Analysis of the Efficiency of NBFCs and Determinants of Profitability of Deposit taking NBFCs

Presented byVasudha RuhelaSummer TraineeDNBS, RBI Kanpur Pursuing

MSc .Statistics (2yr)IIT Kanpur   

Introduction  This project examines the efficiency of companies in the Non

Banking Financial Institution (NBFIs) industry of India. Study of the current performance of NBFCs is shown. Analysis of the determinants of profitability of Deposit taking

NBFCs (NBFCs-D) is being done. Comparison of the determinants of profitability of Deposit taking

NBFCs (NBFCs-D) of Kanpur-Regional Office with that of Other Regional Offices is done.

Different Statistical techniques such as panel data regressions have been used to determine the relationships between variables.

Financial Institutions Act as a conduit for the transfer of resources from net savers to

net borrowers. Helped in reducing regional disparities by inducing widespread

industrial development. The Financial Institutions in India mainly comprises the

commercial banks, the credit rating agencies, the securities and exchange board of India, insurance companies and the specialized financial institutions in India.

Source: Trend and Progress ofBanking in India 2013-14

Chart1: Share of different sectors in total assets of theIndian financial system

Shadow Banking

Shadow banking activities includes Credit intermediation, Liquidity transformation and Maturity transformation.

Why are they called shadow banks? Because there was so little transparency, it often was unclear who

owed (or would owe later) what to whom. Do we have shadow banks in India? The answer is yes. It is yes, because we have Financial institutions

which accept deposits and extend credit like banks, but we do not call them shadow banks; we call them the Non-Banking Finance Companies (NBFCs).

Are they in fact shadow banks? No, because these institutions have been under the regulatory

Structure of the Reserve Bank of India, right from 1963 i.e. 50 full years before the developed west is doing so.

Non-Banking Financial Companies (NBFCs) 

A Non-Banking Financial Company (NBFC) is a company registered under the Companies Act, 1956 engaged in the business of loans and advances, acquisition of shares/stocks/bonds/debentures/securities issued by Government or local authority or other marketable securities of a like nature, leasing, hire-purchase, insurance business, chit business but does not include any institution whose principal business is that of agriculture activity, industrial activity, purchase or sale of any goods (other than securities) or providing any services.

NBFCs have been made mandatory to get registered with the Reserve Bank under Section 45 IA of the RBI Act, 1934 since January 1997.

Heterogeneous group of institutions (other than commercial and co-operative banks) performing financial intermediation in a variety of ways, like accepting deposits, making loans and advances, leasing, hire purchase, etc.

Raise funds from the public, directly or indirectly, and lend them to ultimate spenders.

Broadened and diversified the range of products and services offered by a financial sector.

Gradually, being recognized as complementary to the banking sector due to their customer-oriented services

Source: www.rbi.org.inW P S (DEPR): 21 / 2011 RBI working paper seriesInter-connectedness of Banks and NBFCs in India: Issues and Policy Implications 

Chart 2: Types of NBFCs

Systematically important

Growth of NBFCs Over the years NBFCs have grown sizably both in terms of their numbers

as well as the volume of business transactions (RBI, 2009). The number of such financial companies grew more than seven-fold from 7,063 in 1981 to 51,929 in 1996 owing to the high degree of their orientation towards customers and simplification of loan sanction requirements

The number of NBFCs-D during 2012-13 declined mainly due to the cancellation of Certificates of Registration (COR) and migration to non-deposit-taking category

Chart 3: Number of NBFCs registered with RBI

Source : Report on Trend and Progress of Banking in India 2012-13 and 2013-14 

Assets of NBFC and Banking (SCBs) Sectors as a % to GDP

In developed countries, the share of NBFCs’ assets in GDP ratio is >50%. In fact, if the assets of all the NBFCs below Rs.100 crore are reckoned,

the share of NBFCs’ assets to GDP would go further.

