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CREDIT RISK AND ITS ISLAMIC BANKING IMPLICATIONS

PhD Candidate

Mace Abdullah

MBA, CPA (Inactive)

LL.M. (Taxation), Juris Doctorate

CREDIT RISK AND ITS ISLAMIC BANKING IMPLICATIONS

Abstract

Financial intermediation is the backbone of a financial system. Banks are essential providers of

financial intermediation; even more so in bank-based economies. Financial intermediation

involves underwriting risks. Banks engage in a myriad of financial intermediation transactions

on a daily basis, e.g. lending, leasing, financing and investing. A key form of risk faced by banks

is credit risk. All banks must manage credit risk to remain viable. There are differences between

conventional and Islamic banks as to how credit risk is managed because of the differences in

their banking products. This analytic paper examines how banking credit risk assessment has

evolved in the 21st century and how the two banking systems differ in their management of it.

Malaysia’s banking system, as a recognized world leader in Islamic banking, is featured.

Key words: Credit Risk; Islamic Banking; Basel; Risk-Weighted Assets; Standardized Credit

Risk Approach; Internal-Based Rating of Credit Risk

Introduction

Credit has been part of commercial dealings since the earliest days of civilization. Most people

think of credit today as lending money, although many daily transactions are non-monetary. A

great deal of credit is sales-based. Thus, an accurate definition of credit should be inclusive of

both monetary and non-monetary financing. Accordingly, a working definition of credit is a

transaction between two parties in which one party (called the creditor, lender or obligee)

supplies money, goods, services or securities in return for a promise of future payment by the

other party (called the debtor, borrower or obligor). Generically, the parties are referred to vis-à-

vis one another as the “counterparty.”

Credit plays a key role in any financial system as a lynchpin of financial intermediation. It is

pervasive in modern society and as with most things in life, there are risks associated with it. It is

utilized at all levels of a society, including by government, businesses and individuals. The

primary providers of credit are: the public debt markets (including bond and money markets);

banks (commercial and retail); term lending finance companies (e.g. leasing and pawning

companies); development institutions (e.g. the Islamic Development Bank); cooperatives (e.g.

credit unions) and trade and consumer credit by firms themselves. The global debt market dwarfs

the equity market at nearly twice the latter’s size. Given the size and importance of credit in

financial systems worldwide, assessment of its attendant risks is unavoidable.

This paper discusses the theory of credit risk. It then examines how credit risk management

banking has evolved in the 21st century; paying particular attention to the standards promulgated

to control credit risk. It further discusses how conventional and Islamic banking systems view

and manage credit risk differently. Finally, a taxonomy of credit risk measurement models is

analyzed.

Credit, Debt and Risk

As will be discussed, credit and debt are often used interchangeably, but are not the same. Most

credit is assumed to be debt; and understandably so. Credit as debt, in some economic systems,

can yield tax advantages, thereby boosting returns. Prudent use of credit stimulates growth and

can lead to wellbeing. However, it can lead to overspending and can be used unnecessarily as a

“convenience.” The basic by-product of credit is its risk. Credit risk is the modern equivalent of

measuring the level of trust or confidence human beings can place in one another in their

financial dealings. Though the interaction still contains some of its personal aspects of trust,

modern finance has in some ways made the assessment of credit risk impersonal and objective

through the financial evolution of credit risk assessment methods.

It is settled reason that understanding the terms used in a subject is essential. Scholars of law do

so since the meanings sought are, more often than not, derived from the names given to them.

This process of nomenclature is not the sole right of science or law. Certainly, in finance, as a

component of economics, a social science, the need exists and is beneficial. It is particularly

important when comparatively viewing subject matter. By looking to the etymology of words in

their comparative languages, one can, more often than not, obtain a truer understanding of how

the subject matter is understood from the differing viewpoints.

Take the origin of the word “finance.” Its English origin is from the Latin word finis, meaning to

end, to settle a lawsuit, the payment of a debt, compensation or ransom; later taking the meaning

in French of taxation, revenue and reflecting a sense of development. Finance in the Arabic

comes from timuyyal, meaning to be capitalized or to become rich or wealthy. Hence, in English

finance denotes an obligation ostensibly leading to development; while in Arabic it denotes real

capitalization; not necessarily involving a debt or obligation. Nomenclature can lead to a deeper

understanding. Such is the case with the financial terms credit, debt and risk.

Conventionally, credit comes from the Latin word creditum, meaning belief or trust (Oxford

Dictionary, 2016). On its loftiest technical level, it means “man’s confidence in man” (Downes

& Goodman, 2010). Legally, it has the meaning of “the right granted by a creditor to a debtor to

defer payment of debt or to incur debt and defer its payment” (Black, 1979). Thus, it implies the

existence of underlying debt. Debt, in the English language, comes from the Latin word debitum,

meaning something owed (Oxford Dictionary, 2016). Its conventional meaning is similar,

meaning “money, goods or services that one party is obligated to pay to another in accordance

with an expressed or implied agreement” (Downes & Goodman, 2010). Legally, debt has similar

meaning to its technical use, expanded sometimes to include an aggregate of separate debts or a

total sum of existing claims against a person or firm, sometimes secured by guarantees or

collateral (Black, 1979).

Islamically, credit is called a’itimaan, meaning reliance, dependence, trust and confidence

(Baalbaki, 1996). It has also been understood to mean the belief held by people that a certain

person is wealthy (Elgari, 2003). Technically, it is an obligation created by a creditor for one

who seeks to be permitted to use a particular asset on account of the confidence reposed in him

with respect to it. It is the confidence in someone before an obligation or debt is granted (Id).

Thus, as conventionally, credit in banking terminology implies a debt in money, goods or

services (but with the original denotation of implied trust or confidence). Debt, in Arabic is dayn

and has linguistic origins meaning to obey or become obedient; take or receive a loan or borrow;

buy on credit or incur a debt; be held under authority; become habituated, accustomed to

something; confirmation; death (because it is a debt everyone must pay); or repayment or

compensation (Lane, 1863). Technically, dayn is synonymous with debt; which may be taken in

two senses: (1) private or any personal liability resulting from sale, damage to another’s property

or personal injury, a loan taken, of an obligation; and (2) general or absolute obligation of a

future liability (ISRA, 2010).

Islamically, credit is understood in a similar way. Credit and debt are permissible from a

Shari’ah standpoint. As stated in the longest Verse (Ayat) in the Qur’an, 2:282:

“When you contract a debt (dayn) for a fixed period (ajal musamman), write it

down and let there write between you a writer with impartiality…Let him who

incurs the liability (haqq) dictate… (Ali, 2003).

This is a case of a text with plain meaning or ibaarat al-nass. There is little need for deep

reflection to ascertain that debt is permissible (Nyazee, 2000). Similarly, it is related the Prophet

Muhammad, PHUH1, said:

“On the day I ascended to heaven, I saw writing on the door of paradise that

read: ‘Every charity is rewarded ten-fold and every loan is rewarded eighteen

times.’ I said: ‘O Jibreel2, why is a loan rewarded more than charity?’ He said:

‘Because a person may ask for charity when he does not need it, but the

borrower only borrows in cases of dire need’” (Ibn Majah, 2000).

What is prohibited with respect to credit and debt is ribaa. Ribaa and the notion of dayn are

inextricably linked in the minds of many because debt is more often than not the financial

1 PBUH is an acronym for the traditional salutation on prophets in Islam; it means: Peace and Blessings be upon him. 2 Jibreel is Arabic for Gabriel. The reference is to the “Arch Angel” Gabriel in Christian theology. In Islaam, Jibreel is considered

the Holy Spirit, as he is the one who sits close to the Almighty and conveys His Messages to mankind.

“vessel” that carries ribaa. Ribaa is defined differently depending on its usage. The particular

form of ribaa called interest is most commonly associated with the term in conventional finance.

The Islamic prohibition against interest is not some asinine and arcane one. Its secular and

religious prohibitions precede the Islamic civilization by centuries, e.g. in Mosaic Law and by

Greek philosophers. It was commonly understood in those milieu to be prohibited and harmful.

Risk, as the by-product of credit, literally is means the possibility of something bad happening at

some time in the future; a situation that could be dangerous or have a bad result; a person or

thing that is likely to cause problems or danger at some time in the future. The term is derived

from the French word risqué, meaning something dangerous (Oxford Dictionary, 2016). Its Latin

origin is risicum, meaning a cliff, denoting the nautical danger that rocky cliffs posed to Roman

ships (Technolgies, 2013). Risk, technically, can be defined as the probability of an event and its

unexpected or unwanted consequences. In finance, risk is the potential for loss or probability that

an unfavorable event will happen in the future. Probability in the financial sense does not mean

the same thing as it does from an accounting standpoint. In accounting, probable means that an

event is more likely than not to occur and that it will result in the outflow of resources. Possible,

then, would be a lower level of risk. In finance, probable means that there is likelihood, large or

small, that an unfavorable event will occur.

Islamically, risk is derived from the Arabic khatar with the literal meaning of dangerous,

perilous, risky, hazardous, unsafe and critical (Baalbaki, 1996). It also has the meaning of

something that is an enigma, yet unexpected, grave, serious, momentous and menacing (Wehr,

1960). Technically, it has the connotation of a “situation that involves the probability of

deviation from the path that leads to the expected or usual result” (Elgari, 2003).

Credit Risk

There is some level of risk in all human activities and some risks are simply unknown. Other

risks are so remote as to be improbable. The goal can be stated as seeking to maximize control

over risks that are known, while minimizing the harm over risks that are unknown. Risk in

banking is less philosophical and must be measured as it represents perceived threats to both

expected returns (cash inflows) and the bank’s value, i.e. its assets (which are its financing and

fee contracts, net of its liabilities due to its depositors and investments on behalf of its

customers). In essence, banks seek to measure the probability of loss in order to avoid, transfer,

absorb or share it. If systemic, risk can endanger an entire economy; indeed international debt

and equity markets. Risks are varied and include, but are not limited to: inflationary, market,

operational, mark-up and pricing, fiduciary, legal, conduct, exchange rate, liquidity, sovereign,

wrong-way, interest rate (or profit rate risks in Islamic finance), model and credit. Model risk is

caused linked with the methods used to measure credit risk. Credit risk is the most ominous and

persistent risk faced by banks.

Credit Risk Mitigation. Banks, like all financial firms, seek to avoid, transfer, absorb or share

their credit risk and must shoulder the delegated monitoring that is concomitant with financial

intermediation (Diamond, 1995).

Avoidance measures may includes such techniques as:

mitigating contractual exposure through clear contractual provisions;

the use of know your customer (KYC) FinTech;

proactive monitoring (possibly using FinTech);

netting;

parallel contracting;

portfolio diversification; and

immunization (which is primarily a bond yield risk control strategy).

Risk transference includes the use of such techniques as:

exchange rate contracts;

insurance (in the case of Islamic banking, takaful); and

derivatives, swaps and options (in Islamic banking provided they meet the restrictioins

imposed by the Shari’ah).

Risk absorption includes the use of such techniques as:

collateralization, hypothecation and asset pledges;

guarantees;

compensating (cash) balances;

subordination provision;

debt covenants; and

capital allocation requirements through risk-adjusted return on capital and loan loss

reserves.

Risk sharing requires the use of equity based contracts that allocate risks among participants.

Accordingly, risk sharing involves financing requires capitalization or the contribution of capital

by some or all of the participants. Such capitalization is conventionally found in partnerships and

limited liability companies, e.g. corporations. Some syndicated projects might also qualify as risk

sharing. As noted below, Islamic banking contracts and other financing instruments place

emphasis on risk sharing. It can be said, that other than the case of conventional banking

syndication projects, few conventional banking contracts are equity based. Islamic banking

differs in this respect.

Qualitative risk mitigation refers to prioritizing the identified risks in terms of their importance

or effects on the bank. It further measures the relative importance between risk mitigation

variables. It is based on the perspective of management as guided by the bank’s goals, objectives,

policies and procedures regarding it risk appetite. Figure 1 shows the topography of these broad

approaches to risk mitigation.

Figure 1-Risk Mitigation

Credit Risk in General. Credit risk is a subset of financial risk, i.e. the risk of financial

intermediation. Credit risk is determined by the measurement of risk of loss or diminution of

financial reward to a bank resulting from the likelihood of an obligor’s failure to repay the

contractual obligation emanating from financing and that is expected to be paid from the future

cash flows of the obligor. Credit risk is the estimated loss of revenue arising as a result of the

obligor’s delay in payment, failure to pay on time or in full as contractually agreed. There are

instances where an obligor may fulfill its contractual obligation, yet there may be loss, i.e. due to

inflation, currency exchange rates and non-compliance with both domestic and foreign laws

(Ciby, 2013). Credit risk may comprise more than 70 percent of the average bank’s asset

portfolio (Tajuddin, Shahimi, & Hamid, 2009). Moreover, credit risk analysis is important for

more practical reasons, e.g. establishing creditworthiness of debtors, understanding the

probability and quantum of credit losses, discovering the price warranted by the risk/return

equilibrium and maintaining potential banking relationships with customers.

