A comparative study of bank and non bank financial institutions: A study of profitability indicators
Abstract
This paper investigates the difference in the indicators of the profitability of firms in the Non Banking Financial Institutions (NBFIs) and banking
industry of Bangladesh. Profitability of a financial institution basically depends on its Operating Efficiency, Capital Structure, Fixed Charges &
Income and Liquidity Position. The current research is an endeavor to find out the key profitability indicator variables and their influence over
Net Profit. Moreover it tries to find out the discrepancy between the profitability indicators of these two industries. Statistical techniques of
simple and multiple regressions have been used to determine the relationships between variables. The analysis results show that among the
independent variables the Liquidity Condition and Operating Efficiency have a considerable relationship with Profitability of Bank and Non Bank
sector.
Keywords: Profitability, Financial Institutions, Liquidity, Operating Efficiency
1. Introduction
The 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
dramatically and investors are also recognizing this to be a promising one. So, the profitability of these two
sectors 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 both these sectors and make a comparison.
In this paper, 11 Non Banking Financial Institutions and 11 banks have been selected for performing the analysis.
A model has been developed which tries to determine to what extent the predictor variables (Operating efficiency,
Capital Structure, Liquidity, and Fixed Charges & Income) exert influence over the Profitability of FIs. The paper
is organized as follows, the purposes of the study have been described in Section 2, Section 3 contains the
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methodology, Section 4 states limitation of the study, section 5 tells about the previous literatures on the present
topic of study, Section 6 includes the recent scenario of Bangladeshi Financial Institutions, and Section 7 reports
the results. The final section summarizes and concludes the paper.
2. Objectives of the Study
1. To find out the major financial features affecting the profitability in the Bank and Non-bank Financial
Institutions (NBFI) industry of Bangladesh.
2. To spot out the most influential factor behind these industry’s profitability.
3. To evaluate the differences and make a comparison between this two sector’s profitability indicator variables.
3. Research Methodology
The study is empirical in nature that covers a number of variables. Among these Profitability which is indicated
by Net Profit after Tax (Net Income) is considered as the dependent variable. On the other hand, Operating
Efficiency (Operating Revenue), Capital Structure (Long Term Liability), Fixed Charges and Income (Financial
Expense and Interest Income), Liquidity Position (Current Assets) are considered to be independent variables. We
have considered all the absolute figures for the study.
3.1 Data, Sample and Period under Study:
The study is essentially based on the secondary data collected from annual report of the concerned Bank and Non
bank Financial Institutions (NBFI). Information from books, journals and online publications produced by
academicians were abundantly used. The study has been conducted by using the data between the periods of
2008 to 2010.
3.2 Data Analysis
To observe the issues determining profitability simple regression, multiple regression and F - tests has been used.
The statistical tests have been executed by using the software Microsoft Excel 2007 and SPSS 12.0.
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4. Limitation of the Study
Major limitation of this study is insufficiency of accessible data, the main sources of which are the annual reports
of the Financial Institutions. 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 sector’s 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.
5. Literature Review
It has become a common perception to consider Bank as the significant source of financing. That’s why most of
the studies have been conducted regarding the profitability indicators of banks. But now a day’s non banking
financial institutions are also playing an important role toward the economy. Though the NBFI sector has turn out
to be a promising source of financing, researches with regard to the profitability of NBFI sector is scarce. Farah
Tazrina, Rahman Shah-Noor surveyed (2012) 30 Non Banking Financial Institutions in Bangladesh from the
period of 2006-2008 and concluded that the Liquidity Condition and Operating Efficiency exert significant
influence on Profitability of Non Bank sector in Bangladesh .But operating revenue is another variable which
has a major impact on net profit. So it is undoubtedly true that if the revenue increases, ultimately it has a positive
effect over the profitability.
Azam Muhammed and Siddiqui Sana (2012) inspected 36 Commercial banks in Pakistan on quarterly basis
from 2004 to 2010, to investigate the profitability differences and determinants of commercial banks of Pakistan
Banking Industry for the year 2004 to 2010 (on quarterly basis). According to their investigation the profitability
determinants of foreign banks are different from domestic banks. They conclude that local controlled commercial
banks in Pakistan are more profitable than foreign controlled ones as far as the volume of the profit is concerned
which is reflected in their earnings per share but the foreign controlled commercial banks in Pakistan, as a whole
are more capital efficient as compared to the local controlled commercial banks subject to few exceptions.
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NANDY DEBAPROSANNA (2011) studied the commercial banks of India for 3 years (2005-2007) and
concluded that “Interest Expenses‟ is the only good predictor for „Net Profit‟ of all different bank groups taking
together during the years 2004-05 to 2006-07.
Christos K Staikouras, and Wood Geoffrey E, surveyed with a balanced sample covering the entire EU
banking industries in the period of 1994-1998. According to their inspection the profitability of European banks is
influenced not only by factors related to their management decisions but also to changes in the external
macroeconomic environment. They found that banks with greater levels of equity and large non-loan earning
assets are relatively more profitable. This implies that banks which have are more profitable than those which
depend more heavily on assets. The funds gap ratio is significantly positive, and the proportion of loan loss
provisions to total loans significantly negative. Also, the results proved a positive effect of the concentration
and/or market share variables on bank profitability.
