Determining factors of profitability of NBFIs

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Determining Factors ofProfitability of NBFIs

Based on a study on 5 selected NBFIs in Bangladesh


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Determining Factors of Profitability of NBFIs

Prepared for:

Syeda Mahrufa Bashar

Course Instructor, Financial Institutions

Prepared by:

Md. Raihan Shourov [139]

Ferdous Kabir [140]

Chalan Kanti Roy [141]

Md. Mohaiminul Hasan Khan [150]

Batch MBA 46 D

Date of Submission: January 10, 2013

Institute of Business Administration

University of Dhaka

LETTER OF TRANSMITTALii


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January 10, 2013

Syeda Mahrufa BasharCourse Instructor, Financial Institutions and Markets

IBA, University of Dhaka

Subject: Submission Of Term Paper On Determining Factors Of Profitability

Of Nbfis

Dear Madam:

It is our great pleasure to submit the term paper on Determining Factors

of Profitability Of NBFIs " which is a partial requirement of Financial

Institutions and Markets course. We have found this report informative,

beneficial as well as insightful. We have tried our level best to prepare an

effective report.

We put forth our sincere efforts to study related materials, documents and

examine relevant records for preparation of the report. Within the time limit,

we have tried our best to compile the pertinent information as

comprehensively as possible and if you need any further information, you

can reach us at [email protected].

Sincerely,

Md. Raihan Shourov [139]

Ferdous Kabir [140]

Chalan Kanti Roy [141]

Md. Mohaiminul Hasan Khan [150]

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mailto:[email protected]:[email protected]


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ACKNOWLEDGEMENT

This term paper has been prepared through continual assistance and guidelines from several

generous minds without whom this report completion would have been unreachable.

First of all, we would like to thank and give our attribute to our honorable course instructor

Syeda Mahrufa Bashar, who has been very much friendly and approachable to us through the

course and has given us, a lot of guidance in the preparation of our term paper.

We would also like to express our appreciation to the people, who have helped all through the

term paper. We also like to thank our all group members who were very much friendly and

sincere to complete this term paper properly. However, we hope that this course as well as this

term paper experience will help us to build our career in a successful and precise way in this

area.

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Table of Contents

TABLE OF CONTENTS .................................................................... V

EXECUTIVE SUMMARY ................................................................. VII

1. INTRODUCTION ......................................................................... 1

1.1 BACKGROUND OF THE STUDY ................................................... 1

1.2 RATIONALE OF THE STUDY ....................................................... 1

1.3 OBJECTIVES OF THE STUDY ...................................................... 2

1.4 METHODOLOGY ....................................................................... 2

1.4.1 Data, sample and period under study ........................................................ 2

1.4.2 Data Analysis ............................................................................................ 2

1.5 SCOPE OF THE STUDY .............................................................. 3

1.6 LIMITATIONS ........................................................................... 3

2. LITERATURE REVIEW ................................................................. 4

3.1 NON-BANK FINANCIAL INSTITUTIONS IN BANGLADESH ............... 6

3.2 SERVICES PROVIDED ................................................................ 6

3.3 CLASSIFICATION ...................................................................... 6

3.4 DATA SOURCE AND ANALYSIS FRAMEWORK .............................. 7

3.4.1 Dependent Variable ................................................................................... 7

3.4.2 Independent Variables ............................................................................... 7

3.4.3 Variables Summary: .................................................................................. 9

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3.5 HYPOTHESES ......................................................................... 10

4. ANALYSIS ............................................................................... 11

4.1 Descriptive Statistics .................................................................................. 11

4.2 Correlation

....................................................................................................................... 12

4.3 Regression Result ...................................................................................... 13

4.3.1 Analysis Process: .......................................................................................................13

4.4 Simple Regression Analysis .....................................................................................14

4.5 Multiple Regression Analysis ....................................................................................17

4.6 Findings & Interpretation: ........................................................................... 20

5. CONCLUDING REMARKS ........................................................... 21

6. REFERENCES ........................................................................... 22

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EXECUTIVE SUMMARY

The FI (Financial Institutions) sector is considered to be an important source of financing for all

over the world. The contribution of this industry towards the economy has been enhanceddramatically and investors are also recognizing this to be a promising one. So, the profitability of

this sector is also getting much attention among the stakeholders in recent times.

The objective of this study is to find out the major financial features affecting the profitability

(ROE) in the Non-bank Financial Institutions (NBFI) industry of Bangladesh, to spot out the

most influential factor behind the NBFI industrys profitability and to evaluate the aspects. The

data was collected for five different NBFIs for a period of over five years (2007-2011). For

analysis we used Microsoft Excel 2010. In the analysis, we defined ROE as the dependent

variable and the independent variables are-natural log of total asset (firm size), equity capital to

total asset ratio(capital adequacy), total loan to total asset ratio (asset quality), total deposit tototal asset ratio (deposit financing), loan provision to average total loan ratio (credit risk),

noninterest income to average total asset ratio (noninterest income), operating expenses to

average total asset ratio (management efficiency), net interest margin to average total asset ratio

(interest income) etc. In the analysis, we have conducted correlation matrix, simple regression

and multiple regression along with descriptive statistics.

There were a number of limitations to this study one of them being multicollinearity. To test how

much it affected the results, we made a correlation matrix among all the independent variables

and pointed out six major correlations which could hamper the multiple regression results.

However, we still progressed with the report assuming that the multicollinearity was not thatsevere.

