Performance Analysis Of Commercial Islamic And Conventional

Published Date: 02 Nov 2017

A thesis submitted in partial fulfillment of the requirements for the

Degree of MBA (Master of Business Administration)

Abstract:

Banks are one of the important player in the financial system in any economy. The present study examines the performance of commercial banks in Bahrain. The study is conducted for eight banks for the period of 2001 to 2011. The study mainly uses secondary data for analysis. Regression , Correlation analysis along with mean, median and standard deviation is calculated. The study helps the investors in understanding the performance of the banks taking into consideration various criteria’s. The study is useful for various stakeholders like bankers, investors, Government etc. This gives guidelines to banker to understand the impact of one variable on another. It also gives guidelines to the bank as to where they have to improve. To educates the investors in taking decision regarding the future prospects of the company to channel their investment in different portfolio of securities.

Key words: Banks, performance and analysis

Performance Analysis of Commercial (Islamic and Conventional) Banks in Bahrain

Supervisor

Table of Contents

Chapter 1 Introduction 4

Chapter 2 Literature Review 11

Chapter 3 Research Methodology……………………………………………………………16

Chapter 4 Discussion , Results and Findings 19

Chapter 5 Conclusions 43

References 45

Introduction

Banking system occupies an important place in a nation’s economy. The banking institution is indispensable in modern society. It plays a pivotal role in the economic development of a country and forms the core of the money marketing in advanced country. Banking systems are important aspects of any economic system, providing financial resources for industry, employment creation and overall development. Banks also play an important role in the economy and for the development of the industry.

Financial performance of banks guides to assess the results of a firm's policies, performance, efficiency and effectiveness in monetary terms. These results are shown in the firms return on investment, return on assets, and profit earning. It also guides us to assess how a bank is using its financial and other resources to earn profit. Financial performance evaluation includes net operating income, earnings before interest and taxes, profit after taxes and net asset value. Rather, a thorough assessment of a company’s performance should take into account many different measures. Financial performance is a measure of how efficiently a bank use assets and other resources to generate revenues. This is also used as a general measure of a firm's overall financial condition for a given period of time, and can be used to compare similar firms in the same industry or to compare industries with each others.

Finance and its function play a very major role in determining the profitability and stability of the business. Most of the studies in financial performance analysis of the banks have more stress in comparing financial results of Islamic and non Islamic banking sector undertaking. The present study is undertaken to find out and evaluate financial performance of commercial banks in Bahrain.

Research Overview

Commercial banks in Bahrain have undergone immense regulatory and technological changes. The entry of large foreign banks in the retail banking environment and the recent financial crisis is posing a tough competition for financial institutions in Bahrain. There is an increase in operating expenses due to regulatory requirements, technological and financial innovation. So the need was felt to make a thorough study of the performance of the banks in Bahrain with relation to its profitability, liquidity and credit quality. The rationale behind this study is to explore performance of banking sector of Bahrain.

Financial performance analysis is used to identify the trends and relationships between financial statement elements. Both internal management and external stakeholders of the financial statements need to evaluate a company's profitability, liquidity, and solvency. Interests of various stakeholders are affected by the financial performance of a firm. Therefore, analysis of finance performance of the firm becomes very significant. The type of analysis varies according to the specific interest of the party involved. Creditors are interested in the liquidity of the firm; Bond holders are interested in the cash-flow ability of the firm. Investors are interested in earnings as well as stability of these earnings and Management is interested in internal control, and better performance of the firm. The most common methods used for financial statement analysis are trend analysis, common-size statements, ratio analysis, time series analysis, cross sectional analysis and combined analysis.

Financial ratios are employed to measure the performance of these banks in terms of its profitability, liquidity and credit quality. The tools like correlations and regression analysis is also employed to analyze the various performance indicators taken under this study. The data analysis for correlations and regression is done using SPSS software.

Research Problem and significance

The statement of the problem is to research about the financial performance analysis of eight commercial banks of Bahrain i.e., Albaraka Islamic Bank, Kuwait Finance House, Bahrain Islamic Bank, Bahrain Saudi Bank , BBK, National Bank of Bahrain ,Bahrain Development Bank and Ahli United Bank from the period 2001-2011. The study is undertaken to understand the correlation among the financial performance measured by return on assets and interest income, and the independent variables. As an investor (depositors) or creditors point of view, it becomes important to study the financial performance of a bank. If the performance is not up to the standard then it would create a problem or can cause failure of a bank in near future. So from a safety point of view it is very necessary to study financial health and performance of any bank. The study mainly focuses on correlation and regression to determine the degree of relationship between dependent variables and independent variables at 5% significance level. The variables include profitability(ROA and ROE), efficiency( cost to income), liquidity(liquid assets to total assets), leverage (equity to total assets) and financial strength(capital adequacy).

Research questions and objectives

The study is undertaken to answer various key issues like, whether the financial performance of the banks of Bahrain are good, to analyze their performance by taking into account various ratios and also to determine the relationship between various performance indicators using regression and correlations. The analysis of financial statements responds to key questions like:

What is the ability of the bank to pay short and long debt?

Are the assets underutilized?

Whether the performance of the bank is at par with the level of investment?

In what areas the bank is demonstrating success or failure?

The various objectives behind this study are:

To analyze the operational and financial performances of selected commercial banks in Bahrain using ratio analysis technique.

To study the profitability and Solvency position of selected commercial banks in Bahrain during the study period.

To test the predetermined hypothesis relating to the financial performance of the banks in Bahrain.

To explore the financial trends of various performance indicators.

To explore the possible areas of improvement, if any.

Research methodology

The study of analysis of financial performance of selected commercial banks in Bahrain is descriptive in nature. The study mainly uses secondary data sources like annual reports of various banks and their websites. Eight banks are selected for the study. These sample banks are selected on the basis of their financial performance and judgment. Convenience sampling method is used to select the banks. Only commercial banks are selected for the study. It includes both Islamic and conventional banks. The study is conducted for the period of period of 2001 to 2011.

