is also relatively high. As of October 2003, total

large deposits (with value above Rp100 million) accounted

for 79.2% of total deposits, or 20.5% of total number of

accounts (Chart III.27). There were 9 large banks that had

concentrations of large depositors exceeding that ratio.

Banks with relatively high concentrations of deposit

ownership are expected to take anticipatory steps to

implement liquidity risk mitigation techniques.

Banks» heavy dependence on third party funds

(particularly short-term deposits) reflects in part depositors»

cautious attitudes. But it also indicates a situation where

banks face a risk of funds withdrawals in large amounts,

Chart III. 24Composition of Time Deposits by Tenor

81.4 80.6 72.9

7.1 6.78.5

7.5 7.69.9

5.1 8.7

0

10

20

30

40

50

60

70

80

90

100 4.0

Industry 15 BigBanks State Banks

Percentage

up to 3 month 3 to 6 month 6 to 12 month over 12 month

% over Deposits

0

2

4

6

8

10

12

May Jun Jul Aug Sep Oct

2003

Private Insurance Company (2)State Company (1)

Pension Funds (3)

Chart III. 25Ownership of Third Party Funds by Core Depositors

Billion Rp

-

5,000

10,000

15,000

20,000

25,000

30,000

35,000

40,000


B A N K

Percentage

-5

0

5

10

15

20

25

30

35

40

45

Core Depositors

% over Deposits

Chart III. 26Third Party Funds Ownership

at 15 Big Banks

34


J

B A N K

0

10

20

30

40

50

60

70

80

90

100

79 7665

8292

53

83 86 8378 74

8495 97 94

76 79

21 2435

18

8

47

17 14 1722 26

16

5 3 6

24 21

% nom > 100 Million % nom < 100 Million

A B C D E F G H I K L M N O 15 BB Industry

Percentage

Chart III. 27Composition of Time Deposits by Amount

if these funds are not rolled over upon maturity. This can

put severe liquidity pressures on a bank. However, in the

light of current development of the bond market, which is

characterized by increasing numbers of banks issuing bonds,

banks» funding structure is expected to improve, which

would reduce their dependence on short-term funding.

A high concentration in large depositors has similar

potential for disrupting banks» liquidity, especially in the

context of a continuous downward trend in deposit rates.

Another factor that needs to be considered is elimination

of the blanket deposit guarantee, which will be replaced

in part by a ceiling of Rp100 million per customer in each

bank. This might prompt customers to divide their funds

and place them in several banks and thereby cause fund

migration from bank to bank. Another implication is the

possible migration of these funds outside the banking

industry (Box III.7 : Implications of Implementation of The

New Guarantee Scheme).

Excess liquidity at banks will cause them to be

inefficient, considering that incomes from SBIs and the

interbank money market do not carry high margins.

Banks» liquidity during 2003 was adequate, indeed,

many were over-liquid. This was reflected in a rising liquid

asset ratio5 compared to its position at end-2002. Also,

banks» total liquid assets amount to nearly one fifth of

their total assets (Chart III.28). In addition, a relatively

low percentage of third party funds and other fund

sources were channeled to credits (Chart III.29). Excess

funds were generally placed in marketable securities,

particularly SBIs, and interbank placements. The liquid

asset ratio in semester II/2003 was relatively slower after

having dropped at the beginning of quarter II/2003.

As of October 2003, the ratio of liquid assets to short-

term liabilities6 at 15 large banks was lower than the

banking industry»s average (Chart III.30). Also, it was down

slightly from semester I/2003, with most of these banks

recording a drop in the ratio. At 2 banks the ratio dropped

quite sizably due to a decline in SBI holdings.

A simple stress test conducted on banks» reserves

showed that the state bank group has considerable

5 Cash, current accounts at BI, and SBIs. 6 Current accounts, savings, and deposits of up to 3 months» maturity

40

50

60

70

80

90

100

49 49 49 50 51 51 51 52 52 53 53

44 44 44 45 46 46 46 47 47 48 48

71

74 75 76 76 7679 80 79 80 80

7982 83 85 85 85

87 88 87 88 88


2002 2003

Percentage

Loan/Deposits Loan/FundingInvestment/Funding Investment/Deposits

Liquid Assets/short-term depositsLiquid Assets/Total assets

0

5

10

15

20

25

30

2002 2003

Percentage

Jan Feb Mar Apr May Jun Jul Aug Sep OctDec

Chart III.28Liquid Asset Ratio

Graph III.29Ratio of Funds Channelled over Funds Sources

35


Box III. 7

Chart Box 3.7.1Comparison of Deposit Outflows To Liquid Assets

at 15 Big Banks

If not implemented effectively, the new guarantee

scheme, which limits deposit balances to a planned

maximum of Rp100 million per customer in each bank,

could trigger migration of deposits between banks or

outside the banking industry. This has the potential to

damage bank liquidity.

Results of a simple simulation on 15 large banks

shows that, in general, funds that will migrate between

banks could reach more than 30% of total third party

funds. This estimate is derived from the assumption

that the guarantee ceiling is Rp100 million and that

deposits in excess of this amount are transferred to other

banks or outside the banking industry (worst-case

scenario). Total estimated funds that could migrate

would still be fully covered by banks» liquid assets1 in

Implications of Implementation of The New GuaranteeScheme

aggregate and at the 15 large bank group (using

October 2003 data). Nevertheless, there would be 8

large banks whose liquid assets would not be adequate

to cover migrated funds.

A moderate-case scenario uses the assumption

that customers will split their funds, leaving 50% in

the same bank and transferring the rest of the funds

to another bank or outside the banking industry. In

this case, funds that might migrate from the 15 large

bank group and the banking industry are 18.6% and

19.7%, respectively. On an individual bank basis, there

would be 5 large banks with the potential for funds

migration of more than 30% of third party funds; only

2 banks have insufficient liquid assets to cover the

migrated funds.

Although possible funds migration can be

covered by banks» liquid assets, in the long run such

migration has the potential to cause problems, because

of fund migration from perceived good banks to

perceived bad banks. Total funds that are estimated to

migrate from 15 large banks would be in the range of

8.1% to 61.7% of total third party funds (worst-case

scenario), which would have a significant influence on

these banks.

1 Comprising primary and secondary reserves.

Trillion Rp

Outflow Liquid Assets

-

10

20

30

40

50

60

70

80


potential for experiencing liquidity pressures, if customers

were to make large withdrawals.

A simple stress tests indicates the potential for

liquidity problems. If non-core deposits (NCD) are 30% of

third party funds7 (the moderate-case scenario), banks»

liquid assets8 can cover NCD withdrawals, for the whole

industry and the 15 large banks, but not for the state bank

group. If NCD withdrawals are 50% of third party funds

(worst-case scenario), liquid assets cannot cover NCD

withdrawals (Chart III.31).

Result of this stress test illustrates that banks hold

relatively small amounts of liquid assets, particularly large

7 Current accounts, savings, and deposits8 Primary and secondary reserves.

36


Percentage

50% Deposits

30% Deposits

0

50

100

150

200

250

300

350

400

A B C D E F G H I J K L M N O 15BB

Indu

stry

Sta

te b

anks

Chart III. 31Non-Core Deposits to Liquid Assets

B A N K

A

BC

E

F

G

H

I

J

K

LM

N

OD

Industry

15 Big Banks

0

10

20

30

40

50

60Percentage

development of mutual funds. Meanwhile, liquidity risk

will be moderate on a rising trend due to certain issues,

such as an unsound funding composition (which is heavily

concentrated in large depositors, certain other depositors,

and short-term deposits) and relatively large amounts of

foreign currency liabilities that will fall due after 2003 at

several banks. The Government plan to implement a new

guarantee program (with a ceiling on amounts covered)

also has the potential to put pressure on banks» liquidity.

Moreover, the over-liquid condition that has occurred in

2003 is estimated to continue in 2004, because banks are

likely to continue facing difficulties in channeling their

funds in the form of credits.

In relation to banks» relatively unsound funding

composition and the expanding bond market, banks need

to improve their funding structure, among others through

issuance of long-term bonds, while still observing

prudential principles. Concerning several issues that have

the potential to put pressures on liquidity, banks should

be encouraged to improve their structure, especially with

the approach of the new guarantee scheme that will

replace the blanket guarantee program. In order for the

new guarantee program to operate effectively and to

reduce the potential for deposits to migrate outside the

banking industry, the government guarantee program

could be gradually eliminated, with consideration to the

public»s response.

3.1.3. Profitability

In general, the banking industry»s profitability in 2003

improved as measured by indicators such as the net interest

margin (NIM) and the return on assets (ROA). The banking

industry»s NIM10 jumped from 0.4% in January 2003 to

3.8% in October 2003. Similarly, the banking industry»s

ROA rose from 1.9% in December 2002 to 2.2% in January

Chart III.30Ratio of Liquid Assets to Short-Term Liabilities

at 15 Big Banks

banks. Shocks, such as a bank run, will put pressure on

banks» liquidity. Under a worst-case scenario, only 3 large

banks would have liquid assets that exceed their NCDs.

Under a moderate-case scenario, 10 large banks would

have liquid assets that exceed their NCDs. Taking all existing

reserves9 into account, 3 large banks have the potential

for liquidity pressures because their total reserves are

smaller than NCDs (under a worst-case scenario); 1 bank

has the potential to not cover withdrawals of its NCDs

(under a moderate-case scenario).

Bank liquidity, which was quite adequate during

2003, is expected to remain stable in 2004. Similarly third

party funds would remain stable with an upward trend as

in 2003. However, banks» deposits are expected to come

under pressure from declining SBI rates and the

9 Primary, secondary, and tertiary reserves.10 Net Interest Margin (NIM) (%) : Net Interest Income/Earning Assets

37


2003 and 2.4% as of September 2003, before slipping a

little in October 2003 to 2.3%.

There has been a pronounced downward trend in

interest income from SBIs and bonds during 2003. At the

same time, interest income from credits rose, albeit on a

relatively slow trend.

Since the beginning of 2003, banks» interest income

and expense tended to decline in line with falling SBI rates.

However, banks still managed to maintain their net interest

income (NII) during 2003 at between Rp3.8 trillion to Rp4.5

trillion per month (Chart III.32). This was due to the banks»

ability to maintain quite a large spread between interest

rates on credits and rates on third party funds.

The composition of the banking industry»s interest

income was still dominated by interest income from SBIs

and marketable securities, particularly recapitalization

bonds. For the whole banking industry, interest income

from SBIs and bonds remained in a range of 44% - 47%

of total interest income; for the 15 large bank group, it

ranged from 42% √ 54%.

However, as SBI rates declined, signs began to

emerge of a gradual shift in interest income from SBIs and

bonds to interest income from credits. This was the case

for both the 15 large banks (Chart III.33) and the entire

banking industry (Chart III.34).

As the decline in SBI rates moderates, the banking

industry»s profitability in 2004 would be relatively stable.

The decline in interest income from SBIs and recapitalization

bonds will continue, but at a slower pace than in 2003.

Banks» operational efficiency has not shown any

meaningful change as evidenced by their ratio of

operational income to operational expense (OIOE). As of

September 2003, banks» OIOE reached 90.29%, before

slipping a bit to 89.92% in October 2003. The most

inefficient bank group was the recapitalization bank group

with an OIOE of 99.08%, followed by the state bank group

with an OIOE of 94.04%; the 15 large bank group had an

OIOE of 87.66%. The joint venture and foreign bank

groups remained to be the most efficient with OIOE of

75.51% and 83.56%, respectively.

Trillion Rp

(15.00)

(5.00)

5.00

15.00

25.00

NII Interest Income Interest expense

Dec98

Dec99

Dec00

Dec01

Feb03

Apr03

Jun03

Aug03

Oct03

Feb02

Apr02

Jun02

Aug02

Oct02

Dec02

Chart III. 32Development of Net Interest Income

Percentage

2003

Jan Feb Mar Apr May Jun Jul Aug Sep Oct0

20

40

60

80

100

BI Sertificate Securities Loan Other

Chart III.33Composition of Interest Income at 15 Big Banks

2003Jan Feb Mar Apr May Jun Jul Ags Sep Oct

Percentage

0

20

40

60

80

100

BI Sertificate Securities Loan Other

Chart III.34Composition Interest Income - 2003

38


Source : ARIC - ADB

Percentage

1995 1996 1997 1998 1999 2000 2001 2002 2003-200

-150

-100

-50

0

50

Phillipines

IndonesiaMalaysia

South KoreaThailand

36

46

56

66

76

86

96


2002 2 0 0 3

Percentage

State-Owned Bank

All Bank

Recapitalization Bank

11 Ratio of overhead cost (personnel, training, and rent expenses) to non-operational income.12 Aggregate CAR = Banks» Total Capital/Banks» Total ATMR

Chart III.37 Development of ROA in 5 Asian Countries

Graph III.36CER Comparison

Another indicator, the cost efficiency ratio (CER11 ),

showed that state banks were less efficient than the

industry average (Chart III.35). Therefore, the operational

efficiency enhancement program at state banks needs to

be implemented more seriously.

The banking industry needs to step up its

operational efficiency through, among others,

improvement of work processes, reorganizations, and

shedding less-productive activities. However, compared

with banks in several neighboring countries (Thailand,

Malaysia, and South Korea), Indonesia»s banking industry

as measured by return on asset (ROA) was more

profitable, as illustrated by Chart III.37.

3.1.4. Capital

The banking industry»s capital ratio was quite adequate

as reflected in the aggregate CAR,12 which averaged 20.6%

as of October 2003. During the period from January to

September 2003, banks» CAR averaged more than 20%.

However, banks» aggregate CAR would decline if market

and operational risks are included in the calculation.

Banks» capital in 2004 is estimated to have declined

slightly due to a rise in risk-weighted assets (ATMR), in

line with credit growth. Meanwhile, banks» internal

capitalization capacity will remain relatively low due to

inefficient operations, relatively high operational risks, and

relatively low profitability.

During 2003, the banking industry»s average CAR

was above 20%, with considerable variation by bank

group. The joint venture bank group»s average CAR was

the highest at 32.47%, followed by the national private

foreign-currency banks at 22.81%, the state banks at

18.96%, the BPDs at 18.57%, the foreign banks at

17.60%, and private non-foreign currency banks at

15.61%. Banks» CAR dropped a bit compared to previous

months due to a rise in risk-weighted assets (ATMR), in

line with higher earning assets, particularly credits, coupled

with a decline in marketable securities (mainly SBIs and

recapitalization bonds; Chart III.38).

100

120

0

20

40

60

80

Percentage Percentage


15 B

ig B

ank

IND

US

TRY 0

5

10

15

20

25

30

Sta

te-O

wne

dba

nkInterest Income : Over Head Cost (right axis)Operational Expense/Income (left axis)

Chart III.35 Efficiency Ratio

39


Looking further at the distribution of CARs, banks»

aggregate CAR during 2003 ranged between 20% - 26%.

There were 17 out of 138 banks with CARs between 8%

√ 10%. One of 15 largest banks had CAR of between

8% √ 10%, while 6 banks had CARs of between 10% √

15%. These CARs are quite sensitive to changes in the

quality of productive assets or to a change in the calculation

method, for example, by incorporating additional risk

components.

In the future, banks» capital (CAR) will remain

sufficiently high to accommodate credit expansion.

However, several large banks» whose CARs are below 15%

should raise their capital because operational risks could

cause their CAR to plunge below the required minimum

level of 8%.

This matter warrants serious attention because

banks» capital (CAR) is not yet able to cover all risks.

The current CAR calculation only includes credit risk and

is not taking into account market and operational risks.

Various efforts have been undertaken to enhance capital

requirements, covering among others: ( i)

implementation of a regulation on minimum capital

requirements starting in 2004, which takes into account

market risk; and (ii) a review on adjustments to the

regulation regarding credit risk and implementation of

operational risk in accordance to the proposed new Basel

Accord (Basel II).

Implementation of the regulation concerning market

risk will not significantly influence banks» capital to enhance

capital requirements. Result of a simulation on

implementation of market risk in 47 banks (based on their

31 July 2003 balance sheets) showed that their CARs only

declined between 1.60 up to 205.9 bps with no banks»

CAR falling below 8%. This small effect of implementation

of these new capital requirements was due to the banks»

high capital warrants serious attention and relatively low

net foreign-currency positions.

Similarly, a simulation of operational risks showed

only a moderate impact on 13 large banks» capital. Under

the assumption that 20% of operational profits were

allocated to cover operational risks, capital at these banks

slipped by an average of only 0.3%.

Furthermore, an assumption of zero interest income

from marketable securities (bonds, SBIs, and other

marketable securities) resulted in a quite significant drop

in 13 large banks» capitals, to an average of 4%. However,

only one state bank had the potential for its CAR to slip to

below 8%.

Adopting a more conservative approach to capital

at the 15 largest banks, the analysis indicates that bank

1.70

1.80

1.90

2.00

2.10

2.20

2.30

2.40

Percentage

RWA ROA (%)

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct440

460

480

500

520

540

560

580

2002 2002

Chart III.38 Risk-Weighted Asset and ROA

340

350

360

370

380

390

400

410

420

60

70

80

90

100

110

120

130

140

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct

2002 2003

Loan (left axis)

Marketable Securities (left axis)

BI Sertificates (right axis)

Interbank (right axis)

Chart III.39Development of Banks» Earning Assets

40


Source : ARIC - ADB

1999 2000 2001 2002 2003

-20

-15

-10

-5

0

5

10

15

20

25

30

Jun Feb Apr May Jul OctDec Dec Dec Dec Jan Mar Jun Aug Sep

Malaysia Phillipines Thailand South Korea Indonesia

-

3

6

9

12

15

18

A B CG D F E H I J K M L N O

Indu

stry

Fore

ign

Ban

k

15 B

ig B

ank

Sta

te-O

wne

dba

nk

Chart III.40Ratio Tier 1 To Total Assets

Chart III.41CARs of Several Asian Countries

13 Ratio of core capital to total assets.

capital is still not strong. The ratio of banks» core capital

to total assets was in the range of 4% - 10%, and only 4

banks had ratios above 8%. Application of a more

conservative approach to the capital of 16 large (core)

banks produced variable results,13 with most of these

banks having relatively limited capital. The ratio of core

capital to total assets at 15 of the banks came in between

2.73% to 15.76%, and only 5 banks had ratios of above

8% (see Chart III.40). Meanwhile, the ratio of liabilities

to total capital at 13 large banks was also on average 12

times.

Another problem is the relatively low capitalization

capacity of banks, particularly from internal sources. This

is reflected in the relatively low income from credits,

particularly at recapitalization banks. Nonetheless, the

national banking industry»s CAR was higher than that of

several other Asian countries (Chart III.41).

3.1.5. Market Risk

Market risk facing the national banking industry

during 2003 was still at a controlled level. This condition

is predicted to remain stable until the first semester of

2004, assuming that banks» capital and the exchange rate

remain stable, and SBI rates hold around 8%. However,

pressures on the rupiah exchange rate should be

anticipated during the 2004 general election.

In general, banks have acted prudently as regards

their open positions in foreign currencies, which in quarter

III-2003 averaged 4.70% of capital. Meanwhile,

implementation of market risk in the calculation of capital

adequacy seems unlikely to have a negative impact on

banks» CAR. At the time of actual implementation of

market risk in January 2005, banks that will need to apply

the market risk requirements will be able to maintain CAR

at the minimum level of 8%.

Interest Rate Risk

Interest rate risk exposure faced by the national

banking industry in 2003 was still under control and it is

expected to be stable during 2004. Major factors

supporting this prediction include:

(i) Interest rates on credits are still high compared to

term deposits and other rate-sensitive liabilities. Since

the beginning of 2003, credit rates have been

extremely inelastic with respect to declines in SBI rates;

declines in SBI interest rates have not been followed

by proportionate declines in credit rates;

(ii) Inflation is estimated to come in below the inflation

target predicted by the government and Bank

Indonesia;

41


(iii) Bank capital is quite high, which will enable the banks

to absorb unexpected losses due to interest rate

changes; and,

(iv) Bank liquidity is still relatively high.

However, several banks have maturity profile gaps

because their funding comes from short-term sources (less

than 3 months) while their placements are made in the

forms of credits and recapitalization bonds with more than

3 month maturity, with re-pricing of floating-rate bonds

every three months. In such conditions, these banks»

profits/losses are very sensitive to interest rate changes.

However, rupiah interest rates have been trending

downwards since early 2002 and this has generally had a

positive impact on banks in the short-term. A notable

exception are several recapitalization banks that have

significant amounts of floating-rate bonds; these banks

will experience a further decline in income from coupons

should SBI interest rates continue to drop. However, this

situation can be offset by banks reducing their interest

rates on funding sources, enough to leave their spreads

adequately wide.

Result of a stress test on interest rate declines showed

that several banks would experience declines in CARs, but

would still come above 8% (Chart III.42).

In 2004, SBI interest rates are expected to average

around 8%, as Bank Indonesia still has room to reduce SBI

rates. Banks would be able to mitigate interest rate risk

by setting interest rates at relatively high levels,

notwithstanding declines in SBI interest rates.

Exchange Rate Risk

With a stable rupiah exchange rate in 2003, the

national banking industry faced stable exchange rate risk.

In 2004, this risk is expected to remain stable, although

there is a need for a close watch during the general election.

Banks» prudent approach in carrying open foreign-

currency positions was the primary factor that limited

exchange rate exposure of the national banking industry

in 2003. As an illustration, in quarter III-2003, the net

foreign-currency positions of 50 foreign-currency banks

was only 4.70% of capital.

Other factors that limited risk exposure of the

national banking industry in 2003 include:

• Derivative transactions that were relatively simple

(such as swaps and forwards) and generally for

hedging purposes. More complicated derivative

transactions (such as forward rate agreements (FRA),

futures, and options) were seldom undertaken by the

banks.

• Trading book portfolios were generally small, except

at large banks that participated in the recapitalization

program.

Stress Test Interest Rate

Delta of Interest rate Decreasing (%)

0

2

4

6

8

10

12

14

16

18

Strart 1 2 3 4 5

b d h k n

Chart III.42 Stress Test on Interest Rates

Scenario of Increasing of USD/IDR

5000 1000 1500 2000 2500-4.0

-3.5

-3.0

-2.5

-2.0

-1.5

-1.0

-0.5

Chart III.43Stress Test on Exchange Rates at Bank ≈X∆

42


Based on a stress test on the impact of exchange rate

changes on banks» CARs, only one bank would experience

a relatively significant drop in its CAR (by 3.54%), if the

USD/IDR exchange rate were to rise to Rp2,500/USD. While

this situation is unlikely to occur, this result indicates that

the particular bank»s short exposure in USD would be

relatively significant at 14.2% of capital. However, the bank»s

CAR would remain relatively high, because its capital base

is strong. Results of the stress test on this particular bank

are presented in the accompanying graph.

Impact of Requirement for Inclusion of Market

Risk in Minimum Capital

The requirement for incorporating market risk in the

calculation of minimum capital will be implemented

effective at beginning of 2005. Results of three simulations

undertaken in 2003 showed that implementation of this

requirement would not have a negative impact on capital

of banks that are required to adopt this approach. Results

of the simulations showed that these banks» CARs would

only drop by 4 to 206 bps. All banks tested would still

have CARs above 8%.

3.1.6. Operational Risk

If not well controlled, operational risks facing the

Indonesian banking industry could disrupt financial system

stability in the future. This is indicated by various incidents

of fraud stemming from weak internal controls.

Fraud at several banks has been widely reported

through the mass media in this post-crisis era. In terms of

risk management, fraud is part of operational risks. The

increasing number of fraud at several banks strongly

suggests that operational risks facing the Indonesian

banking industry will need more serious attention in the

future.

Operational risk is one of the loss risks originating

among others from human error, system default, and fraud.

This risk has the attention of the Basel Committee on

Banking Supervision of BIS, resulting in the inclusion of

this type of risk in the components of CAR calculation

specified in the proposed New Basel Accord (Basel II; last

updated in April 2003).