The factors that were found and the ratios used to determine those factors are discussed in details

in Table 01 and the multiple regression model provided as well. From these we devised eight

hypotheses tests in total and continued to find a significant relationship between the dependent

and respective independent variables. The analysis was carried out with the t-test and the p-value

analysis simultaneously with a 95% confidence level. Among the eight factors four were found

to have a significant relationship with ROE based on the simple linear regression. However, in

the multiple regression analysis we find that two out of those four have a significant relationship.

Thus, we have concluded that those two factors, namely Capital Adequacy and Non-interest

Income are reliable indicators to consider during management decisions which would have a

considerable impact on ROE. This is further supported by the fact that a high capital takes down

the equity multiplier in value, thus, the return on equity also goes down whereas noninterest

income should increase the ROE.

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1. INTRODUCTION

1.1 BACKGROUND OF THE STUDYThe financial system is the ultimate engine for achieving economic prosperity of a country, andis involved in the mobilization of financial resources from the surplus to the deficit sector.

Primarily the major responsibility is assigned to banks for the channelization of funds in most of

the countries, particularly in developing countries. As the development process proceeds, NBFIs

become prominent alongside the banking sector. Both can play significant roles in influencing

and mobilizing savings for investment. Their involvement in the process generally makes them

competitors as they try to cater to the same needs. However, they are also complementary to each

other as each can develop its own niche, and thus may venture into an area where the other may

not, which ultimately strengthens the financial mobility of both.

In addition, the development of both banks and non-bank financial institutions (henceforthNBFIs) are necessary for assuring a strong and stable financial system for the country as a

whole. In addition, NBFIs add power to the economy in such a way that enhances the resilience

of the financial system to economic crisis. Non-Bank Financial Institutions (NBFIs) play a

significant role in meeting the diverse financial needs of various sectors of an economy and thus

contribute to the economic development of the country as well as to the deepening of the

countrys financial system.

The importance of NBFIs can be emphasized from the structure of the financial system. In the

financial system of Bangladesh, commercial banks have emerged in a dominant role in

mobilizing funds and using these resources for investment. Due to their structural limitations and

rigidity of different regulations, banks could not expand their operations in all expected areas and

were confined to a relatively limited sphere of financial services. Moreover, their efforts to meet

long term financing with short term resources may result in asset-liability mismatch, which can

create pressure on their financial base. They also could not broaden their operational horizon

appreciably by offering new and innovative financial products. These drawbacks led to the

emergence of NBFIs in Bangladesh for supporting industrialization and economic growth of the

country.

1.2 RATIONALE OF THE STUDYThe FI (Financial Institutions) sector is considered to be an important source of financing for all

over the world. The common assumption is that growing financial performance will lead to

better functions and actions of the organizations. In most of the cases, whenever we refer to

Financial Sector, we actually mean the banking sector. In reality, now-a days, the NBFI (Non-

Banking Financial Institution) has also become one of the most prospective sectors in

Bangladesh. The contribution of this industry towards the economy has been enhanced

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dramatically and investors are also recognizing this to be a promising one. So, the profitability of

this sector is also getting much attention among the stakeholders in recent times. Plenty of

research works have been conducted on the banking sector for identifying its profitability

determinates. But no major work has been done in the NBFI sector yet. So, in this paper we are

asserting an endeavor to conduct a study for determining profitability indicators of NBFI sector.

1.3 OBJECTIVES OF THE STUDY

1. To find out the major financial features affecting the profitability in the Non-bank

Financial Institutions (NBFI) industry of Bangladesh.

2. To spot out the most influential factor behind the NBFI industrys profitability.

3. To evaluate the aspects and make a recommendation based on that to enhance the sectorsprosperity.

1.4 METHODOLOGYThe study is empirical in nature that covers a number of variables. Among these Profitability

which is indicated by ROE (Return on Equity) is considered as the dependent variable. On the

other hand, the independent variables are natural log of total asset (firm size), equity capital to

total asset ratio(capital adequacy), total loan to total asset ratio (asset quality), total deposit to

total asset ratio (deposit financing), loan provision to average total loan ratio (credit risk),noninterest income to average total asset ratio (noninterest income), operating expenses to

average total asset ratio (management efficiency), net interest margin to average total asset ratio

(interest income) etc. We have considered the relative figures rather than absolute figures in

calculation.

1.4.1 Data, sample and period under study

The study is essentially based on the secondary data collected from annual report of the

concerned Non-bank Financial Institutions (NBFI). Information from books, journals and online

publications produced by academicians were abundantly used. In Bangladesh, currently 32

NBFIs are operating in full fledge. So, we used the whole population for pursuing the study andfrom therein we have selected 5 NBFIs through convenient sampling.

The data was taken from five different financial institutions for a period of five years, 2007

2011. All financial data are denominated in terms of Bangladeshi Taka.

1.4.2 Data Analysis

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To observe the issues determining profitability, statistical tools such as correlation, simple

regression, and multiple regression have been used as deemed appropriate. The statistical tests

have been executed by using the Microsoft Excel 2010.

1.5 SCOPE OF THE STUDYThe report has been designed to address the factors determining the profitability of non bank

financial institutions. For this particular case, we are only focusing on the ROE of the

institutions. We have primarily chosen five NBFIs for collecting information. They are Industrial

Promotion and Development Company of Bangladesh Ltd (IPDC), Industrial Development

leasing Company of Bangladesh Ltd (IDLC), United Leasing Company Ltd (ULC), Lank Bangla

Finance Company Ltd. and Industrial and Infrastructure Development Finance Company Ltd

(IIDFC). However, the list may change depending on the quality of the data collected as we will

try to The study has been conducted by using the data of 5 NBFIs between the periods of 2007 to

2011.

