The Profitability Determinants of
Private Commercial Banks in
Bangladesh
Presented
by
Md. Sohel SaklainMd. Sohel Saklain
Examination Committee: Dr. Sundar Venkatesh (Chairperson)
Dr. Juthathip Jongwanich
Dr. Yousre Badir
Professional Master’s in Banking and Finance
1
Agenda
1. Overview of the Banking Sector in Bangladesh
2. Analysis of Profitability: The Case of One Commercial Bank
3. Problem Statement & Objectives of The Research StudyResearch Study
4. Research Methodology
5. Analysis of The Profitability Determinants of Private Commercial Banks in Bangladesh
6. Conclusion and Recommendations for Policy Implications
2
BangladeshFinancial System of
Bangladesh
Central Bank
(Bangladesh Bank)
State Owned Commercial Banks (SCBs)
Private Commercial Banks (PCBs)
Controller of Insurance
(under the ministry of commerce)
Life Insurance
Rural Development
and Cooperative Division
( RDCD )
Co-operative Banks
Micro Credit Regulatory Authority
Micro finance
Institutions
Securities and Exchange
Commission
(SEC)
Dhaka Stock Exchange
Banks (PCBs)
Foreign Banks (FCBs)
Government-owned
Specialized Banks (DFIs)
Non-Bank Financial
Institution (NBFIs)
General Insurance
Chittagong Stock
Exchange
3
•The Financial sector of Bangladesh, like most in
developing countries, is dominated by banking
industry.
1. Overview of the Banking Sector in Bangladesh
6 64 4 4 4 4 4
2 2 2 35 5 5 4
810
13
2730 30
46 7 7
913
9 9
5
10
15
20
25
30
35
Number of Banks in Bangladesh (by Type) from 1975 to 2010
Nationalised banks
Specialised banks
Private banks
4
4 4 4 4 4 42 2 2 3
5 5 5 44
0
5
1975 1980 1985 1990 1995 2000 2005 2010
Year
Private banks
Foreign banks
• In 1982 license to few Private Commercial Banks (PCBs) were given for the first
time.
•First Generation- License in early 1980s, Second Generation- license in late 1980s
and early 1990s , Third Generation- license in Late 1990s and onward
1. Overview of the Banking Sector in Bangladesh Cont..
4 4
30
9
0
10
20
30
40
SCBs DFIs PCBs FCBs
Bank Type
Number of Scheduled Banks (by Type)
in Bangladesh (as on June, 2010)
SCBs
29%
FCBs
7%
Share of Industry Assets by Type(as on
June, 2010)
5
Bank Type
3394
1366
2427
590
1000
2000
3000
4000
SCBs DFIs PCBs FCBs
Bank Type
Number of Bank Branches by Type(as
on June, 2010) DFIs
7%
PCBs
57%
1. Overview of the Banking Sector in Bangladesh Cont..
89.45
70.8962.43 62.07
55.22
40.52
27.8326.06 27.8531.47
46.47
60.81
40
50
60
70
80
90
100
%
Deposit of Scheduled Banks by Types
SCBs
DFIs
6
•The higher interest rate on deposit may be the probable reason for rising
trend of PCBs deposit.
27.83
4.34 4.4 4.37 4.9 5.98 5.97 5.10
18.3426.06 27.85
31.47
6.21 6.37 7.14 5.18 7.04 7.04 6.26
0
10
20
30
40
1980 1985 1990 1995 2000 2005 2010
Year
PCBs
FCBs
1. Overview of the Banking Sector in Bangladesh Cont..
80.2
58.2652.78 52.36
47.17
35.2531.13
49.02
65.39
40
50
60
70
80
90
%
Advances of Scheduled Banks by Types
SCBs
DFIs
7
•One of the probable reason of increasing trend of advances for PCBs is
the quicker and easier loan processing .
21.816.16
22.94 20.42 17.18 16.169.18 6.95
0
13.51
21.05 25.1331.13
3.65 5.29 5.75 5.32 5.54 6.55 5.86
0
10
20
30
40
1980 1985 1990 1995 2000 2005 2010
Year
DFIs
PCBs
FCBs
1. Overview of the Banking Sector in Bangladesh Cont..
9440.30
36555.90
0.00
10000.00
20000.00
30000.00
40000.00
50000.00
Million
Taka
Trend of Net Profit of Scheduled Banks by Type
SCBs
FCBs
8
-44159.20-50000.00
-40000.00
-30000.00
-20000.00
-10000.00
0.00
19
93
19
94
19
95
19
96
19
97
19
98
19
99
20
00
20
01
20
02
20
03
20
04
20
05
20
06
20
07
20
08
20
09
(p)Taka
Year
PCBs
DFIs
• From the year 2006 the profit of PCBs begun to rise in the rocket
high rate and it ended with 36,555.90 million taka in the year 2009.