Operational risk is considered high in Indonesia. As

an example, total losses due to frauds at two large banks

recently amounted to 18.45% and 4.25% of their capital,

respectively, forcing these banks to provide additional

reserves for losses, in the amount of Rp941 billion

(78.42%) and Rp294 billion (100%). As an impact, these

two banks» CARs dropped from 16.35% and 13.82% to

15.08% and 12.63%, respectively. As regards the first

bank, it is estimated that it would not reach its profit

target for 2003.

Calculations based on the basic indicator method in

Basel II showed that the operational risks at 25 large banks

are relatively significant. These banks» CARs would drop

between 1.14% and 14.26%. Calculation using the basic

indicator approach on the two banks just mentioned,

yielded lower impact than actually occurred. Basic indicator

method calculates operational risks from average gross

income in the last 3 years multiplied by a factor b (beta)

that depends upon the bank»s line of business (up to at

maximum 18%).

Based on lessons learned from this experience, Bank

Indonesia, as the supervisory authority, stresses that

implementation of risk management has become very

important. The framework and approach used in risk

management require predictions of operational risks and

the provision of reserves that match actual risk exposure.

Assessment of operational risks can be conducted using

various approaches, from the most basic (such as the basic

indicator method in Basel II) up to very sophisticated

models. Requirements concerning operational risks (as

recommended by the BIS) have been incorporated in Bank

Indonesia regulation number 5/8/PBI/2003 dated 19 May

43


Box III. 8

In line with the government»s decision to

dissolve IBRA at end of February 2004, Bank

Indonesia needs to anticipate several issues related

to IBRA»s tasks being incomplete at the time of

dissolution. Pre-emptive steps are needed to achieve

IBRA»s final goals.

Government Guarantee Program (Blanket

Guarantee)

Uncertainty concerning continuation of the

government guarantee program, which so far has

been handled by IBRA, needs attention in order to

maintain public confidence in the banking industry

(which is already quite low, according to surveys).

Accordingly, there needs to be an effective transition

of the program from IBRA to the Government

Guarantee Program Implementing Unit, which will

take over IBRA»s tasks and responsibilities after

dissolution and prior to the formation of a deposit

insurance institution.

Impact of IBRA’s Dissolution

Bank Rehabilitation Program

Uncertainty concerning the bank rehabilitation

program (for recapitalization banks, taken-over banks,

and other banks under rehabilitation program) can

create negative perceptions of these banks» prospects.

In this regard, some institution or party needs to take

over IBRA»s responsibilities concerning the

rehabilitation process of these banks prior to handing

them over to BI. In addition, attention need to be

given to the possibility of changing exit requirements

concerning IBRA»s tasks.

Asset Management

Uncertainty concerning the management and

settlement of government assets at banks with frozen

operations/activities and taken-over banks, might

cause shortfalls in government revenue targets. This

could disrupt fiscal policy and create difficulties for

the government in servicing its debts. In turn, this

could lower the price of recapitalization bonds and

force losses on banks, due to marked to market

considerations.

2003 and Circular Letter number 5/21/DPNP dated 29

September 2003 concerning implementation of risk

management at banks.

Models for operational risk are implemented by

taking into account the probability of events and impacts

on profit/loss should those events occur. Events can

include fraud, fires, booking errors, and other human

mistakes. Calculation of the probability of events and

the event»s impacts are based upon the probability

distribution of the occurrence of the events. However,

before adopting this model, a bank should first have

sufficient time series data on loss events to be able to

predict the relevant probabilities.

Furthermore, to enhance the effectiveness of banks»

internal controls, BI has also issued a framework and

guidelines for effective internal bank control. Internally,

BI has also completed a framework for a risk-based

approach to supervision. This approach focuses on

measuring banks» inherent risks and risk control systems

or banks» compliance in implementing sound principles in

line with risk management. In parallel, enhancement of

the quality and skills of bank supervisors and audit

44


Trillion Rp Percentage

2002 2003Jan May Sep Jan May Sep

0

20

40

60

80

100

0

2

4

6

Total Deposits Growth

0.0

0.5

1.0

1.5

0

20

40

Capital CAR of Industry

Jan May Sep Jan May Sep

2002 2003


Total Deposits Growth

0

2

4

6

0

20

40

60

80

100Trillion Rp Percentage


2002 2003

personnel in implementing risk-based supervision are being

continuously undertaken.

3.2. DEVELOPMENT OF SHARIA BANKING

During 2003, the sharia banking industry experienced

quite rapid expansion of assets, around 60% (y-o-y),

reaching Rp7.1 trillion (Chart III.44). Asset expansion was

followed by capital expansion of around 17%, while third

party funds expanded by some 60%.

Despite financing extensions and fund channeling

that rose by 50% and 100%, respectively, the quality of

the industry»s earning assets were still sound. This was

reflected in non-performing financing of less than 5%

(Chart III.45).

In general, the sharia banking industry»s earnings

were quite good, although they dropped significantly in

2003 due to large business expansion undertaken by these

banks. Business expansion is expected to continue in the

near future, because market conditions are still very

favorable to growth.

Indonesian Moslem Leader Council»s Religious

Instruction on Proscribed Interest

In December 2003, the Religious Instruction

Committee of the Indonesian Moslem Leader Council

(IMLC) decided on religious instruction regarding interest,

based on the results of their national meeting. The Council

determined that interest is proscribed based on the sharia

principle that proscribes usury in all forms. However, there

are various perceptions among the public as to the meaning

of usury. Some parties outside the IMLC are of the opinion

that not all interest should be categorized as usury; other

Chart III. 45C a p i t a l

Graph III. 46D e p o s i t s

Chart III. 44Total Assets

0

2

4

6

0

20

40

60

80

100

120

140


2002 2003


Total Financing GrowthFDR

Chart III.47F inanc ing

45


0

1

2

3

4

0

5

10

15

20

Jan May Sep Jan May Sep2002 2003

ROA % ROE %

ROA ROE

0

50

100

150

200

0

5

10

15


2002 2003


NPL Nominal NPL (%)

Chart III.48Non Performing Loans

Chart III.49ROA & ROE

parties consider all forms of interest to be usury. Several

matters for consideration in limiting the prohibition of usury

include: Indonesia»s sharia banking network is not yet

widely available; sharia banking products that can

adequately facilitate more intensive international trades

are not yet available; and interest is acceptable as long as

it is agreed to by both parties. The basis of the IMLC»s

decision are: religious instruction regarding interest has

been discussed for quite some time within the IMLC; and

every religious instruction issued by the National Sharia

Board regarding sharia banking operational activities avoids

the application of interest.

3.3. DEVELOPMENT OF RURAL BANK

At the end of quarter II-2003, the total number of

active Rural Banks (that is, excluding Rural Banks with

frozen activities) stood at 2,123, of which 86 were

operating under sharia principles. Between May 2001 and

December 2003, there were 92 applications to establish

new Rural Banks. This large number of applications shows

investors» interest in participating in the development of

small businesses, which is the Rural Banks» market. This

also shows the public»s growing confidence in the prospects

for Rural Banks.

Expansion in Rural Banks» total assets came from

higher credits, mainly funded by deposits. On the side of

funds accumulation, Rural Bank performance still showed

stable growth on a positive trend, again indicating growing

public confidence in Rural Banks.

In line with their rising accumulated funds, credits

extended by Rural Bank also expanded significantly. Rural

Bank credits at the end of June 2003 stood at Rp7,739

billion. This rise in credits boosted the LDR to 79%

compared to 77% at end-2002. Meanwhile, NPLs rose

from 8.7% at end-2002 to 9.1% by the end of quarter I-

2003, before falling back to 8.6% by mid-2003.

In line with improving quality of credit, Rural Bank

profits also trended upwards, as reflected in current year

profits of Rp210 billion in quarter II/2003.

Looking ahead, prospects look good for the Rural

Bank industry. However, it will still face various constraints.

First, the quality of Rural Bank human resources is relatively

limited. Second, the number of Rural Bank»s supervisors is

not adequate. Third, there is tough competition in this

market, including BRI units, commercial bank micro service

units (at, for example, Bank BNI), non-bank financial

institutions and branches of commercial bank.

In relation to the above, Bank Indonesia is

implementing several strategies concerning Rural Bank

industry rehabilitation, enhancement of supervision,

development of a blue print, and strengthening of Rural

Bank infrastructure. The first strategy. Rural Bank industry

rehabilitation program, covers (i) restructuring of problem

Rural Banks through capital injections by owners, mergers,

46


acquisitions, and the promotion of new, quality investors;

(ii) technical assistance from USAID and the Asia

Foundation for problem Rural Banks within the Jabotabek

area. The second strategy is the enhancement of Rural

Bank regulation and supervision system. Third,

development of a Rural Bank blue print: (i) is one part of

the Indonesian Banking Architecture, which is adjusted to

the needs and characteristics of Rural Banks as commercial

micro banks; and (ii) concerns Rural Bank information

technology. The fourth strategy, strengthening capacity

and institutions, covers (i) Rural Bank certified training,

and (ii) cooperation between Rural Banks and commercial

banks/other institutions (the linkage program). Fifth,

development of supporting infrastructure, which covers

(i) formation of a deposit insurance institution; (ii)

empowerment of Rural Bank associations (e.g., Perbarindo,

Perbamida, Asbisindo); (iii) promotion of an Apex institution

for the Rural Bank industry, whose main role would be to

assist Rural Banks in solving liquidity mismatch problems;

and (iv) promotion of a rating agency for Rural Banks.

There are several important issues that need attention

for future development of the Rural Bank industry. First,

there have been complaints from several parties concerning

the relatively high credit rates charged by Rural Banks.

Second, the existence of a linkage program between Rural

(in billion Rp)

Table III.4 Rural Bank Major Indicators

MarMarMarMarMar

20022002200220022002 20032003200320032003NoNoNoNoNo SectorsSectorsSectorsSectorsSectors

DecDecDecDecDec20012001200120012001

DecDecDecDecDec20022002200220022002

∆∆∆∆∆(00-01)(00-01)(00-01)(00-01)(00-01)

JunJunJunJunJun SepSepSepSepSep DecDecDecDecDec

∆∆∆∆∆(01-02)(01-02)(01-02)(01-02)(01-02)

∆∆∆∆∆Dec 02-Dec 02-Dec 02-Dec 02-Dec 02-Jun 03Jun 03Jun 03Jun 03Jun 03

∆∆∆∆∆Jun 02-Jun 02-Jun 02-Jun 02-Jun 02-Jun 03Jun 03Jun 03Jun 03Jun 03

1 Total Asset 4.731 6.474 36,8% 6.91 7.514 8.393 9.079 40,2% 9.723 10.185 12,2% 35,5%

2 Loans 3.619 4.86 34,3% 5.251 5.781 6.419 6.683 37,5% 7.088 7.469 11,8% 29,2%

3 Deposits 3.082 4.28 38,9% 4.666 5.066 5.597 6.126 43,1% 6.629 6.891 12,5% 36,0%

- Saving Account 1.19 1.574 32,3% 1.661 1.706 1.867 2.002 27,2% 2.026 2.075 3,6% 21,6%

- Time Deposito 1.892 2.706 43,0% 3.005 3.36 3.73 4.124 52,4% 4.603 4.816 16,8% 43,3%

4 Profit & Loss 116 223 92,2% 73 151 294 338 51,6% 113 174 -48,5% 15,2%

5 NPLs 16% 12% - 12% 10% 9% 8,7% - 9,1% 8,7% - -

6 LDR 85% 81% - 81% 81% 82% 77% - 78% 79% - -

7 ROA 2% 3,4% - 1,1% 2% 4% 3,72% - 1,2% 2% - -

MarMarMarMarMar JunJunJunJunJun

Banks and commercial banks to boost bank intermediation

to small and micro enterprises. Third, concentrated Rural

Bank ownership; based on tentative data as of January

1999, 327 Rural Banks were owned by 29 groups. Fourth,

uneven geographical distribution of Rural Banks with

concentration in Java and Bali (83% of total Rural Banks).

3.4 LAW ENFORCEMENT

To assist the government in law enforcement in the

area of banking, in December 1998 Bank Indonesia

established the Team for Deviation Investigation in the

Banking Area (TIPPER), which was subsequently changed

to the Special Unit for Banking Investigation (UKIP). The

mission of UKIP is to undertake follow-on actions following

supervision and audit findings as well as public reports

that have underlying criminal aspects. This will be important

in achieving a sound banking system and in bolstering

financial system stability. It will also raise banks» compliance

with prevailing legislation and regulations in the banking

area. In achieving its mission, UKIP has determined strategic

goals that include disclosing in a clear manner each

problem or deviation and recommending legal action

against the alleged perpetrators.

The role of UKIP in stepping-up law enforcement is

also expected to have a preventive impact, such as an

47


Chart III.52Development of Banking Cases Transferred to Law

Enforcement Body (in number of banks)

Chart III.53Completion of Banking Cases (cumulative)

Chart III.51Development of Banking Cases, Where Investigations

Have been Stopped (in number of banks)

Chart III.50Development of Banking Cases Received by UKIP (in

number of banks)

announcement effect on players in the banking field.

Thereby, banksƒwhich are institutions based on trust and

operating with varied business riskƒwill be owned and

managed by persons with a high degree of integrity,

competence, and professionalism. In addition, banking

system stability as a key part of overall financial system

stability, needs to be enhanced and its sustainability

maintained. In the framework of achieving these

objectives, Bank Indonesia has developed the Indonesian

Banking Architecture program, which is expected to

provide guidance in achieving a sound, strong, stable and

efficient banking system and boosting national economic

development. Efforts can include stepping up supervision

and enhancing enforcement effectiveness. This latter

activity entails a stronger investigation process of banking

criminal acts, enhancement of supervision transparency

and regulation enforcement, customer protection, and an

ombudsman for banking problems.

1. Development of Banking Cases Investigations

Since its establishment through 2003, UKIP has

received 376 banking cases at 193 banks, with the highest

number of banks in 1999, namely 61 banks. Since then,

the number has dropped to an average of 32 banks per

year. These banking cases often involved several banks

that are reported more than once due to different locus

delicti or tempus delicti. The high number of deviations in

1999 suggests a critical era in the banking sector when a

(Number of Bank)

61

2732

37 36

0

10

20

30

40

50

60

70

1999 2000 2001 2002 2003

8

17

30

5

42

0

10

20

30

40

50

1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3

(Number of Bank)

1011

10

25 22

0

5

10

15

20

25

1 9 9 9 2 0 0 0 2 0 0 1 2 0 0 2 2 0 0 3

(Number of Bank)

Transfered to law40%

No furtherprocess

53%

in progress7%

48


Chart III.54Types of Banking Violation Cases Followed-Up During

2003 (by number of cases)

number of large banks were liquidated (or had their

business activities frozen) due to operational deviations

with criminal elements. Of the total cases received by UKIP,

78 banks (40%) were handed over to law enforcement

parties for follow-up; 102 banks (53%) cases could not

be investigated further; and 13 banks with 39 cases are

still under investigation. Cases that could not be

investigated further included cases that did not contain

criminal elements. On other occasions, these cases were

reported and handled by law enforcement parties, but

evidence could not be found (particularly at banks that

have been liquidated or their business activities frozen), or

banks» licenses have been revoked and banks» owners/

management have disappeared (particularly Bank

Perkreditan Rakyat).

2. Investigations of Suspected Banking Infringement

During 2003, UKIP conducted investigations at 61

banks. Out of these investigations, 86 cases could not be

continued because they were administrative in nature,

while 37 cases were strongly suspected to have criminal

elements. From the cases that have been investigated, types

of criminal deviations involve:

a. Fictitious changes to credits in order to avoid

regulations concerning the maximum limit for credit

extension, related to violations of both the limit as

well as of the reporting on fund provision.

b. Fictitious financial recording and reporting.

c. Financing of fictitious exports through L/C issuance.

d. Violations of commitments on CDO. And,

e. Abuse of authority by shareholders, commissioners,

directors, and bank officers

The modus operandi of recent banking criminal acts

include: fund withdrawals of other banks» on-call deposits;

illegal use of customers» negotiable certificates of deposit

(NCDs) for cash collatera ls or cash withdrawals on credits;

illegal liquidations of customers» deposits without the

customers» knowledge; and credit extensions with fictitious

NCDs as collaterals.

3. Implementation of CFTRA Functions By UKIP

In accordance with Article 45, Paragraph (3) of Act

15 of 2002 dated 17 April 2002 concerning Criminal Acts

of Money Laundering, UKIP has certain interim

responsibilities before the Center for Financial Transaction

Reporting and Analysis (CFTRA) is operational. In this

regard, UKIP is tasked to collect, maintain, analyze, and

evaluate information on suspicious transactions and to

report results of analyses on transactions that are suspected

to be criminal acts of money laundering to the Police and

Attorney General.

In executing these tasks for CFTRA (up to 20 October

2003), UKIP has received 291 reports of suspicious

transactions from 31 banks. Furthermore, based on

analyses conducted on these reports, analyses of 189

reports have not been followed up; analyses of 82 reports

have been transferred to the Police because of strong

indications of money laundering criminal acts; and analyses

of 20 reports are still in progress.

Reports have not been followed up for several

reasons. These include: the value of the transactions were

below the threshold of Rp500 million; the transactions

were normal business operations; transactions were

rejected by banks; customers» accounts have been closed

Authorization delinquencyby shareholder, commissioner,

directors, and other bank executives32%

Loans engineering to avoidlegal lending limit

regulation41%

Window dressing19%

Counterfeit exportfinance by usance L/C

3%

Commitment violenceto CDO

5%

49


BankingCrime33%

Fraud22%

Corruption15%

Terorist6%

Embezzlement9%

Counterfeit2%

Others13%

Grafik III.55STR reported to Police by Numbers of Reports

because the banks did not feel comfortable doing business

with the customers; or reports were related to cash, for

which reporting is not required. Meanwhile, 82 reports

that are suspected to involve criminal acts of money

laundering have been handed over to the Police. These

have a total nominal value of Rp2.42 trillion equivalent

covering banking crimes, fraud, corruption, embezzlement,

terrorism, counterfeiting, and others.

With the enactment of Act 15 of 2002 concerning

Criminal Acts of Money Laundering and its amendment,

Act 25 of 2003, the CFTRA already has acquired adequate

personnel and equipment, so it is ready to execute its

function. Accordingly, UKIP handed over these functions

to CFTRA on 20 October 2003.

4. Causal Factors in Banking Crimes

From experience to date, banking crimes often occur

due to the following factors:

√ Weak Internal Controls

In executing their operations, banks are generally

equipped with systems and procedures as well as

limits on authority and responsibility at various levels

of the organization. To ensure this system works

smoothly, a control mechanism is also established on

each transaction, to ensure that it is in accordance

with the systems, procedures, and authorities. In

practice, this control mechanism often does not work

as it should, particularly when transactions are

executed by or under the order of parties related to

the banks. In a large recent case, the bank»s branch

office internal control could not catch the deviation

because of dependency on higher-ranking officers at

the bank branch and regional office levels. The

existence of good systems, procedures, and authority

limits do not guarantee that a bank will be free from

criminal cases, if the internal control system does not

function properly as has happened in several well-

publicized cases. Currently, several large banks have

monitoring systems over branch transactions through

the use of information technology (IT). This monitors

limits of authority and the layering of authority in

implementing integrated control; it presents data and

information in a quicker and more accurate way for

decision-making by bank management; and it

enhances the quality of service to customers.

√ Weak bank internal systems and procedures

Several cases of deviation have been caused by

unclear systems, procedures, responsibilities, and

limits to authority. The lack of regulations on such

matters provides wide opportunities for deviations.

With unclear (or no) systems, procedures,

responsibilities, and authority limits, the control

function will not be of much help because there

are many weaknesses that can be utilized for

deviations.

1 Banking Crime 1,954,2612 Fraud 158,2643 Corruption 60,0014 Embezzlement 51,7585 Terrorism 5146 Counterfeit 2537 Others 198,117

Total 2,423,168

NominalNominalNominalNominalNominal(Rp Million)(Rp Million)(Rp Million)(Rp Million)(Rp Million)

Table III. 5STR Reported to Police

NoNoNoNoNo Predicate CrimePredicate CrimePredicate CrimePredicate CrimePredicate Crime

50


√ Low integrity and professionalism of human resources

People that own and operate banks, as institutions

trusted to manage public funds, must be professional

and of high integrity. In this context, integrity is the

main factor in deciding who sits in key positions, like

branch managers or division heads that have wide

authority. Such persons must not have fictitious

backgrounds or have violated banking practices, either

directly and indirectly. Meanwhile, the professionalism

and competence of bank management and executive

officers must have extensive knowledge and expertise

in banking and finance, as well as an ability to

strategically manage banks. Without integrity and

professionalism, people in authority are easily

controlled by parties operating in their own self-

interest. Such a situation would eventually cause

problems that could bankrupt their banks.

√ Sub-optimal Performance of Compliance Directors

and Compliance Units

In an effort to minimize the deviations in bank

operations, Bank Indonesia has determined that each

bank should establish a Compliance Unit and appoint

a Compliance Director, who is responsible for his

bank»s compliance with legislation and regulations in

the banking area. In practice, a Compliance Director

cannot work independently in executing his function

because he/she is still easily controlled by the people

who control the bank. The position of Compliance

Director is difficult. On the one hand, he/she has to

enforce bank»s internal and external regulations. On

the other hand he/she works for the interest of bank

owners and he/she is a member of the board of

directors and therefore cannot act independently. In

this context, the professionalism of a Compliance

Director is at stake. In many cases, Compliance

Directors function sub-optimally, which makes

continued violations possible.

√ Bank supervision and regulations still need to be

enhanced.

Rapid development of the number of banks and bank

offices in the past decade has not been matched by

an adequate supply of supervision and audit

personnel, in both quantity and quantity. In addition,

banking deregulation, which was launched through

PAKTO88, was not followed by adequate prudential

regulations, including on exit policy. Thus, many

violations occurred, including imprudent fund

channeling, particularly to related debtor groups, and

these eventually become non-performing credits.

√ Weak law enforcement regarding banking cases.

Another important problem is law enforcement, as

imposition of sanctions for violations is felt to be

inadequate. Administrative sanctions imposed by

Bank Indonesia are not potent enough to act as a

deterrent for wrongdoers. Therefore, many

banking cases that qualify as criminal cases entail

only light penalties, or are pronounced free from

legal prosecution, or are not even pursued by the

authorities. Consequently, banking crimes

continue.

5. Responsibilities of Banks» Directors

Under Bank Indonesia regulation number 1/6/PBI/1999

(concerning the appointment of compliance director and

standards of internal audit at commercial banks), the

Compliance Director is obliged to ensure that the bank

has fulfilled all Bank Indonesia»s regulations and prevailing

legislation. The Compliance Director must also monitor

and ensure that the bank»s business activities do not violate

prevailing regulations. In other words, a Compliance

Director is obliged to prevent deviations in bank operations

(including those with a criminal element) by setting the

steps required in the compliance procedure at each work

unit.

51


In addition, the bank»s board of directors have

responsibilities as follows:

1. Bank board of directors are responsible for good

supervision of all the bank»s business activities by

ensuring that the bank»s business activities are well

run.

2. Bank board of directors are not guarantors or insurers

of actions that are not proper or prohibited being

undertaken by bank executive officers. From the side

of criminal liability, board of directors are not

responsible for bank losses due to unlawful actions

undertaken by their subordinates, but still have to be

responsible from the point of view of management

accountability, as determined in Act 1 of 1995

concerning limited companies. Therefore, they must

supervise the actions of their executive personnel

thoroughly.

3. Bank board of directors must pay attention to the

implementation of prudential principles on every

business activity of the bank.

4. Bank board of directors must pay sufficient attention

to bank business activities even though all bank

business activities are running well. Board of directors

must know all pertinent facts of the business,

including ensuring that the compliance systems and

internal audit system are implemented in each work

unit.