1.6 LIMITATIONSMajor limitation of this study is insufficiency of accessible data, the main sources of

which are the annual reports of the non banks. In annual reports, companies usually give stress

on the information that generate affirmative intuition about the company and present the

information in their own way, which may become a chief limitation in illustrating the precise

scenario of authenticity. Moreover, though there has been an ample amount of researches

regarding the bank sectors profitability but no substantial work has so far been done in

Bangladesh on the determinants of profitability of NBFIs. So there is a scarcity of literature

in this arena. Morever, we could not break down the data given in the annual report due such as

noninterest income because the annual reports were concise. On the other hand, our sample size

is very small which may have led us to inappropriate conclusion and the impact of competition

from commercial banks was left out in the analysis.

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2. LITERATURE REVIEWTo get an insight of profitability indicators, several studies have been executed up to till date. Butthe fact suggests that, most of the researches have been conducted on banking industry. So, the

evidence with regard to profitability is scarce in the NBFI sector. Also, the studies have been on

topics which bring about a number of other variables on analyzing the return, thus, a single paper

on the studies of ROE of NBFIs has been found. However, the following shows the category and

span of research which have been done on peripheral topics related to return on equity.

Sayla (2012) in Capital Structure Determinants of Non-Bank Financial Institutions (NBFIs) in

Bangladesh tried to relate capital structure decision with several variables including

profitability, liquidity, operating leverage, growth rate, firm size etc. She used long term debtratios, short term debt ratios and total debt ratios as the measures of the dependent variable i.e.

capital structure. The finding was profitability ratio is insignificant in all the three cases of long

term debt ratio, short term debt ratio. And also does not comply with the hypothesis that

profitability has a negative relation with debt ratio in case of long term and total debt ratio.

However profitability has a negative relation to short term debt complying with hypothesis

though the result is statistically insignificant.

Ahmed and Chowdhury (2007) stated in their paper Non-Bank Financial Institutions in

Bangladesh: An Analytical Review that commercial banks of the country are engaged in non-

bank finance activities within the existing banking rules, which is posing difficulties for non-bank financial institutions. While assessing the development and performance of NBFIs in

Bangladesh, Hossain and Shahiduzzaman stated that the performance of the NBFIs in leasing

business suggests that the industry can be growing up in a sustainable basis and they should

concentrate more on their activities in the capital market. However, at present, with high cost of

fund non-banks are forced to compete with the banks those have relatively low cost of fund. This

situation somewhat hampers the growth and development of NBFIs.

According to the analysis Non-Bank Financial Institutions Profitability Indicators: Evidence

from Bangladesh by Rahman and Farah (2012) it is clear that the chosen (Operating Efficiency,

Capital Structure, Fixed Charges and Income, Liquidity Position) profitability indicator variableshave impact upon net profit, but among the independent variables the Liquidity Condition and

Operating Efficiency exert significant influence on Profitability of Non-Bank sector in

Bangladesh.

Financial stability report (2010) of Bangladesh Bank reported increasing ROA and ROE ratios of

the then NBFIs from 2006 to 2010 which they claim the consequence of better utilization of

assets and equity. Moreover, A decomposition of the sources of total income shows that the

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dominant contribution is on account of interest income from traditional business, which lendsto

higher profitability.

The empirical findings of the study of banks profitability by Sufian and Chong (2008) suggest

that all the bank-specific determinant variables have a statistically significantly impact on the

profitability of the Philippines banks. During the period under study, the results suggest that size,

credit risk, and overhead expenses are negatively related to bank profitability, while non-interest

income and capitalisation have a positive impact. The empirical findings seem to suggest that the

rate of inflation is negatively related to Philippines banks' profitability level suggesting that

during the period under study the level of inflation was unanticipated by banks. On the other

hand, economic growth, the growth in the money supply, and the level of stock market

capitalisation have not significantly explained the variations in the profitability of the Philippines

banks.

Gul, Irshad and Zaman stated that individual bank characteristics (internal and external factors)

are considered as determinants of bank profitability in Pakistan. Banks with more equity capital,

Total Assets, Loans, Deposits and macro factors i.e., economic growth, inflation and stockmarket capitalization are perceived to have more safety and such an advantage can be translated

into higher profitability. For this purpose, two hypotheses have been developed for analyzing

banks profitability over specific determinants i.e., Hypothesis 1 states that microeconomic

factors have significant impact on profitability. Whereas, hypothesis 2 states that external factors

of the banks have significant impact on the profitability. The result shows that both hypotheses

have been accepted and have a significant impact on profitability of the Banks in Pakistan.

The study by Saklain (2012) of commercial banks profitability in Bangladesh identified that

asset size does not have a significant effect on profitability. It suggests that to achieve a higher

level of ROA it is not always necessary to be a larger bank. Interest income is always considered

to be the main source of income of a bank, but in the study it is found that NIM/assets ratio doesnot have a significant impact on profitability. But the most significant variable which affects the

profitability was found to be the non-interest income/assets ratio. This indicates that greater

diversification in banking activities positively influence profitability. It is also identified that

investment activities, mainly in shares and debentures (quoted and unquoted) of private sectors

has a significant positive impact on ROA. It suggests that banks which are more exposed to the

capital market or invest higher proportion of funds in unquoted shares and debenture may

achieve higher profitability.