As research topic is financial analysis, a lot of information and data are required to form the substances for the analysis. Hence, the financial data from the companies under the study are required to compute, calculate and interpret the financial ratios. This study entails the development of conceptual and theoretical structure prior to its testing through empirical observation.

Contribution to existing knowledge

Financial institutions are a unique set of business firms whose assets and liabilities, regulatory restrictions and operating activities make them an important subject of research, particularly in scenario of emerging financial sectors. Study in the area of financial performance analysis will not only help in understanding the performance of the company but also helps in contributing to the existing knowledge in this domain by providing a basis for projecting future and clues about how the company will respond to these future situations.

Structure Of the project

The study is divided into 6 chapters which are as under:

Chapter1: Introduction

This chapter gives the brief introduction to the topic by the way of holistic view of the research that is being undertaken and also includes details about the Research Problem and significance, Research questions and objectives, Research methodology, Contribution to existing knowledge and Structure of the project.

Chapter 2: Literature review

This chapter deals with the literature on various studies that have been already undertaken in this area.

Chapter 3: Research Methodology

This chapter throws light on the research methods, samples, Hypothesis, collection of data tools and techniques for analysis and the research design

Chapter 4: Discussion and Results & findings

This chapter would give the hypothesis testing results, correlation and regression analysis and give the findings based on the analysis of data.

Chapter 5: Conclusion and recommendations

This chapter would draw a conclusion by summarizing the research work undertaken and thereby gives useful recommendations based on the findings of the study.

CHAPTER 2

LITERATURE REVIEW

Introduction

The analysis of commercial bank performance is carried out by many researchers in different countries. The bank performance with regard to Islamic and conventional banks is done to understand their effectiveness. The researcher has taken into account various articles on bank performance in Bahrain and other countries of the world.

Bashir, 2000; Haron, 2004; Al-Kassim, 2007; Zantioti 2009, in their reveals that banking financial performance is affected by internal and external determinants. It also reveals that ROA and ROE are very important indicators of profitability of banks.

Bashir, 2000; Haron, 2004; Burhonov, 2006; Al-Kassim, 2007 in their work says that the internal factors that pressurize banking performance are bank size, leverage, loans, short-term funding, overhead, and owners equity and GDP per capita is the external variable. Literatures reveal that financial performance of Islamic banks is positively related to equity and debt financing so, if debt and equity are high, Islamic banks should be more profitable. The study also finds that there s positive correlation between leverage profitability, Bashir (2000).

M. Raquibuz Zaman and Hormoz Movassaghi (2001) in their workemphasizes on the growth of Islamic banking. The study examines and analyses the major products and services offered by various Islamic banks. The findings of the study states that the products and services offered by the Islamic banks do not conform to the traditional Islamic principles

Haron (2004) in their study found that expenditures and profitability are positively correlated. It also reveals that the size of the Islamic banks only had a significant positive correlation with expenditure but was not significant with profitability measures.

Chen et al. (2005) applied frontier analysis using DEA to examine the cost, technical and locative efficiency of 43 Chinese commercial banks during the period 1993 to 2000. In their study they used inputs such as interest expenses, non-interest expenses including administrative expenses, interest paid on deposits, and the price of capital. Outputs used are loans, deposits and non-interest income. The results of the study showed that the large state-owned banks and smaller banks are more efficient than medium sized Chinese commercial banks. Moreover, technical efficiency consistently dominates the locative efficiency among commercial banks in China.

Burhonov (2006) found that there is no clear cut relation between short-term funding and profitability. The regression analysis reveals that the impact of macroeconomic variables, GDP on profitability is not conclusive.

Alkassim (2007) is of the opinion that Return on Assets for Islamic banks in GCC has positive correlation with total assets and total expenses. Zantioti (2009) in their study reveals that equity to total assets and GDP per have a significantly positive impact on profitability of Islamic bank.

Noor Ahmed Memon(2007), in his paper points out the role of Islamic banks as financial mediators and its importance to the society. The study reveals that Islamic Banks entering directly into areas like trade& commerce, industry and agriculture etc is not beneficial as it implies that banks are actually deviating from their actual role as a financial intermediary.

Usman et al (2009) studied on banking system efficiency dynamics with banking sector reforms effect in Pakistan. They selected a data set of 20 commercial banks of Pakistan and measure their efficiency using Data Envelopment Analysis Malmquist Productivity Index of Total Factor Productivity (TFP) from 1990-2005.The index measures the total factor productivity change between two data points for a given period of time. The results supported the hypothesis that the financial reforms improved the level of efficiency in banking sector in Pakistan.

David A. Grigorian found that banks in Bahrain are lagging behind their Singaporean counterparts and there is high competition from other countries in the region. It also reveals that in terms of efficiency Bahrain banks operate at par with the banks in Singapore and their closest competitors in Qatar and the United Arab Emirates.

Mohammad Hassani (2010), in his study addressed some of the issues and challenge that is faced by islamic banking in Iran.

Hameeda Abu Hussain and Jasim Al-Ajmi (2011), in their work emphasizes that Bahrain Banks have a clear understanding of risk, and have efficient risk management practices. It is also found that the credit, liquidity and operational risk are very important risks facing both Islamic and conventional banks. Furthermore, Islamic banks differ significantly from conventional banks in risk management practice. The study also says that the level of risk faced by Islamic bank is significantly more than conventional banks.

Kaleem (2000) analyzes the Malaysian data over the period of January 1994 to December 1999 in order to investigate the performance of Islamic and conventional banks in pre and post global financial crisis 1997-1998. The study concludes that the Islamic banking system is more crises-proofed compared to the conventional banking system due to its asset-linked nature.

Kassim and Majid, (2010) conduct a study aimed to arrive at empirical evidences on the impact of financial shocks (the 1997 and the 2007 financial crises) on the Islamic banks vis-a-vis the conventional banks in Malaysia. The study finds mixed evidences on the impact of the macroeconomic shocks on the Islamic and conventional banks. While the results based on the descriptive statistics indicate that the Islamic banks are relatively resilient to the financial shocks, the results based on the more robust econometric analysis reveal otherwise. The results based on

the IRF analysis show that the Islamic financing responded significantly to macroeconomic shocks in non-crisis and 2007 crisis periods. The VDA results suggest that both Islamic and conventional banks are vulnerable to financial shocks.