Credit risk can be triggered by uncontrollable and controllable variables, or what may be broadly

classified as systematic (systemic) or unsystematic (idiosyncratic), respectively. Credit risk is

sometimes thought of as synonymous with default risk. However, credit is distinguishable from

default risk inasmuch as the latter measures the probability that the borrower, debtor or obligor

will be unable to repay principle and interest (or profit) on the funds advanced because of

default, i.e. bankruptcy or insolvency. Credit risk not only measures the probability of a default,

but also measures the probability of late or partial payments as well. In that sense, default risk

can be seen as one type of credit risk. This view posits that credit risk includes (Investopedia,

2016):

Credit spread risk, which occurs because of volatility in the difference between the risk

free rate of return and given interest or profit rate.

Default risk, which result from an inability to make contractual payments.

Downgrade risk, which result from borrower or issuer risk rating downgrades.

Risk Mitigation

Qualitative Quantitative

Risk Avoidance Risk Transfer Risk Absorption Risk Sharing

Some credit risk analysts include a fourth component of credit risk called recovery rate risk,

which technically is the recovery rate for a bond or the price of a bond immediately after default

as a percent of its face value. However, recovery risk might also ostensibly measure the

likelihood of recovery from collateral on default or from an obligor’s assets in liquidation

(Bielecki & Rutkowski, 2004).

Systematic or uncontrollable risks can be caused by social and/or political instability in a

country, e.g. racial strife, terrorism, political coups or sudden and unexpected regime changes.

Economic risks may arise within an economy or on the worldwide scale due to economic

conditions, e.g. the 2008 financial crisis or recession or inflation within an economy. Other

exogenous risks may include global, regional, national or local events that may impact a

particular financing facility or a portfolio of facilities that are not specific to the obligor, e.g. an

earthquake, power grid failure, etc. Systematic risks are largely uncontrollable3. In the credit risk

context, they can be defined as the possibility that other financial market participants may create

substantial credit problems for participants elsewhere in the financial system (Iqbal & Mirakhor,

2007). Unsystematic, or idiosyncratic, risks are those that are specific to the debtor, borrower or

obligor or its industry or business. These risks can be substantially mitigated by portfolio

diversification. Figure 2 depicts the underlying causes of credit risk.

Because of the volatility of a bank’s asset values (its “book”), which sometimes follow cyclical

swings, or the so-called “bust or boom” economic cycles, impairment has become more

important to credit risk assessment measurement. Credit risk differs from loan impairment

inasmuch as credit risk assessment takes into account future event(s) even when the probability

is fairly small or remote. Future events are not recognized for accounting standards “impairment”

purposes. Credit risk assessment is more comprehensive and will measure events such as an

obligor’s imminent bankruptcy or financial reorganization due to insolvency, macroeconomic

level financial shocks, a change in bank lending standards (or change in the bank’s appetite for

risk based on its capital position, concentrations, etc.) or observable data indicating there is a

measurable volatility in the estimated future cash flows of an obligor that might impact its ability

to service its debt. These assessments may be made on an individual bank asset or on a portfolio

of banking assets. In banking, the assessment starts ex ante, but continues the risk measurement

assessment throughout the life of the asset (albeit concerns may dissipate the closer to maturity).

Financing activities by banks affect both their liabilities to depositors, as well as the equity

positions of shareholders. Accordingly, credit risk analysis measures the probability of a debtor’s

non-performance due to either an inability or unwillingness to perform on a financing contract.

The risk encompasses both the probability of missing payments when due, as well as failing to

3 There is a distinction between systematic and systemic risks. The latter generally used to describe an event that can trigger the

collapse or failure of an entire industry or economy.

Figure 2-Causes of Credit Risk

Source: (Ciby, 2013).

pay principal upon maturity. A loss measure may be the result of macroeconomic as well as

microeconomic factors. The probability of a loss event may in fact not be a single event, nor may

it be solely measurable at the firm level. In other words, it may not be discrete or singular in

nature. Instead, it may be the combined effect of several events and analogue. Moreover, it may

be analyzed for a single obligor or a portfolio of obligors.

Credit Risk in Islamic Banks. Since interest rates are prohibited in Islamic banking, interest

rate risk doesn’t represent a risk per se in Islamic banking. However, systemically it must be

monitored, measured and mitigated; particularly in economies that have dual banking sectors, i.e.

conventional and Islamic. Islamic banks face profit rate risk, which measures the volatility of

their expected returns on financing. Moreover, Islamic banks have risks that are specific to them,

including, displaced commercial risk and reputational risk (called Shari’ah risk). Both

conventional and Islamic banks are “financial firms” and are significant parts of the financial

system of economies around the world. Islamic banks, like their counterparts in conventional

finance, operate by providing facilities to their customers. However, unlike conventional banks,

they do not lend money, except in the case qard hasan, which is without charge and would be

deemed part of the bank’s corporate social responsibilities. Hence, credit risk exists in Islamic

banks and they are not immune from its vagaries.

Notwithstanding that Islamic banks may tenaciously adhere to Islam’s normative prohibitions

and obligations embedded in their contracts, there remains credit risk for two essential reasons.

The first is that financing of any sort is inherently risky. Whenever there is a deferral in the

return on an investment or loan, there exists risk. The risk of the deferral is with respect to both

return and principal. That is to say, that be it a deferred loan or an investment upon which the

investor bank must await return on the contract, “credit” risk exists because the bank has

arranged the financing facility with an expectation of return. That return is based on the bank’s

risk-return profile. Though the “credit” may not be that of the kind conventionally thought of as

credit; it is nonetheless a financing facility and has most of the attributes of lending, except for

risk sharing, including return based on cash flows. Moreover, ostensibly, where Islamic banks

provide risk sharing facilities to private companies (which may be significant), there is no

discernible market to determine a market rate of return or market risk. Hence, the risk the bank is

facing is a variety of credit risk more than it could be considered a rate of return risk. Where the

facility is a mudarabah financing, the return on capital is entirely the risk of the Islamic bank and

therefore even more so a variety of credit risk.

Secondly, Islamic banks have demonstrated a penchant for deferred financing through their

sales-based contracts; most notably, those called murabahah and specifically bai’ bithaman ajil

(BBA) or bai’ mu’ajjil. Each Islamic bank, as is the case in all banks, has to ascertain its appetite

for various forms of financing contracts. As one Islamic finance scholar put it: “The contracts of

murabahah have reached more than 90% of the operations of several banks. So much so that

those that have been successful in employing other modes are found to focus on modes that also

give rise to debts, like istisna’. Considering the fact that the financial assets generated through

murabahah are debts, possibilities of dealing with them within the permissible limits set by the

Sharī‘ah are limited” (Elgari, 2003).This dilemma can be overcome by regulatory mandates. An

example of bank lending composition mandates might be to give a gradually implemented

maximum and minimum contract financing guideline for Islamic banks that mandates a range of

madarabah and musharakah contacts within a given timeframe. Moreover, a small or private

market for equity platformed sukuk might be developed for Islamic banks’ investment banking

branches or subsidiaries. Nevertheless, it can be said that holding equity interests in either of the

three equity-based banking contracts might give rise to equity risk or the risk of holding an

equity interest in a firm. Yet, that risk can be ameliorated by having the equity-based financing

tethered to the underlying real assets of the counterparty or investee firm or business.

Islamic bankers perceive risk sharing financing as being greater than the risk transferring Islamic

sales-based facilities. One survey, though dated and not necessarily statistically sound, does

show that Islamic bankers themselves have been their own worst enemy. They have perceived

that risk levels among risk-sharing Islamic financing contracts (on a scale of 1-5 with 1 being

least risky) are the most risky (Ahmed & Khan, 2007). Table 1 illustrates those perceptions.

Table 1-Levels of Perceived Risk in Islamic Banking Contracts

Contract Type Perceived Risk

Murabahah Sales-based 2.47

Ijarah Lease-based* 2.64

Istisna’ Sales-based 3.13

Salam Sales-based 3.20

Mudarabah Equity-based 3.38

Musharakah Muntanaqisah Equity/Lease-based 3.43

Musharakah Equity-based 3.71 *Ijarah Thumma Bai & Ijarah Muntahiah Bittamlik may involve subsequent sales-based contracts.

Thus, there is an apparent preference among Islamic bankers for fixed returns over a fixed term

vis-à-vis uncertain returns over an uncertain term. That is understandable. Yet, there is an upside

to the use of equity-based banking contracts for counterparties who are well-selected and have

developed a track record of trust and confidence. Moreover, there is no prohibition in Islamic

contracts that prevent targeted terms of financing, targeted returns and project specific financing.

These are contract conventions that could be used in standardized equity-based banking

contracts. Further, there is no prohibition on collateralized equity-based contracts. For example,

in a mudarabah deal that goes “south,” the underlying assets of the partnership may revert back

to the rabb al-mal as part of the liquidation or “milestone” provisions of the contract.

In 2010, credit financing accounted for 75.3% of total financing in Malaysian Islamic banks.

Partnership financing was only 2.7% of total financing. Although Islamic credit-based financing

differs from conventional credit-based financing because the former is largely sales-based and

tethered to an underlying asset and has attendant business risks associated with those sales, the

profit and loss sharing financing was nonetheless anemic and alarming given Islamic finance’s

preference for sharing. Table 2 shows the disparity (Ariff & Rosly, 2011).

Table 2-Islamic Banking Contracts in Malaysia-2010

Source: (Ariff & Rosly, 2011)

Islamic banks do have at their disposal unique parallel contracts that can be used as risk transfer

instruments. Parallel mudarabah and istisna’ financing might be employed to ameliorate

matching problems associated with gravitating towards a more balanced risk sharing financing

portfolio, as well as some of the inherent credit risk in the contracts. Parallel contracts would use

an “on boarding” contract with a “depositor/investor” counterpart with “mirrored” sales or

equity-based contract counterparty on the asset side of the bank’s balance sheet. Thus, parallel

contracting provides an asset “shield” for the corresponding liability.

IFSB-1. The Islamic Financial Services Board (IFSB)4 issued IFSB 1-Guiding Principles of Risk

Management for Institutions (other than Insurance Companies) Offering only Islamic Institutions

offering Financial Services (IIFS) in 2005. In addressing credit risk therein, the IFSB set forth

four principles (IFSB, 2005):

Principle 2.1: IIFS shall have in place a strategy for financing, using various instruments in

compliance with Shari’ah, whereby it recognises the potential credit exposures that may arise at

different stages of the various financing agreements.

Principle 2.2: IIFS shall carry out a due diligence review in respect of counterparties prior to

deciding on the choice of an appropriate Islamic financing instrument.

Principle 2.3: IIFS shall have in place appropriate methodologies for measuring and

reporting the credit risk exposures arising under each Islamic financing instrument.

Principle 2.4: IIFS shall have in place Shari’ah-compliant credit risk mitigating techniques

appropriate for each Islamic financing instrument. (Emphasis part of the standard).

Moreover, the standard states that it is applicable to “financing exposures of receivables and

leases (for example, Murabahah, Diminishing Musharakah and Ijarah) and working capital

financing transactions/projects (for example, Salam, Istisna’ or Mudarabah). IIFS need to

manage credit risks inherent in their financings and investment portfolios relating to default,

downgrading and concentration. Credit risk includes the risk arising in the settlement and

clearing transactions” (Id). In explaining the credit risk exposure for an Islamic bank in the case

of mudarabah financing, IFSB 9 gives the following example of how credit risk arises:

“In cases where Mudarabah is used in project finance, an IIFS advances funds to a customer

who acts as Mudarib in a construction contract for a third-party customer (ultimate customer).

The ultimate customer, who has no direct or contractual relationship with the IIFS, will make

progress payments to the Mudarib who in turn make payment to the IIFS. The role of the IIFS is

to provide bridging finance on a profit-sharing basis to the Mudarib pending its receipt of the

progress payments from the ultimate customer. The IIFS is exposed to credit risk on the amounts

advanced to the Mudarib” (Id). Moreover, IFSB-1 recognized the variable nature of credit risk as

it applies to equity-based financing, i.e. how other kinds of risk can affect credit risk and vice

versa. This might be termed risk cross-pollination. IFSB-1 gives the following examples:

4 The IFSB is “an international organization that issues guiding principles and standards within the banking, insurance and capital

market sectors in order to promote stability in the Islamic financial services industry. It is based in Kuala Lumpur, Malaysia, and

began operations in 2003 (Investopedia LLC, 2016).

The role of IIFS can embrace those of financiers, suppliers, Mudarib and Musharakah

partners. IIFS concern themselves with the risk of a counterparty’s failure to meet their

obligations in terms of receiving deferred payment and making or taking delivery of

an asset. A failure could relate to a delay or default in payment, or in delivery of the

subject matter of Salam or Parallel Istisna’, entailing a potential loss of income and even

capital for the IIFS.