Hifza Malik (2011) used ROA and five independent variables that represent age of company,

size, volume of capital, leverage and loss ratio to test which factor best explains profitability of

Pakistani insurance companies. Result shows that there is no relationship between profitability

and age of the company and there is significantly positive relationship between profitability and

size. Result also shows that volume of capital was significantly and positively related to

profitability. On the other hand the analysis suggests that a reverse and significant relationship

between leverage ratio and loss ratio as independent variables and profitability so this result

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supports last two hypotheses. Hence it is concluded that ROA is affected positively by size,

volume of capital and negatively by leverage and loss ratio.

3.1 NON-BANK FINANCIAL INSTITUTIONS IN BANGLADESHNon-Bank Financial Institutions (NBFIs) are licensed and regulated under the Financial

Institution Act, 1993. NBFIs play an important role in financing various sectors like

industry, trade, housing, transport, information technology as well as the capital market.

There are 30 NBFIs in the country. As on 30th September, 2011 there are 158 branches

of which 60 in Dhaka, 22 in Chittagong and the rest 76 in other districts. As on 30th June,

2011 the total amount of capital and reserve of the NBFIs stood at BDT 51726.32 million. Total

assets and total deposits of the NBFIs were BDT 273424.38 million and BDT 106276.19million respectively. Total outstanding loans and leases of the NBFIs was BDT 190398.6

million. Major sources of funds of NBFIs are Term Deposit, Credit Facility from Banks and

other NBFIs, Call Money as well as Bond and Securitization. NBFIs are allowed to

mobilize term deposit only of tenor not less than six months.

3.2 SERVICES PROVIDEDNBFIs offer all sorts of banking services, such as loans and credit facilities, private education

funding, retirement planning, trading in money markets, underwriting stocks and shares, TFCs

and other obligations. These institutions also provide wealth management such as managingportfolios of stocks and shares, discounting services e.g. discounting of instruments and advice

on merger and acquisition activities. The number of non-banking financial companies has

expanded greatly in the last several years as venture capital companies, retail and industrial

companies have entered the lending business. Non-bank institutions also frequently support

investments in property and prepare feasibility, market or industry studies for

companies.However they are typically not allowed to take deposits from the general public and

have to find other means of funding their operations such as issuing debt instruments.

3.3 CLASSIFICATIONDepending upon their nature of activities, non- banking finance companies can be classified into

the following categories:

1. Development finance institutions

2. Leasing companies

3. Investment companies

4. Mudaraba companies

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5. House finance companies

6. Venture capital companies

7. Discount & guarantee houses

3.4 DATA SOURCE AND ANALYSIS FRAMEWORKTo analyze the determinants of the profitability of nonbank financial institutions 8 variables are

included in this study, one of them are the dependent and the others are as explanatory or

independent variables.

3.4.1 Dependent Variable

ROE measures the rate of return on the ownership interest (shareholders equity) of the

common stock owners. It measures a firms efficiency at generating profits from every

unit of shareholders equity (also known as net assets or assets minus liabilities). It

shows how well a company uses investment funds to generate earnings growth.

3.4.2 Independent Variables

By reviewing several literatures it is found that several researchers identified some common

factors which influence profitability of a bank. Since NBFIs and commercials banks have almost

similar type of operation, factors affecting profitability should be similar for these two types of

businesses. So we included the following bank specific variables to capture the determinants of

profitability of the NBFIs:

Asset Size(Firm Size) is used to capture the fact that larger institutions are better placed

than smaller institutions in harnessing economies of scale in transactions to the plaineffect that they will tend to enjoy a higher level of profits. Consequently, a positive

relationship is expected between size and profits. However, the effect of a growing

banks size on profitability may be positive up to a certain limit. Beyond this point the

effect of size could be negative due to bureaucratic and other reasons. Generally natural

logarithm of total asset (ln A) is used to represent firm size.

Equity capital (Capital Adequacy) has been measured by the ratio of equity capital to

total assets. Its interesting to note that higher the capital level breeds higher profitability

level since by having more capital, an institution has excess capital that can be provided

as loans. In other words, the higher this ratio, the lower the need for external funding and

thus leads to the higher profitability of the bank. Equity to total assets ratio is expected to

have positive relation with performance of the NBFI.

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Loans (Asset Quality) has been addressed by using loans to total assets ratio. As loans is

one of the main sources of income of an NBFI, the ratio of loans to total assets is

expected to affect profitability positively unless an unacceptable level of risk is taken by

an NBFI. Other things constant, the more deposits are transformed into loans, the

higher the interest margin and profits. However, if a financial institution needs to

increase risk to have a higher loan-to-asset ratio, then profits may decrease.

Deposits (Deposit Financing) has been measured by the ratio of total deposits to total

assets which is another liquidity indicator but is considered as a liability. Deposits

are the main source of NBFIs funding and hence it has an impact on the profitability.

The more deposits are transformed into loans, the higher the interest margin and profit.

Hence, deposits generally have positive impact on profitability of the banks. But if a

bank cant transform its deposits into loans efficiently it may bring negative impact on

profitability also.

Loan Provision (Credit Risk) has been measured by the ratio of Loan Loss Provisions

to average Total Loans which shows us how much of the loans have a reserve for a loan

loss. This, in turn, gives us the credit risk of the company as a higher ratio means more

provision for absorbing a loss and vice versa. The coefficient of LLP/TL is expected to

be negative because bad loans are expected to reduce profitability.