James W. Scott and José Carlos Arias (2011) in their study” Banking profitability determinants” surveyed top
five bank holding companies in the United and concluded that profitability determinants for the banking industry
include positive relationship between the return of equity and capital to asset ratio as well as the annual
percentage changes in the external per capita income. There was also a virtual consensus identified concerning the
effect that the internal factor of size as measured by an organization’s total assets had on its ability to compete
more effectively, even in times of economic downturns.
Khizer Ali, Muhammad Farhan Akhtar and Prof. Hafiz Zafar Ahmed(2011) surveyed 22 public and private
sector commercial banks of Pakistan covered the period of 2006-2009 and concluded that the efficient asset
management and economic growth establish positive and significant relation with profitability (measured by ROA
& ROE). They also found that the high credit risk and capitalization lead to lower profitability measured by return
on assets (ROA). The operating efficiency tends to exhibit the higher profitability level as measured by return on
equity. According to their study on the micro independent variables front, profitability seems to have been
positively affected by size, operating efficiency, portfolio composition, asset management and negatively by
capital and credit risk in case profitability is measured by return on assets (ROA).In case profitability is measured
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by return on equity (ROE) profitability seems to have positively affected by capital, portfolio composition and
asset management and negatively by size, operating efficiency and credit risk. On the macroeconomic variables,
GDP is found to having positive effect on profitability (as measured by ROA & ROE).
Malviya Mayank (2012) consolidated the summarized financial statements of the main banks operating in India
during the financial year 2010-11, the public and private sector and found that Public sector banks hold more
capital in absolute terms, relies relatively less on Interest Income, and operates on a lower Cost: Income ratio.
According to their findings Private sectors banks are more adequately capitalized in relative terms, have
accumulated relatively higher Loan Loss Reserves, and hold a higher proportion of liquid assets.
Javaid Saira, Anwar Jamil , Zaman Khalid and Gafoor Abdul examined the top 10 banks for a 5-year
period from 2004 to 2008, in Pakistan to analyze the determinants of top 10 banks’ profitability focusing on the
internal factors only. They concluded that higher total assets may not necessarily lead to higher profits and
dependence on one major asset, may lead to profitability but with less significant impact on overall profitability.
One major finding was the negative relationship of loans towards profitability when one of the banks showed a
loss but total deposit to total assets and total equity to total assets showed a positive and significant relationship
with profitability indicator ROA. Overall it was concluded that Total Assets, Equity/Total Assets, Deposits/Total
Assets, and Loans/Total Assets are the major internal determinants of profitability of banks in Pakistan.
6. Bank & Non-Bank Industry in Bangladesh: An Overview
After the independence, banking industry in Bangladesh started its journey with 6 nationalized commercialized
banks, 2 State owned specialized banks and 3 Foreign Banks. In the 1980's banking industry achieved significant
expansion with the entrance of private banks. Now, banks in Bangladesh are primarily of two types:

Scheduled Banks: The banks which get license to operate under Bank Company Act, 1991 (Amended in
2003) are termed as Scheduled Banks.
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
Non-Scheduled Banks: The banks which are established for special and definite objective and operate
under the acts that are enacted for meeting up those objectives, are termed as Non-Scheduled Banks.
These banks cannot perform all functions of scheduled banks.
There are 47 scheduled banks in Bangladesh who operate under full control and supervision of Bangladesh Bank
which is empowered to do so through Bangladesh Bank Order, 1972 and Bank Company Act, 1991. There are 4
State Owned Commercial Banks (SOCBs) which are fully or majorly owned by the Government of Bangladesh.
There are 30 private commercial banks which are majorly owned by the private entities. Among the PCBs 23
conventional PCBs are now operating in the industry. They perform the banking functions in conventional
fashion i.e interest based operations. There are 7 Islami Shariah based PCBs in Bangladesh and they execute
banking activities according to Islami Shariah based principles i.e. Profit-Loss Sharing (PLS) mode. Nine
Foreign Commercial Banks (FCBs) are operating in Bangladesh as the branches of the banks which are
incorporated in abroad. There are 4 specialized banks which were established for specific objectives like
agricultural or industrial development. These banks are also fully or majorly owned by the Government of
Bangladesh. There are now 4 non-scheduled banks in Bangladesh which are: Ansar VDP Unnayan Bank,
Karmashangosthan Bank, Probashi Kollyan Bank, Jubilee Bank
Non Bank Financial Institutions (NBFIs) are those types of financial institutions which are regulated under
Financial Institution Act, 1993 and controlled by Bangladesh Bank. Now, 31 FIs are operating in Bangladesh
while the maiden one was established in 1981. Out of the total, 2 is fully government owned, 1 is the subsidiary of
a SOCB, 13 were initiated by private domestic initiative and 15 were initiated by joint venture initiative. 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 106276.19 million 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
6
six months. At present term liabilities are subject to a statutory liquidity requirement (SLR) of 5 percent inclusive
of average 2.5 percent cash reserve ratio (CRR). SLR for the NBFIs operating without taking term deposit is 2.5
percent. BASEL Accord now in the process of test run phase will be made compulsory from 2012. Major sources
of funds of FIs are Term Deposit (at least six months tenure), Credit Facility from Banks and other FIs, Call
money as well as Bond and Securitization.