Due to the unique characteristics of each financing instrument, such as the non-binding

nature of some contracts, the commencement stage involving credit risk varies.

Therefore, credit risk shall be assessed separately for each financing instrument to

facilitate appropriate internal controls and risk management systems.

IIFS will consider other types of risks that give rise to credit risk. For example, during

the contract life, the risk inherent in a Murabahah contract is transformed from market

risk to credit risk. In another example, the invested capital in a Mudrabah or Musharakah

contract will be transformed to debt in case of proven negligence or misconduct of the

Mudarib or the Musharakah’s managing partner.

In case of default, some jurisdictions prohibit IIFS from imposing any penalty except

in the case of deliberate procrastination, thus increasing the probability of default.

In most jurisdictions, IIFS are prohibited from using the amount of any penalty for their

own benefit; they must donate any such amount to charity. This increases the cost of

default (Id). (Emphasis part of the standard).

Thus in Islamic banking, each contract has its own inherent credit risks that must be identified,

measured and mitigated. Table 3 summarizes some of the credit risks inherent in basic Islamic

banking contracts.

Some view the potential loss to an Islamic bank from its profit and loss sharing (PLS) facilities

in musharakah and mudarabah financing as “capital impairment risk” (Boumediene, 2011).

Obviously, if what is placed in a PLS contract by the bank is its own capital that is true.

However, if parallel mudarabah is used, that view fades. In Malaysia, Islamic Financial Services

Act 2013 (IFSA) distinguishes investment accounts from Islamic deposit accounts. Investment

accounts are defined by as Shari’ah compliant contracts with non-principal guarantee features

for the purpose of investment. Thus, in mudarabah,and musharakah investment contracts,

neither principal nor return is guaranteed. There is no profit rate risk, but instead, liquidity risk.

Moreover, from an overall holistic view, the loss from any facility on the asset side of a bank’s

book, be it sales, lease or equity-based, impacts and possibly impairs a bank’s capital. That is,

after all, the basis for risk weighted asset classifications (infra). And that is an aspect of credit

risk. But, as shown herein below, Malaysian Islamic banks have its modified the risk weighted

asset classifications computation in order to account for its investment accounts.

Table 3-Specific Credit Risks of Islamic Banking Contracts

Contract Specific Credit Risk

Murabahah as Bai Mu’ajjil

or Bai Bithamin Ajil (BBA)

-Normal credit risk on periodic installments.

-Additional risk associated with purchase order

murabahah of having to sell asset at lower price.

Ijarah -Normal credit risks on periodic installments.

-Ijarah Thumma Bai & Ijarah Munahiah Bittamlik,

the risk of having to sell the asset at a lower price

-Risk of volatile residual value at end of the lease.

Salam and Istisna’ -Risk due to failure of customer to supply

goods/project on time or at all, or if specifications

of goods/project are not according to contract.

-In parallel contracts if fails, the bank is still liable

to perform under the other contract.

Mudarabah and Musharakah -Potential for agency problem

-Potential for adverse selection

-Potential for moral hazard and that capital may be

transformed into debt and recovery problems

-Potential for information asymmetry and opacity

-If deferred delivery, price and credit risk present

-Delegated monitoring costs

-Risk of having to sell asset(s) at a lower price

-Fiduciary risk for banks as mudarib.

Musharakah Muntanqisah -Same as Musharakah

-Normal credit risks on periodic installments.

-Risk of volatile residual value at end of the term.

Tawarruq -Credit risk could become price risk due to the

involvement of t 2 traders

-Normal credit risk on periodic installments.

IFSB-1 mandates Islamic banks to use a holistic approach to credit risk management operations.

The holistic approach to credit management emphasizes the integrated systems approach of the

Islamic bank, as well as the recognition that credit risk is not the only risk faced by Islamic

banks. Other risks, common to all banks, e.g. concentration risk, may influence credit risk in

Islamic banks and risks that are specific to Islamic banks may emerge, e.g. displace commercial

risk. An example of a holistic approach to credit risk management might include the functions of

on-boarding, due diligence, monitoring and reporting and control as shown in Figure 3. Back

testing is described in Basel III as “an ex-post comparison of the risk measures generated by the

model against realized risk measures, as well as comparing hypothetical changes based on static

positions with realised measures” (Basel Committee on Banking Supervision, 2011).

Islamic Financial Services Act of 2013. The Islamic Financial Services Act (IFSA) of 2013 was

enacted to provides regulation and supervision for Islamic financial institutions (IFI) and to

promote financial stability in the Malaysian financial services sector by pursuing greater

compliance with the Shari'ah. One of the major issues addressed in the IFSA was the status of

mudarabah investment accounts. The IFSA classifies investment accounts differently from

Islamic deposit accounts. The latter include current accounts, saving accounts and fixed deposit

Figure 3-Sample Holistic Credit Risk Management Approach

accounts. These accounts have the common features of principal guarantee, Shari'ah-compliant

marketing terms, and withdrawal on demand. Conversely, there is no such obligation, express or

implied, to repay the principal of an investment account (Laws of Malaysia, 2013). Under the

Shari’ah, the guarantee of principal is prohibited in a mudarabah partnership. A mudarabah

partnership, in its simplest form, is a partnership between a rabb al-mal (owner of capital) and

mudarib (the partner who provides the labor and/or expertise to operate the enterprise). Profits

are shared between the partners (mudarib and rabb al-mal as negotiated and agreed upon), while

losses are absorbed by the rabb al-mal. Mudarabah accounts are either restricted or unrestricted,

i.e. restricted by the rabb al-mal as to the undertaking, subject matter, location, term, etc. It is

one of the oldest forms of business organizations in Islam, and indeed civilization. The Prophet,

PBUH, practiced it and was the mudarib for Khadijah, may Allah be pleased with her, who was

the rabb al-mal in their import/export trading enterprise; and were ultimately married.

Mudarabah investment accounts are the profit and loss sharing (PLS) “workhorse” of Islamic

banking. But, they are not the only form of PLS equity-based financing available in Islamic

banking. Musharakah, another form of joint equity “capital” ownership also exists under the

On-Boarding

• Credit Risk Policies and Appetite

• Acceptance Criteria and Credit History

• Customer Scorecard

• Financing Instrument Matching

Due Diligence

• Risk Identification

• Risk Measurement and Underwriting

• Credit Scoring and Modeling

• Concentration Risk Analysis

• Rate or Return on Assets and Risk Weighting

Monitoring & Reporting

• Financial Reporting

• Holistic Risk Assessment

• Portfolio Management

• Database and Information Analytics

• KYC and Business Cycle Needs Assessment

Control

• Negotiation, Ibra and Settlement

• Restructuring

• Recovery

• Liquidation

• Back Testing and Error Feedback

Strategic

Risk

Informed

Approach

Shari’ah. Malaysia has a fledgling capital market, buttressed by its formidable sukuk5 issuances.

Malaysian banks arrange, promote and participate in sukuk issuances. Malaysia remains at this

juncture a bank-based economy. As such, the “lion’s share” of Islamic financial intermediation

in Malaysia and, indeed the Islamic financial “market” worldwide, occurs in Islamic banking.

Accordingly, the Central Bank of Malaysia (Bank Negara Malaysia) or BNM, in order to fortify

IFSA, and clarity and standardize Malaysian banking investment account practices, issued its

Investment Account policy document (BNM, 2014). Therein, BNM defines investment accounts

and standardizes their banking treatment, including their credit risk and related risk profiles, as

well as the capital allocation requirements for them.

Expected Rate of Return. Credit risk is used to determine the expected rate of return as part of

the price discovery process associated with financial intermediation. In conventional finance it is

the interest rate charged on funds and based upon the perceived credit risk of a counterparty.

From an Islamic perspective, it is the credit risk that determines the expected return or profit rate

on financing funds. Credit risk is the exposure of the bank or financial institution resulting from

both the risk profile (as determined by external ratings or the financial institution’s credit risk

database) of the type of counterparty, the specific risk characteristics of the counterparty (as

ascertained by the financial institution’s investigation, due diligence and prudential assessments)

and the term or length of the risk exposure. These credit risk factors influence pricing for banks,

i.e. the interest for conventional banks and the profit rate for Islamic banks.

The credit risk pricing costs are shown in Figure 4 below. They constitute the credit risk

premium for banks. When a “credit asset” is created, it requires an assessment or measurement

all attendant costs and risk in order to properly price the “credit asset.” As discussed throughout,

the credit risks associated with the individual obligor or counterparty must be assessed and

measured. The process is “all-inclusive” and under the internal-based rating approach, the

parameters of credit risk must be measured (infra). The expected loss (EL) given the probability

of default is computed; including the estimated exposure and loss at default and the time estimate

to the probable default. If this cannot be done by the bank, then it must be done by an external

rating process. When financing occurs, it involves the investment of capital, which in must be

priced given the level of counterparty risks. Economic capital risk-based pricing is expected to

ensure that “credit assets” with ‘higher risks’ are reward the capital providers or stakeholders

with higher returns. Stakeholders include the capital provided by accountholders and

shareholders. It also includes the costs that may be required in order to maintain the bank’s

statutory reserve requirement and liquefiable assets or to otherwise employ them as a result of

the financing. Obligor or counterparty specific risk must be “mapped” risk-weighted asset

classification; portfolio and sector risks ascertained by the bank through its credit risk

measurement process using internal data or externally provided data. Portfolio risks are a fact of

5 Sukuk will only be tangentially discussed in this paper, but suffice to say sukuk are Shari’ah-compliant certificates of

ownership (asset-backed securities) in underlying real assets that have been syndicated for monetizing an enterprise (issuer) that

uses the underlying assets to generate cash flows.

life in modern banking. Basel acknowledged as much by mandating risk weighted classifications.

Thus, credit risk and return should be assessed at firm and portfolio levels. As noted

hereinabove, portfolio diversification is an established method of risk avoidance. Like any

business, the “business of banking” has overhead costs that must be incorporated or allocated

into its cost pricing of its “credit assets.” Those costs might be accounted for directly to the credit

risk measurement process for the specific counterparty or indirectly and include the bank’s

general personnel related costs, security, insurance, legal and other such costs. Other cost might

include unexpected costs related to the credit risk process, e.g. country risks associated with

cross-border financing (Ciby, 2013).

These credit risk pricing principles are also fundamental to the Islamic understanding of risk-

return. The legal maxim al-ghunm bil-ghurm is often quoted as the basis for the Islamic risk-

return proposition. By mentioning risk ( ghurm) in the same breath as return (ghunm), the

principle is given practical meaning. Thus, al-ghunm bil ghurm has been translated as ‘‘one is

Figure 4-Credit Risk Pricing Costs

entitled to a gain if one agrees to bear the responsibility for the loss” (Majelle6) and the literal

Arabic translation of ‘‘the profit is with the detriment (or loss),’’ seem conflicting at first blush.

But, thinking of the latter translation in terms of one who is willing to face the risk of detriment

or loss, also expects to make some profit when the loss does not occur, helps bring clarity to the

meaning (Rosly & Zaini, 2008).

However, unlike interest rates in conventional banks that are pre-determined, the rate of return

on financing facilities in Islamic banks are the result of mixed sales and equity-based financing;

the latter may be expected and agreed upon ex ante, but are not actually known until the end of

the accounting period, i.e. ex poste. This phenomenon may be ameliorated by the investment

account policy in Malaysia discussed herein (infra). In any event, investment accountholders,

regardless of the bank’s treatment of them, will have expected returns based either on fixed

interest rates or targeted fixed returns promulgated by the bank; be it conventional or Islamic.

6 The Majelle or Majallah al-Ahkam al-Adliyyah are the codification of Hanafi school of Islamic jurisprudence used by the

Ottoman Empire courts for civil and domestic matters.

Credit Risk

Pricing

Expected Loss (EL)

Obligor Rating

Loss Given Default (LGD)

Probability of Default

(PD)

Exposure At Default (EAD)

Maturity

(M)

Portfolio & Sector Risks

Cost of Capital and

Funding

Economic & Regulatory

Capital

Liquidity Costs

Overhead

Costs

Other Costs

As noted earlier, interest rates must still be monitored as large deposit interest rate and

investment rates of return differentials can lead to arbitrage. “Inter-temporal smoothing,” for

example, in conventional banking, particularly in bank-based financial systems, where equity

markets are not significant competitors with banks, causes banks to “smooth” both rates of return

on liability accounts and to engage in countercyclical capital buffering (Bank of International

Settlements, 2016). . Banks increase their buffer of short-term liquid assets when the economy is

booming and reduce this buffer when it is more constricted. The capital adequacy requirements

of banks are adjusted based on their liquidity positions. In market-based financial systems, with

developed or developing financial markets, the equity market provides competition to banks

which makes the inter-temporal smoothing more difficult. Financial markets provide high returns

in boom times and an incentive for investors to move their savings from banks to financial

markets. In order to remain competitive in such circumstances, banks must cease inter-temporal

smoothing (Allen & Santomero, 2001). In a dual banking system, e.g. where there are Islamic

banks and conventional banks, as that found in Malaysia, without regulation, the conventional

banking system could act as a surrogate for the equity market vis-à-vis Islamic banks; with

depositors or IAH choosing between conventional and Islamic banking accounts unless

otherwise inhibited by religious sentiments. This, in turn, could create a rate of return risk for the

affected Islamic bank(s).