Non Interest Income has been measured by the ratio of Non-interest Income to averageTotal Assets. Non-interest income consists of commission, service charges, and fees,

guarantee fees, net profit from sale of investment securities etc. The ratio is also included

in the regression model as a proxy measure of diversification into non-traditional

activities. The variable is expected to exhibit positive relationship with NBFI

profitability.

Operating Expenses (Management Efficiency) has been measured by the ratio of Non-

interest expense to average Total Assets. This measures how efficient the management is

to minimize non-interest expense while working with assets. The relationship between

the NIE/TA variable and profitability levels may be negative.

Net Interest Margin ( Interest Income ) has been measured by the difference between

the interest income generated by the financial institutions and the amount of interest paid

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out to their lenders (for example, deposits), relative to the amount of their assets. It is

similar to the gross margin of non-financial companies. The NIM variable is defined as

the net interest income divided by average total assets. NIM is focused on the profit

earned on interest activities. A positive relationship is expected between net interest

margin and ROE of an NBFI.

3.4.3 Variables Summary:

Factor Variable Measurement Notation

Dependent

Variable

Profitability ROE Return on Equity = Net

Profit/Average Equity

ROE

Independent

Variables

Firm Size Asset Size Natural Logarithm of Total

Assets

lnA

CapitalAdequacy

Equity capital Equity/Total Assets CA

Asset Quality Loan Loans/Total Assets LA

Deposit

Financing

Deposit Deposits/Total Assets DP

Credit Risk Loan

Provision

Loan-Loss Provisions/ Avg.

Total Loans

CR

Non-interestIncome

Non-interestIncome

Non-Interest Income/ Avg.Total Assets

NII

Management

Efficiency

Operating

Expenses

Non-interest Expense/ Avg.

Total Assets

NIE

Interest Income Net Interest

Margin

(Interest Income Interest

Expense)/Avg. Total Assets

NIM

Table - 01

So our profitability model would be as follows:

ROE = 0 + 1lnA + 2CA + 3LA + 4DP + 5CR + 6NII + 7NIE + 8NIM +

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3.5 HYPOTHESESThe objective of the study is to find out the relationship between the above mentioned variables

as well as the factors that they represent with the institutions profitability, in this case, ROE.

Thus the following hypotheses were formed:

H1: There is a significant relationship between ASSET SIZE and NBFIs profitability.

H2: There is a significant relationship between EQUITY CAPITAL and NBFIs profitability.

H3: There is a significant relationship between LOANS and NBFIs profitability.

H4: There is a significant relationship between DEPOSITS and NBFIs profitability.

H5: There is a significant relationship between LOAN PROVISION and NBFIs profitability.

H6: There is a significant relationship between NON-INTEREST INCOME and NBFIs

profitability.

H7: There is a significant relationship between OPERATING EXPENSES and NBFIs

profitability.

H8: There is a significant relationship between NET INTEREST MARGIN and NBFIs

profitability.

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Note: The independent factors used on the above hypotheses are discussed in the previous section in

details.

4. ANALYSISThis section deals with the results of the study which include the descriptive statistics,

correlation, simple and multiple regressions, which are relevant for the study. In this section, an

attempt has been done to find out the associations between profitability and performanceindicating variables with assistance of few statistical tools.

At first, a simple regression model is executed with each of the independent explainers. In the

second part of analysis, the investigation has been done through multiple regression models. The

dependent and independent factors are kept the same as the simple regression model.

4.1 Descriptive Statistics

The basic descriptive statistics of the variables are presented in Table 2. For each variable, the

table shows mean, median, standard deviation, minimum and maximum value from 2007 to 2011

of five non bank financial institutions of Bangladesh.

ROE SizeEquity

CapitalLoan Deposit

Loan

Provisi

on

Non

Interest

Income

Operatin

g

Expenses

Net

Interest

Margin

Mean 22.04% 22.95 15.49% 49.65% 42.94% 1.01% 2.49% 2.10% 4.24%

Median 14.70% 22.89 13.10% 49.34% 40.67% 0.89% 1.98% 1.88% 3.42%

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Standard

Deviation15.08% 0.60 7.66% 17.01% 9.98% 0.78% 1.86% 0.86% 2.29%

Minimum 2.60% 21.50 6.25% 21.69% 18.91% -0.48% 0.31% 1.24% 1.14%

Maximum 59.68% 24.16 29.45% 87.76% 63.36% 2.85% 6.60% 5.06% 10.46%Table 2

On average, those NBFIs have a return on equity (ROE) of 22.04%. The ROE varies greatly

across different NBFIs as the standard deviation is 15.08% and also the minimum and maximum

values are 2.60% and 59.68%. Asset size has been determined by the natural logarithm of Total

Asset the mean of which is 22.95 and standard deviation is 0.60 which indicates that all the

NBFIs have almost same size. Capital adequacy, asset quality and deposit-these variables are

widely dispersed around the mean and their ranges also support this observation. It means that

the NBFIs have engaged in various combinations of capital structure to finance their operation.