5. Bank board of directors are not expected to monitor

bank routine business activities every day, but they

must have knowledge of the implementation of bank

business activities in general, and give general

directions for important matters in the bank»s

operational activities.

6. Bank board of directors are obliged to check the

implementation of prudential principles as part of their

general supervision and check the bank»s condition

sufficiently frequently.

6. Strategic Steps to Avoid the Occurrence of

Banking Crimes :

a. General awareness

All bank employees must be aware of the possibility

of the occurrence of banking crimes with their

implications.

b. Good understanding

Prevention of banking crimes must be stepped up in

the area of understanding the need for standard audit

guidelines and other types of security against the

possibility of crime in bank operations.

c. Risk assessment

The next step is to include the possibility of banking

crimes in business risks. Supervision guidelines must

be available for daily operations, up to formulating

action plans and operational strategies of each front-

line manager in the event that incidents deviate from

standard operating procedures.

d. Dynamic prevention

Dynamic prevention is risk-based supervision that

functions as a main tool in identifying constraints in

achieving the objective. If implementation of this

policy is quite strict, all levels of personnel will provide

supervision that will safeguard the bank»s resources

as part of their routine jobs.

e. Proactive detection

As a business entity susceptible to crime, bank

management and personnel must have an

understanding of banking crimes, risks that arise due to

banking crimes, and how those risks can be managed.

f. Investigation

As part of the overall audit policy, an ability to

investigate a banking crime must be part of a bank»s

organization. This can be done by an internal work

force/bank team or by experts external to the bank.

The bank crime audit policy must be based on

investigation standards.

52


In relation to the implementation of bank crime

audits, the following matters need close attention:

1. Security, including:

a. To develop a proactive security strategy.

b. To make security a principal matter.

c. To know where everything is.

d. To limit access.

e. To safeguard company equipment.

f. To protect the IT system.

g. To monitor for internet fraud.

h. To safeguard important company information.

2. Segregation of authority/duties.

3. Financial and operational audits.

4. The appointment of a Compliance Director and a

Compliance Unit.

7. Banking Cases in 2003

Major cases in 2003 included:

1. Fictitious exports using a Letter of Credit (L/C)

A bank took over an issuance L/C (WEB) and a standby

L/C submitted by several current account customers

(not debtors), which formally did not come from one

group. The proceeds from the discounted L/C were

to be used for settling the issuance L/C that had fallen

due. This happened repeatedly until quite a huge

nominal value had accumulated. In taking over the

issuance L/C, bank»s personnel and officers made

deviations from internal stipulations (procedures and

authorities) and other legislation (Banking Act, Act

on Criminal Acts of Money Laundering, Eradication

of Corruption Criminal Act, Criminal Law (KUHP), and

Bank Indonesia regulations). The deviations in the

handling of the L/C were:

- The opening bank was not a correspondent

bank.

- Taking over of the export documents was done

before there was acceptance by the issuing bank

(originating in a high-risk country) and there was

only the guarantee of a Letter of Indemnity.

- The issuance L/C that had fallen due was

extended by the customer service manager

without approval by the branch manager.

- A standby L/C had to be used as a counter

guarantee on the goods purchasing contract

between the exporter and importer by the bank

that took over the issuance L/C.

- There were discrepancies in export documents

(fake PEB, fake B/L, and an unclear applicant»s

address).

- Total and type of commodity were not

reasonable (export of sand to Africa).

- Exports were not executed (fictitious exports).

- Discounting proceeds were partly withdrawn in

cash and partly transferred to another bank for

the benefit of the group of the current account

customers.

2. Misuse of Officer Authority

A bank received a transfer from another bank through

the RTGS in a large amount to be placed as deposit-

on-call (DOC). Prior to the transfer, the officer of the

bank that owned the funds would communicate with

the officer of the operational office or branch

manager of the bank that received funds, and agreed

on some funds placement. The funds went directly

to the account of the receiving bank. Without

checking or verification by the operational division or

treasury division, the funds were booked into the

account of the branch office of the receiving bank.

The bank branch manager did not book the funds as

DOC, but through an intermediary gave the funds as

credit to another party. Every month interest was paid

directly by the funds user and not by the bank that

received the funds transfer. The bank that owned

the funds never questioned why the interest was paid

53


by another party that had no legal relationship with

the bank that owned the funds. The problem arose

only when the DOC fell due and the fund user did

not fulfill his obligation to return the funds.

Meanwhile, the bank that received the funds still had

the obligation to return the funds by, among others,

making a reconciliation of the funds of fund owners.

3. Misuse of Authority by Bank Officer

A customer transfer through RTGS, which was meant

to be placed as a deposit under the customer»s name,

was deviated and moved to a current account under

another party»s name based on a letter whose

authenticity was suspect. The modus operandi was

conducted as follows:

- Bank received a fund transfer through RTGS for

the benefit of a customer to be placed as the

customer»s deposit.

- On the same day, the bank officer was suspected

of sending a letter by fax containing an

instruction from the customer to the bank to

transfer those funds to a current account of

another party.

- The change in the mandate of the fund

placement actually had to be done in accordance

with the RTGS regulation, namely the instruction

to change also had to come through the RTGS;

it could not be done through letter/fax/other

method.

- Based on investigation, the authenticity of the

customer letter was doubtful among others

because the letter head and number of the letter

looked like they have been tampered with; the

submission of the letter was by fax; and the

officer»s signature was not acknowledged by the

customer.

4. A Case of Credit with Cash Guarantee (cash collateral

loan)

A bank received a transfer from another bank for the

benefit of a customer»s current account, which was

subsequently transferred into a deposit account by

the customer. That deposit was used as a credit

collateral under the name of another person that had

not met legal and prudential principles. This deviation

involved:

- The credit agreement letter (CAL) was blank

(nominal value, time period of the credit, etc.

were not written yet) except for the debtor»s

signature.

- The debtor did not sign the CAL in the presence

of a bank officer. Instead the blank CAL was

taken by a third party (an intermediary) for

signing by the candidate debtor, so its

authenticity was doubtful.

- The CAL was made without being legalized by

a notary.

- The credit analyst officer did not meet and

conduct an interview with the candidate debtor.

- The type of business and objective of the credit

were not clear. Plus, the debtor was physically

disabled and thus his capacity to conduct

business was doubtful.

- At the time of credit withdrawal, the funds were

transferred directly to another person»s

(intermediary) account in another bank based

on a transfer instruction letter from the debtor,

whose authenticity was doubtful.

- Every month interest payments were made by

another person (intermediary) by debiting the

intermediary account based on an authorization

letter.

54


55

Chapter 4 Non-bank Financial Institutions

Chapter 4Non-bank FinancialInstitutions

56


57


In 2003, the condition of non-bank financial institutions

(NBFIs) was quite stable. They continued to grow, but at a

slower pace than in 2002. The downward trend in SBI and

deposit interest rates reduced returns on the investments

of insurance companies and pension funds. To adjust,

insurance companies and pension funds shifted their

investments into other instruments such as bonds,

marketable securities guaranteed/issued by the

government and mutual funds. Looking ahead, with

continuing low interest rates, NBFIs need to implement

good risk management, or the industry will face increased

risk of deteriorating profitability. Meanwhile, the role of

the NBFI industry supervisory authority has become more

important as regards the issuance of regulations for

prudential development of the industry.

With improving economic and financial climates in

2003, the financial condition of the industry was quite

stable, albeit with uneven growth. The positive

development of the banking industry during 2003 was

not immediately followed by NBFIs. Expansion of total

assets, capital, and total investments of the insurance and

pension fund industries -which have quite large shares in

the financial industry- did not result in higher profits. This

was due to those industries» investment portfolios being

dependent upon bank deposits, which tended to decline.

The downward trend in deposit interests for more

than one year has shifted funds into the capital market.

This shift, which is indicated by the high level of the

composite stock price index and by rapid developments in

the bond and mutual funds markets, reflected improving

public confidence (Graph IV.1). Investment expansion, both

by the general public and investment institutions, has

Chapter 4Non-bank Financial Institutions

heightened risks for investors and financial institutions.

This has led the supervisory authority to issue new

regulations intended to safeguard public funds and the

stability of the industry itself. The regulations were mainly

issued for the insurance industry concerning institutional,

operational and investment issues; new regulations

applicable to the pension fund industry mainly concerned

investment issues.

The role of NBFIs in financial system stability cannot

be ignored, despite total assets that constitute only 9% of

the whole financial industry (Graphs IV.2 and IV.3). The

development of various innovative financial products has

tightened the linkages between banks and NBFIs.

Consequently, instability arising in one institution might

impact the other. Cooperation in product marketing, for

example bancasurance (Box IV.1 Bancasurance:

Advantageous for All Parties?), risks the reputation of banks

that market this financial instrument, despite it being an

insurance companies» product.

In line with the continuing trend of low interest rates,

the insurance and pension fund industries are expected to

Chart IV.1 Developments of Shares, Bonds, Mutual Funds

Source : CEIC, Bapepam

Shares, Goverment bonds (Trillion Rp) Corporate bonds, Mutual funds(Trillion Rp)

0

50

100

150

200

250

300

350

400

450

0

10

20

30

40

50

60

70

80

90

100

2001 2002 2003

Shares Goverment BondsCorporate Bonds Mutual Funds

Dec Dec Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

58


grow in 2004, but at a slower pace. Although shifting of

the portfolio pattern to non-bank products has started,

bank deposits would still be the largest investment asset,

considering that safety would be a major consideration in

insurance and pension investments. Discontinuation of

the blanket guarantee program, in conjunction with the

establishment of a deposit insurance institution, would

be another consideration for the insurance and pension

fund industries. Both pose risks for the NBFI industry.

There are a few steps that could be taken by the

industry to address these various issues. As regards shifting

investments to non-bank products, there is a need to

increase financial management performance (ALMA) in

terms of investment fund management within an

environment of global competitiveness and low interest

rates. Also, the role of the supervisory authority for NBFIs

has become more important, especially as regards the

issuance of regulations to support development of NBFIs

and to ensure prudence in NBFIs» business.

4.1. The Insurance Industry

The insurance industry tended to slowdown during

2002. Comprising 174 companies with a total share of

3.4% of the financial industry»s total assets, the insurance

companies (both life and general insurance companies)

faced many challenges during that year. Interest rates that

trended downward continued to put pressure on the

industry»s profitability, because most of the insurance

companies» investment portfolios was in deposits. In

addition to lower interest rates, the insurance industry

faced other challenges such as competing premiums,

efficiency, fulfillment of risk-based capital (RBC), and many

new regulations, such as that concerning fit & proper tests.

These factors have prompted several insurance companies

to consider a merger strategy. Prominent positive

developments were innovations in alliances and

modernization of insurance products (bancassurance and

unit-link), particularly at joint venture/multinational

companies (Manulife, AIG Lippo, and Prudential Banc).

Of a total of 174 insurance companies in 2002, 60

were life insurance companies with a share of 37.3% of

the insurance industry. Of this total, 15 companies (8 of

which were joint venture companies) dominated (85%)

the life insurance market share. Almost 30% of this large

group is related to banking groups whose policies influence

investment behaviors of the insurance companies. This

significant interrelation with the banking industry, indicates

a quite high systemic risk should instability arise in the

insurance industry.

Meanwhile, of a total of 105 general insurance

companies in 2002, 23 of them (9 of which comprised

joint venture companies) dominated (71.4%) the general

insurance market share. This condition reflected tighter

Chart IV. 2Asset Composition of Financial Institutions

Chart IV. 3 Total Non-Bank FinancialInstitutions 2000 √ June 2003

Banking90%

InsuranceCompany

3%Pension Fund

3%Securities

Corporation1%

FinancingCorporation

3%

Pawn-Shop0%

Sources : DJLK, Ministry of Finance

-

50

100

150

200

250

300

350

400

2000 2001 2002 Jun-2003 *

Life Insurance General Insurance Pension Funds

Corporate Bonds Securities

Unit

59


Box IV. 1 Bancassurance - Advantageous for All Parties?

Chart Box 4.1.1Forms of Bancasurance in Asia

Chart Box 4.1.2Products of Bancasurance in Asia - 2000

Joint Venture Marketing Agency Group *)

14 % 17 %

69 %

12 %

16 %

72 %

Non Life Insurance Life Insurance Mixed

A critical point in handling bancassurance

development is the need to provide an explicit legal

basis for banks to undertake this kind of business. It

will also be important for customers to distinguish this

product from other banking products.

In addition to marketing mutual funds through

banks, another form of vigorous integration between

banks and non-bank financial institutions since the

beginning of 2000 is bancassurance.

Bancassurance (French terminology referring to

the sale of insurance through bank offices) can be

divided into four types:

1. Marketing Cooperation: This entails limited

cooperation where banks only distribute

insurance products, as either stand-alone

products or synergized with bank products. In

general, this type of cooperation does not incur

exchanges of customers» data and only involves

limited investments.

2. Strategic Alliances: A more complex form

cooperation, which involves efforts in product

development, provision of services, marketing

management, recruitment of sales personnel, and

investment in information technology.

3. Joint Venture: This type of cooperation requires

long-term commitments and a pattern of more

intensive customer data information exchanges.

4. Financial Services Group: A form of operational

cooperation, which integrates various financial

service products and provides a one-stop

financial service.

In Asia, the most dominant form of

bancassurance is marketing cooperation (69%), with

unique characteristic that 72% of bancassurance

products is life insurance. This is largely due to the

fact that the general data required to close an

insurance policy is often already available in a bank»s

customer data. In Europe, more than 60% of life

insurance is sold through banks. By contrast, in Asia

only Hong Kong has achieved 25%.

What prompted rapid growth of

bancassurance ?

A downward trend in Net Interest income (NII),

owing to interest rate declines and the global recession

of recent years, are the main factors that have

prompted banks to aggressively seek non interest

income (fee-based income). Also, cooperation with

60


Chart Box 4.1.3% Sales of Life Insurance via Banks √ Europe 2000

Chart Box 4.1.4% Sales of Life Insurance via Banks in Asia - 2003

Source : LIMRA

France Portgl Spain Blgm Irlnd Swedn Nthrld U K

80

70

60

50

40

30

20

10

0

Percentage Percentage30

25

20

15

10

5

0Hong Kong Singapore Malaysia Indonesia Thailand China

Source : AXA Life

market conditions in general insurance as compared to

life insurance. Tough competition in the general insurance

market was prompted by rate wars among general

insurance companies. At the same time, in order to cover

potential risks, general insurance companies normally

undertake reinsurance, for which premiums are increasing.

This situation was aggravated by a decline in investment

income due to lower SBI and deposit rates. Consequently,

profits earned by general insurance companies during 2002

were lower than the previous year; ROA, ROE, and ROI all

recorded declines (Graphs IV.3, IV.4, and IV.5).

Lower deposit rates prompted the general insurance

companies to adjust their investment portfolios. The

option taken by many insurance companies was to shift

from investments in banking products (deposits) to capital

market products (shares, bonds, SUN, and mutual funds)

with the realization that risks could be higher. There was

considerably more investor interest in government

an insurance institution of international reputation will

enhance the local bank»s brand image, while product

diversification adds to the bank»s trustworthiness to

its customers perseption.

For the insurance institution itself,

bancassurance is one way to increase market

penetration by taking advantage of the bank»s

customer database and office network. For this reason,

general insurance institutions that aggressively

undertake cooperation with local banks, are usually

foreign companies that do not have a network in the

local market; to compensate, they chose a local bank

that already has a wide office network.

For the customers, bancassurance has an

additional benefit, namely the ease and generally

lower premiums provided by a one-stop financial

service.

On this basis, bancassurance seems to be an

advantageous solution for all parties. However, there

are several critical points that must be the concern in

developing this financial product. For example, an

explicit legal basis related to licensing for banks to

deal in bancassurance business would be very useful.

On the other hand, it will be very important to

enhance customer knowledge to enable them to

differentiate insurance products from banks» own

products. These will be critical points in ensuring an

advantageous solution to all parties and to prevent

bancassurance from becoming counter-productive to

the financial system stability.

61


securities (Surat Utang Negara/SUN), mutual funds, and

bonds, all of which promised higher returns. Nevertheless,

investments in deposits remained a core component of

insurance companies» portfolios, due to liquidity and

safety considerations as well as growing alliances with

the banking industry through bancassurance (Graphs IV.7

and IV.8).

At the end September 2003, the Ministry of Finance

(the insurance industry»s supervisory authority) issued

several new regulations concerning fit & proper tests,

business operations, audits, financial soundness, and

licensing. These regulations are considered a first step

towards a framework to improve the industry during the

post-crisis period, after the erosion of confidence due to

financial problems and limitations on business activities at

several insurance companies. As regards the regulation

on fit & proper tests, issues concerned the objectiveness

of implementation as well as the possibility of reducing

the number of members of boards of commissioners or

directors because many could fail checks on background

or personal history. (Box IV.2: Implementation of

Regulations on Fit & Proper Tests in the Insurance Industry).

Chart IV. 4ROA Value - Life and General Insurance Companies

Chart IV. 5ROE - Life and General Insurance Companies

Chart IV. 6 ROI Value √ Life and General Insurance Companies

Sources : Industri Asuransi Indonesia, InforDev

General Insurance Life Insurance

1997 1998 1999 2000 2001 2002-15

-10

-5

0

5

10

15

20Percentage

Sources : Industri Asuransi Indonesia, InfoDev

Percentage

1997 1998 1999 2000 2001 2002-80

-60

-40

-20

0

20

40


Source : Industri Asuransi Indonesia, InforDev

Percentage

-20

-15

-10

-5

0

5

10

15

20

25

30

1997 1998 1999 2000 2001 2002


Chart IV. 7 Investment Composition of Insurance Industry √ 2002

Chart IV. 8 Investment Composition ofInsurance Industry √ Quarter II/2003

Other Investment1%Building & Land

4%

Morgages0%

Polis Loan2%

EquityParticipation

13%

Mutual Funds6%

Securities guarantedby goverment

16%

Bonds14%

Shares5%

BI Sertificate1%

SertificateDeposit

0%

TimeDeposits

38%


Other Investment1%Building & Land

4%

Morgages0%

Polis Loan4%

EquityParticipation

13%

Mutual Funds4%

Securities guarantedby goverment

13%

Bond13%

Shares4%

BI Sertificate0%

SertificateDeposit

0%

TimeDeposit

44%


62


Box IV. 2 Implementation of the Regulation on Fit & Proper Tests in theInsurance Industry

The insurance industry is facing tight new

regulations concerning institutional, financial, and

soundness matters as well as their human resources.

The regulation on fit & proper test on members of

boards of directors and commissioners is a positive step

towards the improvement of the insurance industry

climate in order to maintain public confidence.

Implementation of this regulation needs to consider

the impact on industry restructuring and the possibility

of a decline in confidence if the public does not have a

good understanding. There is also a need to monitor

potential mismanagement, which could put financial

pressure on the insurance and other financial industries.

As one of the industries that is very much based

on confidence, the insurance industry became more

tightly regulated in September 2003 with the issuance

of 6 new regulations. These complementing

regulations were issued in an effort to create a tough

insurance business climate and to increase human

resource competence and integrity. In broad outlines,

these regulations concern (1) Evaluation of Ability and

Compliance (Fit & Proper Test) of Insurance Companies»

Members of Boards of Directors and Commissioners

(Minister of Finance/MOF decree number 421); (2)

Implementation of Insurance and Reinsurance

Companies» Businesses; (3) Audit of Insurance

Companies; (4) Financial Soundness of Insurance and

Reinsurance Companies; (5) Licensing and Undertaking

of Business Activities of Insurance Support Companies;

and (6) Business Licenses for Insurance and Reinsurance

Companies. MOF decree number 421 is considered

by several insurance industry players as a first step

towards improvement of the insurance industry.

The Insurance Industry»s Problems

Currently, the insurance industry is facing

significant pressures, including: market competition,

even with banks and security companies; fulfillment

of the RBC regulation; regulations concerning premium

income; investment risk; and potential erosion of

confidence due to financial problems that have been

experienced by several insurance companies (on which

limitations on business activities have been imposed).

As regards the human resource quality of management,

there are indications of less-qualified parties that might

create a moral hazard problem and erode public interest

in insurance. Currently, fulfillment of the RBC regulation

and its relation to investment products is only a gradual

process through 2004. The last portion of this

regulation will strengthen processes related to the

liquidation of unsound insurance companies.

Meanwhile, the regulation on fit & proper test poses

several challenges concerning objectiveness and the

quality of implementation. It is also possible that many

members of top management will not pass, which has

the potential to raise doubts about the stability of the

industry, including the safety of liabilities that are not

covered by the government guarantee program.

Improved Performance Through Infrastructural

Support

Currently, it is estimated that there are 980

officers of insurance companies that will be required

to take a Fit & Proper Test. Of this total, some members

of boards of commissioners and directors are in their

current positions due to family relationships or they

are suspected to be incompetent in the insurance area

63


or they are related to DOT (black list in banking).

Issuance of the 6 regulations is a step towards

increasing public confidence in the Indonesian

insurance industry. In particular, they will strengthen

the capability of each individual in the insurance

industry; a higher, more uniform quality of the industry»s

human resources will facilitate more professional

techniques.

impact on companies» (and the industry»s) finances,

which would lead to liquidation of investments in the

capital market and banking industry. Better regulations

concerning company soundness and audits as well as

institutional matters is one way to strengthen regulation

of the industry. Implementation of MOF decree number

421 over 2 years takes into consideration its impact on

the insurance industry.

From the financial system side, implementation

of these 6 new regulations in the insurance industry is

part of series of steps to maintain stability of the

financial system. Reliable human resources for

managing the insurance financial, risk and marketing

functions is vital, supported by strong insurance

industry infrastructure. Issuance of MOF decree

number 421 makes it important to monitor for possible

fluctuations in public confidence in the short-term,

especially considering socio-political conditions during

the general election when the public is more sensitive

to negative issues. On the investment side, where the

investment market is still susceptible to foreign

developments, the insurance industry needs to take

pre-emptive steps regarding its capital market

investment portfolio. Furthermore, public socialization

will be important for the understanding of MOF decree

number 421 and other regulations. This is necessary

to avoid undermining public confidence in local

insurance companies, which could lead to a rush of

redemptions and accompanying financial pressures.

Implementation of MOF decree number 421

along with other regulations will have various

implications, including the possibility of vacant positions

at the level of directors and commissioners. Other

impacts might involve delays in the continuation of

the internal rehabilitation programs of companies;

possible cases of frauds at some companies whose

officers do not pass the test; and consolidation in the

number of insurance companies. If this situation is

not properly understood by the public, it has the

potential to lead to a rush of redemptions, creating a

domino effect on companies or prompting a shift to

foreign insurance companies. Redemptions would

To date, the activities of insurance companies have

been very closely related to banks, mainly because most

of their funds are invested in banks. Also, interest rate

declines have put pressure on investment income.

Meanwhile, risks have increased due to the shift in

investments to the capital market. Furthermore, this

industry is very sensitive to various issues and competition,

which holds down premiums. Cooperation regarding the

marketing of bancassurance products in conjunction with

several banks introduces a new risk for the banks, i.e.

reputation risk, should problems arise related to the jointly

marketed insurance products.

Table Box 4. 2.1 Composition of Members ofBoards of Commissioners and Directors

Life Insurance 171 148 319General Insurance 318 269 587Social Insurance 24 23 47Reinsurance 14 13 27Total 527 453 980

CompanyCompanyCompanyCompanyCompany CommisionersCommisionersCommisionersCommisionersCommisioners DirectorsDirectorsDirectorsDirectorsDirectors TotalTotalTotalTotalTotal

64


Market liberalization has encouraged many

international insurance companies to enter the Indonesian

market, usually with large capitalization and more

professional human resources. Their presence could

become a separate challenge by increasing competition

through product development/innovation, while domestic

insurance companies still tend to market insurance

products in the traditional way.