BNM Investment Account Standard. However, in the wake of the IFSA discussed above, the

“rules of the game” have changed for Malaysian Islamic banks (MIB). Instead of PER and IRR,

MIB are subject to the rate of return agreement with the investment account holder (IAH) and the

requirement of “liquidity risk funds” (BNM, 2014). Liquidity risk generally arises when a MIB

has to use its own funds to meet a redemption by an investment account holder. Sections 31

through 31.3 and 32 of the Investment Account policy document7 from the Central Bank of

Malaysia (BNM) sets forth the framework for the change to the credit risk treatment of

investment accounts in Malaysia. The following are the pertinent parts of the Investment

Account policy document (the Standard):

31. Computation of Capital Adequacy Ratio

IFI as Mudarib/Wakeel (ie. Entrepreneur/Agent) for the Investment

Account

7 As described on its cover: “This policy document on investment account aims to outline the regulatory

requirements on the conduct of investment accounts which encompass product structuring, oversight arrangement,

risk management, market conduct and disclosure and transparency aspects. This policy document shall apply to

products that are classified as investment accounts.” Furthermore, as used in the policy document, IFI means Islamic

Financial Institution and FI means a non-Islamic financial institution. Also, as used in the policy document an

investment account includes: mudarabah (restricted and unrestricted), musharakah, wakalah and wakalah bil

istithmar.

31.1 Credit and market risk weighted assets funded by investment

accounts that fulfil (sic) the requirements in this policy document shall be

excluded from the calculation of capital adequacy ratio of the IFI. As

such, the IFI shall apply the alpha (α) value of “0 (zero)” for exposures to

assets funded by investment accounts in calculating the capital adequacy

ratio as prescribed in Appendix 10. In addition, any committed but

unfunded investment accounts (where actual cash has not been received

from the IAH) shall not qualify as risk absorbent.

31.2 Notwithstanding paragraph 31.1, IFI is required to ensure adequacy

of capital where the IFI is exposed to the risk of the underlying assets in

the investment account funds in circumstances arising from the IFI’s

involvement to provide liquidity as described in paragraph 22.8.

Financial Institution (FI) as the IAH (i.e. Fund Provider)

31.3 In the case where an FI places funds into an investment account offered by

an IFI, the FI as the IAH shall apply the following approaches in calculating

credit and market risk capital requirements:

(a) look-through approach based on the underlying assets in the nvestment

account as if the underlying assets are directly held by the FI. The look-

through approach must be used when the following conditions can be

fulfilled:

(i) the financial information regarding the underlying assets is sufficient

and appropriately granular to enable calculation of the corresponding risk

weights; and

(ii) frequency of financial reporting of the investment account must be the

same as, or more frequent than, that of the FI as the IAH.

Illustration of the look-through approach and specific requirements on

look-through are given in Appendix 9.

(b) Where conditions in (a) are not met, the FI as the IAH shall treat the

investment account as exposure to equities:

(i) Credit risk

For standardised approach, apply risk-weight of 150%;

For Internal Ratings Based (IRB) approach, apply simple risk

weight of 400%; and

(ii) Market risk

For standardised approach, apply 14% specific risk charge, in

addition to general risk charge;

For Internal Models Approach (IMA) approach, calculate

according to the FI’s internal models for equities.

32. Statutory Reserve Requirement

32.1 All investment accounts are excluded from Eligible Liabilities (EL) base

for purposes of statutory reserve requirement (SRR) computation.

As noted in Section 31.3 (a)(ii) of the Standard, FI or non-Islamic Financial Institutions (IFI) are

still required to account for investment accounts through the use of a “look-through approach.”

That approach is described in Appendix 9 of the Standard. Figure 5 is a schematic of the “look

through approach.”

Figure 5

Source: (BNM, 2014).

The Look-Through Approach requires that a “FI as the IAH shall adopt the approach applicable

for similar asset classes in its portfolio as if the underlying assets are directly held by the FI,

using the relevant rules in the Capital Adequacy Framework (CAF).” The CAF for Islamic

Banks (CAF) for Risk-Weighted Assets (RWA) or the CAF (Basel II Risk-Weighted Assets) or

CAF for Development Financial Institutions (Id).

Moreover, as noted in the Standard, IFI are no longer required to include investment accounts in

their CAF RWA computations. The Standard refers to Appendix 9 as an illustration of the

computation. Figure 6 shows the Appendix 10 computation.

Figure 6

Source: (BNM, 2014).

The modified formula referenced by footnote 42 of the Standard refers to calculating Common

Equity Tier 1 capital, Tier 1 capital and Total Capital ratios accordingly. Footnote 43, Total

Risk-Weighted Assets, Islamic refers to the sum of credit, market and operational risk weighted

assets of IFI. And footnote 44 of the Standard refers to the quantum of investment accounts

recognized as risk absorbent for capital adequacy ratio computation purposes.

Credit Risk Assessment Methods

The assessment of credit risk evolved in the 21st century. That evolution doesn’t mean that all

past methods have been jettisoned, but as banking has become more sophisticated and

technologically savvy, credit risk mitigation methods have evolved. Moreover, in the modern

financial world, more financial integration has proliferated; particularly among emerging

economies. The 2008 financial crisis crescendo caused worldwide alarm at how volatile and

contagious credit risk can be. In response, the banking sectors worldwide have explored ways to

better mitigate and manage credit risk and the other attendant risks that often emanate from it.

Relatively simple early methods of credit risk assessment evolved into accounting and financial

analytic approaches. These methods led to fairly sophisticated statistic models, which have

further evolved into the use of econometric use of regressions focused on predicting the

probability of default. These latter methods were in fact initially so sophisticated that only rating

agencies had the expertise and the data to perform the credit risk measurements. However, credit

rating agencies paled when faced with the volatility and contagious nature of the 2008 financial

crisis. Hence, the practice of credit risk assessment has, with the help of standard setters, e.g.

Basel, evolved to an individual bank or banking system phenomenon.

Two credit risk methods have become widely accepted and used by banks worldwide. Both

reflect a risk absorption approach to credit risk mitigation. One is standardized, while the other is

internal-rating based. In the former, risks, after being mapped to asset classes, are assigned a

given level of risk called a “risk weight.” The risk weight under this approach is standardized

and given by a regulator. Under this approach, banks use external rating agency ratings to

quantify the risk weight applied to capital for credit risk absorption. Thus, counterparties are

grouped by the asset classifications associated with them and are rated by external rating

agencies. The latter method relies on a bank or banking system’s own assessment of its

counterparties and exposures to calculate capital requirements for credit risk. The risk weight is

determined on the basis of determinants defined and econometrically tested on the bank or

financial institution level. Counterparties, individually, or as portfolios, can be rated or scored to

assess the credit risk associated with the banking activity related to them (again according to

asset classifications). Both methods seek to measure the bank and financial system’s ability to

absorb the credit and related risks of its banking activities. Islamic banking, because of its

sanctity of contracts and deeply rooted epistemological religious principles, has brought to light

the reality credit risk asset classifications can vary broadly by banking systems.

Risk analysis has different steps as well. As noted earlier, credit risk mitigation has 4 major

strands, absorption being only 1 of them. The “on-boarding” process of counterparty intake and

financial analysis may be performed on both a personal and financial level. The former would

involve personal credit history and behavior of the applicant or its key personnel or owners. The

latter might involve preliminary financial analysis of the balance sheet and income statement of

an applicant. What can be gleamed of an applicant’s needs, along with what is known of the

bank’s risk appetite and products are used to assess whether a credit risk match potentially exists.

The applicant is “graded” accordingly and given a “scorecard” and credit risk assessment moves

to its more sophisticated steps if so warranted by the scorecard. Traditionally, credit risk has

been assessed using static acronym based analytic mnemonics. They are still in use and part of

the overall credit risk assessment arsenal used by banks.

Static Acronymic Methods. Banks and other financial institutions have used acronymic

formulae to progress through a series of creditworthiness aspects of a credit applicant. They

include:

5Cs-the most long standing of the acronymic credit worthiness tools (Gardner & Mills, 1994):

Capacity refers to the borrower’s ability to meet the loan payments.

Capital is the analysis of the financial position of the borrower; generally using financial

ratios that emphasize tangible net worth.

Collateral is represented by assets that the borrower might offer as a form of security for

the financing.

Conditions refer to the impact general economic trends or developments in special

segments or industries that may have on the borrower’s ability to perform.

Character is the subject assessment that the borrower will try to “honor” the contractual

obligation underlying the financing.

5Ps-another method of evaluating credit applications developed by the Federal Reserve Center

(Federal Reserve Bank of Kansas City; Federal Reserve Bank of St. Louis, 2004). The criteria

are as follows:

People refers to the borrower’s reputation. The bank will check the borrower’s history of

being honest, reputable and timely in honouring his or her financial obligations.

Purpose refers to how the borrower is going to use the funds.

Payment helps bank to identify sources of repayment and aids in structuring the loan

repayment schedule based on the timing of the borrower’s receipt of funds.

Protection refers to collateral or other secondary sources of loan repayment, e.g.

guarantees from third parties. The borrower will pledge the collateral to cover the non-

performing financing.

Prospective or plan refers to the bank’s strategy in case of default. The plan is to

supervise and determine how the loan will be monitored, including the borrower's

financial reports, and periodic inspection of the operations of the borrower.

LAPP-a method developed by (Benz, 1979) is used to evaluate corporate credit application of

borrowers. LAPP is an acronym as follows;

Liquidity is measured by looking at the borrower’s ability to repay short-term. The bank

uses the quick ratio or liquidity ratio to measure liquidity of the company.

Activity a measure of the size of the borrowing firm and its operations and some

percentage were used as the acquisition of assets, inventory turnover, average collection

period, and the average payment period.

Profitability is a measure of how profitable the borrower is. The ratios used include

return on assets (ROA), return on equity (ROE) and gross margins or profits.

Potential is a measure of the resources and financial strength of the borrower, e.g.

financial resources, human resources, management level, and other strengths.

CAMPARI-a formula of 7 factors used to assess the credit risk of smaller enterprises. The 7

factors are a mixture of the 5C’s and 5P’s (Coyle, 2000).

Character: similar to character in 5C's.

Ability to pay: similar to capacity in 5C's, but also includes whether authorization exists.

Margin of finance: margin of finance not 100% therefore, the borrower must pay a

certain percentage of the value of the assets to be financed.

Purpose is similar to purpose in 5P’s.

Amount of the loan and whether it matches the purpose.

Repayment refers to source of repayment.

Insurance refers to life insurance on the borrower in long-term financing and/or on the

subject matter of any financing, e.g. equipment.

These acronymic formulae analysis tools are used to develop scorecards for initial determination

of credit worthiness, including that of the borrower, the asset to be financed, the purpose or need

for the financing and whether they meet the credit risk profile and appetite of the bank. While

these acronyms are still useful, they are static and somewhat subjective in some respects. The

growing demands of modern banking have caused management of credit risk to evolve.

Loan Loss Ratios. Credit risk management attempts to mitigate the “expected” losses identified

through credit risk analysis in relation to the adequacy of both a bank’s capital absorption

capabilities and its loan loss reserves at any given time. Financial analysis of credit risk may

therefore seek to measure the impact lending will have on its loan loss related ratios. These ratios

may include:

Loan Loss Recoveries/Average Net Loans (ANL);

Allowance for Loan Losses/ANL;

Net Loan Charge-offs/ANL;

Net Income/Loan Loss Provision;

Net Charge-offs/Average Net Receivables; and

Direct Cash Loans/Gross Receivables.

This balance sheet reserve approach measures credit risk associated with each asset class. Poor

credit risk management affects a financial institution’s balance sheet as a result of instances of

adverse selection, non-performing loans (assets), toxic assets and burgeoning loan loss reserves

(liabilities). In modern banking, it invariably will affect Basel capital requirements, performance,

bank shareholders and other stakeholders. The latter two are used by finance companies (Gardner

& Mills, 1994). These ratios are also applied to credit concentrations, e.g. by counterparty

classification, banking product and industry.

Accounting Information Ratios. Accounting is the language of business. However, all

accounting is not equal. Internally generated accounting information must be put into more or

less “uniform” formats generically called financial statements. Standards for disclosing and

presenting a variety of financial transactions must be applied to insure fairness and completeness.

Accredited public accounting professionals are tasked with these financial assurances. Their

highest level of assurance comes by certifying financial statement after audit. Audited financial

statements, when available, can provide valuable credit risk information to financial institutions.