As a result, their earning distribution (ROE) and interest spread would vary accordingly. If we

see that Net Interest Margin we find the support of this observation since NIM is widely

dispersed. Operating expenses of the NBFIs is represented by management efficiency in this

table which has a lower standard deviation than that of other variables but still it has a long range

in the data set. Credit risk i.e. loan loss provision has a lower mean of 1.01% for the NBFIs

which is certainly a good thing for profitability but it has a standard deviation of .78% which is

moderately high. Non-interest income represents the level of diversification the NBFI is engaged

in. Since NBFIs by definition, should have different types of businesses including investments,

leasing, consultancy, underwriting, issue management etc. and income from these businesses

should be significant. In the table, this income has a mean and standard deviation of 2.49% and

1.86% respectively. The standard deviation shows that all the NBFIs do not invest in and receive

from investments other than lending in the same proportion of their asset base. Still NIM has a

higher mean than that of non-interest income which means that NBFIs in Bangladesh relyheavily on lending in their asset portfolio.

4.2 Correlation

ROE SizeEquity

CapitalLoan

Deposi

t

Loan

Provisio

n

Non

Interest

Income

Operatin

g

Expenses

Net

Interest

Margin

ROE 1.00

Size 0.19 1.00

EquityCapital -0.48 -0.52 1.00

Loan 0.46 0.18 -0.12 1.00

Deposit -0.23 0.34 0.02 -0.16 1.00

Loanprovision 0.29 -0.58 0.11 0.22 -0.47 1.00

Non Interest

Income 0.71 0.20 -0.22 0.80 -0.29 0.18 1.00

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Operating

Expenses 0.42 -0.15 0.06 0.57 -0.10 0.37 0.54 1.00

Net Interest

Margin 0.16 -0.30 0.17 0.02 0.09 0.50 -0.08 0.65 1.00Table 3

From the table, we can see that ROE has positive correlation with size, asset quality (loans),

credit risk (loan loss provision), noninterest income, operating expenses and net interest margin.

All of these were expected except the correlation with loan provision and operating expenses.

But high operating expenses may be associated with increased businesses and this relationship is

moderate. Non-interest income has strong (.71) relationship with the ROE whereas net interest

margin has a weak relationship (.16).

On the other hand, ROE has negative relation with capital adequacy and deposits. Deposits are

liabilities but have the lowest cost. However, if the deposits are not turned into loans effectively

then expenses will be higher than the income from the deposit, as a result a negative relationship

is possible. High equity capital means high capital adequacy which needs lower external funding

so profitability should increase but increase in equity might also dilute the ROE because increase

in equity (denominator) might offset the increase in income (numerator).

The correlation matrix between the variables is shown below in Table 3. The matrix shows that

there are a few moderately strong correlations among the independent variables as we see that

the absolute values are greater than 0.5 (less than .80) in only a few cases. Therefore, we can

conclude that multicollinearity problem is not extremely severe for this scenario.

If we consider the .50 as moderate or strong correlation we find 4 variables that have moderate or

strong correlation with ROE.

The variables are:

Correlation

Equity Capital -0.48

Loan 0.46

Non Interest Income0.71

Operating expenses 0.42

4.3 Regression Result

4.3.1 Analysis Process:

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1. R2 (coefficient of determination)-refers to what percent variability in the dependent

variables can be explained by variability in the independent variables. R2 equal to 50% or

more will indicate reliable relationship.

2. Significance F (P-value of the F-test)- will tell about fitness or validity of the whole

model.

Decision Rule: If p-value > .05 (level of significance), do not reject null hypothesis.

3. Individual P-value (t test)- will tell about the variable of an individual variable in the

model.

Decision Rule: If p-value > .05 (level of significance), do not reject null hypothesis.

4. Since in the simple regression there is only on independent variable, so significance F

and P-value will be same which is not in case of multiple regression.

4.4 Simple Regression Analysis

The outputs of regression are summarized in the following table:

Dependent

Variable Independent Variable Equation r2 t-test

P value

of test

Profitabilit

y (ROE)

Size ROE = -88.11 + 4.79SZ 0.0366 0.9345 0.3598

Equity Capital ROE = 36.74 - 94.84CA 0.2322 -2.6373 0.0147

Loan ROE = 1.83 + 40.72AQ 0.2109 2.4793 0.0209

Deposit ROE = 36.89 -34.57DP 0.0524 -1.1273 0.2712

Loan Provision ROE = 16.29 + 567.72CR 0.0868 1.4784 0.1529

Noninterest Income ROE = 7.7 + 576.23DV 0.5046 4.8404 0.0001

Operating Expenses ROE = 6.63 + 734.15ME 0.1757 2.2141 0.0370

Net interest marginROE = 17.46 +108.15NIM 0.0269 0.7966 0.4338

4.4.1 Hypothesis Test

H1: There is a significant relationship between SIZE and NBFIs profitability.

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The Model

ROE = -88.11 + 4.79SZ

The r2 value of 0.0365797 suggests that 3.66% variability in ROE is explained by the variability

of the firm size as measured by the natural log of total asset which would make us depend less on

the results. A low t-value of 0.93 and a high p-value of 0.35(higher than .05) suggest that weshould not reject the null hypothesis, thus, we can conclude that we find no significant

relationship between the size of the firm and its return on equity.

H2: There is a significant relationship between Equity Capital and NBFIs profitability.

The Model

ROE = 36.74 - 94.84CA

The r2 value of 0.2321 suggests that 23.21% variability in ROE is explained by the variability of

the capital adequacy as measured by the equity capital to total asset. The p-value (.0147) is less

than level of significance (.05) which suggests us to reject the null hypothesis. Thus, we can

conclude that there is a significant relationship between equity capital and NBFIs profitability as

measured by its ROE.