In the future, the insurance industry is not expected

to change much. In particular, any shift in investment

patterns cannot be undertaken abruptly. Instead, it has

to be undertaken gradually considering that this industry

is oriented towards long-term investments. At the

beginning of 2004, the introduction of risk-based capital

(RBC; a minimum of 100% for each insurance company)

will be effective. Meanwhile, by the end of 2004, the RBC

of insurance companies should reach 120%. As of

December 2002, 15 general insurance companies had not

fulfilled the 100% RBC requirement. The regulatory

necessity to raise capital, amidst limited capacity for

additional capital by domestic companies, limits their

capability for product development.

Shifts in investment patterns by insurance

companies need to be undertaken only after thorough

consideration. For this purpose, enhanced management

performance in investment fund management is vital.

Rising inflows into the capital market that are not backed

by good financial management could spur liquidity

problems if the investments experience default risk,

redemption risk, or a decline in the prices of marketable

securities. Pressures related to such liquidity problems in

the insurance industry could have a systemic feedback

into the banking industry. Meanwhile, in order to fulfill

the 100% RBC requirement, insurance companies can

undertake several steps, including raising additional

capital, undertaking mergers, or focusing on sectors with

better prospects.

4.2. The Pension Fund Industry

To date, development of investment aspects of the

pension fund industry has been more prominent than their

institutional and operational development. On the

institutional side, there are two types of pension funds,

namely employer pension funds (EPF; which are formed

by companies that provide jobs) and financial institution

pension funds (FIPF; which are formed by financial

institutions, like banks and insurance companies). Two

types of benefits are offered, namely Fixed Pension Benefits

(EPF) and Fixed Contributions (FIPF). In the last three years,

FIPF have grown quite significantly compared to EPF. The

total number of pension funds reached 342 (December

2002), where many EPFs and FIPFs were closely related to

banks (state bank, private banks, BPD, foreign banks), in

terms of both establishing the pension funds and program

implementation. Meanwhile, total assets of pension funds

have a 3.0% share in total assets of financial institutions.

This interrelationship suggests potential for systemic risk

to the overall financial system should the pension fund

industry not be managed prudentially.

Basically, pension funds are institutions that have

very tight regulations. To date, the investment regulations

have been extremely conservative and prudent; most

investments are in deposits, although a share in the

capital market is possible. As with the insurance industry,

declining deposit interest rates have contributed to a shift

in the pattern of pension funds» investments. During

2003, the share of deposits has started to decline in favor

of capital market instruments. However, deposits still

dominant, mainly because pension funds» policies follow

the lead of the parent companies (banks); non-bank

parent companies also tend to place their funds in

banking products due to historical relationships between

the parent company and specific banks. Without

efficiency improvements, this shift risks a continuous

decline in the industry»s income.

65


Chart IV. 9ROA & ROI Values - Pension Funds


1998 1999 2000 2001 2002

Percentage

0

5

10

15

20

25

30

ROA ROI

Performance of pension funds (ROI and ROA)

improved only very slightly in 2002 (0.8% and 0.9%), while

their total investments rose to 17.9% (Graph IV.9). This

was due to declining interest rates on bank deposits.

Meanwhile, this industry is going to face various new

constraints, for example, stemming from the plan to reduce

the coverage of the guarantee program. Limits of deposit

insurance (through the Deposit Insurance Institution) might

cause pension funds» investment in deposits (which is often

huge) to exceed the guaranteed limit. As a result, credit

risk faced by the industry could rise and adequate levels

of capital will be very important.

Currently, the pension fund industry in Indonesia is

still very much dependent on the banking industry as

reflected in its fund placements in deposits. However, the

industry»s rate of return is trending downward in line with

declining interest rates. But a deterioration in pension

funds» performance will also influence banks» performance,

for example, through a decline in third party funds or lower

fees obtained through execution of pension fund activities.

In addition, failure on the part of pension funds that are

established by banks would bring reputation risk to bear

on the banks.

In 2004, pension funds are not expected to change

much. Despite great potential, pensions funds will still

face constraints. Investment patterns that are overly

prudent prompt the majority of funds to be invested in

deposits, probably ensuring lower returns for the time

being.

To boost pension funds» performance, efforts can

be made to increase public interest in pension funds,

particularly through FIPF. Also, it will be important to

strengthen their management of investment funds in

an environment of global competition and lower interest

rates.

66


67

Chapter 5 Capital and Money Markets

Chapter 5Capital and Money Markets

68


69


Indonesia»s capital markets experienced extraordinary

development during 2003. The stock market had the

second best performance in the world, while the bond

market expanded rapidly with a tendency towards

oversubscription with each new issuance. For their part,

the interbank money markets did not fluctuate in any way

that could endanger financial stability.

5.1. Development of Indonesia»s Capital Market

During 2003, the capital market experienced

extraordinary expansion as indicated by rises in the

composite stock price and bond price indexes of 63%

and 66%, respectively. This is evidence of the recovery

of the capital market as an alternative source of

financing and investment. However, this growth needs

to be closely monitored due to continuing high credit

and bond refinancing risks. In addition, the valuation

of capital market products may not yet reflect

fundamental values. Such conditions pose a challenge

for the capital market developers to ensure that the

capital market does not become a source of instability

in the financial sector.

Bank Indonesia»s attention to development of the

capital market has become more intense as products and

transactions in the financial system √including the capital

market√ become more integrated. Consequently, problems

arising in the capital market could have a systemic effect

on the broader financial system.

In general, the capital market is becoming more

important to Indonesia»s financial system (Chart V.1). In

2003, the share of financing issued by the capital market

in total financing rose by 5 percentage points compared

Chapter 5Capital and Money Markets

to the previous year, indicating the growing importance

of the capital market as a source of business financing.

During 2003, investment conditions in Indonesia

were still considered to be relatively high-risk for

international investors and rating institutions. This was

reflected in the relatively high sovereign yield spread of

Indonesia»s issuances compared to other South East Asian

countries. Also, the yield spread for Argentina (which

again plunged into crisis) was only 400 bps more than

Indonesia»s. This high risk rating had a negative impact,

namely increasing the interest expense of Indonesia»s

issuers; they had to pay an additional risk premium of at

least 2.16%. This high risk perception was also reflected

in Indonesia»s low rating compared with other developing

countries (Chart V.2).

Chart V.1 A Shift in The Role of Bank Loans VersusCapitalization of Stock and Bond Markets

Sources: Statistic Bank, Bloomberg and CEIC

Bank Loans (26%)

Stock Market Capitalization(23%)

Government BondsMarket Capitalization (22%)

Corporate Bonds MarketCapitalization (23%)

Bank Loans(31%)

Stock Market Capitalization(21%)

Corporate Bonds MarketCapitalization (17%)

Government BondsMarket Capitalization

(31%)

70


However, in line with improving macroeconomic

conditions during 2003, confidence in the Indonesian

economy strengthened, as indicated by Indonesia»s

improved ratings from several international rating

institutions. As a result, there was a rise in capital inflows

during 2003, particularly in the form of portfolio

investment into Indonesia»s capital market.

Improved capital markets have provided many

opportunities for banks and corporations to undertake

investments using alternative financing sources. For banks,

financing through issuance of bonds and shares has

become an alternative to accumulation of customers»

funds. Meanwhile, banks» investments in the capital

market remained limited to non-stock instruments.

Through these instruments, banks can diversify their risk.

At the same time, capital market-based products sold

through the banking industry and developed to maintain

customer bases need to be monitored carefully, considering

the potential risks to banks» reputations.

In line with GDP»s projected growth and conducive

macroeconomic conditions, capital markets look set to

perform even better in the coming years. This is expected

to give a boost to the corporate sector in terms of

alternatives to funding from the banks. However, capital

market analysts predict a possible decline in market activity

due to a wait-and-see attitude around the general election

to be held in April 2004. There is a worry that security

and socio-political disruptions could hurt the capital market

because investors would tend to sell their assets and shift

into cash or other financial instruments (a flight to safety).

Within the framework of maintaining financial

stability, there is a need to step up the importance of good

corporate governance. This is particularly the case as

regards transparency, supervision and enforcement of

regulations, considering that there are still many cases of

violations like insider trading, cornering, and window-

dressing. In addition, the government»s plan to issue an

international bond √to be used for refinancing and as

Indonesia»s international bond benchmark√ needs to be

executed with the right timing.

Stock Market

In general, development of the stock market

contributed to financial system stability by providing an

alternative instrument for investors, for risk diversification

and an alternative source of corporate financing, thereby

reducing dependence upon bank financing. With such

alternatives, the risk of an excessively deep and extended

crisis due to gridlock of financing flows can be minimized.

Development of the stock market was not only

marked by greater market liquidity, but also by investors

having deeper understanding of conditions in the stock

market. Indonesia»s stock market had the second best

gain in global performance, second only to Thailand. The

index, which began the year at 409.13, rose by almost

66% during the year, ending 2003 at 691.90. This rise

was not only dominated by blue chips companies (namely

Telkom, Indosat, Gudang Garam, HM Sampurna and Astra

Internasional) but also by non blue chips like Bumi

Resources, Bank BRI, PN Gas, etc.

Since 2000, stock price volatility has been relatively

low, without any fluctuations like those during the period

Chart V. 2Ratings of Indonesia and Other Developing Countries

0

2

4

6

8

10

12

14

16

18

94 95 96 97 98 99 00 01 02 03

Indonesia Thailand Malaysia Argentina

71


Box V. 1 Mutual Funds

Mutual funds, which have experienced extremely

rapid growth since 2002, have dropped off since

October 2003. This was due to quite large redemptions

at one of the mutual fund investment managers

towards the end of October 2003. Concerns over

potential systemic risk disappeared as the risk did not

materialize, because the investment manager was able

to fulfill its obligations to investors with the support of

loans from its parent company. To avoid reoccurrence

of such fluctuations in the mutual funds market, BI

will continue to make efforts to coordinate market

players and the relevant authorities.

After having experienced extremely rapid growth

in 2002 that continued through quarter III-2003,

mutual funds contracted beginning in October 2003.

In November, mutual funds NAV dropped by Rp13

trillion from its peak in September 2003, to Rp72.8

trillion. This was due to large redemptions, particularly

at one large investment manager. Redemptions were

heavy for two types of mutual funds, namely mutual

funds under cooperation with banks (constituting a

quasi-deposit product) and pure mutual funds, which

did not involve cooperation with banks.

Redemptions of quasi deposit mutual funds were

executed in accordance with the bank»s action plan in

response to BI»s request for observation of prudential

principles in mutual fund activities, reinforced by BI»s

letter dated 3 October 2003 to all commercial banks.

Because that particular redemption was planned al-

ready, it did not spur great concern.

The other part of the redemption occurred in pure

mutual funds, as mentioned, those unrelated to banks.

The triggering factor for this rush of redemptions was

largely due to a change in the method of evaluating

net asset value (NAV) of mutual funds, from an ac-

crual basis to marked to market. This change prompted

redemptions because the new method caused NAVs

to decline.

Redemptions of mutual funds resulted in a decline

in the total amount of government bonds held by

mutual funds, because most mutual funds are «fixed

income», with the underlying investments being

government bonds. In September 2003, the total

amount of government bonds held by mutual funds

reached Rp59.4 trillion; as of November 2003, it had

dropped by 26.1% (Rp15.5 trillion).

Table : Performance of Mutual Funds

DescriptionDescriptionDescriptionDescriptionDescription Sep 2003Sep 2003Sep 2003Sep 2003Sep 2003 Oct 2003Oct 2003Oct 2003Oct 2003Oct 2003 Nov 2003Nov 2003Nov 2003Nov 2003Nov 2003

1. Number of mutual fund 171 181 181

2. Share holders/investment unit: 179,360 184,934 174,892

- foreign 432 469 463

- domestic 178,928 184,465 174,429

3. Net Asset Value (Trillion Rp) 85,87 79,24 72,83

4. Outstanding Number of shares/

investment unit (million) 73,684 68,442 63,263

Source : BapepamChart Box V. 1.1

Developments of NAV and Managed Funds

Source: Capital Market Supervisory Agency (Bapepam)

Managed Fund NAV

12 12 12 12 12 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11

Trillion Rp

0

10

20

30

40

50

60

70

80

90

100

96 97 98 99 00 01 2002 2003

72


To avoid a reoccurrence of such fluctuations in

mutual funds √which could disrupt the financial

system√ cooperation among related parties is very

important. In this regard, to enable early anticipation

of problems, BI continues coordination with market

players (investment managers, banks, etc) and related

authorities (Bapepam and the Ministry of Finance)

through meetings and other communications.

Bapepam has already undertaken steps to support

sound development of mutual funds. During 2003,

Bapepam dissolved 17 mutual funds products that were

considered inefficient in their management and having

total managed funds below the minimum limit as

regulated in the collective investment contracts.

1997-99. In 2003, stock price volatility tended to be quite

limited (around 5%), indicating that the market has

developed well and become more efficient (Chart V.3).

However, the stock prices may not reflect corporations»

fundamental conditions. As a result, the market was still

susceptible to issuers» business risk, shocks and negative

sentiment concerning non-economic conditions, such as

security.

In line with developments of the global and domestic

stock markets as well as implementation of government

programs stated in the white paper, stock prices are

expected to continue rising in 2004. However, a market

correction might occur during quarter I-2004 when stage

1 of the general election is underway.

Within the framework of developing the stock

market, there is a need to ensure good corporate

governance, particularly in terms of transparency and

implementation of tight supervision by the supervisory

authority (Bapepam). Many violations still occur and these

could undermine investor confidence, especially among

small investors.

The rising number of banks undertaking sales of stock

to the public, particularly through initial public offerings

Chart Box V. 1.2Development of Government Bonds

Chart Box V. 1.3Development of NAV & Government Bonds

Source : Database BI, Capital Market Supervisory Agency (Bapepam)

NAV Goverment Bonds

0

10

20

30

40

50

60

70

80

90

12 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11

00 01 2002 2003

Trillion Rp

Chart V. 3 Composite Stock Price Index and Volatility

(y = 509.23e-0.0013x))Source : CEIC, (processed)

0

5

10

15

20

25

30

35

0

100

200

300

400

500

600

700

800

97 98 99 00 01 02 03 04

VJSX (LHS) JCI (RHS) Expon. (JCI (RHS))

Source : Database BI

Total (Trillion Rp)Government Bonds Held

by Mutual Funds & BTO (Trillion Rp)

Total Government BondsGovernment Bonds held by BTO

330

340

350

360

370

380

390

400

410

420

430

440

0

10

20

30

40

50

60

70

80

90

100

110

00 01 02 200312 12 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8 9 10 11

Government Bonds held by Mutual Funds

73


2001

3 per. Mov. Avg. (PER (RHS))

Source : CEIC

Percentage

0.00

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0

10

20

30

40

50

60

70

PER (RHS)

Volatility (LHS)

2002 2003

(IPOs), has contributed to financial system stability. During

2003, two banks held IPOs, Bank Mandiri and BRI, and

each stock sale was oversubscribed. The robust stock

market has opened up a cheap, alternative source of

financing for corporations and offered an alternative

investment instrument to the public.

On the performance side, the banking sector»s stock

prices during 2003 contributed to the strengthening of

overall stock prices. For instance, the financial sector price

index had a positive correlation with the composite stock

price index (Chart V.4). Also, stock issuance by Bank Mandiri

in May 2003 and Bank BRI in October 2003 boosted

capitalization of the Jakarta Stock Exchange (Chart V.5)

Improved performance of banking stocks is expected

to assist with recovery of the investing public»s confidence

in Indonesian banking conditions, particularly as regards

profitability.

For the next 6 months, banking stock prices are

expected to be relatively stable. Further, based on business

performance, the prices of several major banking stocks

(BCA, BRI and Danamon), would rise.

In relation to the above, listed banks are expected to

improve their corporate governance, particularly in relation

to transparency and risk management. This will increase

stability in the stock market and in the overall financial

system.

Bond Market

In line with stable stock market conditions, the SUN

(government bonds ) market became more liquid and

efficient. However, a close watch is still necessary due to

refinancing risk and undersubscriptions, which could erode

government credibility and the sustainability of state

budget financing. Government bonds (issued in the

domestic and international markets) represent an

alternative source of financing for the government; they

also provide useful benchmarks for corporate bonds.

Large issuances of SUN and their varied maturities

have helped make this market more liquid than the

corporate bond market (Chart V.6). However, the

upward trend of SUN yields could disrupt government

Chart V. 5Price Earning Ratio»s of Listed Bank

Chart V. 4Trend of Jakarta Finacial Index (JFI)

Maturity (Year)

YtM (%)

Aug

Sep

Oct

Nov

0 1 2 3 4 5 6 7 8 9 10 119

10

11

12

13

Chart V.6Yeld Curve of Indonesia Goverment Bond

JFI (RHS) JCI (LHS)

JFI

JCI

Source : CEIC

0

10

20

30

40

50

60

70

80

90

0

100

200

300

400

500

600

700

800

1997 1998 1999 2000 2001

74


Source: CEIC

0

0.001

0.002

0.003

0.004

0.005

0.006

0.007

0.008

0

200

400

600

800

1000

1200

1400Liquidity (LHS) Index (RHS)

2001 2002 2003 Nov

Years

Trillions of Rp

0

10

20

30

40

50

03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20

FR VR HB

financial conditions due to higher interest rates on new

issuances.

In addition, large amounts of SUN will mature in the

period of 2004 to 2013, which narrows the long-term

options for SUN refinancing (Chart V.7). This was one of

the factors behind several cases of undersubscription of

SUN issuance in 2003.

Despite the reprofiling of government bonds (which

also added more maturities), the timing of SUN issuance

remains very important because of the government»s need

to reduce its interest burden, especially in the light of

continuing high yields. Undersubscriptions of government

bonds and rising yields illustrate the potential for financial

difficulties if SUN issuances are not planned carefully.

Within the framework of providing benchmarks and

diversifying budgetary financing, timing of the

government»s issuance of the next Yankee Bond needs be

carefully considered. Considerations in this regard include

global interest rates, which are relatively low at present,

and improving investor confidence as reflected in stronger

international ratings for Indonesia. These factors are

expected to accelerate the next issuance of international

bonds (Box V.2 Prospects for Issuance of Indonesia»s

International Letters of Indebtedness Yankee Bonds).

In line with development of the government bond

market, the corporate bond market also improved

markedly. This is evidenced by the rising value of new bond

issuances and market capitalization, which were up 202%

and 3.2%, respectively. However, such rapid development

necessitates close monitoring due to the potential for credit

and systemic risk.

A sharp rise (of 66%) in the corporate bond price

index during 2003 made an important contribution to the

Indonesian capital market. Liquidity of the corporate bond

market (Chart V.8) has picked up in terms of both price

and value of bonds issued. However, a number of 2003

issuers had questionable fundamentals. Debt to equity

ratios remained high in several sectors (such as textiles,

property, and pulp & paper), suggesting continued

vulnerability. The loss given default of 10 biggest

corporations that potentially could go bankrupt is US$27.9

million (approximately Rp237 billion based on the end-

2003 exchange rate). In addition, many investors are still

unsophisticated and unfamiliar with transaction risks in

the capital market. Consequently, there is a need to

improve monitoring of the corporate bond market to avoid

rising systemic risk (Box V.3 Corporate Bonds).

Of the 10 largest corporations in Indonesia that have

issued bonds (Table V.1), several companies have default

ratings (according to S&P). If adequate monitoring is not

undertaken and proper education is not given to investors

in bonds, the realization of credit risk might trigger panic

Chart V.7Maturity Profile of Goverment Bond

Chart V. 8Market Liquidity of Corporate Bond

75


selling by domestic investors, who do not yet understand

the risks in holding bonds.

These conditions are related to the rapid

development of the bond market, which has allowed

several high-risk corporations and industries (for example,

timber and textiles) to act as free-riders in collecting public

funds through the bond market. This needs to be watched

closely to avoid disruption to bond market development

and a drop in general investor confidence. Also, problems

in the bond market could disrupt overall financial system

stability, particularly the banks, because most bond issuers

also finance their businesses through bank credits.

Consequently, to maintain capital market

development and overall financial stability, the bond market

authority needs to enforce good corporate governance √

particularly transparency√ and to maintain tight supervision

over the market. Many violations still occur and these

could undermine investor confidence, which could in turn

erode the larger financial system.

5.2. Development of Indonesia»s Money Market

During 2003, the money market was characterized

by a downward trend in interest rates, in both the morning

and afternoon interbank money market, in line with lower

SBI rates (Chart V.9). This was supported by a continuing

over-liquid condition in the banks, as suggested by, among

others, a relatively low amount of bank credits compared

to funds accumulated.

As just mentioned, interest rates in both morning

and afternoon interbank sessions trended downward

during 2003. As of December 2003, interest rates in the

morning interbank market were down 32.9% compared

to January 2003; interest rates in the afternoon session

dropped by 39.4% (Chart V.10). This reflected abundant

liquidity in the interbank market, which could be observed

from the ratio of credits to third party funds of only 53%

as well as the ratio of fund placements to funding of

80%. This condition of bank overliquidity spilled over

into an oversupply of funds in the money market because

banks consider the interbank money market as an

Table V.1Rating of Default Probability of Large Corporate Bonds

NoNoNoNoNoO/SO/SO/SO/SO/S

(US$ eq.)(US$ eq.)(US$ eq.)(US$ eq.)(US$ eq.)

1. Pratama Datakom Asia BV Media & Publishing 260 7/15/05 27.92. PT Polysindo International Finance Co BV Textiles & Clothing 250 7/30/06 26.93. Sampoerna International Finance BV Tobacco 200 6/15/06 21.54. PT Telekomunikasi Selular Finance Ltd Telecoms/Communications 150 4/30/07 6.95. Indofood International Finance Ltd Food & Drink 280 6/18/07 4.96. DGS International Finance Co BV Agribusiness 225 6/1/07 4.37. DPSL Finance Co BV Financial corporate 150 12/30/10 2.68. PT Polysindo International Finance Co BV Textiles & Clothing 260 6/15/06 1.59. RAPP International Finance Co BV Forest products/Packaging 200 12/15/05 1.1

10. PT Bank Negara Indonesia (Persero) Banking & Financial services 150 11/15/12 0.5

I s s u e rI s s u e rI s s u e rI s s u e rI s s u e r Industrial Sector Industrial Sector Industrial Sector Industrial Sector Industrial SectorMaturityMaturityMaturityMaturityMaturity

DateDateDateDateDate LGD* LGD* LGD* LGD* LGD*

*LGD = Loss Given Default


Bank Indonesia Certificate (SBI)

1 Month Deposit

IBCM (morning)

IBCM (afternoon)

6

7

8

9

10

11

12

13

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov

Percentage

2003

Chart V. 9Development of SBI, Deposit, Interbank

Money Market Interest Rates

76


Box V. 2 Prospects for Issuance of Government International Securities(SUN) (the Yankee Bond)

Prospects for the issuance of a new global bonds

(Yankee bonds) are quite encouraging, in line with

declining global interest rates and Indonesia»s

improved risk premium. Success in issuance of the

Yankee bond will provide an alternative source for

government financing and assist with fiscal

sustainability, thus supporting stability in the overall

financial system. However, there is a need to closely

monitor international interest rates, which could rise

again, adding to the government»s debt servicing

burden.

In financing the 2004 state budget deficit (of

1.2% of GDP), the government will mainly use

government savings and issue a Yankee bond in the

amount of Rp3.5 trillion (USD 400 million). According

to the government»s plan, the Yankee bond will only

be issued if state revenues come in below target.

Prospects for the issuance of a Yankee bond are

quite encouraging in line with declining global interest

rates and Indonesia»s improved risk premium.

However, the international bond market is starting to

look overcrowded; Indonesia»s rating is still weak,

despite recent up-gradings; and Indonesia»s existing

debt is quite large. Furthermore, the possibility of a

rise in interest rates needs to be anticipated in order

to enable the government to undertake refinancing

at the cheapest cost.