1. Overview of the Banking Sector in Bangladesh Cont….
0.700.96
0.740.80 0.70
1.20 1.10 1.101.30 1.40
1.55
2.00
2.402.60
3.20 3.10
2.20
3.102.90
3.182.87
1.00
1.50
2.00
2.50
3.00
3.50
%
Trend of ROA of Scheduled Banks by Type
SCBs
DFIs
9
0.10 0.10-0.10 -0.10 0.00 0.00
0.70 0.74
0.30
0.00
-0.20
-0.10
-0.20 -0.30 -0.60
0.370.22
0.80 0.70
-1.00
-0.50
0.00
0.50
1.00
Year
DFIs
PCBs
FCBs
• PCBs always maintained the second level of ROA in the industry for the
entire period.
• From the year 2009 to 2010 the ROA of PCBs rose remarkably.
2. Analysis of Profitability: The Case of AB Bank Ltd.
162.45 532.19
1,903.49 2,300.62
3,417.19
3,989.52
-500.00
1,000.00 1,500.00 2,000.00 2,500.00 3,000.00 3,500.00 4,000.00 4,500.00
Taka
(million)
Net Profit of AB Bank Ltd.
33,065.40 47,989.34
63,549.86
84,053.61
107,093.0
1
134,003.8
8
-
20,000.00
40,000.00
60,000.00
80,000.00
100,000.00
120,000.00
140,000.00
160,000.00
Total Assets of AB Bank Ltd.
10
-
20
05
20
06
20
07
20
08
20
09
20
10
Year
Net Profit
•Net Profit of ABBL was only 162.45 million in the year 2005 but it became
3,989.52 million in the year 2010 which is almost 25 times increment.
-
20
05
20
06
20
07
20
08
20
09
20
10
Year
Total Asset
2. Analysis of Profitability: The Case of AB Bank Ltd. Cont..
1.1%
3.0%2.7%
3.2%3.0%
1.1% 1.10%1.30% 1.40%
1.55%
2.00%
1.2%1.4%
1.6%1.0%
1.5%
2.0%
2.5%
3.0%
3.5%
%
Comparative Trend of ROA
ABBL
PCBs
11
0.5%
0.6%0.8% 0.9%
1.2%1.4%
0.0%
0.5%
1.0%
2005 2006 2007 2008 2009 2010*
Year
Banking Industry
• After 2006 AB Bank Ltd. maintained a much higher level of
ROA than the banking industry and even the PCBs.
10.6%
20.6%
42.2%
34.2% 33.2%
28.2%
18.1%15.2% 16.7% 16.4%
21.0%24.3%
15.6%
21.7% 22.9%15.0%
20.0%
25.0%
30.0%
35.0%
40.0%
45.0%
%
Comparative Trend of ROE
ABBL
PCBs
2. Analysis of Profitability: The Case of AB Bank Ltd. Cont..
10.6%
12.4% 14.1% 13.8%15.6%
0.0%
5.0%
10.0%
2005 2006 2007 2008 2009 2010*
Year
Banking Industry
12
•The ROE of ABBL reached its peak in the year 2007. In that year the
ROE of ABBL was 42.2%. The reason might be the surge in Net Profit
of ABBL and lower equity in this year.
•In the subsequent years the ROE of ABBL declined continuously but
it remained above the ROE of banking industry and PCBs.
2.09%
1.28%
2.26% 2.42%2.77% 3.05%
2.68%
4.24%
5.06% 4.90% 5.05%
5.91%
0.14%
1.64%2.34%
1.81% 1.77%
2.90%
1.00%
2.00%
3.00%
4.00%
5.00%
6.00%
7.00%
Income Mix of ABBL
NIM
NII
IIOSBD
2. Analysis of Profitability: The Case of AB Bank Ltd. Cont..
1.28%0.14%0.00%
1.00%
2005 2006 2007 2008 2009 2010
Year
13
• NII (Non Interest Income/Total Assets) line always stayed above the NIM line.