The major difference between banks and FIs are as follows:

FIs cannot issue cheques, pay-orders or demand drafts.

FIs cannot receive demand deposits,

FIs cannot be involved in foreign exchange financing,

FIs can conduct their business operations with diversified financing modes like syndicated financing,
bridge financing, lease financing, securitization instruments, private placement of equity etc.
7. Empirical Study and Results
In this section, an attempt has been done to find out the associations between profitability and performance
indicating variables with assistance of few statistical tools. At first, a simple regression model is executed with
each of the independent explainers. In this model, the dependent variable is Net Profit and the independent factors
are Current Assets, Financial Expense, Long Term Liability, Interest Income and Operating Revenue. These
dynamics are chosen in accordance with the eminence that in what degree those can contribute to the
determination of profitability. 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. The
empirical study has been done as a whole to find out the extent of relationship between dependent and
independent variables. After performing the analysis, it will be likely to come to a supposition about the
explanatory powers of the Performance indicating variables towards the profitability.
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7.1 Profitability Analysis of NBFI
7.1.1 Simple Regression Analysis
Model – A
In this section, we will try to estimate simple regression equation where profitability measure i.e. Net Profit (NP)
of 11 NBFIs of Bangladesh will be the dependent variable and the independent variables will be each of the
financial performance indicating factors in different stages. However, simple regression equation will be in the
following format:
Y=a+bX
Where, Y= Dependent variable
a= Y- intercept/constant
b=slope
X= independent variable
Simple regression analysis has been carried out for each of the 5 financial performance indicating variables which
are:
1. CAn=Current Assets
2. FEn= Financial Expenses
3. LTLn= Long Term Liability
4. IIn= Interest Income
5. OP REVn= Operating Revenue
The outputs of regression are summarized in the following table:
Table 1: Simple Regression Models
Dependent
Variable
Profitability
(Net Profit)
Independent Variable
Current Assets(CA)
Financial Expenses(FE)
Long Term Liability(LTL)
Interest Income(II)
Operating Revenue(OP REV)
Equation
r2
NPn= 40.46+0.0303CAn
70%
NPn= 96.32982+0.000435FEn
0.165%
NPn=39.28409+0.024337LTLn
62%
NPn=56.1425+0.072619IIn
39%
NPn=28.10603+0.116666 oP REVn
74%
F test
value
21.46717
0.014852
14.76522
5.719963
26.01501
P value of F
test
0.001230
0.905682
0.003951
0.040448
0.000645
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After observing the values of r2 (Coefficient of determination) and P values of F test in the above table, we
can say that Current Assets and Operating Revenue have the most influential impact over Net Profit. So, it
can be concluded that, Profitability of NBFIs are mostly persuaded by the changes in liquidity condition and
size of the company along with its operating efficiency.
Among this 5 performance indicating variables Current Assets and Operating Revenue have the highest two
values for r2 (70% and 74% respectively) which indicates that these two explain most of the variations in
profitability over this 3 years of time horizon (2008-2010). P- values of F - tests at 95% confidence level of
all the 4 explanatory variables state that the result is significant as it is more than .05. Only exception is in the
Financial Expense (FE) variable which shows an insignificant outcome of the regression. Moreover, Financial
Expense has the lowest value of r2 (0.165%) and P value (0.905682) of F test, which indicates that this
variable has very lower impact on profitability as a predictor (i.e. independent) variable when used in simple
regression analysis.
7.1.2 Multiple Regression Analysis:
In multiple regression analysis, several (more than one) independent variables are used to estimate a
dependent variable. The multiple regression equation looks like:
Y= a+b1X1+b2X2+b3X3+………..+bnXn
Where, Y= Dependent variable
a= Y- intercept/constant
b1, b2, b3.…bn= Net regression coefficients
X1, X2.X3…..Xn = Independent / Predictor variables
Model B:
In this phase, we try to analyze- whether the autonomous variables (i.e. the independent variables) together
have any noteworthy impact on Net Profit of the NBFIs.
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By using our selected 5 performance indicating variables, multiple regression analysis has been executed. We
have got the following model for multiple regressions:
Table 2: Multiple Regression Model
Model – B
r2
F- test value
P- value of F test
Multiple Regression Model
NPn = 19.2404+0.057CAn+0.004FEn+0.046LTLn-0.071IIn -0.185OP REVn
Other Statistics for Model- B
94.29%
34.0437
0.000725
Interpretations:
Profitability related with performance indicators in the following ways –
a. For 1 unit increases (decreases) in Current Assets (and values for other independent variables remaining
the same), Net Profit will increase (decrease) by 0.057 units.
b. For 1 unit increase (decreases) in Financial Expense (and values for other independent variables
remaining the same), Net Profit will increase (decrease) by 0.004 units.
c. For 1 unit increases (decreases) in Long Term Liability (and values for other independent variables
remaining the same), Net Profit will increase by 0.046 units and vice versa.
d. For 1 unit increases (decreases) in Interest Income (and values for other independent variables remaining
the same), Net Profit will decrease by 0.070 units and vice versa.
e. For 1 unit increases (decreases) in Operating Revenue (and values for other independent variables
remaining the same), Net Profit will decrease (increase) by 0.185 units.
