A stable bank system is an important foundation which help modern economies maintain stability and vigorous development. The purpose of this study is to explore some important features which influence performance of commercial banks industry in Mauritius. For this purpose, 10 commercial banks are selected on the source of obtainability of vital information. The data for these commercial banks are collected from their annual report for 10 years, 2005 until 2014. The descriptive and correlation analysis are performed on the data and it is concluded that Credit risk, Operating expenses, Bank size and asset quality have a significant relationship with ROA (Return on asset) while inflation have a negative significant relationship with ROA and GDP has a positive significant impact on the performance of banks.
The results of this study can help Mauritian’s banks, governments, investors, politicians and shareholders for improving performance in the future.
This section explains the background of the study and problem statement which is the performance of banks in Mauritius. Next, it is followed by research objectives and some hypotheses were proposed for the study.
1.2 Contextual Study
Banking is the most delicate business all over the world and they play very significant role in the economy of a country and Mauritius is no exemption. They influence and help to incorporate the economic activities like poverty eradication, production, resources mobilization and distribution of public finance.
The fastest growing economies in Africa, is Mauritius. One sector of Mauritius that has played an important role in changing the Mauritian economy and who also gone through major evolution that is still in progress is the growing profitability of the banking sector.
Moreover, financial intermediaries execute key financial factors functions in economies, provide payment mechanism, match the financial market demand and supply, work with difficult financial instruments and markets, provide market transparency, perform risk transfer and risk management functions. Banks are the most economies that provide a wide range of different services. While many people consider that banks play a slight role in the economy taking deposit and making loans; ( Rose 2006) states that the banking industry principles roles today are as follows; the intermediation role, payment role, guarantor role and the policy role.
Additionally, assessment of bank performance is important for all parties such as depositors, supervisors and bank managers as well as regulators. Banks gives signal to depositors and investors whether to invest or withdraw funds from the bank. Similarly, it gives direction to bank directors whether to improve its deposits service or loan service.
Also, the study of the determinants of the bank’s profitability becomes a vital issue which could help banks understand the present conditions of the banking industry and the critical factors they should consider in making decisions. Studies such as Dermirguc-Kunt and Huizing (2000), found that bank profitability are usually determined by the internal and external factors. Internal drivers of bank performance can be defined as aspects that are influenced by a bank’s management decisions. On the other hand, external determinants of bank profitability are factors that are out of reach of the control of a bank’s management. They signify events outside the influence of the bank.
Therefore, the study looks into the aspects of the factors that lead to performance of Mauritius domestic and foreign commercial banks during the ten years period, beginning of 2005 until 2014. The main players in this study is the commercials banks. The internal variables that in were selected this study is the Liquidity risk, Credit risk, Operating expenses, bank size and asset quality while external variables designated is the annual inflation and annual GDP.
1.3 Problem Statement
As profitability is an essential factor for the smooth running of any business in today’s competitive market, it has a major impact on the performance of any institutions and banks are not to be excluded. So, it is crucial to identify profits determinants to know which variables influence bank’s profitability so that management can concentrate their attention on it and take decisions to amend the factors. Moreover, these determinants will be used to improve efficiency and profits.
Additionally, most studies on assessing the determinants of banks are from developed countries or developed economies. So, evidences from emerging countries or emerging economies seem to be lacking.
On the other hand, there is a declining trend of average profit for domestic commercial banks compared to foreign banks. (Bank of Mauritius, 2013). Thus, the relatively poor performance of domestic commercial banks in Mauritius needed to be inspected.
1.4 Objectives of the Study
The purpose of this study is to inspect the determinants which could affect the performance of domestic and foreign banks in Mauritius by using financial ratios. The bank performances are measured by Return on Assets (ROA), which is the dependent variable of the whole research. The other objectives of the study are;
a) To provide details on how well banks have been managed and perform all the while.
b) Determine and examine the performances of domestic and foreign banks in Mauritius by using a sample of 10 commercial banks from 2005 until 2014.
c) To examine which factor should banks focus on to optimize their performance.
1.5 Hypothesis of the Study
Based on the objectives, the current study seek to test the following hypothesis.
Bank specific variables (Internal variables)
H’ There is a significant/ no significant relationship between Liquidity risk and profitability of bank
H’ There is a significant/ no significant relationship between Credit risk and profitability of bank
H’ There is a significant/ no significant relationship between Operating expenses and profitability of bank
H’ There is a significant/ no significant relationship between Bank size and profitability of bank
H’ There is a significant/ no significant relationship between Asset quality and profitability of bank
Macroeconomic variable (External variables)
H’ There is a significant/ no significant relationship annual inflation and profitability of bank
H’ There is a significant/ no significant relationship between GDP and profitability of bank
1.5 Chapter Layout
Chapter 1 is the introductory which provides an outline of the study context. It cover introduction, contextual study, problem statement, objectives of the study and hypothesis of the study.
The purpose of chapter 2 is to present the Literature review with relevant theoretical and empirical models.
Chapter 3 is an introductory overview of the research methodology which describes how the research is carried out. It includes research design, sampling design and research instrument. Here, secondary data has been collected from banks annual report for 10 commercial banks from a period of 10 years, 2005 until 2014.
Chapter 4 examines the data collected using Descriptive analysis and Correlation analysis then present the patterns of the outcomes. This chapter also describes the results genuinely.
Chapter 5 provides all conclusions of the entire study. It covers the discussion of the major results, summary of the analysis, implications of the study, limitations of the research and recommendations for future researchers.
In conclusion, chapter 1 is mostly a brief overview of the whole investigation paper which consist a few part. The contextual study and problem statement were discussed and the objectives of the study was also stated. Overall, this chapter provides a complete guidance and the following chapters will be discussed precisely in order to explain more in depth regarding about this research.
This section provides a theoretical and empirical review on the determinants of bank performance. In the literature, bank performance is usually stated as a function of internal and external determinants. The internal determinants originate from bank accounts (balance sheet/profit and loss account) and therefore could be termed micro or bank specific determinants of profitability. The external determinants are factors that are not related to bank management but reflect the economic and legal environment that disturbs the operation and performance of financial institutions. A number of explanatory variables have been proposed for both categories.
2.1 Theoretical Literature
2.2 Drivers of commercial banks profitability
The determinants of bank profitability can be divided into internal and external factors. The internal aspects refer to the factors that originate from bank account while external factors are factors that reflect the legal and economic background that affect bank performance.
Firstly, liquidity risk studied by Olwency and Shipho (2011), revealed that managers of commercial bank often take the liquidity management as one of the most decision making. The measurement of their liquidity is related to the process of deposits and loans. Secondly, credit risk analyzed by Maudos and Fernandez de Guevara (2004), says that bank margins affects profitability, the bank loans ratio is mainly used as a measure of bank liquidity or as a proxy for credit risk when data do not permit the loan loss provision. Next, the operating expenses which were also studied by Olwency and Shipho (2011), where they concluded that operational expenses efficiency is one of the most common ways to determine and measure the management efficiency in banks. Chong (2008) said that poor expenses management is the main factor that lead to poor profitability. Fourth, is the bank size as explained by Pasiouras and Kasmidous (2007), they discover a positive and significant relationship between the size and profitability of a bank. This is because bigger banks are likely to have an advanced management of product and loan diversification than smaller banks and also they benefit from economies of scale. Asset quality, still studied by Olwency and Shipho (2011) claims that a good measure of credit risk or asset quality ratio of loan loss reserve to gross loans will lead to better performance of banks as management will avoid borrowers from defaulting. Aklerlof (2002) concluded that there is an empirical evidence that banks with higher asset quality do in fact will hold more cash and securities because asset quality can change financing and real investment decisions.