Hassan and Dridi (2010) compare the performance of Islamic banks (IBs) and conventional banks (CBs) during the recent global crisis by looking at the impact of the crisis on profitability, credit and asset growth, and external ratings in a group of countries where the two types of banks have significant market share. The study suggests that IBs have been affected differently than CBs. Factors related to IBs‘business model helped limit the adverse impact on profitability in 2008, while weaknesses in risk management practices in some IBs led to a larger decline in profitability in 2009 compared to CBs. IBs' credit and asset growth performed better than did that of CBs in 2008–09, contributing to financial and economic stability. External rating agencies re-assessment of IBs‘risk was generally more favorable.

Beck et al (2010) compare the performance of conventional and Islamic banks during the recent global crisis by looking at the impact of the crisis on business orientation, efficiency, asset quality, and stability in countries with data on at least four banks. The study suggests that Islamic banks seem more cost-effective than conventional banks in a broad cross-country sample. On the other hand, conventional banks seem more cost-effective than Islamic banks in a sample of countries with both Islamic and conventional banks. However, conventional banks that operate in countries with a higher market share of Islamic banks are more cost-effective but less stable. There is also consistent evidence of higher capitalization of Islamic banks and this capital cushion plus higher liquidity reserves explain the relatively better performance of Islamic banks during the recent crisis.

This study tries to fill the gap by investigating empirically the impact of financial crisis towards the banking performance for conventional banking industry in Bahrain. In general, like other GCC banks, banks in Bahrain were not as much directly exposed to the securitized and structured financial products (Ellaboudy, 2010). Therefore, Bahraini banks are expected to be generally less impacted by the recent global financial crisis than other emerging economies. The abundance of financial resources for Bahrain and other GCC countries, in addition to the initial macro intervention policies taken by Bahraini government, should help to mitigate the adverse impact of the current global financial crisis (Ellaboudy, 2010).

Conclusion:

There are several studies on bank and their performance. Many studies are focused on comparing Islamic bank performance with conventional banks. There are studies with regard to impact of crisis on bank performance. There are studies with regard to risk levels of various banks. There are few studies on overall bank performance measurement.

CHAPTER- 3

RESEARCH METHODOLOGY

Introduction

Research methodology is the crux of any research. An effective research requires the strong research methodology. It includes the description about data sources used, techniques used for analysis, sampling methods and scope of the study.

3.1 Data sources

The data for the study is collected from the financial statements of Albaraka Islamic Bank, Kuwait Finance House, Bahrain Islamic Bank, Bahrain Saudi Bank , BBK, National Bank of Bahrain ,Bahrain Development Bank and Ahli United Bank to achieve the above mentioned research objectives. The annual report from 2001-2011 of selected banks are used to assess the performance of banks in Bahrain. The study has also used other secondary sources like relevant magazines, journals, websites, newspapers etc to gather the necessary information.

3.2 Tools and Techniques of Data Analysis:

Various methods of convectional statistics like regression, trend analysis and simple correlation are deployed to process the data. These techniques are used to understand the inherent features of the phenomenon under the study. The study has also used the tools like multiple regression and correlation matrix for better analysis. To investigate the correlation between dependant and independent variable at 0.05 and 0.01 levels of significance Pearson Correlation is used. All the statistical calculations are done with the help of SPSS software package. Moreover some key financial ratios are calculated to understand the performance of the banks in terms of profitability, liquidity, solvency and its credit quality.

3.3 Hypothesis:

A test of hypothesis involves making a decision between null and alternate hypothesis in which one hypothesis is assumed to be true. The following hypothesis is taken into consideration regarding the study.

Null hypothesis is accepted if the correlation coefficient shows a significant positive relationship among the selected variables, but if the positive correlation is not significant alternative hypothesis is accepted.

Hypothesis used in the study are:

Hypothesis 1

There is impact cost to income (efficiency) on ROE (profitability) of banks in Bahrain.

Hypothesis 2:

There is impact of capital adequacy (financial strength) on ROA and ROE(profitability) of banks in Bahrain.

Hypothesis 3:

There is impact of leverage ratio on profitability (ROA and ROE) of banks in Bahrain.

Hypothesis 4:

There is positive correlation between customer deposits to profitability (ROE and ROA) of banks in Bahrain.

3.4 Testing Hypothesis:

ROA and interest income are the dependant variable which has an impact on the financial performance of the bank. The independent variables are total assets of the bank, asset utilization ratio which measures the asset management by the bank and the operational efficiency of the bank.

Correlation between the dependant and independent variables is calculated by analyzing the data for all the above variables from 2001-2011 to examine the influence of independent variables on the dependent variable. The above hypotheses are tested using techniques like regression and correlation.

Selection of Sample

For the study we have selected both Islamic and non Islamic banks as a sample. We used random sample and selected even banks as a sample for the study. The selected eight banks are: Albaraka Islamic Bank, Kuwait Finance House, Bahrain Islamic Bank, Bahrain Saudi Bank, BBK, National Bank of Bahrain, Bahrain Development Bank and Ahli United Bank. All these eight banks are leading banks with strong business history.

Study Period:

The study covered a period of ten years i.e. from the period 2001-2011. These ten years are event full year because during these ten years global economy experienced financial crisis and economic slowdown two times. Therefore, the study period is very significant.

Conclusion

The present study is descriptive in nature. It includes financial analysis. Te study is not survey based. It is analysed based on secondary data which is used from annual reports, articles from SSRN, Proquest and Emerald journals. Bank websites are also used. The study is conducted for ten years (2001 to 2011).

CHAPTER 4

RESULTS AND FINDINGS

DISCUSSION

Financial ratios are employed to measure the performance of these banks in terms of its profitability, liquidity and leverage. The tools like correlations and regression analysis is also employed to analyze the various performance indicators taken under this study. The data analysis for correlations and regression is done using SPSS software.

