Sample Research Summary Paper on Determinants of Profitability in the Commercial Bank Industry

ABSTRACT

This research study was conducted to determine the microeconomic and macroeconomic that
influence bank profitability among French banks. To accomplish the study, the researcher
focused their investigation in a panel data covering a longitudinal element of one decade,
ranging from 2009 to 2018 over a cross sectional element of 8 banks from France. As such,
the study was based on an analysis of 80 0bservations. The researcher performed Generalized
Estimation Equation (GEE) tests to determine whether the study variables were directly
correlated to profit levels among French banks. The tests revealed that only one study
variable, the quality of bank assets is positively associated with commercial bank profitability
in the country, while factors such as capital to asset ratio (CAR), ratio of loan to deposit and
leverage terms posited a negative effect on bank profitability in France. In a test involving
macroeconomic variables impacting bank profitability, the researcher concluded that only
three factors, namely inflation rates, interest rates and leverage directly determined the
profitability of French banking institutions

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TABLE OF CONTENTS
ABSTRACT iii
LIST OF TABLES AND FIGURES vi
1.0. INTRODUCTION 7
1.1. Background Information 7
General objective. 7
1.6 Hypothesis testing 8
1.7 Significance of the study. 8
1.2. Statement of Problem 9
1.3. Research aim and Objectives 10
2.0. Literature Review 10
2.1. Firm Specific Factors Influencing Banks Profitability 10
2.2. Macroeconomic factors Influencing Performance in the Banking Industry 13
2.3.1 Capital Adequacy 16
2.3.2 Liquidity 16
2.3.3 Asset Quality 17
2.3.4 Management Efficiency 17
2.3.5. Earnings Performance 18
2.3. Empirical review 18
3.0. DATA AND SOURCES OF DATA 20
3.1. Banks selected 21

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3.2. Profit factors 21
3.3. Microeconomic factors 21
3.4. Macroeconomic factors 21
Data collection 4
Test of significance 4
CHAPTER FOUR 5
4.0. ANALYSIS AND RESULTS 5
4.1. Micro-economic Factors Influencing bank Performance 5
4.1.1. Descriptive Statistics 5
4.1.2. Correlation Analysis 6
4.1.3. Unit Root Test 6
4.1.4. GEE Regression Analysis 8
4.1.5. Co-Integration Analysis 9
4.2. Macro-Economic Factors Influencing Bank Performance 11
4.2.1. Descriptive Statistics 11
4.2.2. Correlation Analysis 12
4.2.3. Generalized Method of Moments Regression Test Models 13
CHAPTER FIVE 16
5.0. CONCLUSION 16
5.1. Research Summary 16
5.2. Conclusion 20

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5.3. Limitations of the Study 20
5.4. Recommendations 21
REFERENCES 22

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LIST OF TABLES

Table 1: Descriptive Statistics Summary 5
Table 2: Pairwise Correlation Analysis results 6
Table 3: Levin-Lin-Chu unit-root test for roa 7
Table 4: Levin-Lin-Chu unit-root test for roe 7
Table 5: GEE population-averaged model Using ROA as the Dependent Variable 8
Table 6: GEE population-averaged model Using ROE as the Dependent Variable 9
Table 7: ROAs as the dependent variable 9
Table 8: ROE as dependent VarIable 10
Table 9: Descriptive Statistics Summary Results 11
Table 10: Pairwise Correlation Analysis 12
Table 11: Generalized Method of Moments with CAR as dependent Variable 13
Table 12: Generalized Method of Moments with NPLs as dependent Variable 14

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1.0. INTRODUCTION
1.1. Background Information
The prime purpose behind the existence of any business entity is to generate profits. However,
consistent changes in the business environment due to new innovations and inventions have
altered this goal, especially for businesses that are not flexible enough to respond to these
changes. The banking industry in particular has experienced turbulences in their profit margin
due to consistent changes in banking regulations, technology competitive strategies and other
microeconomic variables. Today, the main source of income for the banking industry, which is
interest income or fees charged to money borrowers, is experiencing tough competition
following the rise of related platforms offering similar services. For instance, the rise of mobile
phone services allowing customers to borrow and save money, and emergence of Sacco’s that
provide bank related services have attracted a wide range of customers who initially depended on
the banking sector. Such innovations and inventions present new challenges to the banking
industry, as they have to innovate more improvised services and products that will deliver value
to their clients in a bid to retain the customers to enhance and maintain higher income levels and
generate organizational growth.
However, though innovations are crucial in retaining clients and generating more profits in the
banking industry, their effect has not always presented positive results. At times, banking
institutions have reported adverse losses resulting from various innovations that did not merge
with the external and internal factors influencing the positive performance of the bank. Further,
despite various empirical studies on the effect of financial innovations at the macroeconomic
level on the profitability of the banking industry, there are limited studies on products and
channels. Numerous studies have identified a positive effect impacted by consistent innovations