Conventional financial ratios are employed to allow comparison among and between classes of

counterparties. However, accounting information can have the disadvantage of being periodic

when balance sheet based and may also reflect historical values of assets and liabilities, rather

than current or market values. Unless these vagaries are assessed, resulting scores may be

distorted. Moreover, accounting standards are conservative and therefore are reluctant to project

out probabilities. In fact, accounting theory classifies contingencies as either probable or

possible. Those that are probable can be quantified and recorded. Those that are possible are not;

although they may be disclosed in the “footnotes” of the financial statements. Probable means

there is a greater likelihood than not of an event occurring. Possible means there is no greater

likelihood than the event will occur or not occur and therefore cannot be quantified and recorded.

These ratios are more often than not used in the assessment stage of financing, as well as the

monitoring stage. They are used in the debt covenants that require borrowing enterprises to

maintain certain minimum ratios in their financial statements. Data on these ratios can also be

captured by information technology, allowing the bank to develop statistical predictive value of

certain ratios within certain customer types. Each type of ratio described below has been shown

empirically as a link to credit risk. The link may be made stronger or weaker by features of the

counterparty or the debt contract (Demerjian, 2007):

Minimum Coverage (earnings / periodic debt related expense)

Maximum Debt to Cash Flow (total debt / earnings)

Minimum Net Worth (assets – liabilities)

Maximum Leverage (total debt / total assets)

Minimum Current (current assets / current liabilities)

Operating performance has been empirically shown to be a major driver of credit risk. All other

things equal, strong operating performances signal decreased likelihood of default; while the

converse holds true for weak operating performances. That is so because loan repayments are

ultimately made from earnings. Earnings from the accounting financial statement or specifically

the income statement, statement of cash flows and related notes and disclosures generally

provide an informative signal of credit risk. Moreover, studies have shown that current earnings

are associated with future earnings (Finger, 1994), (Nissim & Penman, 2001) and (Abdi, 2011);

and future cash flows (Barth, Cram, & Nelson, 2001). Coverage ratios and debt to cash flow

ratios provide risk signals of a counterparty’s ability to make future repayments. By contrast, net

worth has relatively less predictive informative value as a measure of credit risk (Demerjian,

2007).

External Credit Ratings. One of the principal “tools” used by financial institutions in accessing

credit risk is external credit rating. Ratings are generically produced by rating agencies, who sell

their opinions (called credit ratings) about the credit-worthiness of potential borrowers and

issuers; particularly corporate bonds and asset backed securities. Each agency has its own

methods and models used to designate a borrower’s credit worthiness. Each agency also has its

own ratings scale ranging from best to worst. These ratings are typically AAA, AA, A, BBB,

BB, B, CCC, CC, C and D. AAA indicates the borrower’s ability to meet its credit obligations is

“extremely strong.” A rating of C would indicate the borrower is “very vulnerable” to

nonpayment of its credit obligations. D would indicate that some default has already occurred on

credit obligations.

Rating agencies tend to produce fairly stagnant ratings and are said to often rate through cycles

and favor rating stability. The technologies, accounting practices and market information

efficiency of the borrower’s economy may impact rating frequency and effectiveness. These

credit ratings are not particularly effective for early stage businesses because of their opacity,

short credit reporting and operating history. Credit rating agencies such as Moody’s, Standard

and Poor’s and Fitch’s are far more likely to have bond rating information than small business

early stage loan financing ratings. Moreover, credit ratings from different agencies may or may

not be comparable. Malaysia, for example, has two credit rating agencies, i.e. RAM Rating

Services Berhad and Malaysian Rating Corporation Berhad (MARC); both of which are active in

Malaysia’s nascent, but robust capital market and Islamic capital market.

Because of the problems encountered by smaller businesses, many banks now assess the credit

history of both the small business and the owner(s)/manager(s) of the small businesses. Credit

reporting data are entered into an internally developed or purchased loan risk prediction model

for credit scoring by the agencies. Moreover, there also exist credit reference agencies or national

credit bureaus that provide credit scoring historical databases, where a bank lacks such a

database. These databases encompass both the business and the individuals in the business, based

on their personal credit experience and the business rating where available (DeYoung, Frame,

Glennon, & Nigro, 2010).

An example of a national credit reference agency is Malaysia’s Credit Bureau operated by Bank

Negara Malaysia. It was established under the repealed Central Bank of Malaysia Act 1958 in

1982 and continues to operate under the Central Bank of Malaysia Act 2009. Like other credit

reference agencies in the world, the Credit Bureau collects credit-related information on

borrowers from lending institutions, “warehouses” that information and furnishes the credit

information collected to the financial institutions and others in the form of credit reports of firms

and individuals via an online system known as the Central Credit Reference Information System.

These credit bureaus or registries provide an important role in financial systems by ameliorating

the information asymmetry often faced by banks and other financial institutions, thereby

reducing fraud and helping them make better informed decisions and to avoid adverse selection

(Bank Negara Malaysia, 2014).

Finally, in today’s digital age, many financial institutions obtain information regarding

individuals and business from the internet. The phenomena called the internet of things (IoT), as

well as social media, provide access to information that creditors, banks and other financial

institutions can use to help them assess the creditworthiness and character of individuals and

firms. This information can be platformed using application program interface (API)

technologies into information needed by them to monitor counterparty information, loans and

other pertinent information as part of a risk management lending technology framework or

“finternet.” These finance technological innovations and more are part of the emerging “finternet

of things” or FoT (Monetary Authority of Singapore; The Association of Banks in Singapore,

2016).

Basel and Credit Risk Standards. The Basel Committee on Banking Supervision, based in

Basel, Switzerland, was mandated by the Bank of International Settlements (BIS) in the 1980s in

order to promote standards to enhance bank safety through risk measurement and monitoring

methods. Basel I (1988) or the Basel Capital Accord, as it is called, emphasizes a bank balance

sheet by protecting the regulatory capital of banks (also referred to as Pillar 1). Its approach was

ostensibly one a risk absorption one. Regulatory capital is the amount of capital a bank must

maintain as required by the bank’s regulator and is generally a ratio of bank equity that must be

maintained relative to the “weighted” riskiness of the assets the bank holds. The method is

measured in two steps: the measurement of weighted risk exposures assigned to assets classes;

and the quantification of the regulatory capital available relative to the risk measured (Iqbal &

Mirakhor, 2007).

Regulatory capital is divided into Tier 1 and Tier 2. Tier 1 is the core measure of a bank's

financial strength as determined by its regulator and it typically comprised of the bank’s common

stock, disclosed reserves, stock surpluses or retained earnings; and may also include non-

redeemable non-cumulative preferred stock. Tier 2 is supplemental to the core capital component

and is typically comprised of revaluation reserves, undisclosed reserves, hybrid instruments and

subordinated term debt. The ratio of regulatory capital (Tier 1 and 2) to risk-weighted assets is

the minimum level of recommended regulatory capital or capital adequacy ratio (CAR).

In the wake of banking volatility and rapidly changing financial markets, including financial

product innovation, Basel II was promulgated in 2004. Basel II introduced enhanced prudential

supervisory review processes and more effective market discipline. Market discipline placed

greater emphasis on bank transparency and risk disclosure (Investopedia LLC, 2016). Basel II

gave banks a choice between two capital adequacy requirements: the standardize approach or the

internal ratings-based approach. The choice is between basing their risk-weighted asset (RWA)

calculations on either standard risk weights, as defined by national regulators, or internally

developed risk models; provided regulators approve them in advance. Basel II promulgates

general rules for estimating the credit risk associated with each kind of asset. Credit risk is

evaluated at the client level, based upon the each client’s credit rating. It classifies a bank’s

assets on the basis of debtor profiles, collateral and the nature of the underlying assets according

to 13 kinds of claims and assets as shown below.

Claims on sovereign governments and central banks;

Claims on non-central government public sector entities;

Claims on multilateral development banks;

Claims on banks;

Claims on securities firms;

Claims on corporate entities, including insurance companies;

Claims included in the regulatory retail portfolios;

Claims secured by residential property;

Claims secured by commercial real estate;

Past due loans;

Higher-risk categories;

Other assets; and

Off-balance sheet items.

The first 7 categories of assets relate risks to the kind of debtors the last 4 to risks based on the

nature of the underlying assets. Generally, from these categories, the minimum capital

requirements of a bank is calculated by applying risk weights to assets items after the deduction

of provisions, i.e., net of all provisions required by the usual accounting and auditing regulations

and sound practices (Kahf, 2005). The asset class multiplied by the risk weights for each

respective asset class is called the risk-weighted assets (RWA). These capital weighting

measures are designed to monitor a bank’s ability to absorb loss from the various classifications

of lending (asset classes). Accordingly, CAR = Capital / RWA. The CAR must meet a minimum

ratio floor. Thus, riskier asset category positions require higher risk weights, which in turn

require higher capital reserves. These risk weights with mitigation risk adjustments are the

essence of Pillar 1 of Basel II. The Basel II standardize approach linked the above claims and

assets (asset classifications) to their credit agency ratings. An example8 of that approach is

shown below in Table 4.

Pillar 2 is mandatory supervisory review of capital adequacy. Having addressed the quantitative

standardized approach, Basel II then lists qualitative factors to be considered by the regulators:

Experience and quality of management and key personnel

Risk appetite and track record in managing risk

Nature of markets in which the bank operates

Quality, reliability and volatility of earnings

Quality of capital and access to new capital

Diversification of activities and concentration of exposures

Liability and liquidity profile

Complexity of legal and organizational structure

Adequacy of risk management system and controls

8 Taken from Basel standardize risk weights without certain refinements subject to regulator approval.

Support and control provided by shareholders

Degree of supervision by other supervisors (Id).

Table 4-Basel II Risk Weighted Assets

Claim Type Rating/RW Rating/RW Rating/RW Rating/RW Rating/RW

Applicable to

corporations &

sovereign

governments

and central

banks only

AAA to AA

A+ to A-

BBB to

BB-

BB-

Unrated

Corporations 20% 50% 100% 150% 100%

Regulatory

retail

portfolios-

individual and

small

businesses

75%

75%

75%

75%

75%

Secured by

residential

property

35% 35% 35% 35% 35%

Secured

commercial

real estate

50-100%

50-100%

50-100%

50-100%

50-100%

Sovereign

governments

and central

banks

0%

20%

50%

150%

100%

Banks and

securities firms

Based on

country’s

weight or

external

score

adjusted for

duration

Based on

country’s

weight or

external

score

adjusted for

duration

Based on

country’s

weight or

external

score

adjusted for

duration

Based on

country’s

weight or

external

score

adjusted for

duration

Based on

country’s

weight or

external

score

adjusted for

duration Source: (Glanz & Mun, 2008)

Basel II’s Pillar 3 is market discipline, which emphasizes transparency and disclosure by banks.

It further emphasizes a systematic approach to identifying, measuring, monitoring and

controlling credit risk. Basel II encourages banks to use internal rating-based (IRB) approaches

for measuring credit risk. The foundation or basic IRB approach allows banks to estimate several

components of these models, e.g. probability of default, exposure at default and effective

maturity. Banks are allowed to develop their own models. The banks and the regulator provide

the primary inputs to sophisticated models. Basel II provides a graphic it terms “cut-off points.”

These cut-off points help banks define risk weights by measuring the areas between expected

(EL) and unexpected losses (UL), where the regulatory capital should be held in the probability

of default (PD). Figure 7 graphically depict a loss distribution curve for the EL and UL portions

of the loss frequency curve outlined in Basel II. EL, or expected loss, as indicated in the graphic,

is the loss that is provisioned on an ongoing basis, “built-up and part of the price discovery for

the banking product. This risk is effectively “passed on” to counterparties as part of the expected

credit risk pricing. It is, in effect, the bank’s “hurdle rate” or risk adjusted breakeven point in

pricing where income (pricing) is sufficient to cover expected credit loss, associated funding

costs and overhead costs. EL is based on the bank’s historical default experience and is

sometimes expressed as:

EL = EAD x LGD x PD;

where EAD is exposure at default, LGD is loss given default and PD is probability of default.

These terms will be explained in detail later (infra). UL, or unexpected loss, must be understood,

so as it represents the loss potential that exceeds the historical default experience. There must be

capital available to cover this loss in the eventuality it is incurred. Thus, if there are adequate

“built-up” provisions for loan loss reserves, UL represent the capital required to cover the large

seldom losses by banks due to disruptive market conditions (Basel Committee on Banking

Supervision, 2005).