H3: There is a significant relationship between loan and NBFIs profitability.

The Model

ROE = 1.83 + 40.72AQ


the asset quality as measured by the total loan to total asset. The p-value (.0209) is less than level

of significance (.05) which suggests us to reject the null hypothesis. Thus, we can conclude that

there is a significant relationship between loan and NBFIs profitability as measured by its ROE.

H4: There is a significant relationship between DEPOSIT and NBFIs profitability.

The Model

ROE = 36.89 -34.57DP


the asset quality as measured by the total loan to total asset. The p-value (.2712) is higher than

level of significance (.05) which suggests us to not reject the null hypothesis. Thus, we cannotconclude that there is a significant relationship between deposit and NBFIs profitability as

measured by its ROE.

H5: There is a significant relationship between loan provision and NBFIs profitability.

The Model

ROE = 16.29 + 567.72CR

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The r2 value of .0868 suggests that 8.68% variability in ROE is explained by the variability of the

credit risk as measured by the loan loss provision to total loans. The p-value (.1529) is higher

than level of significance (.05) which suggests us to not reject the null hypothesis. Thus, we

cannot conclude that there is a significant relationship between loan provision and NBFIs

profitability as measured by its ROE.

H6: There is a significant relationship between Non Interest Income and NBFIs profitability.

The Model

ROE = 7.7 + 576.23DV

The r2 value of .5046 suggests that 50.46% variability in ROE is explained by the variability of

the diversification measured by the noninterest income to average total asset. The p-value

(.0001) is lower than level of significance (.05) which suggests us to reject the null hypothesis.

Thus, we can conclude that there is a significant relationship between noninterest income and

NBFIs profitability as measured by its ROE.

H7: There is a significant relationship between operating expenses and NBFIs profitability.

The Model

ROE = 6.63 + 734.15ME

The r2 value of 0.1757 suggests that 17.57%. variability in ROE is explained by the variability of

the management efficiency measured by the operating expenses to average total asset. The p-

value (.0370) is lower than level of significance (.05) which suggests us to reject the null

hypothesis. Thus, we can conclude that there is a significant relationship between operating

expenses and NBFIs profitability as measured by its ROE.

H8: There is a significant relationship between Net Interest Margin and NBFIs profitability.

The Model

ROE = 17.46 + 108.15NIM


the net interest margin as measured by the net interest income to average total asset. The p-value

(.4338) is higher than level of significance (.05) which suggests us to not reject the null

hypothesis. Thus, we cannot conclude that there is a significant relationship between net interest

margin and NBFIs profitability as measured by its ROE.

4.4.2 Summary:

Variable R 2 (Reliability) Significance

Level

P-

value

Null

Hypothesis

Observation

Asset Size 3.66% (Very .05 0.3598 Do not Reject No significant

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Low) relationship

Equity capital 23.22% (Low) .05 0.0147 Reject Significant

relationship

Loan 21.09% (Low) .05 0.0209 Reject Significant

relationship

Deposit 5.24%

(Very Low)

.05 0.2712 Do not Reject No Significant

relationship

Loan Loss

Provision

8.68%(Very

Low)


relationship

Non-interest

income

50.46%

(Moderate)

.05 0.0001 Reject Significant

relationship

Operatingexpenses

17.57%

( Low)

.05 0.0370 Reject Significantrelationship

Net interest

margin

2.69%

(Very Low)


relationship

Out of the 8 variables, we find that only 4 of them have Significant relationship with ROE

(profitability). Moreover, only one of these 8 variables i.e. noninterest income has moderate r2.

Others have very low or low r2

which reduces the reliability of the relation. However, among theremaining 7 variables, 3 found to have Significant relationship with ROE.

4.5 Multiple Regression Analysis

By using our selected 8 performance indicating variables, multiple regression analysis in

Microsoft Excel 2010has been executed. We have got the following model for multiple

regressions:

SUMMARY

OUTPUT

Regression Statistics

Multiple R 0.87204428

R Square 0.760461226

Adjusted R Square 0.64069184

Standard Error 9.040150501

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Observations 25

In the multiple regression result, we can see that r2 is 76.05% which indicates that 76.05%

variability in the ROE can be explained by variability in the 8 independent variables. This value

is strong enough to rely on. The adjusted r2 (adjusted to number of independent variables) is

64.07% which is also reliable. As a result, we will proceed with the result.

In multiple regression, our goal is find out the relationship between the dependent variable and

the entire set of independent variables.

Thus our hypothesis:

H9 : There is significant relationship between dependent variable and at least one of the

independent variables.

ANOVA

df SS MS F Significance

F

Regression 8 4151.189487

518.898685

8

6.34937897

3 0.000874478

Residual 16 1307.589137

81.7243210

8

Total 24 5458.778624

From the ANOVA table, we find that the p-value of F-test (.001) is less than .05, so we reject

null hypothesis and can conclude that there is a significant relationship between dependent

variable and at least one of the independent variables.

CoefficientsStandardError t Stat P-value

Intercept 37.6490 127.8714 0.2944 0.7722

Size -0.7416 5.4894 -0.1351 0.8942

Equity Capital -71.8335 30.2846 -2.3719 0.0306

Loan -21.3865 21.0108 -1.0179 0.3239

Deposit -1.0092 24.6737 -0.0409 0.9679

Loan Provision 100.5224 472.7568 0.2126 0.8343

Non interest

Income 855.9066 214.2377 3.9951 0.0010

Operating

Expenses -626.6803 568.2787 -1.1028 0.2864Net interest margin 340.4572 202.0212 1.6853 0.1113

The following model shows us how we have setup our multiple regression analysis.