• The Investment Income from the Investment in Shares, Bonds and Debenture
(IIOSBD= Investment Income from the Investment in Shares, Bonds and
Debenture/Total Assets) also occupied a significant proportion of the non interest
income.
• The IIOSBD line has the same shape as NII line which indicates that the IIOSBD
had a great influence on the NII.
3. Problem Statement
• Private commercial banks in Bangladesh are
continuously making a huge chunk of profit.
• The profit growth seems to be astonishingly high.
• Good sign for an economy but question of
sustainability arises.sustainability arises.
• Banks are involved in the wide array of other non
traditional banking activities. Some of these profit
seeking activities may lead banks to take very high
exposures to the risk.
14
3. Objective of the Study
This research study only tries to focus on the
Private Commercial Banks (PCB) category
because of its hefty profit growth.
So the main objectives are:So the main objectives are:
• To identify the major determinants of the
profitability of Private Commercial Banks in
Bangladesh in recent years.
• To address some policy implications and
suggest directions for further study.
15
4. Research Methodology
Data:
– Annual data for all the 30 Private Commercial Banks of
Bangladesh for the years 2009 and 2010.
– Source of data: annual report of each bank.
– To capture the recent year’s profitability determinants-
only two years’ data has been considered.only two years’ data has been considered.
– No sampling has been made to select the banks.
Research Method:
– One dependent and nine explanatory variables have been
taken that may influence the profitability of a bank.
– Two multiple regression analyses have been run for the
year 2009 and 2010.
16
4. Research Methodology Cont..Example of variables in few literatures
Literature Dependant
Variables
Independent Variables
F. Sufian & M. S.
Habibullah (2009)
ROA Asset Size, Capital Adequacy, Loans, Deposit,
Loan Loss Provision, NII, GDP, Inflation, Supply
of money
N. Jahangir, S. Shill, &
M. A. J. Haque (2007)
ROE Asset Size, loan and deposit
D. Alpher & A. Anbar ROA, ROE Asset Size, Capital Adequacy, Asset Quality,
17
D. Alpher & A. Anbar
(2011)
ROA, ROE Asset Size, Capital Adequacy, Asset Quality,
Liquidity, Deposits, NIM, NII, GDP, Inflation,
Interest Rate
M. Pervan, I. Pervan,
& A. Guadagnino.
(2010)
ROA, ROE,
NIM
Asset Size, Market Share, Solvency risk(capital
adequacy), Credit risk, Liquidity risk, Operating
Exp. Mgt., Fees Income, HHI Index,
Concentration Index, Inflation, GDP
S. S. Debashis, & N. C.
Shil (2011)
Net Profit Spread, NII, Credit Deposit Ratio, Non
Performing Assets to Net Advances, Provision &
Contingencies, Operating Exp., Business Per
Employee, Profit per Employee
4. Research Methodology Cont..
Dependent Variable:
– Return on Assets (ROA) and Return on Equity (ROE) are most
commonly used
– ROA has been used in this study
Bank Specific Independent Variables:
– Bank specific financial ratios representing capital adequacy, cost
Variable Selection
– Bank specific financial ratios representing capital adequacy, cost
efficiency, Income Expenditure mix, asset quality, and size are mostly
used internal variables. Some of these variables have been used in the
study.
– Based on the case study of AB bank Ltd. we also considered the
investment activities in our variable selection.
Macro Economic Independent Variables:
– GDP, inflation, market interest rates etc. are commonly treated as
external determinants that affect bank profitability. This study has not
covered any external variables. 18
Definitions and Notation of the Variables
Variable Measure NotationDependent
Variables
Profitability Return on Assets (ROA) =Net Profit/Total Assets
ROA
Asset Size Natural Logarithm of Total Assets logACapital Adequacy Equity / Total Assets CAAsset Quality Loans / Total Assets
Non-Performing Loans/ Total Loans
LA
NPL
Deposit Deposits/Total Assets DP
19
Independent Variables
Deposit Deposits/Total Assets DPIncome-Expenditure Structure
Net Interest Margin = NetInterest Income/ Total AssetsNon-Interest Income = Non-Interest Income /TotalAssets
NIM
NII
Investment Activities Investment in Govt. securities/Total Assets Other Investment/Total Assets
IGSEC
OI
So our profitability model would be as follows:
ROA = β0 + β1LogA + β2CA + β3LA + β4NPL + β5DP + β6NIM + β7NII + β8IGSEC+ β9OI + ε
Hypotheses of the Study
The previous discussion in the overview of the banking sector of
Bangladesh and the case study of AB bank Ltd. sections lead us to
predict the following hypothesized relationships with respect to the
profitability:
• Hypothesis H1a: Asset size measured by natural logarithm of total
4. Research Methodology Cont..
• Hypothesis H1a: Asset size measured by natural logarithm of total
assets (logA) has a significant positive impact on ROA
• Hypothesis H2a: Net Interest Margin (NIM) has a significant
positive impact on ROA
• Hypothesis H3a: Banks with more diversified income measured by
Non-Interest Income (NII) tend to be more profitable
• Hypothesis H4a: Investment activities mainly in quoted and
unquoted shares and debentures of private sectors measured by
Other Investment (OI) have a significant positive impact on ROA20
5. Analysis of The Profitability Determinants
Descriptive Statistics
Year ROA Log A CA LA NPL DP NIM NII IGSEC OI
2009
Mean 1.27% 24.96 8.10% 69.03% 6.42% 82.18% 2.39% 3.13% 10.86% 1.40%
Max 3.19% 26.35 23.36% 82.35% 80.99% 89.41% 3.99% 5.05% 31.06% 6.25%
Min -10.85% 23.67 -6.36% 54.83% 0.94% 68.66% 1.25% 0.54% 1.87% 0.00%
Std. Dev. 2.35% 0.47 4.17% 6.87% 14.54% 4.93% 0.61% 1.10% 6.10% 1.52%
21
• Average ROA of 2010 is higher than that of 2009.
• Average NII were higher than the NIM for both the year.
•The percentage of other investment is not so high for both the year.
2010
Mean 1.86% 25.21 8.21% 71.68% 5.13% 79.76% 2.75% 3.70% 8.99% 2.12%
Max 5.10% 26.52 14.86% 83.75% 61.60% 88.57% 4.19% 6.72% 22.63% 7.40%
Min -7.29% 23.65 -31.14% 53.08% 1.14% 68.02% 1.36% 0.42% 0.02% 0.05%
Std. Dev. 1.93% 0.48 7.81% 6.11% 10.88% 5.76% 0.70% 1.36% 4.68% 1.59%
5. Analysis of The Profitability Determinants cont..
Correlation Matrix among Independent Variables
Log A CA LA NPL DP NIM NII IGSEC OI
Log A 1
CA -0.3717 1
LA 0.0046 0.2166 1
NPL -0.4868 0.5290 -0.0696 1
DP 0.3612 -0.5227 0.1807 -0.5012 1
NIM 0.4200 -0.0270 0.0978 -0.2761 -0.1599 1
NII 0.3241 -0.1218 -0.3255 -0.4217 0.0347 0.0154 1
20
09
22
NII 0.3241 -0.1218 -0.3255 -0.4217 0.0347 0.0154 1
IGSEC 0.1151 -0.2025 -0.5984 -0.1426 0.1240 -0.2921 0.6073 1
OI 0.0981 0.0324 -0.0340 -0.1762 -0.0513 0.1661 0.3159 -0.1398 1
Log A CA LA NPL DP NIM NII IGSEC OI
Log A 1
CA 0.6172 1
LA 0.0195 -0.1567 1
NPL -0.5994 -0.9245 -0.0598 1
DP 0.0669 0.0348 0.4133 -0.2797 1
NIM 0.3247 0.1383 0.0737 -0.1456 -0.1585 1
NII 0.2360 0.5665 -0.2162 -0.4488 -0.3031 0.1568 1
IGSEC 0.1545 0.3870 -0.5135 -0.3128 0.1042 -0.0580 0.4293 1
OI 0.1606 0.3405 -0.1891 -0.2250 -0.2494 0.4684 0.5737 0.0979 1
20
10
There is no prima
facie evidence of
multicollinearity for
both the year.
5. Analysis of The Profitability Determinants cont..
Regression Statistics
2009 2010
Multiple R 0.9885 0.9855
R Square 0.9772 0.9711
Adjusted R Square 0.9669 0.9581
Standard Error 0.0043 0.0039
Observations 30 30
23
F 95.1505 74.7313
Significance F 0.0000 0.0000
• The value of R Square is 0.9772 (0.9711) in the year 2009 (2010) which
reflects that the regression model explains 97.72% (97.11%) of the
variation in ROA.
• F-statistic is very much significant. Significance F≈0.000 at 95 percent
confidence interval suggesting that both the model are useful to
determine the determinants of ROA..