Also, corporate governance affects the performance of banks. It is the practices and conducts that guide how a business entity sets its objectives, develop strategies and better plans, monitors and reports its performance and manage its risk (Reddy, 2010). Researches are also of the view that good corporate governance practices lead to better performance of the firm (Chugh, 2009).
Another factor that can affect performance of banks is competition. According to Michael Porter there are certain competitive forces that influence on profitability in every industry. These factors are said to be drivers of competition and profitability in every industry which as well include banking industries around the world. He further explained that it is difficult for firms which function in highly competitive industries to earn positive return on investment. On the basis of the statement it clear that commercial bank profitability is highly influence by certain competitive forces and even some studies have argue that fierce competition within commercial banking industry tends to decrease profits ( Smith, 2012).
Inflation is an external factor which is measured by the annual percentage change in consumer prices. If the inflation is higher, the cost of capital or the interest rate also rises. This indicates that loan demands may decrease and lower the number of borrowers which leads to the funding problem and lower the profits to the bank. Thus, inflation rate should have negative relation to profit performance. Author such as Athanasoglu (2008) focused on inflation and found a positive significant relationship with ROA. On the other hand, Khadil (2009), concluded that inflation has a negative impact on interest margins. Khadil (2009), gave the explanation that ‘that the main activity of bank is lending. The market is therefore based on an offer of credit therefore inflation reduces the demand for credit because it increases uncertainty about the future and it has been proven that if the level of risk aversion decreases for individuals and businesses, it will lead to a decline in lending an performance of banks’.
Another external factor is GDP which is an essential factor which explains how the economy or firms developed so far. If GDP ratio is high, it can denote that banks may increase their profits by obtaining higher demand on borrowing and lending activities. Therefore, GDP might be positively related to profit performance. Goddard (2004), found that there GDP has no impact on performance while Dermiguc-Kunt (2004), find an inverse relationship between GDP and performance of banks. He gave the explanation ‘that in periods of recession the risk of borrower default. To compensate for the increased risk, banks increased interest rate on loans, which improve performance’.
2.3 Empirical Literature
Azam (2012) analyzed the differences and the determinants of domestic and foreign bank profitability in Pakistan banking market. The observation was done between the years 2004 to 2010 on quarterly basis with a sample of 36 commercial banks. The specific dependent variable that has been used is the Return on asset (ROA) and return on equity (ROE). A multiple regression technique has been applied to analyze the internal and external determinants.
The results report that the profitability determinants are not similar from domestic banks. It has also been shown that foreign banks functioning in a market are not only affected by the conditions in the market but also by other factor that could be related to their home markets. It is concluded that local controlled commercial banks in Pakistan are more profitable than foreign controlled ones as far as the volume of profits is concerned which is reflected in the earnings per share.
Similarly, Ayanda (2013) studied the determinants of banks profitability in Nigeria which is a developing country. The bank specific variables used were the return on asset (ROA), return on equity (ROE), and net interest margin (NIM). The independent variables were represented by Total annual assets, loans, annual non-interest income, total annual loans, overhead expenses, bank size, staff salaries, and total loan to total bank deposit and growth rate of broad money. The macroeconomic variables were the Gross Domestic product and inflation. The author makes use of time series data from secondary sources over the period 1980 to 2010. Regression analysis, a cointegration and error correction-model was used to estimate the relationship between profitability and its determinants. The study also made use of panel correlation model.
The findings of this study revealed that capital adequacy through equity to total assets ratio significantly had a negative effect on bank’s profitability both in the long-run and in the short-run in Nigeria. Empirical findings revealed that credit risk variable loan loss provision to total loans had almost perfectly significant negative relationship with profitability in all circumstances. From the macroeconomic variables used, only the growth of money supply is a determinant of bank’s profitability. The growth of money was positively associated with profits in the banking sector.
Ongore (2013) emphasized on the determinants of financial performance of commercial banks in Kenya for ten years from 2001 to 2010. The explanatory was based on secondary data and the data was analyzed using Microsoft excel and econometrics software. A multiple linear regression ant t-statistics were used to determine the relative importance of each explanatory variable in affecting the performance of banks. The major dependent performance indicators used were return on asset (ROA), return on equity (ROE) and net interest margin (NIM). The major determinants (independent variables) were capital adequacy, asset quality, management efficiency and liquidity status.
The study shows that capital adequacy, asset quality and management efficiency significantly affect the performance of commercial bank in Kenya. However, the effect of liquidity on the performance of commercial bank is not strong. The relationship between bank performance, capital adequacy and management efficiency was found to be positive and for asset quality the relationship was negative. The other bank specific factor liquidity management represented by liquidity ratio was found to have no significant effect on the performance of commercial bank in Kenya. It was found that GDP had a negative correlation with ROA, NIM and positive with ROE. On the other hand, inflation had relatively strong negative correlation with financial performance of commercial banks in Kenya.
Likewise, Quin, Yeong and Yunk (2010) explored the performance of local and foreign banks in Malaysia from 2001 to 2010. The data that were used were obtained from local and foreign bank annual report. In order to test the significance of the results, descriptive analysis and correlative analysis were used. Microsoft excel is used to calculate financial ratio for the dependent and independent variables and econometric views was used for data analysis. ROA is used to resemble the performance of bank which is the dependent variable and the independent variable that were examined include bank size, capital ratio, liquidity risk, operating expenses, credit risk, asset quality and debt ratio. A multiple regression line was developed.
In the same manner, Juber and Al-Khawaldeh (2014) investigated the impact of internal and external factors on commercial bank profitability in Jordan from 2007 to 2012 where the author studied 11 domestic commercial banks. The dependent variable that was studied is the return on asset (ROA) and the independent ones were capital adequacy, liquidity and bank size. Return on average asset (ROAA) is used to measure bank performance which is the net profits expressed as a percentage of average total assets. Moreover, multivariate regression analysis was used and a model was developed.
The results demonstrated that internal factors have a significant impact but not capital adequacy and liquidity ratio for the transformed model, which size is insignificant for the transformed and untransformed model. With respect to external factors, inflation, total asset of the deposits money banks divided by GDP and stock market capitalization to total assets was significant associated with the model.
Rachdi (2013) examined the profitability of banks in Tunisia during and before the international financial crisis over the period 2000 to 2010. The measures of profitability that have been used in the study are the return on equity (ROE), return on asset (ROA) and the net interest margin (NIM). The industry- specific factors studied were the capital adequacy (CAP), Liquidity (LIQ), cost-income ratio (CIR), growth of capital (DEP), banks size (SIZE), off-balance sheet activities (OBS) and concentration (HH). The macroeconomic factors that were taken into consideration is the inflation rate (INF) and yearly GDP. Dynamic panel approach was adopted to correct for these potential problems. The linear forms specified as a dynamic model which includes performance as an explanatory variable was as follows. It included the bank specific, industry specific and macroeconomic determinants of bank profitability.