The relationship among the variables in relative terms can be estimated with the help of coefficient of
multiple correlations (R). R= 0.9856 indicates that there exists a very high degree of relationship among the
variables.
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From the value of r2 we can say that all these 5 predictor variables collectively explain 94.29% of the variance
in Net Profit. The P- value (0.00) of F- test states that the multiple regression model is significant as it is less
than .05 or 5% level.
The relative influencing power of the independent variables can be indicated using standardized or Beta (β)
coefficient. In our result, it is found that β
CA
= 1.580 which is greater than β of all other independent
variables. So, we can conclude that Current Asset exerts highest influence among all other predictor variables
on Net Profit (NP). Moreover, it can be observed that CAn is a variable which is statistically significant
because it is significant at 0.004 or .04% level, which is less than 0.05 or 5% level.
As a whole, the regression is found to be suitable and appropriate. So, we can say that, the selected
performance indicating variables have a great extent of impact on profitability of Non Banking Financial
Institutions in Bangladesh.
7.2 Profitability Analysis of Bank
7.2.1 Simple Regression Analysis
Model - C
In this section, we will try replicate the same study done in the previous section to estimate simple regression
equation where profitability measure i.e. Net Profit (NP) of 11 commercial banks of Bangladesh will be the
dependent variable and the independent variables will be each of the financial performance indicating factors.
5 financial performance indicating variables are kept same as the previous model. The variables are:
6. CAb=Current Assets
7. FEb= Financial Expenses
8. LTLb= Long Term Liability
9. IIb= Interest Income
10. OP REVb= Operating Revenue
The outputs of regression are summarized in the following table:
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Table 3: Simple Regression Models
Dependent
Variable
Profitability
(Net Profit)
Independent Variable
Equation
r2
F test value
Current Assets(CA)
Long Term Liability(LTL)
Financial Expense(FE)
Interest Income(II)
Operating Revenue(OP REV)
NPb= -8.26657+0.086207CAb
NPb= 1.34893-0.22296LTLb
NPb= 1.85935-0.14165FEb
NPb= -1.18886+0.559494IIb
NPb=-1.04935+0.675846OP REVb
87%
6%
25%
60%
85%
61.033
0.5943
2.9534
13.61086
51.4266
P value of F
test
0.0000
0.4605
0.1198
0.0050
0.0000
Here we can see the simple regression of selected commercial banks, where all the 5 independent variables
show the results according to their expected signs. Current Assets, Interest Income and Operating Revenue are
supposed to be positively related with the independent variable net profit. Long term liability and financial
expenses show negative signs as expected. It is also found that, Current Assets has the highest explanatory
power (r2=87%) among all the variables and the another most influential explanatory factor is Operating
Revenue having a r2 of 85%.This findings is consistent with the previous findings of NBFI results. These two
variables also have revealed the significant impact over the profitability. The P values (0.000) of these factors
also suggest the results are significant at 95% confidence level. In this model, it is found that Long term
liability pose the minimum impact over the model and the F test also does not show any convincing result as
the P value (.4605) is statistically insignificant.
7.2.2 Multiple Regression Analysis:
Model D:
Table 4: Multiple Regression Model
Model – D
r2
F- test value
P- value of F test
Multiple Regression Model
NPb = -4.293+0.07978CAb+0.236FEb-+.028LTLb-+.531IIb-+.008OP REVb
Other Statistics for Model- D
93.5%
29.8312
0.00099
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Interpretations:
Profitability related with performance indicators in the following ways –
a. For 1 unit increases (decreases) in Current Assets (and values for other independent variables remaining
the same), Net Profit will increase (decrease) by 0.079 units.
b. For 1 unit increase (decreases) in Financial Expense (and values for other independent variables
remaining the same), Net Profit will increase (decrease) by 0.236 units.
c. For 1 unit increases (decreases) in Long Term Liability (and values for other independent variables
remaining the same), Net Profit will increase by 0.028 units and vice versa.
d. For 1 unit increases (decreases) in Interest Income (and values for other independent variables remaining
the same), Net Profit will increase by 0.53 units and vice versa.
e. For 1 unit increases (decreases) in Operating Revenue (and values for other independent variables
remaining the same), Net Profit will increase (decrease) by 0.008 units.
Here it has been observed that the coefficient of multiple correlations is R= 0.9836, which points out that
there exists a very high degree of relationship among the dependent and independent variables altogether.
From the value of r2 it can be inferred that all these 5 predictor variables collectively explain 93.5% of the
variance in Net Profit. That means the predictor variables together can pose a very momentous influence over
the dependent variable. The P- value (0.00) of F- test states that the multiple regression model is significant as
it is less than .05 or 5% level.