Figure 7-Cut-Off Points

Source: (Glanz & Mun, 2008)

Though banks are given the latitude to develop their own credit risk models for probability of

default (PD), most use one of the established reduced form models (infra) for publicly traded

firms that are counterparties. When modeling for retail and unlisted firms, banks normally use

credit scoring or logistic regression, both of which are closely linked to the reduced form models

(Wikimedia Foundation, Inc., 2016). Where a bank or banking system chooses to implement its

own internal-based rating system vis-à-vis a standardized method, the bank and banking system

must demonstrate it utilizes 3 main elements:

Risk parameters, which include probability of default (PD), exposure at default (EAD),

loss given default (LGD) and maturity (M);

Risk-weight functions, i.e. the asset classifications of the Basel II framework that “map”

the risk parameters (above) to risk-weighted assets; and

Minimum requirements or core minimum standards that a bank must satisfy to use the

internal ratings-based approach (Id).

In applying the above elements, banks may use the foundation or advanced methods of credit

risk measurement techniques, i.e. F-IRB and A-IRB, respectively. Both refer to a set of credit

risk measurement techniques proposed under Basel II’s capital adequacy rules for banking

institutions. Under the F-IRB approach the banks are allowed to develop their own empirical

model to estimate the PD for individual clients or groups of clients. Banks can use this approach

only subject to approval from their local regulators. If the F-IRB method is used by banks, they

are required to use the regulator's prescribed LGD and other parameters required for calculating

the RWA (Risk-Weighted Asset). Then total required capital is calculated as a fixed percentage

of the estimated RWA. Under the A-IRB approach, banks are allowed to develop their own

empirical model to CAR. Banks can use this approach only if approved by their regulator.

Under A-IRB banks are supposed to use their own quantitative models to estimate PD

(probability of default), EAD (exposure at default), LGD (loss given default) and other

parameters required for calculating the RWA (risk-weighted asset). Then total required capital is

calculated as a fixed percentage of the estimated RWA. There are 12 core minimum

requirements that a bank must satisfy to use either of the internal-based rating (IRB) methods:

1. Composition which consists of the following attributes:

Reflect borrower and transaction characteristics

Provide for a meaningful differentiation of risk

Be accurate and consistent in the estimation of risk

2. Compliance which requires a bank to demonstrate ongoing compliance with the core

minimum requirements and if does not do so at any time, it must notify the regulator, submit a

plan outlining how it intends to do so, along with definitive timelines for compliance. Regulators

may take appropriate action or require additional temporary capital buffers during non-

compliance.

3. Rating system design or an entire mathematical and technological infrastructure capable of

quantifying and assigning the risk parameters. Banks have the latitude to use several ratings

systems for different exposures, but the methodology must be logical and documented; banks are

not allowed to rating method “shop” in order to minimize regulatory capital requirements.

4. Rating system operations must be independently reviewed periodically; at least once a year,

and all data use in the ratings must be collected and maintained by the bank.

5. Banks must exercise good governance and competent oversight.

6. Banks must satisfy the “use test” as promulgated by Basel that ratings play an essential role

internally in the risk management practices of the bank. A rating system solely devised for

calculating regulatory capital is not acceptable.

7. Risk quantification must properly apply risk parameters to probability of default (PD),

exposure at default (EAD), loss given default (LGD) and maturity (M), including the use of

economic loss principles vis-à-vis accounting loss principles.

8. Banks must have well-defined “back testing” processes to estimate the accuracy and

consistency of their rating systems.

9. Banks using the foundation IRB approach must use the regulator’s estimates of EAD and LGD

and the minimum requirements of the standardized approach for recognition of eligible

collateral.

10. Leases, other than those that expose the bank to residual value risk, must be treated as

exposures collateralized by the same type of collateral.

11. The calculation of the capital charge for equity exposures must be the equivalent to the

potential loss to the bank’s equity portfolio arising from a hypothetical “instantaneous shock

equivalent to the 99th percentile, one-tailed confidence interval” of the difference between

quarterly returns and an appropriate risk-free rate computed over a long-term sample period.

12. Banks must meet the disclosure requirements as mandated by the Pillar 3 of the Basel II

framework on market discipline and failure to meet the disclosure and transparency requirements

therein will make the bank ineligible to use the IRB approach.

Basel III was adopted in general in 2010 and was scheduled to be gradually implemented from

2013 until 2015, but has delayed full implementation to 2019 (Basel Committee on Banking

Supervision, 2011). Basel III covers wholesale, retail, private and investment banking and their

related risk exposure based products. Figure 8 is Basel III’s phase-in arrangement. As can be

noted from Figure 8, a capital conservation buffer has been added by Basel III. The capital

conservation buffer is designed for make banks build capital buffers to be used during periods of

stress. A buffer of 2.5% is recommended Tier 1 and 2 capital structures. If a bank is operating in

the buffer zone, there will no restrictions on conduct of business but there will be restrictions on

distribution of capital via dividends, bonus payments in cash and stock to employees. Basel III

also recommends possible countercyclical capital buffers that may be imposed temporarily to

curtail excessive credit growth and risk taking by banks. This additional buffer could vary from

0-2.5% and be imposed at the national or bank level, if particular bank(s) are taking the

excessive risks. It may be withdrawn when the credit climate improves. Although not the focus

of this paper, Basel III imposes a new strong global liquidity standard (Banking Intellisense,

2013).

Figure 8-Basel III

Source: (Basel Committee on Banking Supervision, 2011).

The net effect of the progression from Basel I to Basel III can be seen graphically in Figure 9.

There has been a decrease in the available capital and an increase in RWA, even without

conservation and countercyclical buffers.

Figure 9-Navigating the Changes from Basel I to Basel III

Source: (PWC Financial Services Institute, 2010).

In December 2015, Basel Committee issued its second consultation on Revisions to the

Standardised Approach for credit risk (Basel IV). The proposed revision this standardized

approach to credit risk capital management came in the wake of industry dissatisfaction with the

initial consultative document issued in December 2014, which essentially recommended that

banks stop relying on external ratings (which had been blamed as partially contributing to the

2008 global financial crisis). The new consultative document reintroduces external ratings in a

limited capacity with an alternative standardized approach for use where external ratings are not

allowed. Table 9 shows the essential changes to the standardized approach Basel IV is

considering (Basel Committee on Banking Supervision, 2015).

Table 9-Basel IV Contemplated Changes to Standardized Approach to Credit Risk

Claim Type RW Changes Contemplated

Sovereign or Central

Bank

Bank exposures would no longer be risk-weighted by reference to

the external credit rating of the bank or of its sovereign of

incorporation, but they would instead be based on a look-up table

where risk weights range from 30% to 300% on the basis of two

risk drivers: a capital adequacy ratio and an asset quality ratio.

Corporate Corporate exposures would no longer be risk-weighted by

reference to the external credit rating of the corporate, but they

would instead be based on a look-up table where risk weights

range from 60% to 300% on the basis of two risk drivers: revenue

and leverage. Further, risk sensitivity would be increased by

introducing a specific treatment for specialized lending.

Regulatory retail The retail category would be enhanced by tightening the criteria to

qualify for the 75% preferential risk weight, and by introducing a

fallback subcategory for exposures that do not meet the criteria.

Secured residential real

estate

Exposures secured by residential real estate would no longer

receive a 35% risk weight. Instead, risk weights would be

determined according to a look-up table where risk weights range

from 25% to 100% on the basis of two risk drivers: loan-to-value

and debt-service coverage ratios.

Secured commercial real

estate

Exposures secured by commercial real estate are subject to further

consideration where two options currently envisaged are: (a)

treating them as unsecured exposures to the counterparty, with a

national discretion for a preferential risk weight under certain

conditions; or (b) determining the risk weight according to a look-

up table where risk weights range from 75% to 120% on the basis

of the loan-to-value ratio. Source: (Basel Committee on Banking Supervision, 2015)

Islamic and Basel Credit Risk Standards. Basel is an international banking standard setter.

Each economy has its own banking regulator. Many Islamic economies and economies that have

a significant Islamic banking system generally follow Basel recommendations. Moreover, Basel

has recently moved towards greater national input control over credit risk management by banks.

As noted herein above (supra), Malaysia, for example, adjusted its credit risk assessment and

banking standard with respect to investment accounts. Similarly, Malaysia has its own

standardize risk weighting approach, which takes into consideration the unique features of

Islamic banking contract products (asset classifications). On October 13, 2015, BNM issued its

Capital Adequacy Framework for Islamic Banks (Risk-Weighted Assets), the “Framework.”

Therein, BNM specifies the credit risk methods to be used by Islamic banks in Malaysia, i.e. the

standardized approach and the internal ratings based (IRB) approach. The latter approach is

subject to “explicit” BNM approval. On the same date, BNM issued the Capital Adequacy

Framework (Capital Components). The two standards are to be used together. The Framework

was pronounced as consistent with the “Capital Adequacy Standard for Institutions other than

Insurance Institutions offering only Islamic Financial Services (CAS) issued by the Islamic

Financial Services Board (IFSB) and the Capital Adequacy Framework (Basel II – Risk-

Weighted Assets) issued by the Bank for banking institutions licensed under Financial Services

Act 2013 (FSA).” (BNM, 2015).

IFSB-2. IFSB-2 states inter alia:

“Credit risk exposures in Islamic financing arise in connection with accounts

receivable in Murābahah contracts, counterparty risk in Salam contracts,

accounts receivable and counterparty risk in Istisnā` contracts and lease

payments receivable in Ijārah contracts, and sukuk held to maturity in the

banking book. In the standard, credit risk is measured according to the

Standardised Approach of Basel II…except for certain exposures arising from

investments by means of Mushārakah or Muḍārabah contracts in assets in the

banking book. The latter are to be treated as giving rise to credit risk (in the

form of capital impairment risk), and risk-weighted using the methods

proposed in Basel II either for “equity exposures in the banking book” or, at the

supervisor’s discretion, the supervisory slotting criteria for specialised

financing” (IFSB, 2005).

Thus, IFSB proposes applying Basel II’s standardized approach to measure credit risk for Islamic

banking products (except where the bank is authorized by the regulator to use IRB). The standard

uses Standard & Poor’s ratings. The strength of IFSB-2 lays in its detailed risk assessment and

mapping to external credit ratings for all Islamic banking contracts that are universally accepted.

Islamic banking contracts such as inah and tawarruq are shunned. Supervisor or regulator

discretion is conceded as to musawamah and bay`bithaman ajil. Moreover, IFSB-2 removes

RWA investment accounts from the CAR calculation, as well as PER and IRR RWA for those

jurisdictions using those smoothing accounts (Id).

The “supervisory slotting criteria” is defined as instances when the regulator of an Islamic bank

chooses to “employ an alternative approach” wherein bank is required to map its internal risk

grades into four supervisory categories for specialized financing each of these categories will be

associated with a specific risk weight. The standard specifically mentions istisna’ (limited and

non-recourse) project financing, musharakah in business ventures and musharakah muntanaqisa

for real estate financing. The risks associated with those Islamic banking contracts are “mapped”

to four “supervisory categories:” strong, good, satisfactory and weak (Id).

IFSB-2 proposes 5 mitigating tools:

Hamish Jiddiyyah (security deposit held as collateral);

‘Urbūn (earnest money held after a contract is established as collateral to guarantee

contract performance);

Kafalah (guarantee from a third party, either recourse or non-recourse);

Rahn (pledging of assets as collateral); and

Ijarah amwal (assets leased under contracts are functionally similar to that of collateral,

inasmuch as they may be repossessed in the event of default). Id.

BNM Capital Adequacy Framework for Islamic Banks. With respect to credit risk, the

Framework establishes both the standardized and internal rating based (IRB) approaches to credit

risk assessment. BNM reserves the right to modify standardized ratings at banks if it is deemed

that risk exposures warrant deviation from the standard. It also directs Islamic banks to capture

all external ratings available from established credit rating agencies for a counterparty and to use

the lower of the two, if two, or the lower of the two highest, if more than two. BNM recognizes

the major external rating agencies as well as the local RAM and MACR agencies. BNM’s

standardized Shari’ah RWA is elaborate and detailed. It is noteworthy that the Framework

specifically mentions that equity participation in a business venture through a mudarabah

contract results in risk that is “similar to the risk assumed by an equity holder in a venture capital

or a joint-venture investment. As an equity investor, the Islamic banking institution assumes the

first loss position and its rights and entitlements are subordinated to the claims of creditors

(BNM, 2015). Accordingly, their risk weighting is “100% risk weight for publicly traded equity

and 150% risk weight for non-publicly traded equity; or Supervisory slotting criteria method

subject to fulfilling minimum requirements.” If the Islamic bank has a receivable from the

mudarib on a project, the external credit rating of the ultimate obligor is used for CAR purposes

and any remaining balance the RWA is 150%. Advance payments to the mudarib are subject to

supervisory slotting (Id).

The IRB is an opt-in approach requiring explicit BNM approval before implementation. The

Framework states that its adoption of the IRB approach:

Acknowledges and differentiates between the foundation and advanced methods of IRB

approaches;

Islamic banks are allowed to adopt a wider range of credit risk mitigation techniques,

subject to requirements set by BNM;

The determination of the CAR for Islamic banks is based on the unexpected loss (UL)

approach as formulated in Basel II;

Based on the UL coverage approach, any excess provisioning of the EL will be

recognized as part of the Islamic bank’s eligible Tier 2 capital; and

Islamic banks will adhere to high standards in implementing any IRB approach and apply

it to its day-to-day risk management processes (BNM, 2015).