It is found that before the US subprime crisis, capital adequacy, liquidity. Bank size and yearly GDP growth affect positively the performance of the banking sector.
It is concluded that Tunisian banking sector was slightly exposed to the effects of the international financial crisis of its low integration in international financial markets and the stock control by specific and rigorous rules of banks by the central bank.
Besides, Sufian (2011) evaluated the profitability of the banking sector in Korea over the period 1992 to 2003. The sample varied from 11 banks in 1992 to 29 banks in 2000. This gives a total number of 251 bank year observations. Bank profitability which is typically measured by the return on assets (ROA) or the return on equity (ROE) is expressed as a function of internal and external determinant. The internal determinants were the factors that are mainly influenced by bank’s management and policy decisions. Such profitability determinants are the level of liquidity, provisioning policy, capital adequacy, expenses management and bank size. On the other hand, the macroeconomics variables reflected the economic and legal environment and these included inflation and GDP growth. To test the relationship between bank performance and the bank specific and macroeconomic determinants described earlier a linear regression model was estimated.
The empirical findings suggested that Korean banks with lower liquidity levels tend to show higher profitability levels. The impact of credit risk and costs are always negative. Business cycle affects a large pro-cyclical impact on banks’ profits. The industry concentration of the national banking system positively and significantly affects banks profitability.
Still, Sufian and Hubibullah (2009) explored the determinants of bank profitability in a developing country and empirical evidences were obtained from Bangladesh. The dependent variables to measure performance were the ROAA, ROAE and NIM. The independent variables used were Total on loans over total asset (Loans/TA), natural logarithm of total asset (LNTA), loan loss provisions over total asset ( LLP/TL), non-interest oncome over total assets (NII/TA), non-interest expenses over total asset (NIE/TA), total book value of shareholders equity over total asset (EQASS). The macroeconomics variables used were GDP and inflation. The bank specific variables were collected from financial statement of a sample of commercial bank operating in Bangladesh over the period 1997 to 2004. This gives us a total observation of 129 banks. Multivariate analysis was used and a linear regression model was developed.
The empirical findings of the study suggested that bank specific characteristics in particular loans intensity, credit risk and cost have positive and significant impacts on bank performance while non-interest shows negative relationship with bank profitability. The results suggested that size has negative impact on return on average equity (ROAE) while the opposite is true for return on average asset and net interest margin. As far for the impact of macroeconomic indicators, it is concluded that the variables have no significant impact on bank profitability except for inflation which has negative relationship with Bangladeshi bank profitability.
In a comprehensive study, Dermiguc Kunt and Huizinga (1999), examine the determinants of bank interest margins and profitability using bank level data for 80 countries from 1988 to 1995. They find that a larger ratio of bank assets to GDP and a lower market concentration ratio lead to lower margins and profit. The findings also suggested that foreign banks have higher margins and profits than domestic banks in developing countries, while the opposite prevails in developed countries. Similarly, the profitability of European banks during the 1990’s was investigated by Goddard (2004) using cross-sectional, pooled cross-sectional, time series and dynamic panel approach. Their model for their determinant of profitability incorporates size, diversification, risks and ownership types. They that despite intensifying competition that is significant persistence of abnormal profit from year to year. The relationship between the importance of off-balance sheet business in a bank’s portfolio and profitability is positive for UK, but either neutral or negative elsewhere. The relationship between the capital assets ratio and profitability is positive.
Additionally, Erina and Lace (2013), analyzed the commercial banks profitability indicators in Latvia over the period 2006 till 2011. Return on asset (ROA) and return on equity (ROE) were used as the major (dependent) determinant of bank performance. On the other hand, asset size, credit risk, deposit, capital and loans of total asset were used as the independent variable. The macroeconomic variables were gross domestic product and annual inflation. For the assessment of the profitability indicators the authors have used descriptive method and by using spss data determination methods, correlation and regression analysis of the obtained data that have been performed. A linear regression model for determination of the profitability indicators. The authors concluded that profitability has had a positive effect on operational efficiency, portfolio composition and management, while it has had a negative effect on capital and credit risks as measured according to ROA, while according to ROE, positive influence is exerted on composition of the capital portfolio and negative on operational efficiency and credit risk. With regard to macroeconomic indicators, the authors had revealed that GDP had a positive impact on profitability as measured by ROA and ROE.
Acaravci and ??alim (2013), canvassed on the Banking Sector profitability factors in Turkey from 1998 to 2011. Data was collected from three biggest state-owned, privately owned and foreign banks. Return on asset (ROA), return on equity (ROE) and net interest margin (NIM) were used as a proxy for profitability of banks. The bank specific determinants which were thought to have effects on profitability are total credits/ total assets, total deposits/total assets, total liquid assets/total assets, total wage and commission incomes/total assets and total equity/total asset. The macroeconomic determinants studied were the real gross domestic product (GDP), inflation rate, real exchange rate and real interest rate. Long-run relationship between the bank specific ad explanatory variables and profitability was explained using time series econometric models and two different models were developed.
The empirical findings showed that (a) the state- owned banks have a high liquid assets to decrease liquidity risk of banks. The privately owned and the foreign banks have more opportunities to invest in various short term liquid assets. (b) In the privately-owned bank, a bad loan reduces profitability while loans for the foreign bank have a positive impact on profitability. (C) The state owned bank normally should strive to attract more deposits as source of funds. But deposits for the privately owned and the foreign bank have an insignificant impact on profitability. (d) Greater bank activity diversification negatively influences return. (e) The lower the need for external funding, the higher the profitability of the state owned and the privately owned banks. (f) In the state owned and foreign real exchange has a significant impact on profitability.
On the other hand, Bashir (2003) studied the determinants of profitability in Islamic banks across eight Eastern countries between 1993 and 1998. The dependent variable used was the profit before tax, return on asset and return on equity. The other bank independent variables were classified as bank characteristics indicators, macroeconomic indicators, taxation indicators and financial structure indicators. Regression analysis was used to measure performance. Also, by using cross-country panel data, the study shows that the Islamic bank’s profitability measures respond positively to the increases in capital and loan ratios. The results revealed that larger equity to total asset ratio and larger loan to asset ratio interacted to GDP lead to higher profit margins. Moreover, foreign ownership seems to have contributed significantly to Islamic bank’s profitability. The results also suggested that tax factors are much more important in the determinant of bank performance. Last, favorable macroeconomic environment seems to stimulate higher profits. Higher GDP per capita and higher inflation rate seems to have a strong positive impact on performance measures.
Jureviciene and Dofttartaite (2013) assessed the commercial banks activity dependence on macroeconomic indicators in Lithuania. The dependent variables used in the study were net profit, Return on assets (ROA), return on equity (ROE), net interest margin (NIM) and the macroeconomic independent variables used were GDP growth, foreign direct investment, gross salary, foreign trade balance, state budget, inflation and unemployment rate. Secondary data was collected from Baltic States commercial banks. The most important sources of information for commercial banks activities analysis were from the balance sheet and profit and loss statement. Using these reports, ratios was calculated. The effectiveness and efficiencies of different commercial banks were evaluated and compared. Multivariate correlation and regression analysis was used to analyze the data and it was concluded that there is a decline in Lithuanian foreign trade balance and government debt increase the net profit margin of Lithuanian banks. Net profit of Latvian commercial banks was positively dependent on GDP growth. ROA and ROE ratios positively depend on GDP growth and state budget are negatively reliant on foreign trade balance and unemployment rate. Net profit margin is directly dependent on inflation, indirectly on foreign trade balance and unemployment rate.