In the study of banking institutions, again it is found that the Beta coefficient is highest for the predictor
variable Current Assets. β
CA
= 0.864 which reveals it wields maximum influence on the dependent variable
among the others. But the result is not statistically significant because it is significant at 32.5% which goes
beyond to our assumed confidence level.
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So after evaluating the results we can originate that this regression is also appropriate. As a whole, we can say
that, the selected performance indicating variables have an enormous impact on the profitability of Banking
Institutions in Bangladesh.
7.3 Comparative Analysis:
Financial Institutions are considered as the life blood of the economy. In this study, the Endeavour has been
extended to check out the factors which are mostly responsible for determining the profitability of Financial
Institutions, both for banks and non bank financial institutions. A comparative scenario between banks and NBFIs
can be drawn from the completed analysis. The following table shows the results from simple regression analysis
for both of the types of financial institutions.
Table 5: Simple regression analysis: Bank and NBFI
Bank
Independent variable
Current Assets(CA)
Long Term
Liability(LTL)
Financial Expense(FE)
Interest Income(II)
Operating Revenue(OP
REV)
NBFI
Equation
NPb= -8.26657+0.086207CAb
r2
87%
F test
61.033
p value
0
Equation
NPn= 40.46+0.0303CAn
NPb= 1.34893-0.22296LTLb
NPb= 1.85935-0.14165FEb
NPb= -1.18886+0.559494IIb
NPb=-1.04935+0.675846OP
REVb
6%
25%
60%
0.5943
2.9534
13.61086
0.4605
0.1198
0.005
85%
51.4266
0
NPn= 96.32982+0.000435FEn
NPn=39.28409+0.024337LTLn
NPn=56.1425+0.072619IIn
NPn=28.10603+0.116666 oP
REVn
r2
70%
F test
21.46717
p value
0.00123
0.17%
62%
39%
0.014852
14.76522
5.719963
0.905682
0.003951
0.040448
74%
26.01501
0.000645
1. In the simple regression model –A, prepared for NBFI, it has been found that the expected signs are
consistent in the outcome except for the variable Financial Expense (FEn). But in case of banks, all the
simple regression results have shown uniformity with the expected signs.
2. In case of NBFIs, all The P – values are statistically significant except for the financial expenses (FE n).
On the other hand, we found financial expense (FEb) and Long term liability (LTLb) to be statistically
insignificant in the analysis of banking institutions.
3. According to the coefficient of determination (r2) of NBFI, the explanatory power of Operating Revenue
(Op Revn) exerts the highest (74%) control among all the independent variables; on contrary Current
Assets (CAb) in case of bank has the maximum (87%) influential power over the dependent variable.
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Table 6: Multiple regression analysis: Bank and NBFI
Multiple regression
equation
r2
F- test value
P- value of F test
Bank
NBFI
NPb = -4.293+0.07978CAb+0.236FEb+.028LTLb-+.531IIb-+.008OP REVb
NPn =19.2404+0.057CAn+0.004FEn+0.046LTLn0.071IIn -0.185OP REVn
93.5%
29.8312
0.00099
94.29%
34.0437
0.000725
4. The results of multiple regressions for both of the sectors show more or less similar pattern. The
coefficients of multiple determinations (R2) are very high for two of the sectors. In case of NBFIs it is a
bit higher (94.29%) which means 94.29% of the variations in the Net Profit can be explained by the
combined variation of all the 5 predictor variables. In the both cases of Banks and NBFIs, results are
found to be statistically significant according to the F tests.
Problem identification and recommendations:
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8. Conclusion and Implications
According to the study, it is clear that the chosen profitability indicator variables have impact upon net profit, but
among the independent variables the Liquidity Condition and Operating Efficiency exert significant influence on
Profitability of both Bank and Non Bank sector in Bangladesh. As we know that Liquidity is considered as one of
the most prominent yardstick of performance measurement of financial institutions. Investors generally perceive
the financial institutions to be superior over the others if it has sufficient liquid or current assets. So when a
financial institution has enough liquidity the investors feel more secured and approach to this FI for their
investment. The more the number of customers increases the more it becomes profitable. Thus this analysis
indicates that why liquidity position exerts more influence on profitability. Again we see operating revenue is the
another variable which has a major impact on net profit. So it is undoubtedly true that if the revenue increases,
ultimately it has a positive effect over the profitability.
The results of multiple regressions suggest that the selected independent variables explain more than 93% changes
in the net profit of NBFI and in case of Banking institutions the extent is as strong as 94%. By analyzing the other
statistical results of multiple regressions we found that the results are very much consistent with the simple
regression. Most of the results are statistically significant and overall provide an idea that operating efficinecy is
the basic determinant of profitability in NBFI sector. In case of Bank, Liquidity condition is found to be the major
16
determinant of profitability. So it can be inferred that this promising and potential sector of Financial Institution in
Bangladesh can flourish very fast and enhance profitability by improving its liquidity position and operating
efficiency.