ROA and interest income are the dependant variable which has an impact on the financial performance of the bank. The independent variables are total assets of the bank, asset utilization ratio which measures the asset management by the bank and the operational efficiency of the bank.

Correlation between the dependant and independent variables is calculated by analyzing the data for all the above variables from 2001-2011. An attempt is made to examine the influence of independent variables on the dependent variable.

The performance of banks can be measured in various parameters. The most important parameter in measuring the financial soundness or performance of banks is profitability ratios. The efficiency of banks are measured in terms of cost to income ratio. The liquidity is measured in terms of liquid assets to total assets proportion. The leverage is measured in terms of proportion of equity to total assets. Hypothesis is framed after looking into the various research carried out in the same field by different authors. Hypothesis is tested using tools like regression and correlation analysis along with mean, median and standard deviation. In this regard, ROA, ROE of eight selected banks are calculated for ten years. Return on assets is the comparison of net income and total assets. This shows the income generated by banks on its assets.

Analysis Return on Assets (ROA) of banks

Table 1 shows the Return on assets of banks. Return on assets of selected eight banks is calculated for ten years (2001-2011).

Table 1: Analysis Return on Assets (ROA) of banks. (Figures in %)

 

ROA

 

AUB

BBK

NBB

BIB

BSB

BDB

KFH

AIB

2011

1.19

1.15

1.91

-2.07

0.94

0.15

1.24

0.22

2010

1.10

1.60

1.89

-4.24

0.60

0.49

1.81

0.47

2009

0.96

1.54

2.02

-2.13

-2.44

0.64

4.89

-2.91

2008

1.31

1.25

1.71

2.55

-2.95

3.31

3.58

0.21

2007

1.56

1.43

2.19

3.79

1.74

1.21

5.30

0.66

2006

1.24

1.94

2.20

3.00

1.64

0.71

1.42

-0.58

2005

1.37

1.95

2.04

2.31

1.41

0.68

7.50

0.70

2004

1.31

1.81

2.08

1.45

1.48

0.42

4.69

0.23

2003

1.39

1.77

1.81

1.08

1.19

-1.18

4.6

0.56

2002

1.16

1.65

1.75

1.00

-12.63

1.35

5.2

1.31

2001

1.18

1.50

1.69

1.41

2.01

1.26

4

1.25

Mean

1.25

1.6

1.94

0.74

-0.637

0.82

4

0.19

Median

1.24

1.6

1.91

1.41

1.19

0.68

4.6

0.47

Std. Deviation

0.16

0.26

0.18

2.49

4.3163

1.08

1.9

1.15

From the above table, it is clear that KFH has highest mean ROA compared to other banks. But recently, that is 2010 and 2011, there is decrease in ROA for KFH. BSB has least mean ROA compared to other banks. There is fluctuation in ROA in all the banks over the years. There is no clear cut increasing or decreasing trend in terms of ROA.BIB has negative ROA since three years(2011, 2010 and 2009).

The analysis for ROE(Return on Equity) of banks

Table 2 shows the Return on equity of banks for the period of ten years from 2001-2011. This is another measurement parameter of profitability. Return on Equity is calculated using net income and equity capital.

Table 2: Analysis of ROE of banks (Figures in %)

 

ROE

 

AUB

BBK

NBB

BIB

BSB

BDB

KFH

AIB

2011

12.1

13.4

16.6

-17

3.9832

0.34

3.3

1.82

2010

10.7

16.3

16.3

-40

2.4123

1.19

3.2

3.17

2009

8.78

15.2

17.7

-14

-9.318

1.37

1.8

-15.74

2008

13

12.9

16

13.4

-13.06

6.07

16

1.18

2007

14.5

12.6

17.1

13.4

7.0299

1.98

28

4.32

2006

15.4

17.4

16.6

17.5

5.6777

2.9

28

-5.23

2005

12.7

16.9

14

11.4

3.2486

2.73

26

5.41

2004

10.6

16.3

16.2

7.76

5.8282

1.52

25

1.62

2003

9.97

18.7

15.1

6.63

4.902

-3.08

23

3.32

2002

7.57

17.4

14.1

5.83

-298.8

2.14

23

6.09

2001

8.58

14.7

13.8

7.44

13.433

2.92

21

5.96

Mean

11.3

15.6

15.8

1.15

-24.97

1.83

18

1.08364

Median

10.7

16.3

16.2

7.44

3.9832

1.98

23

3.17

Std. Deviation

2.5

2.02

1.33

17.4

91.125

2.2

10

6.4119

From the above table, it is clear that KFH has highest mean ROE compared to other banks. But recently, that is 2010 and 2011, there is decrease in ROE for KFH. BSB has least mean ROE compared to other banks. There is decrease in ROE in 2008 and 2009 for all the banks. This is due to recessionary trend in banking as well as other sectors all over the world. There in negative ROE for BIB for the last three years.

Thus the researcher can conclude that KFH stands first in terms of profitability followed by NBB. This is witnessed by ROA and ROE.

Cost to Income Ratio:

The following table shows the cost to income ratio of selected eight banks for the period of ten years from 2001-2011. This measures the efficiency of banks.

Table 3 showing cost to income ratio (Figures in %)

 

Cost to Income

 

AUB

BBK

NBB

BIB

BSB

BDB

KFH

AIB

2011

68.35

73.36

62.12

75.57

64.52

78.38

58.14

91.18

2010

42.33

94.89

56.67

103.30

82.69

76.47

63.25

65.42

2009

78.77

60.23

57.14

70.12

92.86

63.08

68.35

102.86

2008

48.96

81.32

70.21

31.69

53.85

46.15

42.33

81.05

2007

76.47

78.77

46.15

33.15

47.78

48.28

78.77

73.36

2006

63.08

73.36

48.28

43.69

62.12

75.00

48.96

94.89

2005

46.15

81.32

75.00

42.98

56.67

93.75

86.31

60.23

2004

81.32

76.73

92.86

54.65

57.14

154.55

40.00

81.32

2003

76.73

93.75

53.85

58.90

70.21

76.47

50.00

76.73

2002

46.15

92.86

81.32

67.24

54.17

55.56

66.67

64.34

2001

48.28

53.85

76.73

58.46

29.63

56.53

67.63

60.58

Mean

61.50818

78.22182

65.48455

58.15909

61.05818

74.92909

60.94636

77.45091

Median

63.08

78.77

62.12

58.46

57.14

75

63.25

76.73

Std. Deviation

15.38607

13.11457

14.84366

20.84502

16.9535

30.17098

14.68073

14.42649

From the above table, it is clear that BBK has highest mean cost to income ratio compared to other banks. BIB has least mean cost to income ratio compared to other banks. KFH also got second least cost to income ratio among the banks taken for the study. There is increase in cost to income ratio in 2007.08 and 09 for some banks. This is due subprime crisis in banking industry.