Similarly, Saeed (2014), analyzed the bank-related, industry related and macroeconomic factors affecting the bank profitability in the United Kingdom. For this study, 73 UK commercials bank are selected and the empirical data for these banks are collected for the period of 2006 to 2012 from bank scope and bank databases. The bank related variables included in the study were return on assets (ROA) and return on equity (ROE) whereas capital-ratio, bank size, loan size, deposits and liquidity are considered as industry-based variables; GDP, inflation rate and interest rate are taken as macroeconomic variables. Regression and correlation analysis were used on these data and it was concluded that bank size, capital ratio, loan, deposit, liquidity and interest rate have positive impact on ROA and ROE while GDP while GDP and Inflation rate have negative impact. It was also concluded that large banks with extensive assets, capital deposits, loans, equity and macroeconomic factors such as interest rate, economic growth and low inflation rate can achieve safely a competitive advantage and thus achieve higher profitability.
Vinch VO (2010), investigated the determinants of bank profitability in Vietnam. To provide a detailed analysis, a number of variables to proxy for profitability was used including net interest margin (NIM), return on asset (ROA) and return on equity (ROE). Other explanatory variables which were used were bank size (SIZE), capital adequacy (CAR), Risk (RISK), productivity (PRO), operation cost (Expense), ownership (OWN), and concentration (CONC) and the macroeconomics variables used were Inflation and GDP. The data sample included 41 domestic Vietnamese commercial banks for the period from 2006 to 2012. Data was collected from Vietnam bureau of statistics and financial reports of all commercial banks. Multivariate linear regression analysis is employed to explore the relationship between bank profitability and the internal and external factors. It was concluded that capital adequacy is an important determinant of bank profitability while size has marginal and insignificant impact on profitability. It was also found that operating expenses positively and strongly affects bank profitability. Likewise, the ownership of banks is constantly negative. On the other hand, macroeconomics variables such as GDP and inflation affect the performance of the banking sector.
Last but not the least, Sanmantrikul (2013), examined the determinants of bank performance on Asian commercial banks. The study focused on determinants of bank performance in term of profitability of Asian commercial banks among 5 countries- Hong Kong, Thailand, Indonesia, Malaysia and Philippines from 2004 to 2011. The dependent variables used in the study were return on assets (ROA), return on equity (ROE) and net interest margin (NIM) while the independent variables used were equity to total assets (ETA), loan to total assets (LTA), non-performing loan to gross loan (NPL), liquidity asset to customer (LA), logarithm to total asset (LNSIZE) and the macroeconomics variables used were inflation and GDP. To test the data panel data, descriptive analysis and Pearson correlation analysis were used. The findings showed that equity to total assets has a positive significant impact on bank performances. In contrary, loan to total assets, non-performing loan to gross loan and logarithm of total assets have negative significant impact on bank performances. Thailand is significantly higher for the rates of both ROE and ROA also higher than Hong Kong for NIM because of higher opportunities in the interest rate spread and lower competitive environment. Conversely Thailand, is significantly lower than Indonesia for net interest margin (NIM).
The determinants of bank performance included liquidity risk, credit risk, operating expenses, bank size, asset quality, inflation and GDP whereas ROA is the measure of bank profitability. All these factors were commonly used in previous researches. In the literature review, it is stated that some factors have positive relationship towards bank profitability while some others of it has negative relationship.
Overall, this chapter has covered the relevant theoretical and empirical related literature on the bank performance. In practice, this study is ought to find out the bank performance of domestic and foreign commercial banks in Mauritius.
In this chapter, we are going to show the dependent and independent variables used, research design, data collection methods, data sampling, research instrument, and data processing and data analysis. We are using secondary data to examine the performance of commercial banks in Mauritius. The data that we used in this research were obtained from bank financial statement.
3.2 Actual Study
The present study aims is to examine the determinants of bank performance in Mauritius. The variables that would be used include return on asset (ROA) which is the dependent variable while independent variable comprises of liquidity risk, credit risk, operating expenses, and bank size and asset quality while the macroeconomics variables consists of inflation and Gross Domestic Product. Dependent variables are dependent towards independent variables which are further explained below.
3.3 Dependent Variable
Return on asset (ROA) is defined as the ratio of net profits to average total assets expressed as a percentage. Return on asset is normally used to compare the performance and profitability between banks as the majority of banks will have a transfer value that is close to their actual market. Gobin (2001), pointed out the ROA has recognized as the key ratio for the estimation of bank profitability and has become the most elementary measure of bank performance in the literature. Rivard and Thomas (1997) also suggested that ROA is the best choice to measure a bank’s profitability because it will not be affected by high equity multipliers.
3.4 Independent Variable
The bank specific independent variables that will be used in the study is Liquidity risk, credit risk, operating expenses, bank size, asset quality while the macroeconomics variables used will be inflation and Gross domestic Product (GDP).
3.5 Data collection methods
3.5.1 Data sources
The data that were collected for this research is secondary data. Based on the researcher Steppingstones (2004), the secondary data is information that we used to complete a research project. The data that we used in this research were obtained from the local and foreign bank annual reports. The annual reports were taken from 10 different banks based in Mauritius. The duration chosen for this research was from the year 2005 to 2014, 10 years. The bank annual reports were obtained through the website of banks and the Mauritius Bankers Association Ltd. From the financial reports, balance sheet statement, profit and loss statement and notes to account data were gathered to calculate financial ratio in order to run the data in Chapter 4, which is the most important mechanism in this research. On the other hand, the data for external factors that is inflation and GDP were obtained from the Mauritius bureau statistics for 10 years, starting from 2005 to 2014.
3.5.2 Sampling Design
The target population in this research is the conventional banks in Mauritius as the main purpose of this study is to examine the performance of domestic banks in Mauritius by using financial ratios. Mauritius has a population of 21 commercial banks which are 6 local banks and 10 are foreign banks. Therefore, in this study a sample of 10 commercial banks were chosen. Table 3.1 shows the commercial banks that were used in this study.
Table 3.1 List of banks used in the study
Mauritius Commercial Bank
State Bank of Mauritius
Mauritius Post and Corporative Bank
Development Bank of Mauritius
Standard Chartered Bank
Hong Kong Shanghai and Banking Corporation
Bank of Baroda
Moreover, the sampling frame that was used in this research is the Mauritian banks. It was divided into two groups which are domestic and foreign banks mainly to find out the performance of both groups of banks. Furthermore, simple random is this research is employed as the sample was allocated into two different groups which are foreign and domestic banks.
3.5.3 Sampling size
The sampling size in this research has a total of 10 banks including 5 domestic and 5 foreign for 10 years. Overall, there are 100 samples in this research. This is due to the widely used financial statements for 10 years for each selected banks. These banks were chosen to determine the impact of bank performances by using financial ratios.