All in all, the Framework does follow the rubric of Basel II and guidance for Islamic banks found

in IFSB-2; while prudentially maximizing the discretion flexibility that can be placed in BNM to

regulate and supervise the Islamic banks in Malaysia. Islamic banks are given the choice

between the standardized and internal rating based methods of CAR promulgated by Basel and

the unique attributes of Islamic banking contracts used in Malaysia are included in the external

rating asset class exposure rates. In addition to the credit risks that are attendant to Islamic

banking, the Framework includes operating, market and specific risks among others; notably

those related to an Islamic bank’s positions in sukuk. The Framework is comprehensive to say

the least.

Credit Risk Modeling

Credit risk modeling is not perfect. There are errors that can occur in credit risk modeling. All

risk factors may not be known. Some risk factors might have been ignored. Risk factor

volatilities, co-integrations or correlations might be incorrectly measured. There may be under-

weighting or over-weighting of risks. Such misunderstandings and errors result in what is

generically known as model risk. Yet, knowledge of credit risk models is indispensible in today’s

complex banking environment.

Internal Rating Methods. Banks and other financial institutions develop their own internal

credit scoring procedures accessing the creditworthiness of their corporate and retail customers

using established scoring models. This may involve the use of default predictive scoring.

Altman’s Z-Score is the most popular internal credit scoring model (Altman E. , 1968). Credit

scoring modeling is relatively inexpensive to implement, as they rely on accounting information

(Allen, 2002). A study by (Mester, 1997) indicates that approximately 70% of banks surveyed

with assets greater than $5 billion used credit scoring in their small business lending. However,

only 8% of those surveyed with assets up to $5 billion used credit scoring for small business

lending. This phenomenon likely reflects the complexities faced by larger banks in mitigating

their credit risk, as well as Basel’s push towards the RWA methods.

Nevertheless, because of its simplicity, the Z-SCORE can still be a useful tool in making

preliminary assess of credit risk as it relates to the probability of default. It measures that aspect

of credit risk by applying the following formulation:

Z-SCORE = 1.2 x working capital + 1.4 x retained earnings (net worth) + 3.3 x EBIT (earnings

before interest and taxes) + 0.6 x market value of equity + 0.999 x sales.

All variables are scaled by assets, except for market equity, which is scaled by book value of

total liabilities. If the Z-score is > 3, the firm is unlikely to default. If it is between 2.7 and 3.0,

the creditor should be “on alert.” If it is between 1.8 and 2.7, there is a good chance of default. If

it is less than 1.8, the probability of a financial loss is very high. These models may involve some

regression analysis within rating or portfolio classes in the development process and can be

calibrated to a probability of default (PD) for a given borrower. These models are transformation

functions that calibrate scores to get PD from credit score modeling. An example of a logit

calibration, where exp represents an exponent, is (Bluhm, Overbeck, & Wagner, 2010):

PDborrower = 1 / 1 + exp (-SCOREborrower)

Because credit scoring relies on accounting data, they may suffer from the same vagaries as

accounting ratio analyses. However, FinTech or financial technologies, e.g. blockchains do offer

hope that more timely accounting information may make accounting based credit scoring more

useful. Finally, credit scoring can be linear, although there are 4 methods: linear probability,

logit, probit and multiple discriminant analysis. The latter 3 are nonlinear (Id). Table 10 lists

many of the credit scoring models used internationally.

Credit Risk Models. Credit risk modeling has developed rapidly over the past decade to become

a key component in risk management systems at banks and other financial institutions. Several

financial institutions and consulting or advisory firms actively market their “proprietary” credit

risk models. These models permit banks and other end users to measure credit risk in their asset

portfolios or segmented portfolios for purposes of pricing, netting, setting concentration9 limits

and measuring expected risk-adjusted returns. They may, however, differ in their fundamental

assumptions. This, in turn, may lead to what can be termed “model risk” (Bluhm, Overbeck, &

Wagner, 2010). Notwithstanding model risk, models have proved valuable to banks and other

financial institutions because of their forecast or predictive value. The models may be internally

modified as well (Lopez & Saidenberg, 2000).

Modern methods of credit risk measurement follow two alternative branches in the asset pricing

literature of academic finance, i.e. options-theoretic structural models pioneered by (Merton,

9 Concentration limits typically include concentrations measured by: counterparty, product, industry or currency (Banking

Intellisense, 2013).

1974) and a reduced form models utilizing intensity-based models to estimate stochastic hazard

rates, that follow methods pioneered by (Jarrow, Lando, & Turnbull, 1997); (Duffie & Singleton,

1998); and (Duffie & Lando, Term Structures of Credit Spreads with Incomplete Accounting

Information, 2001). Though different in methods, both try to accomplish the same goal, i.e.

estimation or forecasting of default probabilities. Both measure of default risk (which is, in the

view of many, a component of credit risk). Structural models view default as the outcome of a

gradual descent or deterioration. Reduced form or intensity-based models view default as a

sudden, unexpected (stochastic) event (Allen, 2002). There remains “heated debate” as to which

models are superior, but Basel has adopted Merton’s structural form as its approach.

Structural Models. Structural models assume complete knowledge of a firm. It is the kind of

intimate knowledge that firm’s managers would normally possess; which would seem to make it

suitable for internally based rating methods. This modeling technique also assumes that a firm’s

default timeline is predictable. They assume that a default event timeline is gradual vis-à-vis

sudden or abrupt. A default event is only deemed to occur when a firm’s assets are at a

sufficiently low level compared to its liabilities. As noted options-theoretic structural models

were pioneered by (Merton, 1974) and by (Black & Scholes, 1973) and have more recently been

adopted for credit risk measurement. That is rather easy to see since firm value (the basis for

option put/call analysis) is essentially a substitute for firm “capital.” Thus, it follows that bank

capital, as emphasized in the Basel regime can be examined using from a put/call perspective.

Structural models depend on the data regarding a firm’s equity being traded.

Table 10-International Use of Credit Scoring Models

County Name Explanatory Variables USA Altman (1968) EBIT/assets; retained earnings/ assets; working capital/assets;

sales/assets; market value (MV) equity/book value of debt.

Japan Ko (1982) EBIT/sales; working capital/debt; inventory turnover 2 years

prior/inventory turnover 3 years prior; MV equity/debt; standard

error of net income (4 years).

Japan Takahashi, et. al. (1979) Net worth/fixed assets; current liabilities/assets; voluntary reserves plus

unappropriated surplus/assets; interest expense/sales; earned surplus; increase in

residual value/sales; ordinary profit/assets; sales - variable costs.

Switzerland Weibel (1973) Liquidity (near monetary resource asset – current liabilities)/operating expenses prior

to depreciation; inventory turnover; debt/assets.

Germany Baetge, Huss and

Niehaus (1988)

Net worth/(total assets – quick assets – property & plant); (operating income +

ordinary depreciation + addition to pension reserves)/assets; (cash income –

expenses)/short term liabilities.

Germany von Stein and Ziegler

(1984)

Capital borrowed/total capital; short-term borrowed capital/output; accounts payable

for purchases & deliveries / material costs; (bill of exchange liabilities + accounts

payable)/output; (current assets – short-term borrowed

capital)/output; equity/(total assets – liquid assets – real estate); equity/(tangible

property – real estate); short-term borrowed capital/current assets; (working

expenditure – depreciation on tangible property)/(liquid assets + accounts receivable

– short term borrowed capital); operational result/capital; (operational result +

depreciation)/net turnover; (operational result + depreciation)/short-term borrowed

capital; (operational result +

depreciation)/total capital borrowed.

England Marais (1979), Earl &

Marais (1982)

Current assets/gross total assets; 1/gross total assets; cash flow/current liabilities;

(funds generated from operations – net change in working capital)/debt.

Canada Altman and Lavallee Current assets/current liabilities; net after-tax profits/debt; rate of growth of equity –

(1981) rate of asset growth; debt/assets; sales/assets.

Netherlands Bilderbeek (1979) Retained earnings/assets; accounts payable/sales; added value/assets; sales/assets; net

profit/equity.

Netherlands van Frederikslust (1978) Liquidity ratio (change in short term debt over time); profitability ratio (rate of return

on equity).

Spain Fernandez (1988) Return on investment; cash flow/current liabilities; quick ratio/industry value; before

tax earnings/sales; cash flow/sales; (permanent funds/net fixed assets)/industry value.

Italy Altman, Marco,

and Varetto (1994)

Ability to bear cost of debt; liquidity; ability to bear financial debt; profitability;

assets/liabilities; profit accumulation; trade indebtedness; efficiency.

Australia Izan (1984) EBIT/interest; MV equity/liabilities; EBIT/assets; funded debt/shareholder funds;

current assets/current liabilities.

Greece Gloubos and

Grammatikos

(1988)

Gross income/current liabilities; debt/assets; net working capital/assets; gross

income/assets; current assets/current liabilities.

Brazil Altman, Baidya, &

Ribeiro-Dias,1979

Retained earnings/assets; EBIT/assets; sales/assets; MV equity/book value of

liabilities.

India Bhatia (1988) Cash flow/debt; current ratio; profit after tax/net worth; interest/output; sales/assets;

stock of finished goods/sales; working capital management ratio.

Korea Altman, Kim and Eom

(1995)

Log(assets); log(sales/assets); retained earnings/assets; MV of

equity/liabilities.

Singapore Ta and Seah

(1981)

Operating profit/liabilities; current assets/current liabilities; EAIT/paid-up capital;

sales/working capital; (current assets – stocks – current liabilities)/EBIT; total

shareholders’

fund/liabilities; ordinary shareholders’ fund/capital used.

Finland Suominen (1988) Profitability: (quick flow – direct taxes)/assets; Liquidity: (quick assets/total assets);

liabilities/assets.

Uruguay Pascale (1988) Sales/debt; net earnings/assets; long term debt/total debt.

Turkey Unal (1988) EBIT/assets; quick assets/current debt; net working capital/sales; quick

assets/inventory; debt/assets; long term debt/assets.

Source: (Altman & Narayanan, 1997)

Structural models work from the traditional balance sheet axiom that:

Assets (A) = Debt (D) + Equity (E)

Therefore,

At =D(t,T) + Et

Assuming that time t is the present and time T is the 1-year period used by Merton. If at time T:

At > or = F (the face value of the obligation)

The equity holders will pay off the debt and keep what’s left over as Et = AT – F

If however, AT < F

The equity holders will default on the debt issue and ET =0.

This basic model forms the basis for Merton’s put/call option model. As Basel explains:

“The mapping function used to derive conditional PDs from average PDs is

derived from an adaptation of Merton’s (1974) single asset model to credit

portfolios. According to Merton’s model, borrowers default if they cannot

completely meet their obligations at a fixed assessment horizon (e.g. one year)

because the value of their assets is lower than the due amount. Merton

modelled (sic) the value of assets of a borrower as a variable whose value can

change over time. He described the change in value of the borrower’s assets

with a normally distributed random variable” (Basel Committee on Banking

Supervision, 2005).

(Allen & Powell, 2011) elaborate on this by noting:

“The model measures changes to default probabilities based on the distance to

default (DD) of a firm which is a combination of asset values, debt, and the

standard deviation of asset value fluctuations, from which Probabilities of

Default (PD) can be calculated…The point of default is considered to be where

debt exceeds assets, and the greater the volatility of the assets, the closer the

entity moves to default. Equity and the market value of the firm’ assets are

related as follows:”

Thus, as stated in the accounting axiom above and at the initial time 0:

A0 = E0 + D0

where A = firm assets; E = firm equity; and D = the face value of the firm’s debt.

At time T (is usually set as one year), the firm pays off the bond, with remaining equity paid to

the shareholders. The firm defaults if the debt obligation exceeds the asset value of the firm at T.

In that instance, the bondholders take ownership of the firm and the shareholders get nothing and

because they have limited liability, shareholders equity cannot be negative. The amount that is

paid to obliges or creditors = b. Equity at T the amount that might be paid to the shareholders is:

ET = AT – b

where the debt value is greater than the asset value, then:

ET = 0.

Thus the value of a firm’s stock at debt maturity:

ET = max (AT – b, 0)

This result is the same as the payoff of a call option on the firm’s value with strike price b under

Merton’s analysis. A call option gives the holder the right or option to buy the underlying asset

from the counterparty obligee, at a specified price (the strike price) up to a specified date (the

expiration date). This is the so-called long call option position.

If, at T, assets exceed debt obligations, the firm’s shareholders will exercise the option to repay

the debt obligation and keep the residual as profit. If loans exceed assets, then the option will

expire unexercised and the firm owners, although they personally have limited liability, will lose

the firm due to default.

The call option is in the money where AT – b > 0, at the money where AT – b = 0 and out the

money where AT – b < 0.