Thus, with regard to efficiency of banks, BIB and KFH stands tall compared to other banks.

Table 4: Capital Adequacy ratio of banks (Figures in %)

Table 4 shows the capital adequacy of banks in Bahrain for the period of ten years from 2001-2011. Capital adequacy takes into account Tier 1 capital and Tier 2 capital to Risk weighted assets. This is the measurement parameter of financial strength.

 

CAR

 

AUB

BBK

NBB

BIB

BSB

BDB

KFH

AIB

2011

16

14.9

25.1

50.1

63.347

60.3

26

27.2

2010

14.1

18.6

22.9

23.2

55.678

57

22

23

2009

15.1

17.5

22.3

42.3

62.767

74.1

23

25.6

2008

13.8

20.1

19.3

45.1

42.733

110

18

20.1

2007

16.2

23.3

28.3

55.1

60.791

133

22

22.2

2006

14.8

24.1

28.7

30.7

86.256

41.3

24

25.33

2005

13.1

20.2

28

33.1

136.15

44.5

22

20.133

2004

20.3

25.7

27.3

28

63.796

54.8

24

22.156

2003

21.8

21

22.8

23.4

54.255

72.6

25

23.869

2002

19.7

15.6

22.8

22.6

9.0713

87.9

21

24.568

2001

20.2

20

19.7

23.7

27.06

113

20

25.668

Mean

16.8

20.1

24.3

34.3

60.173

77.2

23

23.6204

Median

16

20.1

22.9

30.7

60.791

72.6

22

23.869

Std. Deviation

3.08

3.4

3.39

11.9

32.482

30.4

2.3

2.32184

From the above table, it is clear that BDB has highest mean Capital Adequacy ratio compared to other banks. AUB has least mean Capital Adequacy ratio compared to other banks. BSB and BDB has got maximum Tier1 and Tier 2 capital to risk weighted average assets compared to other banks with highest standard deviation. There is no specific trend of Capital Adequacy ratio for various banks.

Liquid assets to total assets of banks

Table 5 shows the Liquid assets to total assets of banks for the period of ten years from 2001 to 2011. This is the measurement parameter of liquidity position.

Table 5: Liquid assets to total assets of banks (Figures in %)

 

Liquid assets to Total assets

 

AUB

BBK

NBB

BIB

BSB

BDB

KFH

AIB

2011

4.70

2.90

9.24

2.76

4.48

0.34

17.83

2.79

2010

3.29

8.15

14.72

2.18

2.90

0.68

12.36

0.24

2009

6.65

12.8

2.18

2.64

8.15

1.03

14.00

0.52

2008

9.24

14.88

2.64

3.19

11.03

6.18

12.87

-0.65

2007

14.72

12.90

2.90

3.73

7.22

3.17

13.23

0.56

2006

2.18

3.29

8.15

2.18

4.70

2.94

15.89

0.07

2005

2.64

6.65

6.18

2.64

3.29

1.53

12.8

0.31

2004

13.23

2.18

3.17

3.42

6.65

2.96

14.88

1.13

2003

15.89

2.64

4.70

2.60

11.28

5.46

12.90

0.79

2002

14.88

2.18

3.29

2.28

9.24

5.40

13.67

0.63

2001

12.90

2.64

6.65

3.02

14.72

6.15

14.22

0.73

Mean

9.12

6.473636

5.801818

2.785455

7.605455

3.258182

14.05909

0.647273

Median

9.24

3.29

4.7

2.64

7.22

2.96

13.67

0.56

Std. Deviation

5.397644

4.939634

3.790994

0.507885

3.72627

2.228164

1.623074

0.846842

From the above table it can be concluded that there is variations with regard to liquidity position of the banks. KFH bank has got highest liquidity compared to other banks. AIB bank has got least liquidity compared to other banks. There is decreasing trend of liquid assets to total assets position for BDB. There is increasing trend of assets to total assets position for AIB. But BIB ahs got stability in its liquidity position compared to other banks.

Equity to total assets of banks

Table 6 shows the equity to total assets of banks for the period of ten years from 2001-2011. This is the measurement parameter of leverage position.

Table 6 : Equity to total assets of Islamic banks (figures in %)

 

Equity to Total assets

 

AUB

BBK

NBB

BIB

BSB

BDB

KFH

AIB

2011

61.26

22.86

43.38

12.07

23.63

42.63

22.86

16.83

2010

24.42

23.38

25.45

10.70

24.85

40.74

23.38

18.54

2009

25.92

24.17

24.31

15.41

26.17

46.86

24.17

18.09

2008

43.38

42.63

24.42

19.04

22.61

54.49

26.54

10.04

2007

25.45

40.74

25.92

28.41

24.72

61.26

21.61

12.20

2006

24.31

46.86

22.86

17.16

28.84

24.42

21.72

13.95

2005

22.86

54.49

23.38

20.21

43.38

25.92

24.72

14.79

2004

23.38

25.92

24.17

18.72

25.45

27.91

27.33

19.82

2003

24.17

43.38

24.85

16.29

24.31

38.24

38.06

23.50

2002

23.63

25.45

26.17

17.17

4.23

43.08

99.44

26.81

2001

24.85

24.31

22.61

18.99

14.96

44.63

99.32

27.36

Mean

29.42091

34.01727

26.13818

17.65182

23.92273

40.92545

39.01364

18.35727

Median

24.42

25.92

24.42

17.17

24.72

42.63

24.72

18.09

Std. Deviation

12.03859

11.6572

5.834656

4.625801

9.390081

11.52485

30.18801

5.681204

There is stability in equity to total assets position for AUB except for the year 2008 and 2011. The same stability is maintained for NBB except for the year 2011. There is decreasing trend with regard to equity to total assets position of KFH. BDB has got highest mean equity to total assets ratio compared to other banks. BIB has got least mean equity to total assets ratio compared to other banks.