3.5.4 Data analysis
There are five bank-specific independent variables in our study which are liquidity risk, credit risk, operating expenses, and bank size and asset quality while the dependent variable in the study is return on asset. In this study, the data were extracted from the annual report of banks. Then, the financial ratios were calculated using Microsoft Excel by arranging it according to the years, banks and variables. The numbers are easily administered due to the suitability and efficiency provided by the software. After computing the data from excel, the data were exported by exporting to Econometric view in order to examine the relationship between these independent variables and dependent variable. Data analysis was used at the start by using descriptive analysis which provides the degree and directions of these variables.
The macroeconomic variables included in the study is Inflation (INF) and Gross Domestic Product (GDP). The data was collected from the Mauritius bureau statistics during 10 years from the period 2005 until 2014. To analyze the external determinants, regression techniques was used and tested via STATA (version 13) computer software.
3.5.5 Descriptive analysis
Descriptive analysis is used to designate the basic feature of the data in the study. They provide simple summaries about the sample and the measures. They are used to present measureable descriptions in a manageable form. This analysis demonstrate the summary statistics of the data set for the bank performance for both foreign and domestic banks related with the independent variables. It measures the mean, median, maximum and minimum level, standard deviation and kurtosis.
3.6 Multiple regressions
Multiple regressions are a flexible method of data analysis that may be appropriate whenever a numerical variable is to be examined in relationship to any other factors (Berger, 2003). Relationships may be a nonlinear; independent variables may be computable or qualitative and once can examine the effects of a single variable or multiple variables with or without the effects of other variables taken into account (Cohen 2003). In this study a multiple regression line was developed.
Y= b’+ b’x’ + b’x’ + b’x’ + b’x’ + b’x’ + b’x’ + b’x’ + ??
Where, Y= return on asset= net income/total assets
X’= Liquidity Risk= net loan/ deposit and short term funding
X’= Credit Risk= Loan loss provision/net interest income
X’= Operating expenses= Non interest income/total average assets
X’= Asset quality= Non-performing loan/gross loan
X’= Bank size= Log (Total asset)
X’= Inflation (INF)
X’= Gross Domestic Product (GDP)
Where Y is the return on asset and it is the dependent variable. Y is dependent on the other seven independent variables such as X’, is the ratio of net loan to deposit and short term funding which indicates the liquidity of the bank. X’ is the loan loss provision to net interest income which indicates the operating expenses of the bank. X’ is the non-interest expenses to total average assets which indicate the bank’s credit risk. The asset quality is X’ which indicate the ratio non-performing loan to gross loan. X’, which is the bank size by using natural logarithm of total assets. X’ is the annual inflation and finally, X’ is the GDP. All these independent variables are most expected to affect bank profitability. With the use of multi regression analysis, we are able to determine which independent variable will have a superior impact on the bank’s performance.
3.7 Pearson Correlation Coefficient
The Pearson correlation coefficient is a measure of the strength of a linear relationship between variables. Pearson’s can range from -1. -1 shows a perfect negative linear relationship between variables, 0 indicates no linear relationship between variables and 1 indicates a perfect positive linear relationship between variables. This method is used to test the relationship between the dependent and the independent variables.
In order to test the significance of the results, descriptive analysis, multiple regression analysis and correlation analysis were used. All the data and information were collected mainly via internet and the financial reports of the banks. Microsoft excel is used to calculate financial ratio for the dependent and independent variable and econometric views and STATA software are used for data analysis. This chapter provides a brief guide and awareness of the relevant data that are to be used in the next chapter which is data analysis.
DATA ANALYSIS AND FINDINGS
In the earlier chapter, this study has determined the appropriate data to be tested on this chapter to find out the substantial relationship between the performance of banks and other independent variables between domestic and foreign commercial banks in Mauritius, during the period of 2005 until 2014. This chapter is separated into 2 sections. The first provides the descriptive analysis of the data and variables for the study which helps to measure the central tendency. Next, the correlation analysis is studied between performance of banks and each of the independent variables.
4.1 Descriptive Analysis
Descriptive analysis is used to define the simple features of the data in this research. This set of descriptive analysis displayed the several summary statistics for the return on assets for both domestic and foreign commercial banks related with the independent variables that are liquidity risk, credit risk, operating expenses, bank size, asset quality, inflation and GDP in a number of different ways. The movement of the return on assets of domestic and foreign commercial banks in Mauritius during the ten year period correspondingly. Next, the study tests on the relationship of the independent variables with the dependent variables.
4.1 Trend analysis
Table 1: Trend Analysis of ROA of Mauritius Domestic Commercial banks
The figure shows the movements of ROA level of the five domestic commercial banks in Mauritius, through the ten-year period of beginning 2005 until 2014. The ROA level has been changing over the period. The local bank which accounts the highest ROA level (0.0992) as of 2013 SBM bank, while the bank which records the lowest ROA level (-0.0105) as of 2010 Bank One. The lowest figure of Bank One is due to few causes; instabilities in stock price, rise in liability and expenses and fall in assets and income.
Table 2: Trend Analysis of ROA of Mauritius Foreign Commercial bank
The figure illustrate the movement of ROA level for the five foreign commercial bank grounded in Mauritius; through the ten-year period of beginning 2005 until 2014. The ROA level has also been changing in foreign banks. The foreign bank which records the highest ROA level (0.087) as of 2011 Barclays Bank, while the foreign bank which records the lowest ROA (- 0.0065) as for 2007 AfrAsia Bank. One of the reasons that roots AfrAsia Bank’s ROA drop extremely is the decrement in earnings made in that specific year.
4.2 Descriptive analysis for the dependent and independent variables
Table 3 shows the descriptive analysis for both domestic and foreign banks
Variable Obs Mean Std. Dev. Min Max
ROA 100 0.030875 0.017775 -0.0065 0.0992
LIQ 100 3.063834 2.416184 0.112 15.6802
CRE 100 1.253747 0.90637 0.0538 5.275
OPE 100 0.017108 0.01512 0.0001 0.092
SIZE 100 24.56244 4.680382 20.033 54.9817
ASSET 100 0.047426 0.063977 0.0001 0.3337
INF 100 5.51 2.619835 2.5 9.7
GDP 100 4.03 0.809102 2.5 5.4
Sources from annual banks report and bureau statistics of Mauritius
Table 3 represents the descriptive summary statistics. The descriptive analysis discovers and presents an outline of all variables. This research has a total of 100 observations which comprises of 10 years annual report of 10 different domestic and foreign owned commercial banks in Mauritius, for the period 2005 to 2014. Based on the table above, we can see that most of the ratios used in the research are linked to our dependent variables which is the return on asset. Further, the results show that ROA yield a negative value at -0.0065 (0.65%).
4.3 Regression Analysis for the dependent and independent variables
Table 4 shows the regression analysis for both domestic and foreign banks
Combine N Coef. t-statistics
LIQ 100 0.000474 0.672
CRE 100 -0.00159 -2.303
OPE 100 0.216653 5.632
SIZE 100 0.000688 2.49
ASSET 100 -0.05898 -2.31
INF 100 -0.00113 -2.86
GDP 100 0.001608 -2.81
Based on the regression results, the multiple regression equation for the bank specific determinants can be written as the following.
Y= b’+ b’x’ + b’x’ + b’x’ + b’x’ + b’x’ + b’x’ + b’x’ + ??