5. Analysis of The Profitability Determinants cont..
Regression Statistics
2009 2010
Coefficients t Stat P-value Coefficients t Stat P-value
Intercept -0.0191 -0.3554 0.7260 -0.0488 -0.8944 0.3817
Log A 0.0015 0.6225 0.5406 -0.0004 -0.1684 0.8679
CA -0.1704 -6.2757 0.0000 0.1305 3.4777 0.0024
LA 0.0471 2.7490 0.0124 0.0167 0.8786 0.3901
24
LA 0.0471 2.7490 0.0124 0.0167 0.8786 0.3901
NPL -0.1113 -12.5910 0.0000 -0.0406 -1.5478 0.1373
DP -0.0471 -1.9188 0.0694 0.0447 2.0676 0.0519
NIM 0.1751 0.9814 0.3381 0.1245 0.9062 0.3756
NII 0.4152 3.2677 0.0039 0.4540 4.7546 0.0001
IGSEC 0.0309 1.2741 0.2172 -0.0323 -1.2864 0.2130
OI 0.1373 2.1722 0.0420 0.1331 1.8856 0.0740
• The coefficient of NII is the highest for both the year.
5. Analysis of The Profitability Determinants cont..
• Hypothesis H1a: Asset size measured by natural logarithm of totalassets (logA) has a significant positive impact on ROA
•Coefficient = 0.0015 and -0.0004
t= 0.6225 and -0.1684
p= 0.5406 and 0.8679
Hypothesis Test
p= 0.5406 and 0.8679
Result: Rejected
• Hypothesis H2a: Net Interest Margin (NIM) has a significantpositive impact on ROA
Coefficient =0.1751 and 0.1245
t= 0.9814 and 0.9062
p= 0.3381 and 0.3756
Result: Accepted25
5. Analysis of The Profitability Determinants cont..
• Hypothesis H3a Banks with more diversified income measured by Non-Interest Income (NII) tend to be more profitable
Coefficient = 0.4152 and 0.4540
t= 3.2677 and 4.7546
p = 0.0039 and 0.0001
Result: Accepted
Hypothesis Test
Result: Accepted
• Hypothesis H4a: Investment activities mainly in quoted and unquoted shares and debentures of private sectors measured by Other Investment (OI) have a significant positive impact on ROA
Coefficient = 0.1373 and 0.1331
t= 2.1722 and 1.8856
p= 0.0420 and 0.0740
Result: Accepted
26
6. Conclusion and Recommendations
Asset size:
– No 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:
– It is always considered to be the main source of income and found to have
positive impact on profitability
Non-interest income:
Major Findings
Non-interest income:
– The most significant variable which affects the profitability
– This indicates that greater diversification in banking activities positively
influence profitability
Investment activities:
– Other Investment- mainly in shares and debentures (quoted and unquoted) of
private sectors have 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 27
6. Conclusion and Recommendations Cont..
• Diversified banking activities- bring more new and innovativeproducts and services - can have argument whether it should bewelcomed or not
• Diversification reduces risks, but if the earning includes volatiletrading activity in higher proportion the risk may become higher.
• More exposure in the capital market may bring more risk – when
Policy Relevance
• More exposure in the capital market may bring more risk – whenspeculation rather than the real financial indicators is dominant.
• New and Innovative products- create more complexity- customerscan be exploited by higher fees and commission.
Non-traditional activates of banks (other than deposit taking andlending) may lead banks to higher exposure to the risk. So, from theregulatory perspective, risk management should be the key focus.
28
6. Conclusion and Recommendations
The policy direction should be directed in such a way which willenhance the resilience and efficiency of the financial institutionswith the aim of intensifying the robustness as well as stability ofthe banking sector.
• Capital adequacy should be emphasized so that banks are ableto withstand any negative shock
Recommendations
to withstand any negative shock
• Ring-fencing traditional banking from investment bankingactivities
• Putting limit on the exposure to risk taking investmentactivities can be one of the way to minimize the risk
• The risk taking investment activities also should be monitoredvery closely by the supervisor
• Fees and commission should be monitored and managed sothat a customer is not deceived
29
Future Research Direction
• Inclusion of macroeconomic variables such as
GDP growth rate, inflation rate (INF) and real
interest rate (RI).
6. Conclusion and Recommendations Cont..
interest rate (RI).
• Use of Panel Data Set.
• To analyze the linkage between the bank’s
profitability and their exposure to the capital
market more intensively
30
31