ROE = 37.65 0.74logA 71.83CA 21.38NPL 1.01DP + 100.52CR + 855.90NII

626.68NIE + 340.45NIM +

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Now, we will go through the individual hypothesis:

Asset Size: P-value (.8942) higher than .05. So, do not reject null hypothesis and we

cannot conclude there is significant relationship between asset size and ROE.

Equity Capital: P-value (.0306) less than .05. So, reject null hypothesis and we canconclude there is significant relationship between equity capital and ROE.

Loan: P-value (.3239) is higher than .05. So, do not reject null hypothesis and we can

conclude there is no significant relationship between loan and ROE.

Deposit: P-value (.9679) is higher than .05. So, do not reject null hypothesis and we can

conclude there is no significant relationship between deposit and ROE.

Loan loss Provision: P-value (.8343) is higher than .05. So, do not reject null hypothesis

and we can conclude there is no significant relationship between loan loss provision and

ROE.

Non-interest Income: P-value (.0010) is lower than .05. So, reject null hypothesis and

we can conclude there is significant relationship between noninterest income and ROE.

Operating expenses: P-value (.2864) is higher than .05. So, do not reject null hypothesis

and we can conclude there is no significant relationship between operating expenses and

ROE.

Net Interest Margin: P-value (.1113) is higher than .05. So, do not reject null hypothesis

and we can conclude there is no significant relationship between net interest margin and

ROE.

4.5.1 Summary:

Here, R2 = 76.05% (strong) which increases the reliability of the model. On the other hand,

validity of the whole model is justified by the fact that significance F (0.000874478) is less than .

05.

Variable Significance Level P-value Null Hypothesis Observation

Asset Size .05 0.8942 Do not Reject No Significant relationship

Equity capital .05 0.0306 Reject Significant relationship

Loan .05 0.3239 Do not Reject No Significant relationship

Deposit .05 0.9679 Do not Reject No Significant relationship

Loan Loss Provision .05 0.8343 Do not Reject No Significant relationship

Non-interest income .05 0.0010 Reject Significant relationship

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Operating expenses .05 0.2864 Do not Reject No Significant relationship

Net interest margin .05 0.1113 Do not Reject No Significant relationship

From the results, we can see that only equity capital and noninterest income have Significant

relationship with ROE. For non-interest income the result was same in simple regression. Forequity capital, the result was also same in simple regression but r2 was low (23.22%).

4.6 Findings & Interpretation:

Variable Correlation Matrix Simple Regression Multiple Regression

Observation Sign/Slope Observation Sign/Slope Observation Sign/slope

Equity

Capital

-0.48 Negative Significant

Relationship

- 94.84 Significant

Relationship

-71.8335

Loan 0.46 Positive Significant

Relationship

+ 40.72 No Significant

relationship

-21.3865

Non Interest

Income

0.71 Positive Significant

Relationship

+ 576.23 Significant

Relationship

855.9066

Operating

expenses

0.42 Positive Direct

Relationship

+ 734.15 No Significant

relationship

-626.6803

Based on correlation matrix, above mentioned four variables have high correlation with

ROE and among these, capital adequacy is negatively correlated with ROE.

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and simple regression, equity capital is negatively related with the ROE. It is obvious from the

fact that if equity capital increases then the denominator in ROE increases which ultimately

reduces the ROE ratio. However, noninterest income had significant positive relation in all the

three tests which we could not break down further due to limited data. Usually, non interest

income is the prime source of income for NBFIs which includes advisory fee, underwriting

commission, issue management fee etc. Thus, it is safe for us to say that for these two factors,

managers may decide to manipulate them to see and expect a considerable change on the ROE of

a specific firm, provided that all external factors holds constant.

6. REFERENCES

1. Annual Report (2011- 2007):

1.1 United Leasing Company

2.1 IDLC

3.1 Lanka Bangla

4.1 IIDFC

5.1 IPDC

2. Sayla Sowat Siddiqui (January 2012). Capital Structure Determinants of Non-Bank

Financial Institutions (NBFIs) in Bangladesh. World Review of Business Research Vol. 2.

No. 1. January 2012. Pp. 60 78

3. Hossain And Shahiduzzaman. Development of Non Bank Financial Institutions

to Strengthen the Financial System of Bangladesh.

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4. Rahman and Farah (march 2012) . Non Bank Financial Institutions Profitability

Indicators:Evidence from Bangladesh IJAR-BAE Vol. 01. Issue 01. Article No. 03

5. Ahmed and Chowdhury (March 2007). Non-Bank Financial Institutions in Bangladesh:

An Analytical Review. Policy Analysis Unit (PAU) Research Department, BangladeshBank

6. Financial Stability Report 2010 (October 2011), Bangladesh Bank.

7. Sufian and Chong (2008). Determinants Of Bank Profitability In A Developing

Economy: Empirical Evidence From The Philippines .AAMJAF, Vol. 4, No. 2, 91112

8. Gul, Irshad and Zaman (March 2011). Factors Affecting Bank Profitability in Pakistan.

The Romanian Economic Journal

9. Saklain(May 2012). The Profitability Determinants Of Private Commercial Banks In

Bangladesh.Asian Institute of Technology (School of Management)

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Documents

Determining factors of profitability of NBFIs