References
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5. Malviya, Mayan, 2012, “An analysis on the profitability, risk and Growth indicators of public and
private sector Banks”, International Journal of Transformations in Business Management, Vol.1, JanMar.
17
6. Farah, Tazrina and Rahman, Shah-noor, 2012, “Non Bank Financial Institutions’ Profitability
Indicators: Evidence from Bangladesh”, International Journal of Applied Research in Business and
Economics, Vol.1, March, pp.11-21.
7. Scott, James W., and Arias Jose C., 2011, “Banking Profitability Determinant”, Business Intelligence
Journal, Vol.4, p.209-230.
8. Ali, Khizer, Akhtar, Farah M, and Ahmed Zafar H, 2011, “Bank-Specific and Macroeconomic
Indicators of Profitability - Empirical Evidence from the Commercial Banks of Pakistan”,
International Journal of Business and Social Science, Vol. 2, p.235-242.
Appendix
Multiple Regression of NBFI
Variables Entered/Removed(b)
Variables
Entered
Model
1
Variables
Removed
OP, FE, II,
CA, LTL(a)
Method
.
Enter
a All requested variables entered.
b Dependent Variable: NP
Model Summary
Model
1
R
Adjusted R
Square
R Square
Std. Error of
the Estimate
.986(a)
.971
.943
17.85968
a Predictors: (Constant), OP, FE, II, CA, LTL
ANOVA(b)
Model
1
Sum of
Squares
Regressio
n
Residual
Total
54294.299
df
Mean Square
5
10858.860
1594.841
5
318.968
55889.140
10
F
Sig.
34.044
.001(a)
a Predictors: (Constant), OP, FE, II, CA, LTL
b Dependent Variable: NP
18
Coefficients(a)
Unstandardized
Coefficients
Model
1
B
(Constant
)
CA
FE
LTL
Standardized
Coefficients
Std. Error
19.240
8.694
.057
.011
.004
.001
Beta
t
Sig.
2.213
.078
1.580
5.056
.004
.381
4.418
.007
.047
.011
1.512
4.188
.009
II
-.071
.018
-.613
-4.074
.010
OP
-.185
.077
-1.369
-2.404
.061
a Dependent Variable: NP
Simple regression Table: NBFI
1. Independent variable current asset and Dependent variable: Net Profit
Regression Statistics
Multiple R
0.83941
R Square
70%
Adjusted R Square
0.671788
Standard Error
42.82929
Observations
11
ANOVA
df
SS
MS
F
Significance F
Regression
1
39380.01
39380.01
21.46812333
0.001230776
Residual
9
16509.13
1834.348
Total
10
55889.14
P-value
Lower 95%
Upper
95%
Lower
95.0%
Upper
95.0%
Coefficients
Standard
Error
t Stat
Intercept
40.46717
17.82679
2.270019
0.0493615
0.140159054
80.79417
0.140159
80.79417
CA
0.030371
0.006555
4.633371
0.001230776
0.015542928
0.045199
0.015543
0.045199
2. Independent variable Financial Expense and Dependent variable: Net Profit
Regression Statistics
Multiple R
0.040589
19
R Square
0.165%
Adjusted R Square
-0.10928
Standard Error
78.73801
Observations
11
ANOVA
df
SS
MS
F
0.014852
Regression
1
92.07459
92.07459
Residual
9
55797.07
6199.674
10
55889.14
Total
Significance F
0.905682
Coefficients
Standard
Error
t Stat
P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
96.32982
25.3402
3.801462
0.004208
39.0063
153.6533
39.0063
153.6533
FE
0.000435
0.003568
0.121867
0.905682
-0.00764
0.008507
-0.00764
0.008507
3. Independent variable Long term Liability and Dependent variable: Net Profit
Regression Statistics
Multiple R
0.788223
R Square
62%
Adjusted R Square
0.579217
Standard Error
48.49454
Observations
11
ANOVA
df
Regression
Residual
Total
Significance
F
SS
MS
F
1
34723.66
34723.66
14.76522
9
21165.48
2351.72
10
55889.14
0.003951
Coefficients
Standard
Error
t Stat
P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
39.28409
21.03838
1.867258
0.094712
-8.30803
86.8762
-8.30803
86.8762
LTL
0.024337
0.006333
3.842554
0.003951
0.010009
0.038664
0.010009
0.038664
20
4. Independent variable Interest Income and Dependent variable: Net Profit
Regression Statistics
Multiple R
0.623366
R Square
39%
Adjusted R Square
0.32065
Standard Error
61.61839
Observations
11
ANOVA
df
MS
F
5.719963
Regression
1
21717.71
21717.71
Residual
9
34171.43
3796.826
10
55889.14
Total
Significance
F
SS
0.040448
Coefficients
Standard
Error
t Stat
P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
56.1425
25.35531
2.21423
0.054071
-1.21521
113.5002
-1.21521
113.5002
0.072619
0.030363
2.391644
0.040448
0.003932
0.141306
0.003932
0.141306
Intercept
II
5. Independent variable Operating Revenue and Dependent variable: Net Profit
Regression Statistics
Multiple R
0.861956
R Square
74%
Adjusted R Square
0.714408
Standard Error
39.95182
Observations
11
ANOVA
df
SS
MS
F
Significance
F
26.01501
0.000644725
Regression
1
41523.81
41523.81
Residual
9
14365.33
1596.148
10
55889.14
Total
21
Coefficients
Standard
Error
t Stat
P-value
Lower 95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
28.10603
18.15843
1.547823
0.156071
12.97118172
69.18325
-12.9712
69.18325
OP rev
0.116666
0.022874
5.100491
0.000645
0.064922718
0.16841
0.064923
0.16841
Multiple Regression of Bank
Variables Entered/Removed(b)
Variables
Entered
Model
1
Variables
Removed
II, LTL, FE,
OP, CA(a)
Method
.