Success in the issuance of a Yankee bond would

reduce risk for both the government and corporations

(including banks) and thereby contribute to the main-

tenance of Indonesia»s financial system stability.

Total government debt is quite large, at

Rp1,317.3 trillion or 81.8% (2002) of GDP. Of this

amount, recapitalization bonds √which carry high

interest rates√ amount to Rp412.4 trillion, which is a

risk for government budget sustainability.

Are prospects for issuance of the Yankee bond

viable?

1. In response to declining interest rates, global

markets have recently been flooded with bond

issuance, including by Asian markets to take

advantage of the relatively low cost of borrowing.

Issuance of bonds by banks in Asia (excluding

Japan and Australia) went up 20%, from USD12.5

billion in the first semester of 2002 to USD14.9

billion in the first semester of 2003.

2. Total government debt is already high, being

equivalent to 81.8% of GDP, well above the safe

limit of 60% (benchmark best practice). This

situation is aggravated by high interest rates on

domestic debt, which could create a financial

problem for the government. Furthermore,

payments of interest and principal are bunched

in 2004 and 2005, which could dampen investor

interest in buying the Yankee bond.

3. Indonesia»s rating is still below investment grade

(S&P B-; the current rating for the 1996 Yankee

20032003200320032003 20042004200420042004 20052005200520052005 20062006200620062006

Table : Projection of Government»sPayments of Interest and Principal

Domestic Interest 55.2 53 49.9 48.7Foreign Interest 26.8 27.5 26.6 26Total 82 80.5 76.5 74.7Domestic Principal 13.5 30.5 35 36.7Foreign Principal 16.7 46.4 48.9 47.9Total 30.2 76.9 83.9 84.6Total Interest andPrincipal 112.2 157.4 160.4 159.3

Source : Ministry of Finance

77



IBCM (morning) (Trillion Rp) IBCM (afternoon) (Trillion Rp) Morning PUAB’s Interest rate (%) Afternoon PUAB’s Interest rate (%)

0

2

4

6

8

10

12

14

0

10

20

30

40

50

60PercentageTrillion Rp

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

2003

alternative placement for funds, promising profits with

quite low risks. This is amplified by perceptions of high

credit risk on the part of the banks, causing them to seek

relatively safe placements, such as SBIs and the interbank

money market.

Government policy on guaranteeing interbank

money market transactions supported this condition.

During most of 2003, the guarantee interest rate ceiling

for the interbank money market was calculated based on

the average interbank money market rate at JIBOR member

banks (11 banks). Since September 2003, the maximum

guaranteed interest rate in the interbank money market

has been higher than the guarantee ceiling for rupiah

deposits due to a change in the formula for calculation of

the latter (a sizable positive margin in the calculation was

eliminated). Relatively high interest rates in the interbank

market caused banks to place their funds in the interbank

market, which added to the oversupply of funds in that

market and pushed rates down.

Fund placements in the interbank money market

adversely affect bank intermediation. Relatively high rates

(which do not differ much from those on SBIs), along with

a government guarantee causes banks to prefer the

interbank money market rather than relatively risky credits.

Also, the guarantee on the interbank money market could

become an additional burden for the government.

In 2004, these conditions are predicted to continue.

There would be high liquidity in the interbank money

bonds is BBB), which will cause the Yankee bond

to carry a high interest rate because of a large

risk premium. This was also reflected in the yield

spread of 198.7 basis points (at 21 August 2003),

which has improved recently but remains relatively

high. This indicates improving investor confidence.

Impact on Financial System Stability

1. Bank Mandiri»s foreign currency debt issue was

over-subscribed, and the Yankee bond is expected

to attract similar interest.

2. Success in the issuance of a Yankee bond will

renew government access to international capi-

tal markets; it will help with fiscal sustainability;

and it will not disrupt financial system stability.

However, it will be important to maintain a close

watch for a possible reversal of interest rate de-

clines, as this could become a burden for the

government.

Chart Box V. 2.1Development of Yield Spread* of Indonesia»s

Yankee Bond

*) Yield spread Yankee Bond RI 7.75 (1 Ags 2006) dg US Treasury 3.5 (15 Nov 2006)Source : Bloomberg

230.0

275.2

320.8321.0319.5

331.8329.5

Feb Mar Apr May Jun Jul Aug0

50

100

150

200

250

300

350

2003

Chart V. 10Development of Interbank Money Market

Interest Rates and Transaction Volumes

78


Box V. 3 Corporate Bonds

The bond market experienced some euphoria in

2003. This was brought on by declining SBI interest

rates, which prompted investors to shift to profitable

investments; by the prospect of elimination of the guar-

antee program; and by strong purchases of mutual

funds backed by recapitalization bonds. Moreover, im-

proving market perceptions of Indonesian companies

and declining country risk boosted the bond market.

During 2003, there were 54 issuances of bonds

totaling more than Rp 25.4 trillion. Of these, 80% (43

issuers) were private corporations, including potential/

existing large bank borrowers in the amount of Rp 19.2

trillion or 35.8% of total bank credits extended up to

October 2003.

Impact on Banks

Funds raised from bonds issuance would be partly

used by debtors to repay bank credits (both directly or

indirectly, that is, after being used for business restruc-

turing). However, this would reduce the growth of

credit. In addition, banks now face a new competitor

(the capital market) in credit channeling and this could

cause them to loose potential clients, as has already

happened at several banks.

Impact on the Financial System

There is little potential risk for the financial sys-

tem, particularly the banking sector. However, with-

out adequate regulation, it is possible for under-quali-

fied debtors to issue bonds, which could result in de-

faults, as happened with PT Sinar Mas and PT Riau

Andalan Pulp and Paper.

On one hand, the issuance of corporate bonds

could reduce banks» credit risk. On the other hand, an

alternative source of financing will further reduce the

growth of credit, which will hamper development of

intermediation and cause SBIs to remain a principal

source of revenue. Another impact is that the entry of

a new competitor will force the banks to operate more

efficiently and to lower interest rates on their credits.

market; interest rates would continue on a downward

trend; and banks would continue to seek alternatives to

high-risk credit placements. The plan to reduce coverage

of the blanket guarantee program will eventually eliminate

the guarantee on the interbank money market, which will

reduce banks» interest in placing their funds in that market.

On the downside, several small banks that have often

been borrowers in that market could experience liquidity

problems.

To avoid such a negative impact, the guarantee

program should be eliminated carefully and in stages.

Banks should continue to be reminded to actively place

their funds in earning assets, such as credits, including to

boost the real sector, which would directly support

economic growth.

79

Chapter 6 Payment System

Chapter 6Payment System

80


81


In general, risks within the Indonesian payment system,

particularly liquidity risk and credit risk, can be minimized

by implementation of the Bank Indonesia Real Time Gross

Settlement system (BI-RTGS). Remaining liquidity and credit

risks still need to be continuously monitored and further

reduced.

Further progress in this regard can be realized

through good management of technical risk and liquidity

monitoring of the BI-RTGS system. To avoid technical risk,

BI will give utmost attention to the robustness of the

system. Robustness of the BI-RTGS system can be

improved, among others, by achieving a high level of

availability (for example 99%) and by the support of a

good communication network. BI also makes various

efforts to minimize operational risk in the BI-RTGS system.

In addition, there is on going monitoring of the

possibility of a shortage of market liquidity. This monitoring

is meant to detect the possibility of a liquidity shortage

that would endanger smooth operation of the payment

system and could even trigger systemic threats to financial

system stability.

Since implementation of the BI-RTGS system in

November 17, 2000, there has been a shift in the use of

the payment system from clearing system to BI-RTGS

system. The volume of transactions processed by the BI-

RTGS system in the reporting year rose 93.11% while total

value rose by 51.94% relative to 2002. Reflecting the shift

to BI-RTGS, the transaction volume of clearing activities

dropped by 24.63%; total value dropped by 25.39%. In

2003, the share of daily use of the BI-RTGS system came

to 94.79%, leaving the clearing system with 5.21%

(Rp85.6 trillion and Rp4.7 trillion, respectively). This

Chapter 6Payment System

indicates that 94.79% of the payment system risk has

shifted from the clearing system to the BI-RTGS system.

The shift from the clearing system to the BI-RTGS

system has changed the nature of payment system risk.

Previously, risk cumulated during the course of the day,

because the clearing system operates based on multilateral

netting with settlement at the end of day. Now, the risk is

spread out during all operational hours of the BI-RTGS

system (06.30 up to 17.00 Western Indonesian Time).

Distributing risk in this way requires users of the BI-RTGS

(in this case banks) to manage their liquidity during the

entire day. By this means, the shift from the clearing system

to the BI-RTGS system supports financial system stability,

which is the objective of introducing the BI-RTGS system.

To ensure good management of payment system risk,

it is necessary to oversee the payment system. Payment

system oversight in Indonesia is implemented with

reference to standards contained in the Core Principles

for Systemically Important Payment Systems (CP SIPS) using

a self-assessment method. Efforts in this regard ensuring

good management of payment system risk are made both

Chart VI. 1Clearing Transaction

2000 2001 2002 2003

3,000,0002,750,0002,500,000

2,250,000

2,000,0001,750,0001,500,000

1,250,000

1,000,000750,000

500,000

250,0000

Clearing RTGS (Netto)

Poly. (RTGS (Netto)) Poly. (Clearing)

10 1112 1 2 3 4 5 6 7 8 9 10 1112 1 2 3 4 5 6 7 8 9 10 1112 1 2 3 4 5 6 7 8 9 10 1112

Trillion Rp

R 2KLIRING = 0,9695

R 2RTGS = 0,8121

82


internally by BI and by external parties. Efforts by external

parties include establishment of the risk management

committee within the National Payment System

Communication Forum, comprising representatives from

five banking associations. This committee discusses joint

efforts related to good management of payment system

risk, which will be made by users of the payment system

(banks) and BI.

Currently, the BI-RTGS system is quite safe and

efficient. This condition has to be maintained. From the

side of daily activities, the BI-RTGS system processes an

average value of Rp85.6 trillion and an average volume of

17,055 transactions per day. By nominal amounts, most

transactions concern settlement of marketable securities

transactions administered by BI (SBIs and government

bonds). By volume, most transactions were bank

customers» transactions (74.6%).

Currently, banking liquidity in relation to settlement

of payment transactions is sufficiently good. This is

illustrated by the share of the value of transactions

successfully settled, namely 99.99% (Rp85.6 trillion). This

leaves the share of nominal value of transactions cancelled

at end of day (status QCNL) at only 0.01% (Rp9.2 billion).

This is evidence that the payment system operates smoothly

and that liquidity in the payment system is quite adequate

for transaction settlement by participating banks.

As for monitoring financial system stability, smooth

processing of transactions by the BI-RTGS system is an

important factor that is expected to reduce liquidity failure

and systemic risk stemming from liquidity shortages in any

large bank, which could disrupt the overall system. Most

material transactions are made at the beginning and end

of the day. Therefore, the BI-RTGS by-laws adopt a

graduated payment schedule rule and BI has a policy of

differentiated pricing at different times for processing by

the BI-RTGS system. This is intended to encourage

transactions to be sent and settled during the morning,

and not to be concentrated in the afternoon.

Within the framework of financial system stability, in

relation to trades of marketable securities and bonds issued

by the government within the framework of financial system

stability, BI has implemented the Bank Indonesia Scriptless

Securities Settlement System (BI-SSSS). Implementation of

this system constitutes BI»s effort to adopt the Delivery Versus

Payment (DVP) mechanism aimed at minimizing payment

system risk arising from the settlement of marketable

securities (SBIs and government bonds). With

implementation of the BI-SSSS, fund settlement can be

executed simultaneously with marketable securities

settlement, thereby minimizing the risk of payment failure.

In 2003, payment transactions through the clearing

system were on a downward trend. The daily average value

of clearing transactions declined from Rp6.2 trillion to

Rp4.7 trillion, while the daily average volume declined from

Chart VI. 2Unsetled RTGS Transaction

0

10

20

30

40

50

60

70

80

90

100

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Settle Not Settle

Percentage

Transaksi RTGS yang Tidak Settle (Not Settle)

ACPT (T.Settle)

PSED (T.Settle)

RJTD (T.Settle)

HCNL (T.Settle)

QCNL (T.Settle)

1.40

1.20

1.00

0.80

0.60

0.40

0.20

-Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec

Percent

CodeCodeCodeCodeCode DescriptionDescriptionDescriptionDescriptionDescription

ACPTACPTACPTACPTACPT Transaction cancelled √ due to incomplete

transmission

HCNLHCNLHCNLHCNLHCNL Transaction cancelled by Host

PSEDPSEDPSEDPSEDPSED Settlement pending √ waiting for data

QCNQCNQCNQCNQCNL Queue Cancelled √ transactions in queue

cancelled by sender (bank) due to business

consideration (prioritization)

RJTDRJTDRJTDRJTDRJTD Transmission rejected by supervisor

83


470,514 to 300,903 transactions. Despite these declines,

the BI clearing system (which is a multilateral netting

settlement system) still constitutes the country»s second

largest payment system (next to the BI-RTGS system).

Although the risk emerging from use of this system is very

small (5.21% of total value of settlements), this risk still

needs to be well managed.

Management of clearing risk is still necessary

although the potential for systemic risk is quite low. This

is done through improvement of operational aspects of

the clearing system, comprising enhancement of technical

and non-technical aspects as well as clearing schedule

arrangements. In the framework of reducing clearing risk,

BI has also implemented other risk mitigation steps in the

clearing system. For instance, limiting the value of

interbank debit notes (to a maximum of Rp10 million per

transaction) and limiting the value of credit notes that can

be settled through the clearing system (to less than Rp100

million per transaction). In addition, within the framework

of tackling the possibility of settlement failure through the

clearing system due to insufficient liquidity, the Failure to

Settle (FtS) scheme in line with guidelines contained in the

CP-SIPS will be adopted. With the FtS scheme, BI as

settlement operator would not be responsible for

insufficient funding experienced by clearing participants

in settling their clearing results.

In conclusion, risks in the Indonesian payment system,

particularly liquidity risk, have been reduced through

implementation of the BI-RTGS system. However,

continued monitoring of risks in the payment system is

necessary in order to maintain an efficient, smooth, and

safe payment system.

Chart VI. 3 Average Clearing Cycle

Source : Bank Indonesia

Trillions of Rp350,000

300,000

250,000

200,000

150,000

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Article I

Muliaman D Hadad1, Wimboh Santoso2 & Dwityapoetra S. Besar3

October 2003

1 Head of Financial System Stability Bureau √ Directorate for Banking Research and Regulation, Bank Indonesia; e-mail address: [email protected] Bank Executive Researcher at Financial System Stability Bureau √ Directorate for Banking Research and Regulation, Bank Indonesia; email address: [email protected] Bank Researcher at Financial System Stability Bureau √ Directorate for Banking Research and Regulation, Bank Indonesia; email address: [email protected]

Interest rates on deposits and credit are very important in calculating banks’ cost of intermediation and

in giving preliminary indications of overall economic efficiency. This paper explains the structures of banks’

cost of funding and credit interest rates in order to explain factors that have influenced the high levels of

credit interest rates in the period from January 2002 to June 2003. The estimation method used is the Cole,

Santoso and Heffernan method, complemented by the Historical Average Cost Approach for calculating

contributions to bank costs (overhead costs) using quarterly financial data.

This model is used to answer two main questions: Is the calculation of bank interest rates quite

reasonable?; and, what are the determining factors? Data limitations in this paper require that the estimation

results be interpreted cautiously.

This research mainly shows that banks’ cost of funding has come down in line with falling SBI interest

rates. However, banks’ credit rates are unusually high (overpriced) compared to the average cost of funds at

several banks, according to these estimates. Therefore, the overall cost of intermediation is still high compared

to what would normally be expected. There are several important causal factors. One is banks’ tendency to

limit competition because their liquidity is still quite adequate and their income from SBIs and bonds is still

high. These factors cause banks to adopt a wait-and-see attitude in the short-run regarding developments in

the money market and real sector. In addition, there is also a possibility that implementation of bank risk

management, particularly as regards product pricing, is still not accurate and tends to burden debtors with

excessively high risk premiums, which boosts the level of credit rates.

Abstract

Study on the Cost of Intermediation At Several Large Banks in Indonesia:Are Commercial Banks’ Interest Rates on Credits Overpriced?

Keywords: Cost Intermediation, Bank

JEL Classification : G21, G28

88

Article I

Chart 2Components of COF and Credit Interest Rates (Rp)

Bank (ex-post) Estimasi

Profit Margin

Risk Premium

Overhead Cost

Guarantee

Cost of fundReserve Requirement

Cost of funds

Loan Interest rateCompononts

Loan

1.1.1.1.1. BACKGROUNDBACKGROUNDBACKGROUNDBACKGROUNDBACKGROUND

Effectiveness of monetary policy and financial system stability depends in part upon several important parameters

that are not directly under the control of the central bank. These parameters include the supply elasticity, the demand for

real and financial assets and the relationship between deposit and credit interest rates. All of these are influenced heavily

by the structure of the financial system, especially money market conditions and the level of sophistication, competition,

and availability of alternative financing sources.

Rigidity of borrowing interest rates is often considered a factor that hampers smooth transmission between monetary

policy and the real economy. For example, Bank Indonesia lowered SBI interest rates by a total of 280 basis points in the

period of January 2003 to June 2003, but credit rates declined only 64 basis points during the same period. This small

decline in credit rates has limited the impact of easier monetary policy on the real sector.

Surveys indicate that this rigidity stems from factors

that are both internal and external to banks. The internal

factors include the earning assets structure while some of

them are sensitive to SBI»s rate and this stimulate bank to

limit their credit rates in order to protect their profit margins.

This is worsen also by long-term funding sources which is

relatively high-cost. At the same time, banks have also been

slow to implement optimal risk management, making it

difficult to determine accurate pricing for individual debtors.

From the external side, a large number of customers

are still waiting for further declines in interest rates before

obtaining loans from banks, and many potential debtors»

projects are not bankable.

This paper is focused more on the supply side, which looks at bank interest rates (that is, pricing) based on data

from January 2002 up to June 2003. The objective is to know whether bank pricing (in terms of cost of funds and credit

rates) reflected reasonable intermediation costs during that

period. In addition, analysis of the cost of funds (COF) is

used to complement the analysis of credit interest rates,

which is more observable and readily available. Considering

data and methodological limitations, this study is expected

to be a reference point for further work on intermediation

conditions in Indonesia.

2.RESEARCH METHODOLOGY

This research is conducted in a simple, quantitative way,

by making comparisons between estimated cost of funds

and credit rates on the one hand, and bank actual data (ex-

Source : Data 8 bank besar diolah2002 2003

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun

25

20

15

10

5

0

Percent

Credit Interest RateCOFSBI (1m)

Chart 1 Trends of SBI, Cost of Funds and Credit Interest Rates

89

Article I

post) on the other. This provides a picture of factors that influence pricing formation of this market. In general, the

research methodology entails a literature study, estimation and simulation.

3. LITERATURE REVIEW

Commercial banks offer various types of savings services with varying degrees of coverage. Each feature is aimed at

meeting the needs of corporate and individual customers for saving funds or making transactions. For simplicity, the

model in this paper is limited to savings in current accounts, savings accounts, and rupiah-denominated fixed-rate deposits.

Floating interest rates could also be accommodated using a cost of fund based upon certain benchmark interest rates, for

example LIBOR or JIBOR, for compensating risk. Basically, this model is built to be flexible enough for further research to

use variable interest rates.

Theoretically, important issues in intermediation are related to the cost to creditors of obtaining information to

access credible debtor and differences in liquidity preferences as between creditors and debtors. This information cost

also reflects banks» cost of funds and interest rates on credits.

This study use the model developed by Heffernan (1996), which calculates the cost of intermediation as the difference

between banks» cost of funding and their credit rates. A high cost of intermediation suggests an inefficient economy and

weak bank performance. For analysis of the structure of the cost of fund and credit rates, see Rose (2002), who explains

that there are several components to cost of funds, such as interest cost, minimum reserve requirements, overhead costs,

profit margins, and risk premium. Application to the Indonesian context uses rupiah minimum reserve requirements of

5%, a 0.25% guarantee premium, and certain risk premiums calculated based on average credit risk in Indonesia plus an

asset yield spread.

The calculation of risk premium is difficult, therefore several approaches were used to meet bank operations, as

Copeland (1983) uses a table of premium grades credit quality, for example a standard risk premium of 0.5% or in special

cases 1.5%. In addition, an asset-spread approach can be used by calculating the difference between the yield on risk-

free marketable securities and the yield of another marketable securities with similar characteristics (maturity, duration,

liquidity, etc.). For example, the yield on Indonesia»s Yankee bond (a US$ government) or Surat Utang Negara (government

securities in rupiah) and the average yield on Indonesian corporate bond.

One measure of a bank»s efficiency is the accounting value of net interest income against total earning assets.

Meanwhile, a measure of profitability is before-tax profit relative to average capital (equity). This study focuses on

measurements of income and profitability as used by Demirguc-Kunt (1998).

4. DATA

The model»s data used for the cost of funds are deposits, savings, and rupiah current accounts, on a quarterly

frequency for five large banks from January 2002 to June 2003. For reviewing bank»s efficiency, the analysis uses banks»

balance sheets and profit/loss data, starting from January 2002. The weighted average for each saving types are used as

benchmark in calculating saving interest rates.

Risk premium can be calculated using the yield spread on Indonesian government bonds against US government

bonds with similar characteristics in terms of duration to maturity, liquidity, and so forth. JP Morgan has issued two types

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Article I

of estimated spreads of developing countries» government bonds (Cunningham (1999)). However, a spread that is more

suitable for Indonesia is the Emerging Market Bond Index (EMBI) because of its wider coverage (which includes Indonesia)

and its long data series, starting from 1991.

Data used in this study have been collected from various sources, largely from banks» monthly reports (balance

sheet and profit/loss report), which are available in Bank Indonesia. The JP Morgan spread data is available at Bloomberg.

Data on SBI interest rates and weighted average savings, and other data are obtained from Recent Indicator Reports,

which are compiled for Bank Indonesia»s internal use.

5. MODEL

The model used is a simple one that explains component structures and bank behavior. As explained by Shaffer

(1989 and 1993), an assumption of profit maximization leads to a simple equation where market forces can be calculated

explicitly. This framework combines relationships between certain balance sheet accounts (particularly deposits and credits),

which can illustrate bank intermediation spreads explicitly.

Banking activities are assumed to be strictly traditional (that is, the calculation does not take into account other

bank debts, off balance sheet transactions, and fee-earning business). Banks only take deposits and place funds in the

form of credits. On the assumption that a rise in deposits is used to fund credits, to meet minimum reserve requirements,

and to fund other non-interest earning assets, then additional assets can be expressed mathematically as follows (Cole

1991, Santoso, 2000):

t0-t1 = d0-d1=(r0-r1) + (l0-l1) +(p0-p1), where

t = total assets l = credits

d = deposits (savings) p = non-interest earning assets

r = minimum reserve requirement

The interest margin, which also constitutes intermediary costs, comprises overhead costs, the cost of capital, and

risk premium in the calculation of credit interest rates.

Using delta (d) to represent the increment, the above equation may be written as follows:

δt = δd = δr + δl + δp

If we simulate minimum reserve requirements and overhead costs (dr and dp, respectively), we get the following

equation:

δd = α δd+δl+β δd

where:

α = minimum reserve requirement (in %)

β = proportion of overhead cost

To simplify the calculation, d can be moved into the following equation and after that incremental credit (l) becomes:

l = d(1-α -β)

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Article I

Percent

Sk. Bunga Kredit-Bank

Sk. Bunga Kredit-Est

COF-Bank

COF-Est

Q1 2002 Q2 2002 Q3 2002 Q4 2002 Q1 2003 Q2 2003

0

5

10

15

20

25

Chart 3 COF and Bank Interest Rate (ex-post)and Estimation Results

Defining il to be the credit interest rate and id the deposit interest rate, the income interest rate on savings (r) can be

expressed as follows:

r = (ill √ idd √ cd) / d

r = ild (1-α -β)+idd √ cd /d

r = il (1-α -β) √ id √ c

where c is the cost of intermediation. Calculation of the credit interest rate can then be completed by re-arranging to:

il = (r + id + c) / (1 -α -β).