Return on asset= 0.096230 + 0.000474 LIQ + 0.001589 CRE + 0.216653 OPE + 0.000688 SIZE + (- 0.05898) ASSET (-0.00113) INF + (0.001608) GDP + ??
The intercept of b’ equal to 0.09203 specify that the return on asset will rise by 0.096203 units, when independent variables which are liquidity risk, credit risk, operating expenses, size, asset quality, inflation and GDP equal to zero.
H’= There is a/no significant relationship between liquidity risk and profitability of banks
Primarily, there is insignificant relationship between the ROA and LIQ (Liquidity Risk) with the t-value= 0.672, it has a significant coefficient estimate of 0.000474. When LIQ rises by 1 unit, the ROA will also surge by 0.000474 units. So, any movements in the LIQ would not disturb the ROA. The ratio of net loans to deposit and short term funding is used in this study as a measure of liquidity. A positive effect specifies that the capacity of banks to well manage liquidity. So, the poorer the value of this ratio, the more liquid the bank is. Since liquid assets are related with lower rates of return, a positive relationship is estimated between this variable and performance.
H’= There is a/no significant relationship between credit risk and profitability of banks
Subsequently, the CRE (credit risk) has a significant negative relationship with ROA with the t-value= -2.303, it has a coefficient estimate of -0.001589. When CRE increases, it will cause ROA of banks to decline. The connection between these two components has a 95% confidence level. We measure credit risk using the ratio of loan loss provision to net interest revenue in order to capture the relationship of credit risk and bank profitability. For credit risk, theory suggests that better exposure to credit risk is usually linked with reduced firm profitability and hence, we accept a negative relationship between ROA and credit risk. As a result, null hypothesis is prohibited and it is concluded that credit risk has significant relationship with profitability of banks.
H’= There is a/no significant relationship between operating expenses and profitability of banks
The OPE (operating expenses) has positive and significant relationship with ROA with t-value= 5.632, it has a coefficient estimate of 0.216653. OPE increases by 1 unit then the ROA increases by 0.216653 units. This prove that whenever there is a movement in the OPE; it will carry any effect to the ROA. Operating expenses is calculated by using the non-interest expenses divided by average assets. The positive and significant coefficient between OPE and ROA displays that the bank is proficiency in its expenses managements. In addition, positive coefficients could also show that banks are able to pass on most of the high overheads costs to deposit rates or larger lending assets in order to keep profits. Therefore, a null hypothesis is rejected and it is considered that operating expenses has significant relationship with profitability of bank.
H’= There is a/no significant relationship between bank size and profitability of banks
Another independent variable involved in this study is the bank size. The table above shows that SIZE (bank size) has a positive relationship with ROA with t-value=2.490, it has a coefficient of 0.000688 units. This shows that whenever size fluctuate, it will bring any effect to ROA. Bank size is being calculated by using logarithm of total assets of individual banks. A researcher such as Bikker and HU (2002) demonstrates that size positively influences profitability. If relative size of a firm’s expands, its market power and profit increases as banks attain economies of scale when bank’s size is large. This results advise that the larger the size of the banks, they can have additional reserves for giving loans to borrowers and thus increase their earnings and profits levels. Null hypothesis is rejected and it is concluded that bank size has significant relationship with profitability of bank.
H’= There is a/no significant relationship between asset quality and profitability of banks
Asset (asset quality) also has a significant negative relationship with ROA with the t-value=-2.310, it has a coefficient estimate of -0.05898. As a rise in the asset by 1 unit, it will lead to fall in ROA by 0.05898 units. When the asset rises, it will bring an adverse effect on the assets. As argued in the literature, though banks incline to be more profitable when they are able to accept more lending activities, yet due to the asset quality of lending portfolio is approved that a higher level of reserve is needed. As a result, we can reject a null hypothesis and conclude that asset quality has significant relationship with profitability of bank.
H’= There is a/no significant between Inflation and Profitability of banks
Inflation (INF) has a significant negative relationship with ROA with the t-value -2.86, it has a coefficient of -0.00113. A rise in the value of inflation will lead to a fall in the bank performance (ROA) by -0.00113. Inflation affect the purchasing power and bank regime, opportunity cost of holding currency in the future deteriorate loans policy, disturb business plans and performance of banks. Although banks is more influenced by interest rates rather than inflation in the price of goods and services yet inflation is an important factor. Therefore, it can be concluded that inflation has a significant relationship with bank performance.
H’= There is a/no significant between GDP and Profitability of banks
Gross domestic product (GDP) has a positive significant relationship with ROA with t-value= -2.81 and has a coefficient of 0.001608. A rise in the value of GDP will increase the bank performance by 0.001608. A rise in GDP means the economy is performing well with better technologies, development in telecommunication and infrastructures. Investors will be more interested to take loans and invest in the economy. Therefore, null hypothesis is rejected and it is concluded that GDP has a positive significant relationship with ROA.
4.4 Comparison of mean value between the domestic and foreign banks.
Table 5 shows the mean Value for the dependent and independent of domestic bank specific variables
ROA LIQ CRE OPE SIZE ASSET
0.027782 4.011228 1.479576 0.015976 25.58744 0.059874
Table 6 shows the mean Value for the dependent and independent of foreign banks specific variable s
ROA LIQ CRE OPE SIZE ASSET
0.033968 2.11644 1.027918 0.001824 23.53743 0.034978
In the first bank profitability variable, we found that there is insignificant positive relationship between ROA and LIQ. LIQ does not disturb ROA directly. A bank with huge amount of loans does not illustrate that the bank will perform well. In contrast between domestic and foreign banks, foreign banks have more deposit and funds than domestic banks thus foreign banks contribute a higher amount of return on assets than domestic banks. According to (Freixas and Holthousa, 2004), foreign banks will also have less liquidity as they can rearrange capitals from the parental institute and affiliates located in different countries. On the other hand, domestic banks are having greater liquidity risk than foreign banks. Therefore, it contributes a lower ROA. The positive relationship with profitability supports the findings of Bourke (1989) while Pasiouras and Kosmidou (2007) approve to the negative relationship of liquidity with profitability.
Comparing between domestic and foreign banks, domestic banks have higher mean of CRE (credit risk) of 1.479576 which result a lower ROA of 0.027782, while for the foreign banks it has a poorer average mean of CRE of 1.027918 which found a higher ROA of 0.033968 compared to local banks. From the outcomes, we can say that domestic banks have been involved in complex amount of high-risk loans, risky loans or lower quality bank loans as compared to foreign banks. Domestic bank that select to implicate in high risk loans is largely due to the opposition with foreign banks. By holding higher risk loans also suggest that domestic banks have higher obstacles in maximizing its profit. Thus, the performance of foreign bank is better than domestic banks.