Sources: i) Reports on Trend and Progress of Banking in India, 2006-2013 ii) Hand Book of Statistics on Indian Economy, 2012-2013 iii) 2nd National Summit: Non-Banking Finance Companies- “The way forward”, The Associated Chambers of Commerce and Industry of India,23rd January, 2015 – New DelhiNote: Assets of NBFC sector include assets of all deposit taking NBFCs and Non -Deposit Taking NBFCs having assets size Rs. 100 crore and above (NBFCs-ND)

Table 1 : Assets of NBFC and Banking (SCBs) Sectors as a % to GDP

Performance of Non Banking Financial Institutions

Cross Country Analysis* Globally, the size of non-bank financial intermediation was equivalent to 117

percent of GDP as at the end of 2012 for 20 jurisdictions and the euro area. US has the largest system of non-bank financial intermediation with assets of

$ 26 trillion, followed by the euro area ($ 22 trillion), the UK ($ 9 trillion) and Japan ($ 4 trillion).

On an average, the size of non-bank financial intermediation in terms of assets was equivalent to 52 per cent of the banking system. However, there were significant cross-country differences, ranging from 10 per cent to 174 per cent.

Non-bank financial intermediation is relatively small in the case of emerging market economies compared to the level of GDP.

In India, Turkey, Indonesia, Argentina, Saudi Arabia the amount of non-bank financial activity remained less than 20 per cent of the GDP as at end 2012.

* As per the latest available report on Cross-Country analysis of NBFCs:“Non-Banking Finance Companies: Game Changers”, Speech delivered by Shri P Vijaya Bhaskar, Executive Director, Reserve Bank of India

Performance of Non Bank Financial Institutions(Cont..)

Non-Deposit taking Systemically Important NBFCs (NBFCs-ND-SI)

NBFCs-ND-SI are not raising resources by way of public deposits, they are regulated with fewer rigors compared with NBFCs-D.

Even this type of reclassification of NBFC-ND-SI came into existence since mid-2006 although, the Reserve Bank has initiated measures effective 2000 to reduce the scope of ‘regulatory arbitrage’ between banks, NBFCs-D and NBFCs-ND (RBI, 2008) recognizing their importance, essentially from the systemic stability point of view.

With the recent happening of global financial crisis, the regulators’ attention world over has received increased attention towards the systemically important financial institutions (SIFIs).

Item 2013 2014P Percentage Variation

1.Share Capital 674 695 7.402. Reserves & Surplus 2,276 2,457 8.003.Total Borrowings 8,104 8,902 9.804.Current Liabilities & Provisions574 647 12.80Total Liabilities/Assets11,601 12,701 9.501.Loans & Advances 7,600 8,455 11.202.Hire Purchase Assets 805 896 11.303.Investments 1,945 2,075 6.604. Other Assets 1,250 1,276 2.10Memo Items1. Capital Market Exposure(CME)885 1,029 16.402.CME to Total Assets(percent)7.6 8.13.Leverage Ratio 3.0 3.0

(in billion Rs.)

Items 2013 2014P1.Total Income 1,272 1,4362.Total Expenditure 1,039 1,1473.Net Profit 233 2904.Total Assets 11,601 12,701Financial Ratios(percent)(i) Net Profit to Total Income18.3 20.2(ii) Net Profit to Total Assets2 2.3

(in billion Rs.)

Financial performance of NBFCs-ND-SI sector(As of March) 

Source: Financial Stability Report(Including Trend and Progress of Banking in India 2013-14)

00.5

11.5

22.5

Gross NPA to Total Advances Net NPA to Total Advances

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ent

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11.5

22.5

Perc

ent

Source: Trend and Progress of Banking in India 2013-14

Asset qualityDeteriorating since the quarter ended March 2013 (Chart 4). Reserve Bank issued separate guidelines for both banks and NBFCs with an objective of mitigating the stress due to their NPAs.

Chart 5: Trends in Return on Assets of NBFCS-ND-SI

Chart4: Asset Quality of NBFCS-ND-SI 

ProfitabilityROA of NBFCs-ND-SI increased to 2.5 per cent in September 2014 after remaining at around 2.3 percent in previous three quarters (Chart 5).

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Capital adequacyAs of March 2014, by and large, the capital adequacy position of the NBFCs-ND-SI remained comfortable and was well above prudential norms. Nevertheless, CRAR of the NBFCs-ND-SI slipped from the peak of 29.0 per cent as of September 2013 to 27.8 per cent by the quarter ended September 2014 (Chart 6).