Customer Deposits to total assets of banks

Table 7 shows the Customer Deposits to total assets of banks for the period of ten years from 2001-2011. This is the measurement parameter of leverage position.

Table 7 : Customer Deposits to total assets of Islamic banks (figures in %)

 

Customer Deposits to Total assets

 

AUB

BBK

NBB

BIB

BSB

BDB

KFH

AIB

2011

5.40

7.87

4.43

5.46

5.3

5.37

6.92

6.65

2010

6.15

7.63

2.81

5.40

5.9

4.96

7.31

6.02

2009

5.25

4.43

2.97

6.15

6.6

5.46

7.87

2.35

2008

4.43

2.81

5.40

7.31

6.4

5.40

7.63

1.62

2007

2.81

2.97

6.15

4.48

6.6

6.15

7.42

3.36

2006

2.97

7.87

5.25

2.90

5.6

5.25

4.17

4.43

2005

7.87

7.63

3.32

8.15

4.5

3.32

4.13

2.81

2004

7.63

5.40

7.87

4.22

3.7

5.04

4.22

2.97

2003

7.87

6.15

7.63

5.63

3.7

5.23

5.63

9.19

2002

7.63

5.25

7.87

6.23

3.2

5.22

6.23

7.68

2001

3.32

3.32

7.63

6.4

2.9

5.89

6.11

8.19

Mean

5.575455

5.575455

5.575455

5.666364

4.945455

5.208182

6.149091

5.024545

Median

5.4

5.4

5.4

5.63

5.3

5.25

6.23

4.43

Std. Deviation

2.006845

2.006845

2.006845

1.456944

1.399545

0.716642

1.438899

2.627723

From the table, it is clear that there is minor difference in mean Customer Deposits to Total assets of various banks with range of 4.945455 to 6.149091. There is highest mean Customer Deposits to Total assets for KFH compared to other banks. There is least mean Customer Deposits to Total assets for AIB compared to other banks. Based on the figures in the table, it can be concluded that all the banks are having almost similar Customer Deposits to Total assets position with some minor differences.

Regression Analysis

Regression Analysis technique is used to assess the relationship between a dependent variable and two or more independent variable. It helps in understanding how variation in independent variable has an impact on the value of the dependant variable. Regression analysis is carried out for different variables in each country using SPSS.

Hypothesis 1

There is impact cost to income (efficiency) on ROE (profitability) of banks in Bahrain.

Regression Model for ROE (profitability) on cost to income (efficiency):

Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

Model

R Square Change

F Change

df1

df2

Sig. F Change

1

.165

.027

-.135

14.95703

.027

.169

1

6

.696

a Predictors: (Constant), cost to income

The above table is the Model Summary table which reports the strength of relationship between cost to income (efficiency) on ROE. This table provides the R and R2 value. The R value is 0.165, which represents the very low correlation and, therefore, indicates a low degree of positive correlation. The R2 value refers to the coefficient of determination which indicates how much of the dependent variable: ROE (profitability), can be explained by the independent variable cost to income (efficiency).

Coefficients

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Model

B

Std. Error

Beta

1

(Constant)

-13.849

46.184

-.300

.774

COI

.280

.683

.165

.411

.696

a Dependent Variable: ROE (profitability)

The above table, Coefficients, reveals the information of each predictor variable. This helps in predicting the ROE. It is evident from the table that both the constant and ROE do not contribute significantly to the model as the sig. Value is higher than 0.05. The B column under the Unstandardized Coefficients column states the regression equation as:

ROE (profitability)= -13.849+.280 (COI).

COI=cost to income

Thus hypothesis 1 is rejected as there is no significant impact of Cost to income on ROE at 95% confidence level.

Hypothesis 2:

There is impact of capital adequacy (financial strength) on ROA and ROE(profitability) of banks in Bahrain.

Regression Model for ROA (profitability) on capital adequacy (financial strength)

Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

Model

R Square Change

F Change

df1

df2

Sig. F Change

1

.472

.223

.093

1.31935

.223

1.717

1

6

.238

a Predictors: (Constant), CAR

The above table is the Model Summary table which reports the strength of relationship between capital adequacy (financial strength) on ROA. This table provides the R and R2 value. The R value is 0.472, which represents the positive correlation and, therefore, indicates a not high and not low also degree of positive correlation. The R2 value refers to the coefficient of determination which indicates how much of the dependent variable: ROA (profitability), can be explained by the independent variable capital adequacy (financial strength).

Coefficients

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Model

B

Std. Error

Beta

1

(Constant)

2.280

.920

2.479

.048

CAR

-2.978E-02

.023

-.472

-1.310

.238

a Dependent Variable: ROA

The above table, Coefficients, reveals the information of each predictor variable. This helps in predicting the ROA. It is evident from the table that both the constant and ROA contribute significantly to the model as the sig. Value is less than 0.05. Thus there is impact of capital adequacy (financial strength) on the ROA (profitability) of banks. The B column under the Unstandardized Coefficients column states the regression equation as:

ROE (profitability)= 2.280+-2.978E-02 (CAR).

CAR=Capital adequacy ratio

Regression Model for ROE (profitability) on capital adequacy (financial strength)

Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

Model

R Square Change

F Change

df1

df2

Sig. F Change

1

.646

.417

.320

11.57802

.417

4.295

1

6

.084

a Predictors: (Constant), CAR

The above table is the Model Summary table which reports the strength of relationship between capital adequacy (financial strength) on ROE. This table provides the R and R2 value. The R value is 0.417, which represents the positive correlation and, therefore, indicates a not high and not low also degree of positive correlation. The R2 value refers to the coefficient of determination which indicates how much of the dependent variable: ROE (profitability), can be explained by the independent variable capital adequacy (financial strength).