Under the Merton model, probability of default PD is a function of the distance to default DD or

the number of standard deviations (ơ) between the value of the firm and the debt obligation, as

determined by using the market value of assets (A) less the amount of debt obligation (b) divided

by the volatility of assets ơA:

-A b

σA

PD can be determined using the normal distribution. For example, if the distribution is normal

and DD = 2 standard deviations, we know there is a 95% probability that assets will vary

between one and two standard deviations. There is a 2.5% probability that they will fall by more

than two standard deviations or 2.5% at each tail of the normal bell shaped distribution.

Credit risk companies, e.g. KMV, have large worldwide databases from which to provide

empirically based estimated default frequencies. Thus the KMV model consists of three steps.

Firstly, estimate market value and volatility of firm’s assets. Secondly, calculate DD. Thirdly,

match distance to default to an empirically obtained EDF.

Merton assumes that asset values are log normally distributed. Distance to default and

probability of default are calculated as:

2ln( / ) + ( -0.5 )

= V

V

A F μ σ TDD

σ T

where A = market value of firms assets, F = face value of firm’s debt, µ = an estimate of the

annual return (drift) on the firm’s assets.

Thus,

PD = N (-DD)

N = cumulative standard normal distribution function (Allen & Powell, Measuring Real Capital

Adequacy in Extreme Economic Conditions: an Examination of the Swiss Banking System,

2011).

Reduced Form Models. Reduced form models decompose observed credit spreads to detect the

term structure of default probabilities. Reduced form models do not specify the structural

variables leading to default. Defaults are modeled at various points. Defaults occur randomly

with probabilities determined by intensity or “hazard” functions. These credit risk rating

approaches typically measure the probability of default, PD (conditional on there being no

default prior to time t), so-called “first pass” modeling; estimate loss given default, LGD (1

minus the recovery rate); exposure at default, EAD (value of the obligation at default); and the

maturity, M. The basic probability of an expected loss (EL) function is:

EL = PD x LGD x EAD

EL is defined as the loss rate expected for a defined group of counterparties. It is the product of

the counterparties’ probability of default (PD) and the loss given default (LGD) and the exposure

at default. In other words, it is:

EL = PD (%) x LGD (%) x EAD

LGD = charge-offs net of recoveries/outstanding balance of debt at default; while EAD =

outstanding balance of debt at default. The implications of the time horizon or maturity of a

given obligation are considered by expressing the probability of default over the term. That

expression is (pt)t >/= 0; where pt is the probability of default at a given point in time (t) and the

time interval is [0, t] or from zero to the term of the obligation (Bluhm, Overbeck, & Wagner,

2010).

EL may vary across different credit asset classes and different types of counterparties; even those

considered mass or general public, affluent and high net worth. This is a significant element

pricing financial products. The estimation of EL must be determined at the asset classification

level and cover one economic cycle, i.e. one good and one bad economic period. In

circumstances where the EL estimation is based on credit loss data incorporating only one good

economic period due to unavailability of credit loss data, a conservatism buffer as discussed in

Basel III can be applied in order to reflect the probability of a bad economic period. This

phenomenon is addressed by Basel in its survey of cyclical effects in credit risk measurement

models (Allen & Saunders, 2003). As stated in that working paper: “…good economic times

provide the rising tide that lifts even the shakiest of financial boats. Thus, ex post realizations of

credit problems display clear procyclical patterns – increasing during recessions and decreasing

during expansions” (Id). Allen and Saunders graphically depict this macro-phenomenon as

shown in Figure 10 below.

Figure 10-Example of a Procyclical Shift

Source: (Allen & Saunders, 2003).

Thus, it can be said that reduced form models are fundamentally empirical as they use observable

risky debt prices (and credit spreads) in order to derive the stochastic hazards or shocks likely to

trigger defaults (Allen, 2002). These reduced form models have the advantage of default

probability and distance to default estimates of credit risk levels in Islamic and conventional

banks. The methodology is also neutral as to bank size. However, as noted, they do not model

the structural factors that lead to default. Reduced form models decompose the credit spread to

solve CS = PD x LGD (Allen & Saunders, 2003).

Proprietary Models.

KMV. KMV offers a proprietary model based on the options theoretic structural approach, but

differs from other structural models as it considers systematic factors impacting default

correlations using a three level approach, by incorporating:

a composite market risk factor;

an industry and country risk factor; and

regional factors, e.g. Southeast Asia and sector indicators, e.g. extraction, technology, etc.

KMV has a large worldwide database from which to provide empirically based estimated default

frequencies (EDF). Moreover, KMV model consists of three steps:

estimating market value and volatility of firm’s assets;

calculating DD; and

matching DD to an empirically obtained EDF (Allen & Powell, Measuring Real Capital

Adequacy in Extreme Economic Conditions: an Examination of the Swiss Banking

System, 2011).

CreditMetrics. These models use a structural Value at Risk (VaR) approach, but are transition

models, i.e. they measure the probability of default using historical default experience of the

borrower or comparable or similarly profiled borrowing firms. It is standardized in the sense that

it uses credit ratings. However, it is built around a credit migration matrix that measures the

probability that the credit rating of any given obligation will change over the course of the credit

horizon or term. The credit migration matrix considers the entire range of credit events, including

upgrades and downgrades as well as actual default. It is a mark-to-market (MTM) model, rather

than a probability of default (PD) based model. CreditMetrics uses migration probabilities

matrices that are stochastic, i.e. using random probability distributions or patterns.

Credit Portfolio View (CPV). CPV is another structural model that uses a transition matrix

approach like CreditMetrics, but does not assume equal transition probability among

counterparties of the same grade, as CreditMetrics. CPV uses external ratings and creates

migration adjustment ratios by linking macroeconomic factors, e.g. GDP growth, unemployment

rates and other econometric data, to migration probability (the probability that the counterparty’s

external credit rating will change in either direction, which is a feature of credit risk).

Quantitative models often assess credit risk on a portfolio basis. CPV is one the most advanced

proprietary model in its consideration of cyclical factors by converting unconditional credit

migration matrices into conditional matrices dependent upon macroeconomic factors. Each cell

in the credit transition matrix has a probability of that particular counterparty, rated at both the

beginning and ending of a period, i.e. migrating. CPV incorporates the downgrade aspect of

credit risk into its assumption that the probability of downgrades (upgrades) increases in bad

(good) economic periods. Thus, the conditional transition matrix represents the migration

probabilities for each counterparty cell, conditional on the state of the macro-economy that is

expected to prevail at the credit horizon. The model also uses a “lag” model to forecast

macroeconomic conditions based on both fundamental macroeconomic and idiosyncratic risk

variables

Credit Portfolio Analysis. A portfolio is a collection loss variables (Bluhm, Overbeck, &

Wagner, 2010). In credit risk parlance, a portfolio is a collection of more than one underwritten

counterparty risk. Portfolios avert risk through diversification. Diversification is the technique of

spreading risk by putting assets in several categories with a broad range of risks in each. As a

credit risk “tool” it is a form of risk avoidance. It therefore reduces concentration risk.

Concentration risk in banking is accomplished by spreading a bank's assets over a variety of

counterparties the bank has financed. Concentrations statistically represent the single most

significant cause of major credit problems. Credit concentrations are any exposures or unusually

high percentage losses given default, where the potential losses are large relative to the “bank’s

capital, its total assets or, where adequate measures exist, the bank’s overall risk level” (Basel

Committee on Banking Supervision, 2000). Concentration risk can impact the stability of

individual banks, as well as an entire financial system. This risk is largely unaccounted for in

Basel credit risk asset tier capital reserve provisions, as well as so-called internal rating based

models discussed. It arises when diversification anomalies occur due to large “individual”

borrowings bringing with them idiosyncratic risk that cannot be diversified away by the

remaining portfolio assets. It also arises due to inordinately large business “sector”

concentrations that bring with the concentration systematic risk due to local, regional or global

volatilities (Grippa & Gornicka, 2016).

Expected loss (EL) for a portfolio is:

ELPF = SUM (ELi) = SUM (EADi x LGDi x PDi)

where PF is the portfolio collection bank assets, i is each of the individual assets and SUM is the

sum. The PD can be derived as noted supra as N(-DD) or N = cumulative standard normal

distribution function and DD being the distance to default.

The corresponding UL of a portfolio then is:

UL2

PF = SUM (EADi x EADj x LGDi x LGDj) x

SQR [PDi (1 – PDi) PDj (1- PDj)] pi j

where pi j = Corr (Li, Lj) = Corr (1di, 1dj) the so-called default correlation (Corr) between paired

counterparties i and j and SQR is the square root of the correlated function.

Model Risk. Given the rapid evolution of risk management models and Basel’s interest in

internal-based risk (IRB) measurement, it seems prudence for banks to have in place a model risk

management policy. Model risk arises for a number of reasons at various stages of operations,

e.g. design, implementation, use and documentation. Assumptions, hypotheses, inputs,

programming, validation and control are all areas deserving of constant vigilance. Model risk

should be managed like other types of risk, i.e. identified, measured, mitigated and controlled.

Banks should identify the sources of risk and its pervasiveness. Model risk increases with

complexity. New banking risks, particularly credit risks, may require new inputs and

assumptions. Model risk can affect both individual models and their interaction with other

model; even the entire infrastructure, caused by interaction and dependencies among models,

common assumptions, data, or methodologies. Hence, this aspect of credit risk management

should be part of the overall bank’s system. An effective validation framework should include 3

core attributes:

• Evaluation of conceptual soundness, including developmental evidence

• Ongoing monitoring, including process verification and benchmarking

• Outcomes analysis, including back-testing (Board of Governors-Federal Reserve System/Office

of the Comptroller of the Currency, 2011).

Table 11 compares some of the credit risk approaches described herein above.

Table 11-Model Comparisons

Source: (Allen & Powell, Credit Risk Measurement Methodologies, 2011)

Conclusions and Recommendations for Further Research

Credit risk remains the single most ominous risk facing banks, both Islamic and

conventional, in the modern world of finance. Islamic banking has at its disposal, an arsenal

of contracts that are ethically and financially viable. The deep roots of Islamic banking

contracts can be seen in the etymology of its terms, which guide one to the sharing

principles upon which Islamic finance is girdered; to the notions of trust (amanah) and

mutual assistance (ta’awun). The stability, as well as the sanctity of Islamic banking is vital

to Islam. The Prophet, PBUH, himself was a torchbearer of one of those contracts,

mudarabah. It deserves more than it has been given.

Malaysia is a stalwart of Islamic finance in the 21st century. But, as the finance industry

begins to see what Malaysia long ago saw, i.e. the promise of the Islamic way of banking,

there will be much competition. Islamic banking must strive to adhere to its foundational

principles and avoid matters that are doubtful. Yet, it must advance and continue to innovate

within the dictates of the Shari’ah. One glowing look at the complexity of the credit risk

models that have evolved into the 21st century should make it very clear that being the

leader can be arduous. Hence, there is a need to continue develop the requisite talent and

cadre of scholarly finance human capital and invest in the technology and innovation to

maintain the leadership.

There is also a need for scholarly research that is based on both the epistemology of Islam

and the growing body of knowledge in the field of credit risk. Islamic banking is not just

banking in Malaysia. It is the gateway to its nascent Islamic capital market. Hence, the

scholarly literature, research, technology, innovation and banking techniques must be

advanced. There are banking and finance instruments that are used in conventional finance

that may be best avoided by Islamic banking as products. But, that does not wall-off efforts

to understand them better and to use them as “tools” to better the Islamic finance world. For

example, some conventional instruments are clearly dangerous (even the conventional

banking admits as much). But those same instruments may have predictive and

informational value for Islamic banking. So, they cannot be ignored; no matter how difficult

they may seem to understand or abhorrent to Islamic finance thought. The area of credit risk

is an area where a clear understanding of those instruments is essential.

Specific research should focus on “staying ahead of the curve” and might include :

1. Testing and validation of credit risk measurement methods and models in the Islamic

context.

2. Research into the impact (benefits and potential risks) associated with the continued

evolution of financial technologies (FinTech) and the use of its attendant technologies and

innovations, e.g. the development and uses of the “finternet .”

3. Empirical credit risk comparisons between conventional and Islamic banking using

variables such as distance to default and probability of default along the lines of that

conducted by (Boumediene, 2011).

4. Empirical research into the decomposition of economic capital in conventional banking

and Islamic banking.

5. Research into disclosure and transparency among Islamic banking jurisdictions.

6. Research into specific human resource “critical mass” in the field of risk management

(and specifically credit risk) that is needed for Islamic banking risk management in order to

make the Islamic banking system one of the best in the world. See (Van Greuning & Iqbal,

2008): “Efforts should be made to develop customized research and training programs on

risk management. Such training programs should certify participants after successful

completion of the program.”

7. Research and development of Islamic banking credit risk analytic models for existing and

emerging financing structures and products, e.g. asset backed collateralized obligations.

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