At the end, cost of intermediation that constitutes the difference between credit and deposit interest rates can be

obtained (i(i(i(i(il l l l l √ i√ i√ i√ i√ iddddd))))). Calculation of risk premium in credit interest rate is based on Indonesia»s country risk, which is a calculation

of the difference between USD-dominated securities issued by the government of Indonesia and those issued by the US

government with similar characteristics. This risk premium can be considered as a compensation for a company or a bank

that incurs cost for issuing a riskier product.

6. RESULTS OF STUDY AND TESTS

As SBI rates have declined since early 2002, banks have generally adjusted their cost of funds quickly. However,

based on estimation results, the estimated cost of intermediation in quarter II-2003 was 2.43% lower than what was

actually observed. This suggests that costs of intermediation and actual credit rates are much higher than would normally

be expected. And while credit rates are still on the decline, they are coming down only very slowly.

This analysis shows that banks still have room in their current intermediation spreads (that is, without reducing

deposit rates further) to lower credit rates. This can be done by, for example, reducing their profit targets (ROE) and by

more accurate debtor credit risk analysis through implementation of risk-based assessment. Several large banks have

adopted this approach but their overhead costs and operational risks are still high. They tend to pass on this burden to

their debtors, which limiting declines in credit rates.

A decline of 2.21% in credit interest rate so is the optimal probability which allow banks to reduce real credit rates.

In practice, banks have reduced credit rates for selected sectors are given for productive credits and based on results of

assessment of debtor conditions and bank»s experience/competency in line with the sectors being financed.

Cost of Funds

Overall, the cost of funds at the banks in this study has

been on a declining trend since quarter I-2002. This decline

is in line with declines in SBI rates, which turned down in

January 2002. However, some longer-term savings have been

relatively stagnant.

Still, there is considerable variation among banks. For

example, one large bank still has an actual cost of funds

that is still higher than estimated. This shows that although

the average cost of funds is already quite low, some banks

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Article I

still have high credit rates because the cost of their funding is inflated by longer-term, high-interest deposits. Results also

show that other banks have lowered their cost of funds, but not significantly. This development needs to be monitored

in order for banks not to experience negative interest rate spread again.

Influence of Lower Minimum Reserve Requirements on COF

A simulation of relaxing minimum reserve requirements (which are included in COF), shows that the impact on the

COF and on credit rates is relatively small. This is because the minimum reserve requirement ratio is already low (5%) and

the opportunity loss from idle placements has been included the cost of funds, using the SBI interest rate as a cost proxy.

Reduction (or even elimination) of minimum reserve requirement and the guarantee have a relatively small effect,

equivalent to an average decline in credit rates of only 0.5%.

This is roughly the same as a bank policy adjustment to lower

its ROE target by 5.7% (from base target to 13.6%). This

shows that minimum reserve requirements are not a dominant

factor in banks» cost of funds and credit interest rates. A

better solution is demonstrated by a simulation that shows

banks could reduce credit rates further by adjusting their

profit targets by reviewing bank»s business plan and reducing

its ROE targets.

Credit Interest Rates

Although credit rates are on a downward trend, most

banks» actual interest rates are still much higher than

estimated (that is, much higher than would normally be

expected). On average, this difference is at least 2 √ 3%,

which is considered to be the room for banks to lower their

interest rates.

Continuing high credit rates could also imply that

overhead costs at the five banks are too high, particularly

when compared with other South East Asian countries», in

the range of 1 √ 2%. Many banks» operations are still very dependent on branch networks but do not yet use sophisticated

technology, such as telephone/pc banking. High operational risks are another factor that contributes to high bank

overheads.

An additional important factor concerns competition. If the credit market is quite competitive, different credit rates

should reflect different clusters of banks, whereas the response of banks within one cluster should be relatively similar. All

five of these banks tend to limit credit rate reductions, which indicates that competition between banks has not recovered.

Banks» liquidity is adequate and bank income from SBIs and bonds is still high. Therefore, in the short-term, banks are

adopting a wait-and-see attitude towards the money market and the real sector. Also, banks are still affected by the

Table 1 Influence of Changes in Minimum ReserveRequirements and Guarantee Interest Rates on COF

COFCOFCOFCOFCOF

StandardStandardStandardStandardStandard

Reserve requirmentReserve requirmentReserve requirmentReserve requirmentReserve requirmentdecrease todecrease todecrease todecrease todecrease to

Reserve requirmentReserve requirmentReserve requirmentReserve requirmentReserve requirmentand loan interest and loan interest and loan interest and loan interest and loan interest = 0%= 0%= 0%= 0%= 0%

Q1-2002 13.97% -0.43% -0.70% -0.73%Q2-2002 13.29% -0.41% -0.67% -0.70%Q3-2002 12.38% -0.38% -0.62% -0.65%Q4-2002 11.54% -0.35% -0.58% -0.61%Q1-2003 11.11% -0.34% -0.56% -0.58%Q2-2003 9.60% -0.29% -0.48% -0.50%

AverageAverageAverageAverageAverage -0.37% -0.60% -0.63%

COFCOFCOFCOFCOF

StandardStandardStandardStandardStandard

Reserve requirmentReserve requirmentReserve requirmentReserve requirmentReserve requirmentdecrease todecrease todecrease todecrease todecrease to

Reserve requirmentReserve requirmentReserve requirmentReserve requirmentReserve requirmentand loan interest and loan interest and loan interest and loan interest and loan interest = 0%= 0%= 0%= 0%= 0%

Q1-2002 19.05% -0.54% -0.73%Q2-2002 18.37% -0.63% -0.82%Q3-2002 17.45% -0.59% -0.77%Q4-2002 16.73% -0.83% -1.01%Q1-2003 15.79% -0.31% -0.49%Q2-2003 14.29% -0.37% -0.56%

AverageAverageAverageAverageAverage -0.55% -0.73%

* average 5 banks 22.9% (»02) and 19.3% (»03)* average big banks* average public bank

Table 2Influence of ROE Changes on Credit Interest Rates

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Article I

Chart 5Cost to Average Assets

Bank E

Bank D

Bank C

Bank B

Bank A

0% 1% 2% 3% 4% 5%

2003200220012000

trauma of delinquent credits during the crisis of 1997/98;

during this post-crisis period, and they have tended to

safeguard their capital as a cushion against potential losses.

One of the five banks shows quite an interesting

phenomenon where credit rates remain high, despite declines

in its cost of fund. This shows that the bank is trying to use

credit interest income to compensate for declines in its income

from marketable securities (which carry variable interest rates).

Considering that the difference between actual and estimated

interest rates is still quite large, that particular bank could

recalculate its profit target and start lowering credit interest

rates.

Currently, consumer credits rate are already on the

decline, including for credits channeled to the consumption

sector, including to the property sector, which is on the

rebound. Considering that the estimation results based on

optimum assumptions and difference between actual √

estimated credit interest rates is still quite large, further

lowering of credit interest rates can still be undertaken by

banks.

Weak demand for credit and rising undisbursed credits

(Chart 6) provide an impetus to lower credit interest rates,

which would raise the demand for credits. However, in the

short-term, high credit interest rates and credit rationing seem

to be a matter determined by banks» particular business

considerations. Therefore, a push from the supervisory

authorities to reduce credit interest rates would be helpful

as competition among the banks does not seem to be

working quickly enough.

Cost of Intermediation

High intermediation spreads can be costly to the

economy because they lead to high lending rates. At the same time, this spread is the key mechanism through which

banks obtain profits and protect themselves from credit risk. Therefore, an analysis of spreads is important in knowing

whether a bank with high spreads is covering inefficient operations or if it is obtaining profits to strengthen the bank and

create a solid banking system.

Chart 4Overhead Cost to Productive Asset

Big Bank

5 Bigest Bank

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

2002 2003

Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar Apr May Jun

Chart 6 Comparison of Cost of Intermediation BetweenActual (ex-post) and Estimation Results

Percentage8

7

6

5

4

3

2

1

0

Q1 2002 Q2 2002 Q3 2002 Q4 2002 Q1 2003 Q2 2003

Bank

Estimation

94

Article I

In Indonesia, the estimated cost of intermediation has

increased since quarter II-2002, but it is considerably smaller

than actual, observed costs of intermediation. Consequently,

the actual intermediation cost could still be reduced by 2 √

2.5%, mainly by more efficient banking operations.

Conclusions and Policy Implications

This paper analyzes a simplified bank pricing

methodology and considers the implications for the cost of intermediation. The analysis confirms results of previous

study and surveys. Namely, banks» cost of funds has declined more or less in line with SBI interest rates, but credit rates

are unusually high, because banks» intermediation costs are high, due in part to inefficient operations.

Internal factors causing the high cost of intermediation include banks» unwillingness to compete aggressively;

adequate levels of liquidity; and high levels of income from SBIs and bonds. Consequently, banks still adopt a wait-and-

see attitude towards the money market and the real sector developments. Also, there is a possibility that implementation

of bank risk management, particularly in relation to product pricing, is not sufficiently well developed. This tends to

burden debtors with high risk premiums that translate into high credit rates.

In the framework of accelerating declines in the cost of intermediation, it would be useful to push banks to enhance

efficiency, to reduce lending rates and to increase lending.

The possibility of relaxing banking regulations to reduce lending rates needs to be approached very carefully. It

should only be implemented within a coordinated macro and micro policy framework in order to achieve conducive

financial stability.

Finally, further research is needed, including into the lessons learned from other countries» experiences, particularly

countries in South East Asia, or elsewhere, that have experienced similar problems.

Table 3 Gap between Actualand Estimated Costs of Intermediation

Q1 2002Q1 2002Q1 2002Q1 2002Q1 2002 Q2 2002Q2 2002Q2 2002Q2 2002Q2 2002 Q3 2002Q3 2002Q3 2002Q3 2002Q3 2002 Q4 2002Q4 2002Q4 2002Q4 2002Q4 2002 Q1 2003Q1 2003Q1 2003Q1 2003Q1 2003 Q2 2003Q2 2003Q2 2003Q2 2003Q2 2003

Bank ABank ABank ABank ABank A 0.82% 1.06% -0.09% 0.02% -0.37% -0.30%

Bank BBank BBank BBank BBank B -5.22%- 4.01% -4.50% -4.65% -5.68% -5.86%

Bank CBank CBank CBank CBank C -2.82% -2.93% -2.58% -2.38% -2.73% -2.59%

Bank DBank DBank DBank DBank D -1.60% -1.86% -0.78% -1.44% -2.54% -2.69%

Bank EBank EBank EBank EBank E 0.16% -0.03% 0.33% 0.27% -0.39% -0.69%

AverageAverageAverageAverageAverage -1.73% -1.55% -1.52% -1.64% -2.34% -2.43%

95

Article I

Berger, Allen N., and Robert DeYoung, Berger, Allen N., and Robert DeYoung, Berger, Allen N., and Robert DeYoung, Berger, Allen N., and Robert DeYoung, Berger, Allen N., and Robert DeYoung, ∫Problems Loans and Cost Efficiency in Commercial Banksª Journal of

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Staff Paper Vol. 46., No. 2 (June 1999)

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Press, pp. 257 - 271

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Magazine of Bank Administration, August 1983.

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World Bank Working Paper No. 1900, Maret 1998

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97

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Article II

Muliaman D. Hadad1, Wimboh Santoso2 & Bambang Arianto3

1 Head of Financial System Stability Bureau √ Directorate for Banking Research and Regulation, Bank Indonesia; e-mail address: [email protected] Bank Executive Researcher at Financial System Stability Bureau √ Directorate for Banking Research and Regulation, Bank Indonesia; email address: [email protected] Bank Researcher at Financial System Stability Bureau √ Directorate for Banking Research and Regulation, Bank Indonesia; mail address:[email protected]

Indonesia»s banking crisis of 1997/1998 provided a valuable lesson because of the high public cost of

rescuing the banking industry, a cost that reached more than 50% of GDP at the time. The banking crisis also

caused a loss of public»s confidence in the local banking industry that has been very slow to return. Consider-

ing these significant impacts, monitoring and analysis of factors that contribute to banking crises need to be

undertaken and continued in the future. In this review, causal factors are considered from both the real and

banking sectors, as well as other sharply fluctuating factors, which from now on will be called shocks. U sing

a model presented by Hardy and Pazarbasioglu (1999), logit analysis looks at several indicators of shocks and

of conditions in the real and banking sectors. It concludes that these indicators are useful as early warning

signs of banking system instability, and they could be used as inputs into policy formulation to prevent the

reoccurrence of a banking crisis.

Keywords: Macroeconomy, Banking Crisis

JEL Classification : E44, G21

Early Indicators of Banking Crises

Abstract

December 2003

98

Article II

I. INTRODUCTION

I.1. Background

Indonesia»s banking crisis of 1997/1998 provided a valuable lesson that, when serious problems in the banking

sector are not detectedƒand fixedƒat an early stage, they can lead to a collapse of public confidence in the banking

industry. In addition, efforts to rescue the national banking system and to revive public confidence in that system can

require major amounts of public financing. In Indonesia»s case, the government has spent more than Rp500 trillion to

rescue and rehabilitate the banking sector, including through the Bank Indonesia Liquidity Assistance facility and the Bank

Recapitalization program.

Banking sector crises is related, directly and indirectly, to various activities that are normally undertaken by the

banking industry. On the side of funds accumulation, the amounts and composition of public deposits in the banking

system have a powerful effect on banking industry stability. Withdrawals of public funds on a large scale and in a rush

can be a severe shock to bank liquidity. If this situation is not tackled immediately, it will further create problems, like

insolvency. Banks will be forced to offer extremely high interest rates on savings in order to retain public deposits, and

these high rates will soon become too costly for the banks, hitting their profitability, especially if revenues sources drop

off, too, as happened in 1997√98.

Meanwhile, on the side of funds channeling, the composition of earning assets contributes to a bank»s resilience in

dealing with problems originating from outside the bank. For example, credit performance is very much determined by

prospects for industries that receive credits, as well as general macroeconomic conditions, such as inflation and the

exchange rate. From another perspective, economic growth often influences bank credit allocation policies towards

certain sectors, creating credit concentrations in some. This happened in the period immediately before the 1997/98

banking crisis, when credit was concentrated in the property sector, which was experiencing extremely rapid growth at

the time.

As mentioned, problems in the banking industry can originate from both the internal and external sides of the

banking industry. On the internal side, such problems can be viewed from the development of an individual bank»s

performance (at least those large enough to have a systemic impact) or from the performance of the overall banking

industry. Meanwhile, macroeconomic conditions and developments in industries that are heavily financed by banks, can

indicate potential problems for bank performance from external factors.

Therefore, it is important to undertake an on-going effort to monitor certain factors that are directly or indirectly

related to banking activity. For example, it would be useful to monitor banks» internal indicators, macroeconomic indicators,

and other variables that might give early warnings of problems in the banking industry. In this regard, a review needs to

be conducted on macro indicators that can be used as early signals of potential banking problems, so that preventive

actions can be taken before existing problems erupt into crisis.

1.2. Research Objectives

This review on early indicators of banking crises is directed at obtaining an understanding of factors internal and

external to banks that have the potential to indicate the existence of problems in the banking industry that could lead to

crisis.

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Article II

1.3. Research Methodology

This review generally adopts the model researched by Hardy & Pazarbasioglu (1999). In this regard, the independent

variables are divided into three large groups, namely:

1. Real sector variables, for the purpose of explaining inefficiency in the use of banking credit and changes in repayment

capacity;

2. Banking sector variables, for the purpose of explaining bank resilience to significant changes, in both assets and

liabilities, and;

3. Shock variables, which are used to explain other factors that directly or indirectly (through the real sector) influence

banking conditions.

Data for this review comes from Macroeconomic & Financial Data in International Financial Statistics, IMF (CD-ROM

version, April 2003), which includes annual economic and banking data for 40 countries. Of these, 31 countries have

experienced severe distresses and 9 other countries are used as control models. With the coverage of those 40 countries,

the data totals 417 observations.

1.4. Discussion

This paper is divided into four chapters. Chapter I contains research background, objectives, research methodology,

and discussion. Chapter II explains other research on this topic, the theory on logit methodology, and statistical tests

using Type I & Type II errors. Chapter III presents research results and interpretations as well as an application of this model

to Indonesia»s current economic situation. Finally, Chapter IV describes the conclusions.

II. Literature Review

II.1. Banking Crisis

Several economic experts believe that the banking industry requires special attention because of its susceptibility to

external influences and because it is an integral part of the payment system.4 As part of the payment system, problems

in the banking industry can spread quickly throughout the entire economy, with an impact that is well beyond the effect

on any single company. In this regard, concern arises about «snowball effects» stemming from the collapse of one bank

that may lead to the collapse of other banks and other companies that have business relations with the banks.

Several analysts present reasons to support the statement that the banking industry is an industry that requires

special attention. These reasons include observations that the banking industry has:

1. A low cash to asset ratio;

2. A low capital to asset ratio; and

3. A high short-term funding to total deposit ratio.

In these conditions, large-scale fund withdrawals in a rush would cause liquidity problems for the banking industry,

which would then prompt banks to use every means possible to allow withdrawals by the public, including efforts to sell

assets at cheap prices. This condition brings about distress for the entire banking system and may have a follow-on

impact on profitability, which could eventually lead to insolvency.

4 George F. Kaufman, ≈Preventing Banking Crises in the Future: Lessons from Past Mistakes∆, The Independent Review, v.II, n.1. Summer 1997, p.55.

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Article II

Banking crises in various countries, particularly in the Asian region, have prompted researchers to undertake reviews

of indicators that can give early warnings of crisis or other pressures on the banking industry. Kunt & Detragiache (1998)

define a crisis as a situation where one of the following conditions are fulfilled:

1. The ratio of non-performing assets to total assets in the banking system exceeds 10%;

2. The cost of the rescue operation is at least 2% of GDP;

3. Large scale transfers of ownership of banks to the government (nationalization); or

4. Extensive bank runs or emergency measures been enacted by the government, such as freezes on public deposits,

prolonged closing of bank offices (bank holidays), or generalized deposit guarantees.

Hardy & Pazarbasioglu (1999) further state that problems in the banking industry can be categorized into two broad

groups, namely ≈severe distress∆ and ≈full-blown crisis∆. Severe distress occurs when banking problems have cumulated

to a certain point but have not reached one of the conditions defined by Kunt & Detragiache (1998) above. A full-blown

crisis occurs when one of those conditions is fulfilled. Hardy & Pazarbasioglu further state that a crisis or major problem

in the banking industry can originate from the real sector, from sources internal to the banking sector, and from drastic

changes in certain economic indicators. For example, a sharp drop in GDP, a jump in real interest rates, a decline in the

incremental capital output ratio (ICOR), a sudden depreciation of the exchange rate, a sharp rise in inflation, a burst in

credit expansion or a significant shift in capital flows. The same issue is also described by Kunt & Detragiache (1998), who

says that banking crises tend to occur when macroeconomic conditions deteriorate. In this regard, low GDP growth is

very closely related to rising risk in the banking industry. In addition, increased risk for the banking industry can also

originate in high inflation, including when efforts to reduce inflation entail a sharp rise in real interest rates.

In the case of banking crises in the Asian region, Hardy & Pazarbasioglu (1998) state that the causes included

exchange rate appreciation followed by an extremely sharp depreciation, and sharp increase in foreign debts followed by

frequent defaults. In addition, major problems (although not of crisis proportions) in the banking industry generally

originated in domestic factors, such as excessive credit expansions to the consumer sector and high real interest rates on

deposits. Banking problems that lead to a crisis are generally caused by excessive credit expansion, especially from foreign

debts and sharp fluctuations in the real effective exchange rate.

II.2. Statistical Method and Tests

Logit Model

In general, dependent variables in regressions are not limited to a certain range. However, in some cases the

dependent variable may, by definition, lie between 0 and 1 (for example a probability) or only take on the values 0 or 1

(that is, binary values, for example, «yes» or «no»). In such a case, the logit model is often used, as represented by the

following equation:

(1)

In the above equation, P is a dependent variable that lies between 0 and 1. Taking anti-logs (exponential adjust-

ment), the following equation is derived :

uXP

P++=

−

βα1

ln

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Article II

(2)

If beta is larger than 0, the value of P will approach 0 when the value of X approaches minus infinity (-•); the value

of P will approach 1 when the value of X approaches plus infinity (•). Therefore, the value of P lies within the range of 0

to 1. Graphically, the logistic curve P is presented below:

The estimation procedure for the logit model is

influenced by the nature of P, namely whether it has values

between 0 and 1, or its values are only 0 or 1. If the value of

P lies between 0 and 1, then the method undertaken is to

transform P and derive Y=ln[P/(1-P)]. The next procedure is

to regress Y on a constant and variable XiXiXiXiXi. However, if the

value of P is binary (that is, 0 or 1), then the procedure is to

use the maximum likelihood method because the logarithmic

value of P/(1-P) is undefined. Several assumptions used in

the logit method are as follows:

(i)

(ii)

(iii) Y1, Y2, ....., YN all are statistically independent

(iv) No linear relationship amongst the Xik

Estimation using Maximum Likelihood

Estimation using maximum likelihood has a different final objective than the ordinary least square (OLS) method, but

has the same process as the OLS method in reaching that final objective. The final objective of the maximum likelihood

method can be explained as follows. For example, Pi=P(Yi=1|Xi). Then, P(Yi=0|Xi)=1-Pi and probability of deriving observation

result Yi (0 or 1) is shown by P(Yi|Xi)=PiYi(1=Pi)1-Yi. In this regard, in general the equation can be represented by :

(3)

The values of Pi and P(Y|X) in the above equation are determined by the value of b coefficient, whose estimation is

the final objective of the maximum likelihood method. Therefore, the function of b likelihood can be represented by:

(4)

)(11

uXeP

++−+=

βα

Chart 1Logistic Curve

Y

1

0

Y

NiYi ,.......,1,1,0 =∈

)exp(1

)exp()1(

ikk

ikkii Xb

XbXYP

∑∑

+==

ii Yi

Yi

N

i

PPXYP −

=

−=∏ 1

1

)1()(

)(),( XYPbXYL ≡

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Article II

(5)

With the consideration that it is easier to apply a summation procedure than a multiplication procedure, the above

equation is converted to:

(6)

Further, taking first derivatives of the above function, then the likelihood equation derived for the logit model is as

follows:

j=1, ......., k (7)

or

j=1, ......., k (8)

In short, using this procedure to derive the estimated equation, entails obtaining an estimate for the parameter b

that provides the largest observation value of Y.

Type I & Type II Errors

The decision to reject or not to reject the null hypothesis, in this case that specific indicators cannot be used to

predict banking crises, entails two possible errors. First, there is a possibility of rejecting the null hypothesis when it

should be accepted. This type of error is called a «Type I» error. Second, there is a possibility of accepting the null

hypothesis when it should be rejected. This is called a «Type II»

error. This is summarized in the following table.