Chart6: CRAR of NBFCS-ND-SI

Performance of Non Bank Financial Institutions(Cont..) > Deposit taking NBFCs (NBFCs-D)

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Net NPA to Total AdvancesGross NPA to Total Advances

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f(x) = 8.51359E-14 x⁵ − 0.000000017693 x⁴ + 0.00147077 x³ − 61.1298 x² + 1270350 x − 10559600000R² = 0.610039603911011

f(x) = 8.51359E-14 x⁵ − 0.000000017693 x⁴ + 0.00147077 x³ − 61.1298 x² + 1270350 x − 10559600000R² = 0.610039603911011

Return On Assets(ROA)

Perc

ent

Chart 7: Trend in Assets Quality of NBFCs-D

Chart 8: Trends in Return on Assets of NBFC-D

Source: COSMOS Section , DNBSReserve Bank of India, Kanpur

Asset qualityDecrease in Net NPA to Total Advances and Gross NPA to Total Advances from 2.64 and 3.67 as on quarter ended December 2012 to 0.48 and 0.30 as on quarter ended March 2015..

ProfitabilityROA of NBFCs-D increased to 2.18 per cent in quarter ended March 2015 from 0.9 percent in quarter ended June 2012(Chart 8) .There is a polynomial trend in between this period.  

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Net Interest Margin(NIM)

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Net Interest Margin (NIM)The Net Interest Margin of NBFCs-D has considerably increased from 0.12 percent as on quarter ended June 2012 to 1.66 percent as on quarter ended March 2015(Chart 9).There is a polynomial trend followed by NIM in between this period.

Chart 10: Trends in Cost Income Ratio of NBFCS-D

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Cost Income Ratio

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Cost Income Ratio (CIR)CIR is maintained around 55 percent between the Quarter ended September 2012 and quarter ended June 2012(Chart 10).The highest Cost Income Ratio(CIR) in the time period from quarter ended June 2012 till quarter ended March 2015 was recorded as 109.18 percent in quarter ended September 2014.

> Deposit taking NBFCs (NBFCs-D) (Cont..)Chart 9 Trends in Net Interest Margin of NBFCs-D

Source: COSMOS Section , DNBSReserve Bank of India, Kanpur

Determinants of Profitability of NBFCs-D Some of the commonly used accounting measures/ratios for an analysis of

efficiency/profitability are cost- to-income ratio (CI), net interest margin (NIM), and return on assets (ROA).

Chart 11: Trends in Accounting Measures reflecting Efficiency

2011-2012 2012-2013 2013-2014 2014-2015

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ROANIMCIR

Financial Year

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Source: COSMOS Section , DNBS,Reserve Bank of India, Kanpur

Dependent Variables Definition Source CIR Cost-to-Income ratio : (operating

costs(including provisions and contingencies ) /Total Income) * 100

Operations and Performance of Commercial Banks”, Trend and Progress of Banking in India(2012-2013)

NIM Net interest margin : (net interest income / Total assets )*100

ROA Return on Assets: (net profit/Total assets)*100

Criterion of Selection of Independent Variables

Dependent Variables

Definition Source

NII Net Interest Income= Interest Earned - Interest Paid

Research Papers:“Determinants of Profitability of Banks In India” (B.S.Badola and Richa Verma) and “Determinants of Profitability of Non Bank Financial Institutions’ in a developing country :Evidence from Bangladesh” (Md.Sogir Hossain Khandoker et.al)

NONII Non-Interest Income= Total Income - Interest Income

Loans Total Loans and Advances

Deposits Total DepositsNPA Non-performing Assets

as percentage to Net Advances

PC Provision and Contingencies (P&C)

OE Operating Expenses : Includes establishment expenditure, salary expenditure and –expenditure on technology up gradation

NOF Net Owned FundGDP Gross Domestic Product Own InterestCRAR Capital Risk Adequacy

Ratio

Description of data  Panel data of 254 NBFCs –Deposit taking is collected for this study. In

econometrics, the term panel data refers to multi-dimensional data frequently involving measurements over time. This data is generated by pooling time-series observations from 2011 to 2014 across 254 Deposit taking NBFCs. Country : India Panel Data of NBFCs –D Collected by: COSMOS Section, DNBS,RBI

KanpurYears Available: 2011,2012,2013,2014 (of 4

quarters each)

Data Description:

This data is of different deposit taking NBFCs present in all the regions (AHM,BAN,CAL,CHA,CHE,DEL,HYD,JAI,JAM,LUC,MUM,PAT,THI) in India.