Coefficients

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Model

B

Std. Error

Beta

1

(Constant)

19.406

8.072

2.404

.043

CAR

-.413

.199

-.646

-2.072

.048

a Dependent Variable: ROE

The above table, Coefficients, reveals the information of each predictor variable. This helps in predicting the ROE. It is evident from the table that both the constant and ROE contribute significantly to the model as the sig. Value is less than 0.05. Thus there is impact of capital adequacy (financial strength) on the ROE (profitability) of banks. The B column under the Unstandardized Coefficients column states the regression equation as:

ROE (profitability)= 19.406+-.413 (CAR).

CAR=Capital adequacy ratio

Thus hypothesis 2 is accepted as there is significant impact of capital adequacy (financial strength) on the ROA and ROE (profitability) of banks at 95% confidence level.

Hypothesis 3:

There is impact of leverage ratio on profitability (ROA and ROE) of banks in Bahrain.

Regression Model for ROA (profitability) on leverage ratio of banks in Bahrain

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.575

.331

.219

7.78318

a Predictors: (Constant), ROA

The above table is the Model Summary table which reports the strength of relationship between leverage ratio on ROA. This table provides the R and R2 value. The R value is 0.575, which represents the high positive correlation and, therefore, indicates high degree of positive correlation. The R2 value refers to the coefficient of determination which indicates how much of the dependent variable: ROA (profitability), can be explained by the independent leverage ratio of banks(Equity to total assets).

Coefficients

Unstandardized Coefficients

Standardized Coefficients

T

Sig.

Model

B

Std. Error

Beta

1

(Constant)

24.143

3.810

6.336

.001

ROA

3.656

2.124

.575

1.722

.136

a Dependent Variable: ETA

The above table, Coefficients, reveals the information of each predictor variable. This helps in predicting the ROA. It is evident from the table that both the constant and ROA contribute significantly to the model as the sig. Value is less than 0.05. Thus there is impact of leverage(equity to assets) on the ROA (profitability) of banks. The B column under the Unstandardized Coefficients column states the regression equation as:

ROA (profitability)= 24.143+3.656 (ETA).

ETA=Equity to total assets ratio

Regression Model for ROE (profitability) on leverage ratio of banks in Bahrain

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.612

.170

.031

8.66910

a Predictors: (Constant), ROE

The above table is the Model Summary table which reports the strength of relationship between leverage ratio on ROE. This table provides the R and R2 value. The R value is 0.612, which represents the high positive correlation and, therefore, indicates high degree of positive correlation. The R2 value refers to the coefficient of determination which indicates how much of the dependent variable: ROE (profitability), can be explained by the independent leverage ratio of banks (Equity to total assets).

Coefficients

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Model

B

Std. Error

Beta

1

(Constant)

27.392

3.279

8.354

.000

ROE

.258

.233

.412

1.107

.311

a Dependent Variable: ETA

The above table, Coefficients, reveals the information of each predictor variable. This helps in predicting the ROE. It is evident from the table that both the constant and ROE contribute significantly to the model as the sig. Value is less than 0.05. Thus there is impact of leverage(equity to assets) on the ROE (profitability) of banks. The B column under the Unstandardized Coefficients column states the regression equation as:

ROE (profitability)= 27.392+.258 (ETA).

ETA=Equity to total assets ratio

Thus hypothesis 3 is accepted as there is significant impact of leverage ratio (equity to total assets) on the ROA and ROE (profitability) of banks at 95% confidence level.

Regression Model for cost to income (efficiency) on capital adequacy (financial strength)

Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

Model

R Square Change

F Change

df1

df2

Sig. F Change

1

.076

.006

-.160

8.92021

.006

.035

1

6

.858

a Predictors: (Constant), CAR

The above table is the Model Summary table which reports the strength of relationship between cost to income (efficiency) on capital adequacy (financial strength). This table provides the R and R2 value. The R value is 0.076, which represents the low positive correlation and, therefore, indicates low degree of positive correlation. The R2 value refers to the coefficient of determination which indicates how much of the dependent variable: cost to income (efficiency)), can be explained by the independent variable capital adequacy (financial strength).

Coefficients

Unstandardized Coefficients

Standardized Coefficients

T

Sig.

Model

B

Std. Error

Beta

1

(Constant)

66.217

6.219

10.648

.000

CAR

2.874E-02

.154

.076

.187

.858

a Dependent Variable: COI

The above table, Coefficients, reveals the information of each predictor variable. This helps in predicting the efficiency (cost to income ratio). It is evident from the table that both the constant and Capital adequacy contribute significantly to the model as the sig. Value is less than 0.05. Thus there is impact of Capital adequacy (financial strength) on the efficiency(cost to income ratio) of banks. The B column under the Unstandardized Coefficients column states the regression equation as:

Efficiency(cost to income ratio) =66.217 + 2.874E-02 (COI).

COI=cost to income ratio

Regression Model for cost to income (efficiency) on leverage ratio

Model Summary

Model

R

R Square

Adjusted R Square

Std. Error of the Estimate

1

.220

.048

-.110

9.28147

a Predictors: (Constant), ETA

The above table is the Model Summary table which reports the strength of relationship between cost to income (efficiency) on leverage ratio (equity to total assets). This table provides the R and R2 value. The R value is 0.220, which represents the low positive correlation and, therefore, indicates low degree of positive correlation. The R2 value refers to the coefficient of determination which indicates how much of the dependent variable: cost to income (efficiency)), can be explained by the independent variable leverage ratio equity to total assets).

Coefficients

Unstandardized Coefficients

Standardized Coefficients

t

Sig.