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in the finance sector such as ATMs, Portfolio Investment Schemes, credit cards and debit cards
as well as electronic funds transfer (EFT). However, Sufian & Chong (2008) established a
significant negative correlation coefficient between product innovation and bank financial
performance. Effects of financial innovations remains a paradox hence the question, do banc
assurance, diaspora banking and agency banking have any significant effect on bank profitability
in France?
1.2. Statement of Problem
There have been intensive research across regions and generally across the world, to examine the
variables that often affect the profit margins of financial institutions. Researches on profit
margins within the banking sector are categorised into three classifications. To begin with, the
first researches are on the determining factors affecting bank’s profits across nations. These
factors have been scientifically researched by various scholars, For instance, Perera and
Wickramanayake (2016), study of 122 nations and Ashraf study of 14 nations. In both the
studies, the scholars identified difference in interest rates and legislations as factors affecting
profitability. The second type of classification is based on the profits determining factors across
lending institutions within the same area. Example of search researches include Rasid 2017 study
on GCC countries, in this research he identified inter-competitions as the main factor affecting
profitability and Comelia 2015 study on EU nations identified inflation rates and interest rates as
the significant factors affecting profitability. The last group of studies are those interested in
factors affecting profitability within a given nation. A good example is the Maldonald (2014)
research of the United States. This research was established on providing literature on factors
that led the great crisis and recommendation for future operations in the banking industry.

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Most of the previous researches were based on return on equity (ROE), within the finance sector
ROE refers to the measure on business profitability based on equity Chowdhury & Rasid, 2017.
This ratio shows how prudently firm managers are using firms’ resources Çalim, 2013. On the
other hand return on assets (ROA). ROA shows how profitable a business is in relation to its
total assets. ROA provides insightful information’s that facilitate to have an edge against their
competing rivals, Chowdhury & Rasid, 2017. ROA’s are in general indicators for capital
intensity, usually firms that require a high initial capital to operate have a lower ROA, Saona
(2016).
The studies examine the micro and macro environment as potential influencer bank’s
profitability. The micro environment refers to the internal factors, (leadership, human resource),
Acaravci & Çalim, 2013. According to Saona (2016) specific outcomes in the banking sector
relate directly to managerial choices. Whereas, the macro environment refer to the external
factors affecting productivity, these factors are usually out of the control of firm managers,
Chowdhury & Rasid, 2017. The study identifies the macro and micro environment as factors
affecting profitability in the banking sector, and in the long run reduced rates on equity
1.3. Research aim and Objectives
This research has the main purpose of ascertaining the firm-level and the macro-economic
determinants affecting the success in profitability within the French Banking industry. The
specific research objectives include:
1.3.1. To examine whether the financial performance of commercial banks in France follow a
random walk hypothesis.

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1.3.2. To investigate the key firm-specific factors influencing performance in the French
Banking Institutions.
1.3.3. To establish external or macroeconomic variables that impact commercial bank
profitability in France.
General objective.
 To examine the effects of capital adequacy on profit levels of banks in France.
 To investigate the impact of asset quality on commercial banks financial ;
 To examine the effects of managerial efficiency on the financial performance of banks in
France
 To determine the influence of liquidity on the profitability of commercial banks
 To determine the impact of gross domestic product growth rate and inflation on financial
performance of commercial banks.
 To investigate the determinants of bank performance in France.

1.6 Hypothesis testing
i. Liquidity ratio has no effect on profitability
ii. Deposit to assets ratio has no effect on bank financial perfromance
iii. Capital ratio has no effect on profitability
iv. Interest rates and inflation rates has no effects on profitability.
1.7 Significance of the study.
This study is seeks to investigate the factors influencing banking profitability using France as the
study sample. As such, the study will provide coincide information on how to improve
profitability in the banking industry in France. Through the provisions of the study, bank

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managers will gain on ways to enhance better service delivery. The study is mainly concentrated
on the management and maximization of a bank’s liquidity value, since decline in profit
generation have been attributed to result from poor liquidity management. As such, thus study
will provide an insight to the management on how to make informed decisions on liquidity
management and increase profit levels.
The main objective in this study is to investigate policy management in commercial banks by
reviewing specific factors such as capital adequacy, credit, interest and inflation rates with the
aim of recommending appropriate strategies that can be used to improve profitability among
banking institutions in France. This strategy can provide insights to policy making institutions
such as the capital market authority to generate effective policies that will assist them generate
more profits. Further, the study will assist bank regulators in managing bank liquidity levels to
evade credit risk. The study will also provide a basis for future researchers who may wish to
advance the investigation on liquidity management and profit generation.