Variables

Net Interest Income(NII), Non-Interest Income (NONII), NPA as percentage to Net Advances (NPA), Provision and Contingencies (P&C), Operating Expenses (OE), NET owned Fund (NOF) ,cost-to-income ratio(CIR) ,Net interest margin (NIM), Return on assets (ROA),Total Loans and Advances, Investments ,Deposits, and Borrowings of the different companies

**AHM,BAN,CAL,CHA,CHE,DEL,HYD,JAI,JAM,LUC, MUM,PAT and THI stands for Ahmedabad, Bangalore, Kolkata, Chandigarh, Chennai, Delhi, Hyderabad, Jaipur, Jammu, Lucknow, Mumbai, Patna and Thiruvananthpuram.

Used statistical software R and SPSS for analysis . Scaling of data Since some variables like NII, NONII, NPA, PC, OE, NOF, NIM, Total

Loans and Advances, and Deposits are divided by the corresponding total assets size of the companies so that the proper weight age can be given to each company.

Multicollinearity The variables causing multicollinearity are dropped from the

model by using Akaike Information Criterion in order to identify the variables that have high explanatory powers and are, therefore, more important in managing the operations of a NBFCs.

.

Data Analysis & Presentation Technique

Data Analysis

Description of Models

Since analysis is based on panel data. So we are considering three different models :Ordinary least Squares regression model (OLS), fixed and random regression models.

Assumptions

Normality of errors is expected to follow according to central limit theorem. Heteroscedasticity is assumed.Cross-sectional dependence is a problem in macro panels with long time series*. Here we have micro panel data i.e. only four year data quarter wise.

*Ref : “Getting Started in Fixed/Random Effects Models using R (ver. 0.1-Draft)”, available at http://dss.princeton.edu/training/, retrieved on June 30th ,2015

Different Models Considering ROA as Profitability Indicator

Independent variables : NII,NONII,NPA , PC, OE, NOF , Loans, Deposits. Dependent variable. :Return on assets (ROA) There is no multicollinearity in the model. Hence the models fitted using Return on Assets (ROA) as dependent variable are

described below :ROA OLS

regressionWithin or Fixed Effects

Random Effects

GDP -0.03 -0.0647 -0.07NONII 37.53* 8.38* 7.73*NII 49.42* 8.61* 7.72*Loans -0.85* -0.147 -0.183Deposits 1.30* 0.126 -0.325OE -3.58* -7.865* -7.245*PC -1.54* -0.793 -1.003NOF 0.828* -0.412* -0.212CRAR -0.00003* -0.00001 -0.00002NPA -0.00005* -0.00001 -0.000014Adj R Sq. 0.74 0.49 0.52F-Statistic 971.7 358.19 362.9

Note :The Asterisk (*) sign shows that the corresponding variable is significant at 5 % level of significance.

Hausman test shows that the random model is best fitted to the data. Hence, NONII, NII and OE are coming out to be significant at 5 % level of significance.

Results shows that the higher values of NONII and NII are associated with higher values of ROA for all estimators while OE has negative impact on ROA.

Different Models Considering NIM as Profitability Indicator

Independent variables : NONII,GDP, NPA, PC, OE, NOF ,Loans, CRAR, Deposits Dependent variable. : NIM Multicollinearity in the model is removed using AIC technique. Hence the models fitted using Net Interest Margin (NIM) as dependent variable

are described below :

NIM OLS regression

Within or Fixed Effects

Random Effects

GDP 0.403* -0.0775 -0.0686NONII -70.78* -70.41* -70.39*OE 67.49* 66.89* 66.85*NPA 0.000003* 0.00012* 0.00012*Loans 3.412* -2.8617* -2.576*NOF -0.823* -1.401* -1.552*Deposits -2.93* 1.085 1.129PC -2.371 -0.282 -2.873Adj R Sq 0.99 0.994 0.99F-statistic 2.11E+05 65871.5 67735.4

Note :The Asterisk (*) sign shows that the corresponding variable is significant at 5 % level of significance.

Hausman test shows that the fixed effect model is better fitted but both the models random and fixed are providing the same results. Hence, NONII, OE, NPA, Loans and NOF are coming out to be significant at 5 % level of significance.

Result shows that the higher values of Loans, NOF and NONII leads to decrease in NIM while higher values of NPA and OE are associated with increase in NIM for all estimators.