In ideal conditions, efforts can be made to minimize both

type I and type II errors, by choosing more «powerful» tests

(see following paragraph). However, it is more generally

assumed that the occurrence of a type I error will have a higher

cost than a type II error.5 In this regard, the consequence is to

set the probability of a type I error at low level, for example

1% or 5%, and use an estimation technique that is as «powerful» as possible (also see following paragraph)

The probability of the occurrence of a Type I error is often represented by the notation a, and is known as the level

of significance of the test. The probability of a Type II error is represented by the notation b. The probability of not making

∏ ∑∑∑

=

−

+

+=

N

i

Y

ikk

Y

ikk

ikkii

XbXb

XbbXYL

1

1

)exp(11

)exp(1

)exp(),(

[ ]∑=

−−+=N

iiiii PYPYbXYL

1

)1log()1(log),(log

0)exp(1

)exp(

1

=

+−∑ ∑

∑=

ij

N

i ikk

ikki X

Xb

XbY

[ ]∑=

==−N

iijiiiXbXYPY

1

0),1(

5 Damodar N. Gujarati, ≈Basic Econometrics∆, 4th.ed, p.908.

Reject Type I error No error

Do not reject No error Type II error

DecisionDecisionDecisionDecisionDecisionNull hypothesis fulfilledNull hypothesis fulfilledNull hypothesis fulfilledNull hypothesis fulfilledNull hypothesis fulfilled Null hypothesis not fulfilledNull hypothesis not fulfilledNull hypothesis not fulfilledNull hypothesis not fulfilledNull hypothesis not fulfilled

Table 1Table 1Table 1Table 1Table 1Type I & Type II ErrorsType I & Type II ErrorsType I & Type II ErrorsType I & Type II ErrorsType I & Type II Errors

ConditionConditionConditionConditionCondition

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Article II

a Type II error is known as power of the test. In other words, the power of a test is the ability to reject the null hypothesis

when that condition is not fulfilled.6 In general, applications of a and b in hypothesis testing are done by setting a at a

certain level (for example 1% or 5%), and then attempting to minimize b by maximizing the power of the test.

III ESTIMATIOM RESULTS AND INTERPRETATION

III.1. Estimation Results

This review of early indicators of a banking crisis generally adopts the model used by Hardy & Pazarbasioglu (1999).

The hypotheses used in this review are:

H0 = the real sector, banking sector, and shock indicators cannot be usedcannot be usedcannot be usedcannot be usedcannot be used as early indicators of a banking

crisis

H1= the real sector, banking sector, and shock indicators can be used can be used can be used can be used can be used as early indicators of a banking crisis

Further, the model is estimate using a model specifications as follows :

Where :

CSD = Crisis / severe distress PDBR = Real GDP

KNSW = Private Consumption INVS = Investment

DPK = Third party funds KRSW = Credit to private sector

REER = Real Effective Exchange Rate PDEF = Inflation

In this model specification, almost all independent variables are in logarithmic form and first differences. In this

regard, the use of logarithmic independent variables is aimed at explaining the changes in dependent variables, which are

not always proportional to the changes in independent variables. For its part, the dependent variable takes on binary

values (0 and 1), where 1 indicates crisis or severe distress and 0 indicates no crisis or severe distress.

In general, data for the real sector group cover real GDP growth (PDBR), private consumption growth (KNSW) and

investment growth (INVS). Data for the banking sector variables cover third party funds (DPK) and credit to the real sector

(KRSW), while those for the shock variables cover inflation (PDEF) and the real exchange rate (REER).

Estimation results indicate that (with 95% level of confidence) there is a relationship between the occurrence of a

crisis (or severe distress) in the banking industry and: real GDP growth; the real effective exchange rate; the growth of

credit to the private sector; the change in public deposits; and private consumption growth. Meanwhile, changes in

investment and the inflation rate are not significant. Estimation results conducted using the EViews program are presented

in the accompanying Table

Turning to the incidence of Type I and Type II errors (with a 10% cut-off point), there are 15 observations (3.62% of

the sample) where the model did not predict a banking crisis when a crisis actually occurred, thus causing a Type I error.

6 Ibid.

),,,,,,( PDEFREERKRSWDPKINVSKNSWPDBRfCSD =

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Article II

In addition, there are 59 observations (14.25%) where estimation leads to the conclusion of a crisis when no crisis actually

occurred, thus causing a Type II error. In other words, results of the tests on Type I and Type II errors show that for 82.13%

of the sample (340 observations), the model was a reliable indicator of a banking crisis.

VariableVariableVariableVariableVariable CoeficientCoeficientCoeficientCoeficientCoeficient Std. ErrorStd. ErrorStd. ErrorStd. ErrorStd. Error z=Statisticz=Statisticz=Statisticz=Statisticz=Statistic Prob.Prob.Prob.Prob.Prob.

C -2.440598 0.248.169 -9.834.404 0.0000

DLPDBR -11.51757 4.079719 -2.823130 0.0048

DL RER -6.983.535 1.554.213 -4.493.294 0.0000

DLKRS(-2) 3.291.377 1.485.540 2.207.393 0.0273

DLDPK (-2) -3.377.351 1.478.805 -2.286.931 0.0222

DLKSW (-2) 1.390.082 0.652.175 2.131.457 0.0331

DLINVS (-1) -0.910.838 0.474.818 -1.918.286 0.0551

DLPDEF (-1) -0.208.565 0.131.684 -1.583.827 0.1132

Log likelihood -103.2181 akaike info criterion 0.537.286

Restr. log likelihood -124.6481 Schwarz criterion 0.615.080

LR statistic (7 df) 42.86002 Hannan - Quin likelihood -0.249.319

Probability (L stat) Mc Fadden R-squared 0.171.924

Table 1Estimation Results

Correct Estimates 340 82.13

Type I Error 15 3.62

Type II Error 59 14.25

Total 414 100.00

ObservationObservationObservationObservationObservation %%%%%

Cut-off Point = 0,1Cut-off Point = 0,1Cut-off Point = 0,1Cut-off Point = 0,1Cut-off Point = 0,1

Table 3Results of Test on Type I & Type II Errors

Diagram 1Probability of the Occurrences of Crises/Severe Distress in 40 Countries

238 253 273 273 288 298 299 423 423 423 439 536 536 542 542 548 566 566 566 576 576 578 578 578 612 612 622 628 634 634 638 664 674 674 722

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Code Country

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

0.45

0.5

122 122 128 128 132 134 134 138 138 138 142 144 146 146 146 156 158 172 172 176 181 181 182 182 186 186 186 193193 196 196 199 199 233 238

Code Country

The capability of this model to predict a crisis (or severe distress) in the banking industry is depicted in the following

diagram.

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Article II

For Indonesia, the probability of a crisis was well

predicted as simulations indicate the probability of crisis at

more than 70% using this model.

III.2. Interpretation

Using the model specified earlier, crisis (or severe

distress) in the banking industry can be predicted by the use

of six indicators, namely: real GDP growth; rising private

consumption; declining investment; sharp exchange rate

depreciation; heightening credit extensions to the private

sector; and continuous declines of total public deposits.

Rising private consumption, accompanied by declining investment and declining real GDP can be interpreted as a

fall in the capacity of the economy to produce goods and services. This situation will hurt companies» capacity to make

profits and repay their credit from the banking industry. Further, expanding credit by the banking industry will worsen

existing conditions because credit is no longer being extended based on business viability. Consequently, the ratio of the

banking industry»s non-performing loans will be rising, which in turn will harms banks» performance. With an accumulation

of problems in the banking industry that are caused by problems in the real sector, public confidence in the banking

industry will deteriorate, causing a drop in deposits.

Problems cumulate, as foreign investors take the view that Indonesia»s economic fundamentals are deteriorating as

reflected, among others, in declining real GDP and rising non-performing loans. Consequently, many foreign investors

will withdraw their funds. If this is done on a large scale and in a rush, the exchange rate will depreciate sharply. This

depreciation will further hurt companies» repayment capacity and banks that have high foreign-currency denominated

liabilities.

This combination of negative factors can put severe pressure on the banking industry, which may well lead to crisis.

Therefore, development of these indicators can be used as indicators of potential problems, which if not tackled immedi-

ately, can lead to a banking crisis.

IV. CONCLUSION

Analysis of annual data on 40 countries (of which 31 experienced crisis or severe distresses) shows that macroeco-

nomic and banking indicators together with shock variables can be good early indicators of crisis in the banking industry.

The macroeconomic indicators include slowing economic growth, declining volumes of investment, and rising private

consumption. Also, factors internal to the banking industry that can be early indicators of crisis include rising credit to the

private sector, and sharply declining total third party funds. Useful shock indicators are rising a inflation rate and a sharp

exchange rate depreciation.

In the case of Indonesia, current economic indicators suggest that there is no potential for a banking crisis in the

short-term. This can be seen from GDP growth, which is showing an upward trend, a relatively stable rupiah exchange

rate, investment that has tended to be stagnant since the crisis, slow expansion of credit to the real sector, a declining

Diagram 2 Probability of theOccurrence of 1997 Crisis in Indonesia

1984 1985 1986 1987 1989 1990 1991 1992 1993 1994 1995 1996 1997

0.2

0

0.1

0.3

0.4

0.5

0.6

0.7

0.8

0.9

Years

106

Article II

trend in inflation and stable public deposits. However, there is one indicator that requires attention, and that is rising of

private consumption. On one hand, a rise in private consumption can boost the economy by raising demand for goods

and services. However, if it is not matched by a rise in investment and domestic production, it could put pressures on the

prices of goods and services, causing rising inflation and higher interest rates, which could push up non-performing loans

due to debtors» declining repayment capacity.

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Article II

Aldrich, John H., and Forrest D. Nelson, 1984, ≈Linear Probability, Logit and Probit Models∆, Series: Quantitative

Applications in the Social Sciences, Sage University, California.

Damodar N. Gujarati, 2003, ≈Basic Econometrics∆, 4th Ed. McGraw-Hill, Singapore.

Dermiguc √ Kunt, Asli, and Enrica Detragiache, 1998, ≈The Determinants of Banking Crises in Developing and

Developed Countries∆, IMF Staff Papers Vol. 45 No. 1 (March), International Monetary Fund, Washington.

Goldstein, Morris, Graciela L. Kaminsky, and Carmen M. Reinhart, 2000, ≈Assessing Financial Vulnerability: An

Early Warning System for Emerging Markets∆, Institute for International Economics, Washington.

Hardy, Daniel C. & Ceyla Pazarbasioglu, 1999, ≈Determinants and Leading Indicators of Banking Crises: Further

Evidence∆, IMF Staff Papers Vol. 46 No. 3 September/December 1999, International Monetary Fund, Washington.

_________________________________, 1998, ≈Leading Indicators of Banking Crises: Was Asia Different?∆, IMF

Working Paper 98/91, International Monetary Fund, Washington.

Kaminsky, Graciela, Saul Lizondo, and Carmen M. Reinhart, 1998, ≈Leading Indicators of Currency Crises∆, IMF

Staff Papers Vol.45 No. 1 (March), International Monetary Fund, Washington.

Kaufman, George F., 1997, ≈Preventing Banking Crises in the Future: Lessons from Past Mistakes∆, The Indepen-

dent Review, v.II, n.1., p.55.

Ramanathan, Ramu, 1998, ≈Introduction to Econometrics with Applications∆, 4th Ed., The Dreyden Press, HBJ, New

York.

Bibliography

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109

Article III

Article III

Company Failure Indicators in Indonesia :As An Additional Early Warning Tool On Financial System Stability

Abs t r act

1 Head of Financial System Stability Bureau √ Directorate for Banking Research and Regulation, Bank IndonesiaΩ; e-mail addressΩ: [email protected] Bank Executive Researcher at Financial System Stability Bureau √ Directorate for Banking Research and Regulation, Bank IndonesiaΩ; email address: [email protected] Bank Researcher at Financial System Stability Bureau √ Directorate for Banking Research and Regulation, Bank IndonesiaΩ; email address: [email protected]

Muliaman D Hadad1, Wimboh Santoso2 & Ita Rulina3

December 2003

The purpose of this study is to obtain empirical evidence on financial ratios that are able to discriminate

failed companies behavior from those that are not, as well as to compare the capability of two techniques that

are often used in predicting bankruptcy. Techniques used in this study are Discriminant Analysis and Logistic

Regression. Coefficients of the independent variables are estimated using the simultaneous approach for

Discriminant Analysis and maximum likelihood method for Logistic Regression. This study shows that liquidity

ratios are the best discriminators in differentiating failed companies from those that are not. Furthermore, this

study also shows that Logistic Repression is a better approach than Discriminant Analysis relatively. This is

reflected by the values of correct estimates of Logistic Regression that is on average higher than those of

Discriminant Analysis, where these average values were each 86.72% and 78.1% for 1 year before the event of

bankruptcy.

Keywords: Bankruptcies, logistic regression, and discriminant analysis.

JEL Classification: G33, C35

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Article III

I. INTRODUCTION

I.1. Background

1997 crisis that occurred in Indonesia incurred very expensive fiscal cost, reaching 51% of GDP. This crisis stimulated

a realization of the importance of financial market stability and financial institutions» soundness, which form the financial

system. Financial market stability and financial institutions» soundness are able to dampen a crisis, which actually are

interactions between several risks that need to be well managed constantly. One of the risks that must be managed well

to avoid disruption to financial system stability, is companies» failures to repay their borrowings. Companies» failures to

repay their borrowings can be called corporate failure.

A study by Beaver (1966) is often used as a main reference in corporate failure studies. Beaver looked at a company

as a reservoir of liquid assets, which was supplied by inflows and drained by outflows. Beaver used 30 ratios applied to

79 failed and non failed companies» pairs. Using the univariate discriminant analysis as the statistical tool, Beaver concluded

that working capital funds flow/total assets and net income/total assets were able to differentiate failed companies and

those that were not, each at 90% and 88% accuracy.

Altman (1968) conducted another study on the same topic as Beaver but he used the multivariate discriminant

analysis and produced a model using 7 financial ratios. In his study, Altman used a sample of 33 pairs failed and non

failed companies. The model could accurately predict 90% of failure cases at one year prior to bankruptcy.

Studies on this topic continue to be conducted and the latest one on the subject was focused on the statistical

testing tool. Ohlson (1980) was the first researcher that used the logit analysis to predict companies failures. On his

study, Ohlson used 105 failed companies and 2058 non failed companies and found 7 ratios as the best predictors of

failed companies with accuracy level closed to Altman»s study.

The importance of corporate failure was also supported by Krugman, who discussed global financial downturns

and included balance sheet fundamentals theory as a signal of a crisis (Krugman, 1999). Although many studies on

corporate failure have been conducted, it looks like they are going to be continued because the business world develops

so rapidly and the question always arises whether the factors that cause corporate failure remain the same.

I.2. Issues

It is necessary to identify factors that cause corporate failure that will give impact on financial system stability and

financial institutions» soundness. This will enable us to identify a crisis earlier and minimized the loss of a crisis. Based on

this condition, this study will focus on:

1. Which financial ratios are able to differentiate failed companies from those which are not.

2. Whether the Discriminant Analysis or the Logistic Function will be the best statistical tool to predict failed companies.

1.3. Objectives

The objectives of the study are :

1. To obtain empirical evidence on financial ratios which are able to discriminate the behaviors of failed companies

from those that are not.

2. To obtain the best statistical testing tool to be used in predicting companies» failure.

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Article III

1.4. Benefits

This study is expected to bring benefits to the following parties :

1. Creditors and Investors

Creditors have an interest to know whether companies are able to repay their borrowings. Investors have an

interest to know whether companies are sound and able to give optimal returns on their investments. Creditors and

investors can use this study to minimize potential losses of their placements.

2. Auditors

On the other hand, auditors are responsible for making evaluation on their clients going concern. Auditing Standards

Statement number 30, Indonesian Accounting Association 1993, states that when an auditor concludes that there is a

fundamental doubt on their client»s ability to continue going concern, the auditor is obliged to disclose this in his report.

An auditor»s inability to predict their client»s failure is called as audit failure (Taylor and Glezen 1994) and can entail quite

high legal claim cost. The growing number of legal claims on auditors, which will cause higher audit failure cost, will

prompt audit companies to enhance the failure prediction techniques used.

3. Bank Indonesia and Government

As already mentioned in the beginning, the main objective of this study is to identify factors that influence financial

system stability and financial institutions» soundness. From this point of view, this study will be useful for Bank Indonesia

and the government.

For Bank Indonesia, particularly the Banking Research and Regulation Directorate, Bank Supervision Directorate,

and Bank Examination Directorate are working units that are concerned with corporate failure. As regards the government,

the Capital Market Supervisory Board (Bappepam) will be the predominant user of this study. As regards Bank Indonesia,

one of the tasks of bank supervisors/examiners is to assure that banks operate in prudential manner to safe depositors»

interest. To improve bank supervisors/examiners» evaluation on Banks» loan quality, this study can be used as one of early

warning tools. It is expected that supervisors/examiners are able to detect bank that lend money to unsound companies

as early as possible. In the end, supervisors evaluate credit risks faced by banks, banks actions to undertake these risks,

and supervisory actions needs to be taken on this bank. After that, supervisors/examiners/policy makers can make

evaluations whether the risks are systemic because for example the debtor is a large company that is also being financed

by other banks.

1.5. Methodology

The paper is organized as follows :

Chapter I, contains background, issues formulation, objectives, benefits, and methodology.

Chapter II, present theoretical concepts of corporate failure technique, definition of failure, and uses of financial

reports.

Chapter III, describes the model used in this study, notations, variable definitions and measurement, data collection

technique, as well as characteristics of data obtained.

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Article III

Chapter IV, present data analysis, which are divided into two sections. The first section contains statistical data

descriptions, while the second contains discussion on statistical test results.

Chapter V, contains the conclusions, recommendations, and descriptions of limitation of the research.

II. LITERATURE STUDY

II.1. Development of Research Techniques on Corporate Failure

Beaver was a pioneer in corporate failure study and his research is often considered as a milestone in this area. The

approach adopted by Beaver was the univariat, where each ratio without being followed by other ratios is tested on its

capability to predict corporate failure. Altman (1968) tried to improve on Beaver»s study by adopting the multivariate

linear discriminant analysis (MDA), a method often proved to make limitations. The MDA technique used by Altman is a

regression technique of several uncorrelated time series variables that uses cut-off values to determine the classification

criteria for each group. The advantage of using the MDA technique is that all characteristics of the variables observed are

included, together with their interactions. Altman also concluded that the MDA reduces the measurement distance/

dimensionality from the researchers by the use of cut-off points. In general, because the MDA is easy to use and

interpreted, it is often the choice of researchers on corporate failure all this time.

However, in using financial ratios to predict corporate failure, the MDA technique uses the error method that

follows the characteristics of data used. With this condition, the important issues that have been discussed many times

in research literatures are that of the use of the proportional assumption and zero intercept of the financial ratios (Lev

and Sunder, 1979, Whittington, 1980; McDonald and Morris, 1984; Rees, 1990; Keasey and Watson, 1991). As such,

overall, the resulting empirical proofs become more uncertain and there is no formal statements confirming that more

sophisticated ratios are better than the basic ratios. For this reason, simple ratios are still used in most studies on

corporate failure.

Another problem related to the MDA on prediction of corporate failure is the problems of data normality, inequality

of dispersion matrix of all groups, and non-random-sampling of companies that fail and do do not fail. Each of this

problem makes the regression result becomes ordinary.

In general, researchers ignore these limitations and continued on Altman»s research with the hope of obtaining a

more accurate model. Several examples of researches conducted afterwards are :

1) Probability membership classes project conducted by Deakin, 1972;

2) The use of quadratic classifier (Altman, Haldeman and Narayanan, 1977);

3) The use of cashflow based model (Gentry, Newbold and Whitford, 1987);

4) The use of quarterly financial report information (Baldwin and Glezen, 1992);

5) Current cost information (Aly, Barlow and ones, 1992; Keasy and Watson, 1986).

But, none of these researches obtained better accuracy than Altman»s research. Furthermore, in many cases,

application of bankruptcy models faced difficulties because models used turned out to be more complex.

What ought to get attention regarding development of statistical testing techniques used to predict bankruptcy is

the statistic testing technique used by Ohlson (1980). In 1980, Ohlson used the logistic regression (logit analysis) to

predict bankruptcy, a method that avoids the limitations of the MDA technique. In the logit analysis, the assumption of

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multivariate normal distribution is ignored. With this assumption, the limitations in the statistical testing technique for

bankruptcy using the MDA can be overcome by logit. Logit, together with the probit analysis (a variation of logit), are

called as the conditional probability model because logit provides conditional probability of observations derived from

one group.

Another consideration in using logit is among others the logit model has a statistical advantage. However, this

model has to be modified to ensure the validity of the parameter coefficients with the group influence resulting from the

data panel.

II.2. Information Obtained From Financial Report

The research on corporate failure starts at financial ratio analysis. The main reason for the use of financial ratios

is that a financial report usually contains important information concerning the condition and future prospects of the

company (Fraser, 1995). A financial report is a report concerning a company»s past performance, which is often used

to predict the company»s performance in the future. Decisions made by the company»s management usually are related

to two main information. First, information stated in the revenue and expense group, while the second, the timing of

the occurrences of those revenue and expense transactions. In several cases, the management is motivated to act not

exactly honestly in reporting the revenues and tax expense it has to pay. A company»s management also often reports

higher profit only for the purpose to attract investors or to overcome financial pressures being experienced by the

company.

The use of financial ratios to make a statement on the going concern capability of a company is a technique that is

largely used. Financial ratios are replacement measurements in making an observation on the real characteristics of a

company.

Studies using financial ratios were started in 1930»s and several follow-on studies put more focus on business

bankruptcy. Most of those research results were convinced that a company that was bankrupt had different ratios than

one that is not. In general, ratios that measure profitability, liquidity, and solvency have been successful in being indicators

of business bankruptcy.

In conducting a research on bankruptcy, Beaver (1966) used the following financial ratios: cash flow/total debt,

current assets/current liabilities, net income/total assets, total debt/total asset, working capital/total assets.

Altman (1968), who has conducted a research on bankruptcy after Beaver, again used financial ratios as factors that

can be evaluated to indicate a company»s bankruptcy. The financial ratios used by (1968) were Current Assets/current

Liabilities, Market Value of Equity/Book Value of Debt, Net Sales/Total Asset, Operating Income/Total Asset, EBIT/Total

Interest Payments, Retained Earnings/Total Assets, Working Capital/Total Assets, Working Capital/total Assets, Retained

Earnings/Total Assets, Earnings Before Interest and Taxes/total assets, market value equity/book value of total debt, sales/

total sales.

With the Logistic Regression statistical test, Ohlson (1980) again conducted a research on financial ratios that can

be indicators to see a company»s bankruptcy. The financial ratios used by Ohlson in conducting his research are as follows:

total liabilities/total assets, working capital/total assets, current liabilities/current assets.

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II.3. Company Bankruptcy

II.3.1. Definition of Bankruptcy Commonly Used in International World

Standard & Poors (S&P) defines bankruptcy (default) as follows:

The first occurrence of a payment default on any financial obligation, rated or unrated, other than financial obligations

subject to a bona fide commercial dispute; an exception occurs when an interest payment missed on the due date is made

within the grace period.

While, the definition of bankruptcy by ISDA (International Swaps and Derivatives Association) is when one of the

following condition occurs :

1. A company that has issued indebtedness letters stopped operation (bankrupt)

2. A company that is not solvent or is not able to pay debts

3. A claim on bankruptcy has emerged

4. A bankruptcy process is occurring

5. The receivership has been appointed

6. All assets have been transferred to the custody of a third party

A financial theory assumes that a perfect bankruptcy system gives quite valuable benefit to the economy. In general,

two types of costs are known in a case of a company»s bankruptcy, namely direct cost and indirect cost. Direct cost is cost

that is directly incurred by the company to pay lawyers, accountants, and other professionals to restructure its finance and

then report it to the creditors. In addition, the interests that the company has to pay on further borrowings, which usually

are more expensive, are also direct cost of the bankruptcy. Meanwhile, indirect cost is the potential loss faced by the

company that is suffering from financial difficulties, such as loss of customers and suppliers, loss of new projects because

its management is concentrating on settlement of financial difficulties in the short term. The loss of the company»s value

when the Manager or Judge liquidates a company that still owns a positive net present value is also an indirect cost of the

bankruptcy. When looking at quite high direct and indirect costs of a company that is experiencing financial difficulties,

a modern bankruptcy court will attempt to keep the company as a going concern and tackle creditors» claims as quickly

as possible. An established bankruptcy law will give protections for the creditors as well as give a good mechanism for

solving the disputes between the parties quicker. By eliminating uncertainty, the established bankruptcy system will

prompt the businessman and large company to take larger risks. This can also reduce cost of capital by requesting a

finance expert to calculate/estimate how creditors will be paid when default occurs.