Enter
a All requested variables entered.
b Dependent Variable: NP
Model Summary
Model
1
Std. Error of
the Estimate
325325361.3
.984(a)
.968
.935
6713
a Predictors: (Constant), II, LTL, FE, OP, CA
R
Adjusted R
Square
R Square
ANOVA(b)
Model
1
Regressio
n
Residual
Sum of
Squares
157862015
744784100
00.000
529182953
743265000
.000
df
Mean Square
F
Sig.
5
31572403148
95682000.000
29.831
.001(a)
5
10583659074
8653000.000
22
Total
163153845
282216700
10
00.000
a Predictors: (Constant), II, LTL, FE, OP, CA
b Dependent Variable: NP
Coefficients(a)
Unstandardized
Coefficients
Model
1
B
(Constant
)
CA
Standardized
Coefficients
Std. Error
42937194
06.832
.080
Beta
t
19922313
54.595
Sig.
-2.155
.084
.073
.864
1.091
.325
LTL
.028
.088
.032
.321
.761
FE
.237
.113
.831
2.086
.091
OP
.008
.437
.011
.019
.986
II
.531
.538
a Dependent Variable: NP
.736
.987
.369
Simple regression Table: Bank
1. Independent variable current asset and Dependent variable: Net Profit
Regression Statistics
Multiple R
0.933536
R Square
87%
Adjusted R Square
0.85721
Standard Error
4.83E+08
Observations
11
ANOVA
df
SS
MS
F
Significance
F
61.03305
2.67428E-05
Regression
1
1.42E+19
1.42E+19
Residual
9
2.1E+18
2.33E+17
10
1.63E+19
Total
Coefficients
Standard
Error
t Stat
P-value
Lower 95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
-8.26657
2.73E+08
-3.02773
0.014299
1444292188
-2.1E+08
-1.4E+09
-2.1E+08
CA
0.086207
0.011035
7.812365
2.67E-05
0.061244917
0.111169
0.061245
0.111169
23
2. Independent variable Financial Expense and Dependent variable: Net Profit
Regression Statistics
Multiple R
0.49707
R Square
25%
Adjusted R Square
0.163421
Standard Error
1.17E+09
Observations
11
ANOVA
df
Regression
Residual
Total
Significance
F
SS
MS
F
1
4.03E+18
4.03E+18
2.953445
9
1.23E+19
1.36E+18
10
1.63E+19
0.119816
Coefficients
Standard
Error
t Stat
P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
1.859353
6.22E+08
2.988705
0.015233
4.52E+08
3.27E+09
4.52E+08
3.27E+09
FE
-0.14165
0.082422
-1.71856
0.119816
-0.3281
0.044805
-0.3281
0.044805
3. Independent variable Long term Liability and Dependent variable: Net Profit
Regression Statistics
Multiple R
0.248884
R Square
6%
Adjusted R Square
Standard Error
-0.04229
1.3E+09
Observations
11
ANOVA
df
Regression
Residual
Total
SS
MS
F
1
1.01E+18
1.01E+18
0.594301
9
1.53E+19
1.7E+18
10
1.63E+19
Significance
F
0.460519
24
Coefficients
Standard
Error
t Stat
P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
1.348931
6.21E+08
2.17117
0.058003
-5.7E+07
2.75E+09
-5.7E+07
2.75E+09
LTL
-0.22296
0.28921
-0.77091
0.460519
-0.87719
0.431285
-0.87719
0.431285
4. Independent variable Interest Income and Dependent variable: Net Profit
Regression
Statistics
Multiple R
0.775862
R Square
60%
Adjusted R Square
0.557735
Standard Error
8.49E+08
Observations
11
ANOVA
df
Regression
Residual
Total
Significance
F
SS
MS
F
1
9.82E+18
9.82E+18
13.61086
9
6.49E+18
7.22E+17
10
1.63E+19
0.005003
Coefficients
Standard
Error
t Stat
P-value
Lower
95%
Upper
95%
Lower
95.0%
Upper
95.0%
Intercept
-1.18886
6.41E+08
-1.85535
0.096526
-2.6E+09
2.61E+08
-2.6E+09
2.61E+08
II
0.559494
0.151653
3.68929
0.005003
0.21643
0.902558
0.21643
0.902558
5. Independent variable Operating Revenue and Dependent variable: Net Profit
Regression Statistics
Multiple R
R Square
0.922529
85%
Adjusted R Square
0.83451
Standard Error
5.2E+08