Model

B

Std. Error

Beta

1

(Constant)

12.989

28.659

.453

.666

ETA

.233

.424

.220

.551

.601

a Dependent Variable: COI

The above table, Coefficients, reveals the information of each predictor variable. This helps in predicting the efficiency (cost to income ratio). It is evident from the table that both the constant and leverage do not contribute significantly to the model as the sig. Value is more than 0.05. Thus there is no impact of leverage (equity to total assets) on the efficiency (cost to income ratio) of banks. The B column under the Unstandardized Coefficients column states the regression equation as:

Efficiency(cost to income ratio) =12.989+.233 (COI).

COI=cost to income ratio

Regression Model for cost to income (efficiency) on liquidity ratio (liquid assets to total assets)

Model Summary

R

R Square

Adjusted R Square

Std. Error of the Estimate

Change Statistics

Model

R Square Change

F Change

df1

df2

Sig. F Change

1

.490

.240

.114

3.95622

.240

1.900

1

6

.217

a Predictors: (Constant), LTA

The above table is the Model Summary table which reports the strength of relationship between cost to income (efficiency) on liquidity ratio (liquid assets to total assets). This table provides the R and R2 value. The R value is 0.490, which represents the high positive correlation and, therefore, indicates high degree of positive correlation. The R2 value refers to the coefficient of determination which indicates how much of the dependent variable: cost to income (efficiency)), can be explained by the independent variable liquidity ratio (liquid assets to total assets).

Coefficients

Unstandardized Coefficients

Standardized Coefficients

T

Sig.

Model

B

Std. Error

Beta

1

(Constant)

22.945

12.216

1.878

.109

LTA

-.249

.181

-.490

-1.378

.217

a Dependent Variable: COI

The above table, Coefficients, reveals the information of each predictor variable. This helps in predicting the efficiency (cost to income ratio). It is evident from the table that both the constant and liquidity do not contribute significantly to the model as the sig. Value is more than 0.05. Thus there is no impact of liquidity (liquid assets to total assets) on the efficiency (cost to income ratio) of banks. The B column under the Unstandardized Coefficients column states the regression equation as:

Efficiency (cost to income ratio) = 22.945+-.249 (COI).

COI=cost to income ratio

CORRELATION ANALYSIS

Correlation is used to measure the relationship among the various parameters (profitability, efficiency, capital adequacy, leverage, liquidity and customer deposits to total assets) for measuring the performance of banks by the researcher. Correlation analysis shows the relationship among the factors identified at 5% and 1% significance level. Correlation coefficients were obtained using SPSS. In each cell of the correlation matrix, Pearson’s correlation coefficient, p-value fir two-tailed test of significance and sample size is given.

ROE

ROA

CAR

COI

LTA

ETA

CDT

ROE

Pearson Correlation

1

.821

-.646

.165

.297

.412

.763

Sig. (2-tailed)

.

.013

.084

.696

.476

.311

.028

N

8

8

8

8

8

8

8

ROA

Pearson Correlation

.821

1

-.472

-.158

.684

.575

.913

Sig. (2-tailed)

.013

.

.238

.709

.061

.136

.002

N

8

8

8

8

8

8

8

CAR

Pearson Correlation

-.646

-.472

1

.076

-.270

.242

-.539

Sig. (2-tailed)

.084

.238

.

.858

.518

.563

.168

N

8

8

8

8

8

8

8

COI

Pearson Correlation

.165

-.158

.076

1

-.490

.220

-.396

Sig. (2-tailed)

.696

.709

.858

.

.217

.601

.331

N

8

8

8

8

8

8

8

LTA

Pearson Correlation

.297

.684

-.270

-.490

1

.533

.648

Sig. (2-tailed)

.476

.061

.518

.217

.

.174

.082

N

8

8

8

8

8

8

8

ETA

Pearson Correlation

.412

.575

.242

.220

.533

1

.377

Sig. (2-tailed)

.311

.136

.563

.601

.174

.

.357

N

8

8

8

8

8

8

8

CDT

Pearson Correlation

.763

.913

-.539

-.396

.648

.377

1

Sig. (2-tailed)

.028

.002

.168

.331

.082

.357

.

N

8

8

8

8

8

8

8

ROE=Return on equity

ROA=Return on assets

CAR=Capital adequacy ratio

COI=Cost to income ratio

LTA=Liquid assets to total assets ratio

ETA=Equity to total assets ratio

CDT=Customer deposits to total assets

From the table, it is evident that correlation coefficient between ROE and ROA is 0.821 (this shows high positive correlation) and the p value for two-tailed test of significance is 0.013(p s less than .05) and can be concluded that there is high significant relationship between ROE and ROA variables at 95% confidence level. This shows there is positive relationship between ROA and ROE (parameters of profitability).

From the table, it is evident that correlation coefficient between ROE and CAR is -.646 (this shows negative correlation) and the p value for two-tailed test of significance is 0.084(p s more than .05) and can be concluded that there is no significant relationship between ROE and CAR variables in determining the bank performance at 95% confidence level.

The correlation coefficient between ROE and COI variables is 0.165 (this shows low positive correlation) and the p value for two-tailed test of significance is 0. .696 (p s more than .05) and can be concluded that there is no significant relationship between ROE and COI in determining the bank performance at 95% confidence level.

The correlation coefficient between ROE and LTA variables is 0. .297 (this shows low positive correlation) and the p value for two-tailed test of significance is 0. .476 (p s more than .05) and can be concluded that there is no significant relationship between variables ROE and LTA in determining the bank performance at 95% confidence level.

The correlation coefficient between ROE and ETA variables is 0. .412 (this shows positive correlation) and the p value for two-tailed test of significance is 0. .311 (p s more than .05) and can be concluded that there is no significant relationship between ROE and ETA variables at 95% confidence level.

The correlation coefficient between ROE and CDT variables is 0. 763 (this shows high positive correlation) and the p value for two-tailed test of significance is 0. 028 which is less than 0.05 and can be concluded that there is significant relationship between ROE and CDT at 95% confidence level.

The correlation coefficient between ROA and CAR variables is -0.472 (this shows negative correlation) and the p value for two-tailed test of significance is 0. .238 (p s more than .05) and can be concluded that there is no significant relationship between ROA and CAR at 95% confidence level.

The correlation coefficient between ROA and COI variables is -0.158 (