II.3.2. Bankruptcy in Indonesia

The definition of bankruptcy in Indonesia refers to government regulation as replacement of law number 1 of 1998

concerning Amendments to Bankruptcy Law, which states :

1. A debtor, who has two or more creditors and does not pay at least one debt after it has fallen due and that debt

cannot be claimed, is declared bankrupt by authorized court decision, whether at the debtor»s own request or at the

request of one or more of the debtors» creditors.

2. The request mentioned above can also be lodged by a public prosecutor for the sake of public interest.

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The bankruptcy law basically determines how disputes are settled when a company cannot fulfill its debt obligations

anymore and also how to settle disputes between individuals related to business conducted. There are several important

criteria :

1. The accounting has to be clear. Asset valuation has to be transparent and uses ways that are commonly acknowledged

(international standards);

2. Debt grading level based on priority of guarantee determines who should be first in the settlement of debt. For

example : In the case of a bankrupt company; who should have the first right to receive payment and should get the

next right;

3. The civil court regulates parties that have interests, parties that arrange the bankruptcy process, the competent

court, and the way/process to be undertaken in settling the case;

4. Determination of penalties by an authorized court if one of the parties does not fulfill a promise. The length of time

given to a company that considers itself able to settle its debts on its own;

5. Although it is pronounced bankrupt, of course a company can still operate for a while. In this case, the prerequisites

and the parties that should supervise the rehabilitation process are determined. A company that is pronounced

bankrupt does not need to immediately stop all its activities. They must be given opportunities to finalize financial

matters and other activities for the interest of the parties that claim repayments of debts;

6. Settlement of disputes can also be done through an outside the court arbitrage.

A company that is pronounced bankrupt if within a determined period cannot make payments on debt principals

and or interests. Bankruptcy can also be requested by a company»s owners or also by its creditors.

In addition to the terminology bankruptcy described above, in the business world the terminology delisting is also

know. The Jakarta Stock Exchange registration regulation number 1B of 2000 and 2001 state the following as regards

delisting rules :

1. Delisting can be undertaken at the request of an issuer or when determines by the Bourse. In the case of delisting

that is determined by the Bourse, the opinion of the Securities Registration Committee has to be heard first.

2. Delisting at the request of an issuer can only be undertaken when it has been decided by the shareholders» general

meeting and the related issuer has settled all its obligations to the Bourse.

3. Delisting at the request of an issuer is submitted two months before the date delisting becomes effective by stating

the reasons and attaching the minutes of the shareholders» general meeting mentioned above.

4. In the case the request for delisting is fulfilled, the Bourse is obliged to make an announcement on the delisting plan

at least 30 days before the date delisting becomes effective.

5. An issuer, which securities are listed at the Bourse, that experiences one of the following conditions will be considered

to be imposed with delisting :

a. For 3 consecutive years has suffered losses, or has a loss balance of 50% or more of paid-in capital in the

company»s balance sheet of the last year;

b. For 3 consecutive years has not paid cash dividends (for shares).Has not fulfilled its obligations for three times

(for bonds);

c. Its own total capital is less than Rp3,000,000,000,- (three billion rupiah);

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d. Total shareholders is less than 100 (people/entity) during 3 consecutive years based on the annual reports of the

issuer/Securities Administration Bureau;

e. There hasn»t been any transactions during 6 consecutive months;

f. The financial report developed is not in accordance with the generally accepted accounting principles and

regulations determined by Bapepam;

g. Violates the regulations of the Bourse in particular and the capital market in general;

h. Undertaking actions that violate public interests based on an authorized institution»s decision.

i. An issuer is liquidated because of merger, amalgamation, bankruptcy, dissolution (mutual funds) or other reasons;

j. The issuer is pronounced bankrupt by the court;

k. The issuer is facing claims/cases/incidents that materially influence the condition and going concern of the

company;

l. Specifically for mutual funds issuer, the net asset value declined less than 50% of the value of first offerings due

to operating loss.

III. METHODOLOGY

III.1. Model Specifications

Discriminant analysis and logistic regression are statistical techniques that are most suitable when the dependent

variables are non-metric or categoric (for example, male and female; bankrupt and not bankrupt). In most cases, dependent

variables consist of two groups, for example male group versus female group or bankrupt company group versus non-

bankrupt company group. There could also be three grouping, such as short group, medium group, and tall group.

Discriminant analysis is able to settle regressions with two or more dependent variable groups. If two dependent variable

groups are used, this technique is commonly known as two-group discriminant analysis. If three dependent variable

groups are used, it is commonly called the Multivariate Discriminant Analysis. The Logistic regression, commonly known

as the logit analysis, is limited to two groups, although a more complex alternative formula can handle more than two

groups of dependent variables.

Discriminant Analysis

Discriminant analysis attempts to produce the best linear combination of two or more independent variables, which

will discriminate the bankrupt group from the non-bankrupt group. This is achieved by the statistical decision rule of

maximizing the between-group variance relative to the within group variance. This relationship is expressed as the ratio of

between-group to within-group variance.

The equation in the discriminant function is a linear combination of the financial ratios of the company group that

will produce a new axis Z, which is a diagonal line with 45-degree angle of financial ratios used. The new axis, called Z,

gives a maximum capability to differentiate the two group companies. The new axis Z is called discriminant function and

a projection of one point in the discriminant function is called discriminant score. Z is a discriminant function determines

the values of w1 dan w2 of the above discriminant function in order to maximum the value of lambda (l).

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The discriminant function is derived by maximizing the value _ and is called Fisher»s linear discriminant function. The

evaluation of the significance of the discriminant variable can be seen from the average financial ratios, whether they

differ significantly between those of the bankrupt companies and those of the non-bankrupt companies.

The discriminant analysis derives the linear combinations from an equation that takes the following form:

Z = ω1 x1 + ω 2 x2 +º+ ω n xn

Where:

Z = discriminant score

ω i = discriminant weights

xi = independent variables (financial ratios)

Thus, each company in the sample receives a single composite discriminant score, which is then compared to a cut-

off value, which determines to which group each company belongs.

Discriminant analysis gives the best result provided that the variables in every group follow a multivariate normal

distribution and the covariance matrices for every group are equal. However, several past researches have shown that

especially bankrupt firms violate the normality assumption and the assumption of equal covariance matrices for every

group. Multicolinearity between independent variables even becomes a serious problem, particularly when the stepwise

procedure is used (Hair et al. 1992). However, empirical studies have proved that the problems connected with normality

assumptions were not weakening its classification capability (to differentiate the bankrupt group from the non-bankrupt

group), but its prediction ability.

Estimation with Discriminant Analysis

The most frequently used methods in estimating equations using discriminant analysis are the simultaneous and the

stepwise methods. The simultaneous method estimates the discriminant function by entering all the variables simultaneously

into the discriminant function, without considering first the discriminatory power of individual variables. This method

then chooses variables that have the most discriminatory power. For its part, the stepwise method starts with a selection

of independent variables that have the most discriminatory power. It then adds other independent variables as long as

the equation»s discriminatory power increases. The simultaneous method used in this research is included in the SPSS

program package used at Bank Indonesia.

In choosing the preferred estimate of a discriminant function, several issues require the researcher»s close attention,

namely:

1. Is there a significant difference between the two groups of companies? Statistical judgement is made in this regard

by calculating Wilk»s Lambda test statistic. To test the statistical significance of the calculated value for Wilk»s Lambda,

it can be converted into an F ratio.

Between group sum of squaresλ =

Within group sum of squares

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LnP

PZi

ii( )1 −

=

2. To test the statistical significance of the discriminant function, a multivariate test of significance is used. This test can

use the value of Wilk»s Lambda or an approximation using a Chi-Squared statistic.

3. Analyze the squared canonical correlation (Gujarati) to determine the ability of the independent variables to explain

the differences that occur between the two groups of companies.

4. The coefficients used in the discriminant equation are obtained from the Standardized Cannonical Discriminant

Function Coefficient table (Gujarati).

5. Meanwhile, to determine a cut-off point, it is necessary to check the value of the variables in the matrix structure

table.

Logistic Regression

Logistic Regression is used to analyze the probability of certain events occurring, as predicted by certain independent

variables. Mayer and Pifer (1970) adopted a limited dependent variable regression model in their research. This approach

uses the symbol ≈1∆ for bankrupt companies and ≈0∆ for non-bankrupt companies. Econometric experts identify this

model as the linear probability model (LPM). However, Gujarati is of the opinion that this approach does not guarantee

that the estimation results will lie in areas between 1 and 0; therefore, the regression equation has to be estimated

subject to certain limitations. The Logistic Regression approach can be adapted for the LPM (Aldric & Nelson. 1984) so

that there is a guarantee that the estimation results will lie between 0 and 1. The equation formed is:

where:

yi = dependent variable of cross section i data and period of time t

b1 = Intercept for all cross section i data and period of time t

bk = coefficient of independent variable k for all cross section i data and period of time t

xik = the kth independent variable for cross section i data and period of time t

ei = disturbance (error) term for observation

The assumptions used here are that the average disturbance value is 0 or E(eiI xi) = 0; variance µi for each value of

x is the same or var (µi I xi) = (µi2 I xi) = s2; there is no autocorrelation between disturbances or cov (µI, µj I xi, xj) = 0.

From equation 1, unconstrained probability estimate (Zi) is derived. For example, Pi is the probability that a company

is categorized as being bankrupt and P=(1-Pi) is the probability that a company is categorized as being not bankrupt, then

the logit function will be as follows :

y x eik

K

k iki

N

i= + +==β β1

11Σ Σ (1)

With some algebraic manipulation, Pi can be re-written as:

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P

e

ei

z

z=+( )1

Y

1

0

Y

The constant (b1) and coefficients (bk) on the

independent variables of equation 1 can be estimated using

the maximum likelihood approach. This approach estimates

values for b1 and bk such that the probability of the

observation value Y (dependent variable) is as close as possible

to its actual value. The logarithmic value of Pi will be in the

range of 1 and 0, producing the following chart:

Logistic Regression Estimation Method

The estimation method for Logistic Regression is maximum likelihood. The objective of the maximum likelihood

method is to obtain parameter estimates that yield the closest values to observation value Y. In general, this equation is:

[ ]=

==−N

iijiiiXbXYPY

1

0),1(Σ j=1, ......., k

The difference between this model and Discriminant Analysis lies in the following statistics that the researcher»s

attention:

1. Goodness-Of-Fit (Pseudo R2)

The traditional R2 [Gujarati] is less suitable for a model with a limited dependent variable (Aldrich and Nelson, 1984)

because the value of the dependent variable is either 0 or 1. The success criteria using the traditional R2 is the level

at which the error variance is minimized, which is the same of the logit model using the maximum likelihood

approach.

Previous studies use several methods to measure the pseudo R2. Several studies, such as McFadden (1973), Aldrich

and Nelson (1984), and McKelvey and Zavoina (1975) showed that various pseudo R2s, calculated with different

techniques would produce different values despite using the same model and data. To determine the best pseudo

R2 is somewhat arbitrary. Zimmerman (1996) suggested that the pseudo R2 from the McKelvey and Zovoina (R2MZ)

model was the best choice. However, R2MZ gives a value that is more sensitive to error misspecification than McFadden»s

pseudo R2, particularly in the binary probit and logit models. This research uses McFadden»s pseudo R2.

2. Test For Specification Errors

This research also tests the regression»s ability to estimate the probability of companies going bankrupt by using all

observations. The result is a set of probability numbers between 0 and 1. By using a certain cut-off point, this model

will produce 3 category of estimates: correct estimates, ≈type I error∆ (see following paragraph) estimates and ≈type

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II error∆ (also see following paragraph) estimates. The cut-off point is the probability that determines whether a

company is categorized as a bankrupt or non-bankrupt company.

This approach has often been used by researchers in estimating the probability of a company going bankrupt (Martin,

1977; Sinkey, 1975; Bovenzi, Marino and McFadden, 1983; Korobow and Stuhr, 1976, 1983; Espahbodi, 1991). For

example, suppose the cut-off point value is determined to be 0.5. This means that if the estimated probability

produced by the model is > 0.5, that company is included in the bankrupt group; if the estimated value is < 0.5, that

sample is included in the non-bankrupt group. Type I errors occur when the model produces estimated values > 0.5

for companies that do not go bankrupt. Type II errors occur when the model produces estimated values of < 0.5 for

companies that do go bankrupt. The lower the cut-off point, the larger the number of companies that are estimated

to go bankrupt and the smaller the number of companies predicted not to go bankrupt.

The choice of the cut-off point plays an important role in discriminant analysis. As a general rule, best criterion for

determining the cut-off value is the ratio between actual bankrupt companies and actual non-bankrupt companies in the

sample. For example, a sample comprising 50% of bankrupt companies and 50% of non-bankrupt companies should

use a cut-off point of 0.5. Similarly, a sample comprising 60% bankrupt companies and 40% non-bankrupt will use a cut-

off point of 0.4.

III.2. Descriptions of Research Variables and Data

Variables used in this study are liquidity ratios, profitability ratios, and solvency ratios.

Liquidity:

The total cash funds required by a company to finance its disbursements depend very much upon the company»s

line of business. Consequently, company management does not like the use of benchmarks for critical liquidity ratios.

Nonetheless, companies generally suffered a severe lack of liquid assets immediately after bankruptcy episodes, and

usually these companies borrowed even larger amounts for managing their short-term liabilities. Past research shows

that useful liquidity ratios for bankruptcy prediction models include the short-term debt/revenue from operations ratio

and the cash/total asset ratio.

Profitability:

A company»s profitability, which is usually measured as a return on capital, is a key factor for monitoring the liquidity

and solvency aspects of its operations. In the long-term, a company must make sufficient profit from its business in order

to be able to pay its liabilities. Continuous losses will soon weaken the solvency of a company, and if the company wants

to expand its business, it needs retained earnings to contribute to this need. In the short-term losses can immediately

reduce the company»s liquidity. Furthermore, the company»s profitability will influence the company»s ability to obtain

financing from abroad.

Solvency:

If financial markets are not perfect, capital structure will be important in the contractual relationship between

shareholders and creditor. The larger the amount of shareholders» equity, the lower the company»s financial risk and the

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easier for the company to borrow from third parties. Furthermore, the ratio of equity to total assets provides information

on past performance and also acts as a buffer against losses in the future.

Liquidity variables used in this study are:

1. Cash to current liabilities ratio

2. Cash flow to current liabilities ratio

3. Cash flow to total assets ratio

4. Cash flow to total debt ratio

5. Cash to net sales ratio

6. Cash to total assets ratio

7. Current assets to current liabilities ratio

8. Current assets/net sales ratio

9. Current assets/total assets ratio

10. Current liabilities/equity ratio

11. Equity/fixed asset ratio

12. Equity/net sales ratio

13. Inventories/net sales ratio

14. Long-term debt/equity ratio

15. Total debt/equity ratio

16. Net Income/total assets ratio

17. Net sales/total assets ratio

18. Operating income/total assets ratio

19. Liquid assets/current liabilities ratio

20. Liquid assets/net sales ratio

21. Liquid assets/total assets ratio

22. Retained earnings/total assets ratio

23. Total debt/total assets ratio

24. Working capital/net sales ratio

25. Working capital/equity ratio

26. Working capital/total assets ratio

Research Data

Data used in this research are obtained from the quarterly financial reports of companies that are (or have been)

listed at the Jakarta Stock Exchange (JSE). Unfortunately, data on companies delisted from the JSE are limited and related

documents often do not give information as to the reasons for the companies being delisted. Due to the many reasons

that a company can become delisted from the JSE, it was necessary to simplify the collection of sample companies that

are categorized as bankrupt. Accordingly, the criteria for a delisted (bankrupt) company were limited as follows: a company

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Standardized 0.593 R2L 0.662 R1L 0.919 R1L

Canonical -0.731 R3L -0.558 R5L 0.533 R7L

Discriminant 1.052 R6L 0.955 R6L -0.327 R16S

Function 0.353 R12S 0.321 R17P 0.430 R17P

Coefficients 0.312 R17P -0.637 R20P -0.674 R20P

-0.698 R20P 0.614 R24L

-0.278 R28S

Classification

Results 74.5% 77.3% 78,1%

3 year before3 year before3 year before3 year before3 year before

FailureFailureFailureFailureFailure





Table 1 Comparison of Discriminatorsbased on Discriminant Analysis

that during 3 consecutive years suffered losses, or a company with a loss balance of 50% or more of paid-in capital in the

company»s previous year»s balance sheet.

On this basis, the sample consists of 32 companies, of which 16 companies are still active on the Bourse and 16

companies have been delisted from the JSE. Due to data limitations, the grouping of bankrupt versus non-bankrupt

companies does not take into consideration the industries and asset sizes of those companies. Because the timing of

companies becoming delisted was not always the same, the financial data used for those companies are for 3 years prior

to becoming delisted. Meanwhile, data for listed companies cover the period 1999 to 2002.

IV. EMPIRICAL RESULTS

Results of data processing using the SPSS statistical software for Discriminant Analysis and EViews software for

Logistic Regression, as well as the related discussion, are presented in the two sections of Chapter IV, namely Discriminant

Analysis and Logistic Regression.

IV.1. Discriminant Analysis

To choose one or more variables that have a good ability to differentiate bankrupt from non-bankrupt companies is

not an easy matter, because the average data on these company groupings do not differ much. One way to eliminate

variables that do not have discriminatory ability is to use the simultaneous estimation method (using this SPSS program).

Output in this regard is presented below.

Output of the discriminant analysis in this paper is divided into 3 sections: the best discriminatory variables simulated

at 3 years, 2 years, and 1 year prior to bankruptcy.

Simulation of companies at 3 years prior to bankruptcy produces a Wilks» Lambda value of 0.797 or a Chi Squared

value of 86.028 with a significance of 5%, which means that the discriminant function is statistically significant. This

shows that the average values for the two groups of companies differ significantly. The discriminant function for condition

at 3 years prior to bankruptcy comprises six variables, namely R2L, R3L, R6L, R12S, R17P and R20P. The analysis indicated

that 6 variables were important in predicting bankruptcy. The classification result for this equation is 74.5%, which means

that the model is accurate 74.5% of the time in classifying companies into the two groups, 3 years prior to bankruptcy.

Estimation at 2 years prior to bankruptcy produces a

Wilks» Lambda value of 0.731 and a Chi Squared value of

78.468 with a significance of 5%, which means that the

discriminant function is statistically significant. The

discriminant function for condition at 2 years prior

bankruptcy comprises 7 variables, R1L, R5L, R6L, R17P, R20P,

R24L, and R28S. The analysis indicated that 7 variables were

important in predicting bankruptcy. The classification result

for this equation is 77.3%, which means that the model is

accurate 77.3% of the time in classifying companies into

the two groups, 2 years prior to bankruptcy.

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Simulation of conditions 1 year prior to bankruptcy produces a Wilks» Lambda value of 0.654 or Chi Squared value

of 52.431 with a significance of 0.000, which means that the discriminant function is statistically significant. The discriminant

function for condition at 1 year prior to bankruptcy comprises the R1L, R7L, R16S, R17P, and R20P variables. The analysis

indicated that 5 variables were important in predicting bankruptcy. The classification result for this equation is 78.1%,

which means that the model is accurate 78.1% of the time in classifying companies into the two groups, 1 year prior to

bankruptcy.

Statistically, these results are somewhat difficult to interpret because the average value of Wilk»s Lambda is surprisingly

close to 1, which means that the difference between the groups is not large. Nonetheless, the chi-squared test produces

a statistically significant value, as mentioned. For 3 years prior to bankruptcy, the R6L (Cash/Total Assets) variables have

the largest parameter values of 1.052, indicative of its importance as determining variables in that equation. At simulation

of conditions at 2 years prior to bankruptcy, R6L (Cash/Total Assets) and R1L (Cash/Current Liabilities) variables have the

largest parameter values of each 0.955 and 0.662, suggesting that these two liquidity ratios are the key determinants. At

1 year prior to bankruptcy, variables R1L (Cash/Current Liabilities) and R20P (operating income/total asset) have the

largest parameter values of each 0.919 and √0.674.

This description shows that liquidity ratios do play an important role in discriminating between the bankrupt and

the non-bankrupt companies. In addition, when the three simulations are compared, simulation of conditions 1 year

prior to bankruptcy gives the best statistical results. This means that the closer the company is to bankruptcy, the greater

the accuracy of the analysis in predicting the bankruptcy.

IV.2. Logistic Regression

Estimation results of the logit model are similarly categorized into 3 sections, simulations at 3 years, 2 years, and 1

year prior to bankruptcy. The chosen cut-off point is 0.5, because the sample size for the bankrupt companies is the same

as for non-bankrupt companies, namely 16 companies in each group.

For simulation at 3 years prior to bankruptcy, the EViews output produces an equation with correct estimates of

80.99% for a model comprising the R5L, R13L, R20P, R31L, R7L, and R14S variables. This means that these variables,

taken together, can accurately explain the difference between the two groups in 80.99% of the cases.

The estimated equation for 2 years prior to bankruptcy (with the same cut-off point) produces 85.54% correct

estimates for a model comprising the R5L, R20P, R31L, and

R7L variables. This means that these variables together can

accurately explain the difference between the two groups

for 85.54% of the cases.

For the simulation at 1 year prior to bankruptcy (with

a cut-off point of 0.5), the estimated equation accurately

explains the difference between the two groups in 86.72%

of the cases.

Comparing the Discriminant Analysis and Logistic

Regression approaches, both approaches produce the best

R5L R5L R5L

R13L R20P R20P

R20P R31L

R31L R7L

R7L

R14S







Table 2 Comparison of DiscriminatorsBased on Logistic Regression

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results at simulations at 1 year prior to bankruptcy. Also, both techniques show that liquidity ratios play an important role

in discriminating companies that are bankrupt. Overall, the Logistic Regression appears more reliable than Discriminant

Analysis, as indicated by the former»s relatively high average

correct estimates.

However, the combinations and types of discriminatory

variables produced by the two techniques are different.

Common discriminatory variables as between the two

approaches and across the periods prior to bankruptcy (that

is, 3, 2 or 1 year) are ratios related to liquidity. This is in line

with Beaver»s hypothesis and results.

The estimated Logistic Regression model can be used as a tool to calculate the possibility that a company will

experience financial distress in the future, thereby detecting the possibility of rising credit risk in a bank at a relatively early

stage. This could help bank supervisors/auditors in ensuring that a bank is taking prudent actions to anticipate the

possibility of rising credit risk. It would also help anticipate pressures on the financial system.

RECOMMENDATIONS FOR FUTURE RESEARCH

This research has limitations that could be improved with further research, as follows.

First, data on delisted companies are not adequate at the JSE. Therefore alternative data sources need to be

considered.

Second, due to data limitation in this research, bankrupt and non-bankrupt companies are not categorized by

industry. Therefore, analysis of financial factors specific to certain industries could not be incorporated.

Third, this research does not differentiate companies according to the size of their assets. This is important because

the size of a company»s assets can make a difference in the company»s ability to generate liquidity when it comes under

financial pressure.

3 years prior to bankruptcy 74.5 80.99

2 years prior to bankruptcy 77.3 85.54

1 year prior to bankruptcy 78.1 86.72

Correct EstimatesCorrect EstimatesCorrect EstimatesCorrect EstimatesCorrect Estimates DiscriminantDiscriminantDiscriminantDiscriminantDiscriminant

(in percentage)

Table 3 Comparison of Correct Estimates betweenOutputs of Discriminant Analysis and Logistic Regression

LogisticLogisticLogisticLogisticLogistic

125

Article III

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