Comparing between domestic and foreign banks, domestic banks have higher mean of OPE (operating expenses) of 0.015976, which results a lower ROA of 0.027784 while for foreign banks it has a poorer mean of 0.001824, constitute higher ROA of 0.033968 compared to local banks. The higher return on assets of banks displays that foreign banks are more cost efficient than domestic commercial banks. It might be due to the cause that the usage of innovative electronic and expert training by foreign banks. In a developing country like Mauritius, foreign bank’s technological advantage is rather strong, it has permitted banks to overcome any informational drawback as well as lower its wage expenses. For domestic banks to compete with foreign banks, they need to invest massively in technology therefore, increasing its costs. Although, the early result shown a positive relationship between OPE and ROA, yet there is an opposite relationship shown comparing the mean of domestic and foreign banks. In addition, shortages in domestic bank’s managing loan portfolio’s might leads to greater non-performing loan as compared to foreign banks.
Moving to bank size, we have reached a positive relationship between size and profitability of banks. Domestic bank ROA is 0.027784 is practically lower than foreign banks ROA 0.033968 even though the size of domestic bank is 25.58744 is bigger than foreign banks 23.53743. Higher amount of size of local banks show that domestic banks have a greater proportion of the domestic market. This supports the findings of Bikker and Hu (2002) who finds a significant positive relationship between these two variables.
A negative relationship between asset quality and profitability of banks has been reached. In comparison, domestic banks normally suffer from poor asset quality. The mean of asset quality for domestic banks is 0.059874 compared to foreign banks asset quality which is only 0.034978. With the arrival and existence of foreign banks in Mauritius, it has caused domestic banks to work in a more dangerous environments In terms of earnings and management. Foreign banks gives most talented officials a better career prospect has fascinated most of the expert to their banks compared to local banks which have an absence of expertize to control their lending operations which may result in a high value of non-performing loan. In addition, most of the time domestic banks are confronted with low credit borrowers which result in a high probability of non-performing loan if these borrowers default. On the other hand, foreign banks usually deal with high credit worthiness customers which result in a better performance. This backs the study of Dang (2011), who finds that loan is the major asset of commercials bank from which they generate income and non-performing loan are the best proxies for asset quality.
4.5 Correlation Analysis
The correlation table below will show all the matrix of all the possible correlations among the seven variables that are listed. Pearson Correlation, r value illustrate the measure of relationship between the 2 variables. Pearson r value for ROA with ROA is equal to 1. This shows the correlation with itself would be perfect. The statement for the correlations are as follows.
4.5.1 Correlation analysis between ROA and all ratios of Domestic banks.
Table 7 shows the correlation results for all the domestic banks
ROA LIQ CRE OPE SIZE ASSET INF GDP
LIQ -0.0085* 1
CRE -0.1255 0.5064 1
OPE 0.0951*** 0.3768 0.4729 1
SIZE 0.1545 0.1503 -0.237 0.0158 1
ASSET -0.3168 0.1652 0.6052 0.2539 -0.4101 1
INF -0.1785 -0.1493 0.2217 -0.1202 -0.1662 0.261 1
GDP -0.0261 -0.1844 0.014 -0.1219 -0.0745 -0.0094 0.6444 1
*, **, *** significant at 1%, 5%, 10%
Table 7 studied the correlation of domestic banks. The outcome showed by Asset r= -0.3168 has a strong negative relationship with ROA. This showed that ROA of domestic banks in Mauritius is powerfully related to the management of non-performing loan (NPL). With lesser NPL, the bank could use the opportunity cost to do investing fund which will enhance the profitability of bank. While other variables like CRE has a fragile negative relationship with ROA.
On the other hand, SIZE showed there is a moderate positive correlated with ROA r = 0.1545. It is true as domestic banks in Mauritius is still growing phase which could classified as small bank if comparing with other larger banks in other countries.
LIQ r= -0.0085 has moderate negative relationship with ROA. Local banks are depending on liquidity. Depositors would like to deposit and invest in the particular banks with low liquidity risk. With more deposits and funds, domestic banks will get greater ROA.
The correlation among independent variables are normal except for asset to LIQ r= -0.4101 and Asset to SIZE.
Inflation rate is negatively significant to ROA with negative sign, similarly to the study of Chong (2008), implying that banks have tendency to face with faster increase in operating costs than the growth revenues, this brings out a reduction on bank profit.
GDP is positively and statistically significant to ROA which indicate that the countries with higher GDP are able to sustain their economic growth which is essential to boost up loan demand and supply thus increasing profit.
4.5.2 Correlation analysis between ROA and all ratios of foreign banks.
ROA LIQ CRE OPE SIZE ASSET INF GDP
LIQ 0.2538* 1
CRE 0.1568 0.5244 1
OPE 0.4854*** 0.3604 0.5392 1
SIZE 0.5827 0.3101 0.3284 0.7594 1
ASSET 0.1073 0.2893 0.6946 0.6044 0.3686 1
INF 0.2363 -0.1838 0.0724 -0.029 0.0939 0.1772 1
GDP 0.2582 -0.038 0.0307 -0.0665 0.0424 0.0819 0.6444 1
Table 8 shows the correlation results for all the foreign banks
*, **, *** significant at 1%, 5%, 10%
Table 8, examined the correlation of foreign banks. The results showed only OPE r = 0.4854 has a very strong negative relationship with ROA. This showed ROA of foreign banks is developing in Mauritius is powerfully related to the management of non-interest expenses. Non-interest expenses are useful in profitability of foreign banks. Qualified training, increase in wages, improvement of operating serve could greatly improve the foreign bank profitability. Besides SIZE r=0.5827 has a moderate positive correlated with ROA. Local banks could get a better profitability if the bank grows larger. On the other hand, Asset to SIZE r= 0.3686 has a strong positive relationship with each other.
In the same manner, inflation has a negatively significant relationship with ROA and GDP has a positively relationship with bank performance. Inflation and GDP affects both the domestic and foreign banks.
To conclude, two methods was used to analyze our data, which are descriptive analysis and correlation. The performance of bank in Mauritius is meaningfully affected by internal and external variables. By using descriptive analysis we found that foreign banks based in Mauritius has higher return on assets, lower liquidity risk, lower credit risk, better quality assets even though small bank size comparing to domestic banks in Mauritius. We found that operating expenses has the toughest correlation to ROA by using correlation analysis. However, inflation and GDP, the macroeconomics variables affects both the local and foreign banks. A conclusion on the overall study will be drawn in the next chapter.
DISCUSSIONS, IMPLICATIONS, RECOMMENDATIONS AND CONCLUSION
The performance of domestic and foreign commercial banks in Mauritius, for the ten years starting from 2005 until 2014 was investigated. In chapter 5, the first element is the summary of analyzes made followed by the discussions of the major results. Next, is the study of implications and last element is the limitations that were faced thought the whole process while conducting this research and the recommendations made.
5.1 Summary of Analysis
Descriptive method was the first method of analyzes which transfer all the raw data into an easy and understandable information that make readers have easy access to the mean, standard deviation and others. In descriptive analysis, there is the existence of significant relationship among all the variables with ROA except for liquidity.
The other method used is the correlation analysis. Correlation determines which internal factors is greatly correlated with the performance of banks in Mauritius and to which ratio is better to focus in in order to enhance profitability.