Different Models Considering CIR as Profitability Indicator

Independent variables : NII, NONII,GDP, NPA, PC, OE, NOF ,Loans, CRAR, Deposits Dependent variable. : CIR Multicollinearity in the model is removed using AIC technique. Hence the models fitted using Cost Income Ratio (CIR) as dependent variable are

described below :

CIR OLS regression

NOF 66.7*

GDP 7.38*

NPA 0.0028*

Loans -36.27*

Deposits -51.85

Adj R Sq 0.06089

F-statistic 43.13

Note :The Asterisk (*) sign shows that the corresponding variable is significant at 5 % level of significance.

Results show that the NOF, GDP, NPA, and Loans are coming out to be significant at 5 % level of significance.

Higher values of loans results in decrease in CIR.  

On the same lines, the Comparison of Kanpur Regional Office with Other Regional Offices is done

Conclusions

The overall summary of Different Models Considering ROA, NIM and CIR as Profitability Indicators separately for Kanpur Regional office and other regional offices which includes AHM,BAN,CAL,CHA,CHE,DEL,HYD,JAI,JAM,LUC,MUM,PAT,THI is given below :

Comparison of the profitability indicators of NBFC-D of Kanpur-RO with that of the other regional offices:

Profitability Indicators

Region NONII NII Loans OE NOF CRAR NPA

ROA LUC *(+) *(+) *(-)OTHER *(+) *(+) *(-) *(-)

NIM LUC *(-) *(+) *(+)OTHER *(-) *(-) *(+) *(-)

CIR LUC *(+)OTHER *(+)ROA:

In Kanpur RO, Decrease in OE and Increase in NONII and Loans leads to increase in ROA while in other RO’s, instead of Loans, increase in NII and decrease in NPA leads to ROA’s increase.NIM:In Kanpur RO, Increase in NONII and decrease in Loans and OE leads to decrease in NIM while in other RO’s, increase in NONII, Loans and NOF and decrease in OE leads to NIM’s decrease.CIR:In Kanpur RO, decrease in CRAR leads to decrease in CIR while in other RO ’s , decrease in NPA leads to CIR’s decrease.

Conclusions(Cont..) Influential factors behind the NBFC Deposit taking

industry’s profitability:

Profitability Indicators

GDP NONII NII Loans OE NOF NPA

ROA *(+) *(+) *(-)

NIM *(-) *(-) *(+) *(-) *(+)

CIR *(+) *(-) *(+)

Fee based income i.e. Non Interest Income, Net Interest Income and Operating expenditure are main determinants of ROA.Therefore In general, For increasing Returns on Asset (ROA) , NBFCs-D may increase their lines of credit and increase their Fee based income business apart from focusing on their main line of business which will improve their Margins too if they can simultaneously control their Operating expenses (OE).

For decreasing NIM, they have to increase NONII, NOF and Loans while need to decrease OE and NPA. NBFCs -D should look for improving capital base i.e. Net Owned Fund (NOF) so that they can implement their IT infrastructure smoothly since it involves huge cost.

Increase in deployment of Loans and improvement in the Asset Quality leads to obtain a optimum level of CIR.  

Recommendations:

NBFCs should increase their NOF :NBFCs may face decline in their profitability indicators in the short run but in the longer run it will benefit them. Since introduction of new small and payment banks will increase competition in this sector catering the same customer base and will pose a tough challenge to these NBFCs.

Improvement in CRAR will lead to increase in the loss absorbing capacity of the company; increase in capital will help them in improving the market perception of their financial soundness. This may lead to ease in raising their resources and funds to shore up their NOF. With higher NOF and income, companies will be in better position to implement IT infrastructure which initially requires high cost but after reaching break even it can reduce their operation costs and thus leading to improvement in Cost to income ratios too.

Since this data is of much use subject to its reliability and availability and this study leaves room for further study in different areas of NBFI functions such as products of productivity analysis, Data Envelopment Analysis (DEA).

Limitations Although this study was carefully prepared, I am still aware

of its limitations and shortcomings.

Time Period: In this study, it would have been better if a larger time period was covered. It'd have given a better picture of the NBFCs sector in India.

The project is done on few variables affecting the profitability. There are bound to be other variables which may considerably affect the profitability of banks.

Thank You