Observations
11
25
ANOVA
df
SS
MS
F
51.4266
Regression
1
1.39E+19
1.39E+19
Residual
9
2.43E+18
2.7E+17
10
1.63E+19
Total
Coefficients
Standard
Error
t Stat
P-value
Intercept
-1.04935
3.23E+08
-3.24649
0.010054
OP REV
0.675846
0.094244
7.171234
5.24E-05
Significance F
5.24406E-05
Upper
95%
Lower
95.0%
Upper
95.0%
-1780534613
-3.2E+08
-1.8E+09
-3.2E+08
0.462651498
0.889041
0.462651
0.889041
Lower 95%
26
List of Banks
Name of the banks
Dutch Bangla Bank Ltd
National Bank Ltd
United Commercial Bank Ltd
Dhaka Bank Ltd
Bank Asia Ltd
Brac bank
Eastern bank Ltd
Jamuna Bank Ltd
Standard Bank Ltd
Mutual Trust Bank Ltd
Prime bank Ltd
List of NBFI’s
Name of the NBFI's
Banladesh Finance & Investment Company Ltd (BFIC)
Bangladesh Industrial Finance Company Ltd (BIFC)
Bay Leasing & Investment Ltd
Delta Brac Housing Fianace Corporation Ltd(DBH)
Fidelity Assets & Securities Company ltd
Fareast Finance & Investment Ltd
First Lease Fianace & Investment Ltd
GSP finance company Ltd
Infrastucture Developmant Company Ltd
International Leasing And Fiancial Services Ltd
IDLC Finance Ltd
27
Dependent
Variable
Profitability
(Net Profit)
Dependent
Variable
Profitability
(Net Profit)
Independent Variable
Equation
r2
F test value
Current Assets(CA)
Long Term Liability(LTL)
Financial Expense(FE)
Interest Income(II)
Operating Revenue(OP REV)
NPb= -8.26657+0.086207CAb
NPb= 1.34893-0.22296LTLb
NPb= 1.85935-0.14165FEb
NPb= -1.18886+0.559494IIb
NPb=-1.04935+0.675846OP REVb
87%
6%
25%
60%
85%
61.033
0.5943
2.9534
13.61086
51.4266
Independent Variable
Current Assets(CA)
Financial Expenses(FE)
Long Term Liability(LTL)
Interest Income(II)
Operating Revenue(OP REV)
Equation
r2
NPn= 40.46+0.0303CAn
70%
NPn= 96.32982+0.000435FEn
0.165%
NPn=39.28409+0.024337LTLn
62%
NPn=56.1425+0.072619IIn
39%
NPn=28.10603+0.116666 oP REVn
74%
F test
value
21.46717
0.014852
14.76522
5.719963
26.01501
P value of F
test
0.0000
0.4605
0.1198
0.0050
0.0000
P value of F
test
0.001230
0.905682
0.003951
0.040448
0.000645
28
Simple regression analysis: Bank and NBFI
Bank
Independent variable
Current Assets(CA)
Long Term
Liability(LTL)
Financial Expense(FE)
Interest Income(II)
Operating Revenue(OP
REV)
NBFI
Equation
NPb= -8.26657+0.086207CAb
r2
87%
F test
61.033
p value
0
Equation
NPn= 40.46+0.0303CAn
NPb= 1.34893-0.22296LTLb
NPb= 1.85935-0.14165FEb
NPb= -1.18886+0.559494IIb
NPb=-1.04935+0.675846OP
REVb
6%
25%
60%
0.5943
2.9534
13.61086
0.4605
0.1198
0.005
85%
51.4266
0
NPn= 96.32982+0.000435FEn
NPn=39.28409+0.024337LTLn
NPn=56.1425+0.072619IIn
NPn=28.10603+0.116666 oP
REVn
r2
70%
F test
21.46717
p value
0.00123
0.17%
62%
39%
0.014852
14.76522
5.719963
0.905682
0.003951
0.040448
74%
26.01501
0.000645
Multiple regression analysis: Bank and NBFI
Multiple regression
equation
r2
F- test value
P- value of F test
Bank
NBFI
NPb = -4.293+0.07978CAb+0.236FEb+.028LTLb-+.531IIb-+.008OP REVb
NPn =19.2404+0.057CAn+0.004FEn+0.046LTLn0.071IIn -0.185OP REVn
93.5%
29.8312
0.00099
94.29%
34.0437
0.000725
29
Model – B
r2
F- test value
P- value of F test
Model – D
r2
F- test value
P- value of F test
Multiple Regression Model
NPn = 19.2404+0.057CAn+0.004FEn+0.046LTLn-0.071IIn -0.185OP REVn
Other Statistics for Model- B
94.29%
34.0437
0.000725
Multiple Regression Model
NPb = -4.293+0.07978CAb+0.236FEb-+.028LTLb-+.531IIb-+.008OP REVb
Other Statistics for Model- D
93.5%
29.8312
0.00099
30