5.1.1 Summary of Hypotheses
Liquidity Risk Liquidity risk has insignificant relationship with ROA
Credit Risk Credit risk has significant relationship with ROA
Operating Expenses Operating expenses has significant relationship with ROA
Bank Size Bank size has significant relationship with ROA
Asset Quality Asset Quality has significant relationship with ROA
Inflation Inflation has negative significant relationship with ROA
GDP GDP has positive significant relationship with ROA
5.2 Discussions of Major Results
The first objective of this study is to examine the performance of domestic and foreign banks. Referring to Chapter 4 table 5 and 6 which illustrate the average ROA between domestic and foreign banks, it is found that foreign banks is better than domestic banks. Foreign banks have higher ROA and lower LIQ, CRE, OPE, SIZE and ASSET risk compared to domestic banks thus they can better manage their risks more professionally although they are smaller in size.
The second objective is to determine the internal determinants that affect the banking performance. According to table 7 and 8, it is found that CRE, OPE, SIZE ASSET, INF and GDP have significant relationship with ROA and that LIQ does not significantly affect the performance of banks.
The third objective is to identify the relationship between the factors affecting ROA and it is found that all the seven determinants could predict the ROA of banks.
Liquidity Risk, the results obtained from the analysis shows that liquidity risk has an insignificant relationship with the profitability of the banks. The results is alike with the results of Kosmidou (2006). Thus a bank need to keep enough liquidity so that liquidity can determine the profits of the banks. It makes sense, if we find the ratio is positive, this signifies that banking sector in Mauritius did not declare dividend to shareholders. Liquidity and profitability are interlink because as one increases the other decreases.
Credit risk has a significant relationship with the profitability of the banks. The results is similar with the findings of Noullas (1997). The t-value= -2.303 and it has a coefficient estimate of -0.001589. Loans and advances are major variables in determining asset quality of bank. A bank do not only exist to accept deposits but also offer credit therefore they are inevitable exposed to risk. If banks lend to borrowers who they do have adequate knowledge about, they will definitely be faced with credit risk thus reducing bank performance. Thus, hypothesis 2 is accepted.
On the other hand, Operating Expenses Risk accept hypothesis 3 is accepted because OPE has a significant relationship with the profitability of the banks. This supports the findings of Neceur (2003) Operating expenses affects ROA positively and significantly. Operating expenses are the expenses incurred in conducting banks ongoing operations. An important component of bank’s operating expenses is the interest payment that it must make on its liabilities. If the operating expenses increase that is additional cost for example by employing and training staff, improving service facilities in the banks among others will lead to better performance of the bank.
Bank size affects ROA of banks positively and significantly. The t-value=2.490 and it has a coefficient estimate of 0.000688 units. The results supports the findings of Pasiouras and Kosmidou (2007).If banks grow in size they can benefit from economies of scale therefore boosting up the performance of banks. However, it can be seen in the study that even if domestic bank are larger in size yet they have lower liquidity and are faced with higher credit risk as compared to foreign banks. Therefore, hypothesis 4 is accepted.
Asset quality has affected ROA of banks negatively and significantly. The t-value=-2.310 and it has a coefficient estimate of -0.05898. Loan are usually the largest of the asset that carry potential risk to banks. Securities have recognizable risks. In other words, asset quality specifies the type of debtors to the bank. Asset quality is a vital issue for bank to avoid the bank from going bankrupt. If the bank have more risky assets on their balance sheet, then the capital will be lower implying greater asset. Thus, hypothesis 5 can be accepted.
Concerning the macroeconomics variables, the findings suggest that inflation was anticipated among all domestic and foreign commercial banks accordingly and it has a negative significant relationship. High inflation will lead to fall in consumer purchasing power, as a result their disposable income cannot buy the same quantity of goods therefore consumer preventing them from taking loans. A fall in the demand of loan will reduce bank performance.
On the other hand, GDP finds direct and significant impact on return on assets which indicates that rapid economic growth increases profitability in Mauritius commercial banks. Movements in general activities are expected to generate direct impact on profitability of banks. In relation to GDP, the results supports the findings of Athanasoglou (2008) who find a positive relationship between GDP and ROA however the results contracts Bentium (2012) who indicates that GDP have a negative relationship with ROA.
5.3.1 Managerial Implications
Profitability is the central apprehension for investors. Thus, internal determinants could be a guide for investors to discover whether the bank has achieved their desire output and performance. With useful information, they may be able to realize when to make investment decisions accurately so as to avoid losses. Mwenda (2011), found that when there was restructuring of financial sector from year 2008 in Africa both investors and depositors moved their cash and investment to foreign banks which were considered safer.
5.3.2 Governmental Implications
This study is helpful for government and policy makers. Since commercial banks play a central role in financial sectors which saves the surplus of fund from households, offer loans and develop a country’s economic therefore government can use this study as their guidance to monitor the performance of banking industry.
5.4 Limitation of the study
Firstly, the subprime crisis which happened in year 2008 to early 2009 have been ignored, even though it has indirectly affected the financial sector in Mauritius which would have completely changed the results for inflation and GDP.
The second limitation is that the study is mostly dedicated on the seven internal variables to examine the performance of banks. It does not cover all the aspects fully and ignored other internal variables such as Corporate Governance, customer, ownership structure among others and external variables such as competition and real interest income.
Moreover, the study emphasizes on secondary data that is restricted to information obtainable from the yearly financial statement of banks and also the duration of the study is very small from 2005 to 2014 which could influence the results.
The third limitation is the estimation of each ratio. There are several different formulas to compute each ratio. Different formula used different denominator and measurement, therefore, it will give different figures of ratios which will in turn gives a different value in Return on Assets as well.
a) If banks want to sustain a good liquidity position, they must review their profitability on various products and services. They need to evaluate where prices can be increased on a regular basis to maintain profitability. Banks should also monitor their accounts receivables effectively to guarantee prompt payment.
b) To evade credit risk, management should be careful in setting up a credit policy that will not negatively affect profitability and they also need to know how credit policy affects the functioning of their banks to ensure good utilization of deposits and maximization of profits. Banks need also to assign more funds to default management and try to retain optimum level of adequacy.
c) Furthermore, as asset quality and profitability are negatively correlated in the banking industry, managers are recommended to keep an eye on credit-enquiring effectiveness and they also need to control their operating expenses.
d) Moreover, researches who want to study more on this topic, should take into account more ratios in the study so that they can have a clearer analysis and able to see the changes in ROA. In addition, future researches can take into consideration the financial crisis to examine the performance of banks as it will have a strong impact on a country’s banking sector. It is also recommended to use additional statistical analysis in the study.
e) In addition, more external variable such as exchange rate, corporate tax and monetary value can also be considered to further test.
f) As seen in the research, GDP is an important external factor which affects profitability of banks regardless of ownership therefore bank management should look into this seriously as it could enables them to come out with good strategies, have their own competitive advantage and hence, increase their profits.
To conclude, bank’s return on asset of domestic and foreign commercial banks is greatly influenced by LIQ, CRE, OPE, SIZE, INF and GDP. The results showed that local banks has lower Liquidity, bad quality asset, higher credit risk, lager bank size yet lower ROA as compared to foreign commercial banks in Mauritius. It is highly recommended for banks to invest more in research and development, human capital and technology as OPE is highly correlated with ROA. However, it is found that inflation and GDP both affects the performance of local and foreign banks. Banks should focus more on how to manage their credit risk and asset quality in order to prevent from default borrowers which may lead to a bank run down.
So, I would suggest future researches to take into account more internal factors and other global macroeconomics variables that affect the performance of banks in order to get a better understanding of the study.