2.0. Literature Review
2.1. Firm Specific Factors Influencing Banks Profitability
The following are the specific-banking variables affecting profitability, CAR; this is a ratio of
total capital invested in a bank against total risk a bank is exposed to. The extent to which
adequacy ratio may affect profitability remains unclear, however, according to a study by
Buchory (2015). There exist a negative relationship the associated variables, as an increase in
capital base leads to a reduced ability to offer credit. Similarly, there have also been subsequent
studies that infer, a high adequacy ratio creates a good public that results to a high profitability
margin (Abreu and Mendes 2001; Molyneux and Thornton 1992; Saeed 2014; Djalilov and
Piesse 2016).

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The second variable affecting bank profitability are the Bank deposits. Bank deposits refer to the
securities a customer bring to the bank for safe keeping, Naceur & Goaied, 2005. Bank deposits
are estimated as asset to deposit ratio. Lee and Hsieh, 2013 categorise the deposits as liabilities
owed by the bank to the depositor. These school of thought is supported by Menicucci &
Paolucci, 2016, he observed that when the ratio is large, the bank has a likelihood of increasing
its profit margins, this is as a result of increased income-generating activities. Therefore, it is
expected that deposits will have a positive effect on bank performance. However, the assertions
of the deposit hold if and only if banks are able to make sound income-generating activities.
However, Dietrich & Wanzenried (2011, 2014) during their study on bank growth deposits and
bank profitability, established that the effects of deposits on performance were ambiguous and
inconclusive.
Albeit, the natural logarithm of deposits formula has also been used by other researchers to
calculate embedding of networks. For instance, Sufian & Habibullah, 2009 show that banks with
an increased number of branches tend to have more deposits, thus they attracts more customers,
and therefore, they have higher profitability levels. Similarly, Sufian & Noor, 2012 asserts that
network embedding helps unearth customer hidden pattern in preference.
Asset quality – as highlighted by rations such as the non –performing loan ratio
This is a proportion of the total number of assets to loans. The loans to total asset ratio estimates
the sources of bank incomes. It is estimated that this ratio affects bank performance negatively,
unless a banking institution posits unbearable risks, (Rani & Zergaw, 2017).
Management efficiency as defined by ratio of cost to income

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Niţoi & Spulbar (2015) using a heteroscedastic SFA, examined the differences in efficiency costs
for commercial banks within central eastern and central Europe. Differences under the study
were as a result of variables measuring; levels of economic advancements, liquidity ratios,
stability of the macroeconomic sector, risks in credit and solvency, proficiency of financial
mediation process, performance of banks and loan specialization. They further carried out
analysis across different countries to identify differences in performance between countries.
Also, Andries (2011) carried an analysiss on CEE countries by examining variables that affected
productivity within the sector by use SFA and DEA. In both studies, the Malmquist productivity
index was developed to access productivity projectiles of the banks. Similarly, Psillaki &
Mamatzakis (2017) carried out a similar study. They analysed the effects on monetary
restrictions and structural reforms on CEE banking industry’s cost efficiencies: Using the ERBD
indicator of financial transition and the Fraser economic model. They further used the SFA
estimated cost efficiencies scores to examine the importance of legislations and reforms on the
banking sector. In addition, Andries & Căpraru (2011) used the SFA’s cost effectiveness
technique in 17 central and eastern European countries, to examine the relationship between
economic linearization, the structure of banking system and the performance of banks. He
measured them in terms of cost effectiveness and the complete productivity development index.
Then based on the b-subvergence and s-convergence, Nurboja & Košak (2017) analysed the
relation in EU membership and the gap in cost effectiveness of South East European (SEE)
banks in non-EU nation. They found out that the cost effectiveness gap in relation to EU banks
was as a result of lowered bank rates. Also, the SFA was performed to determine cost efficiency
ratings. For assessment purposes both the generalized system moments method (GMM) and the
fixed model were used.

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Finally, the causes in profitability for banks in in eastern and central Europe and transitioning
countries in Russia was analysed by Djalilov & Piesse (2016). According to their outcomes
profitability determinants differ between transitioning economies. Also, the writers found out
that banking is more competitive and banks are likely to fail during onset of transitioning.
Finally, they discovered that capitalisation plays a major part in ensuring profitability for the
banks.
Academic studies focussing on the effectiveness of financial institutions with frontier analysis
have also increased in the latest years. Berger and Humphrey (1997) performed a study on 130
nations spreading across 21 different time intervals and various organization that practicing
different frontier methods. The parametric methods studied include: Thick frontier approach
(TFA), stochastic frontier approach (SFA), Distributional free approach (DFA). Consequently,
non-parametric methods that were used included: free disposal hull (FDH) and data envelopment
analysis (DEA). The frontier methods were to determine which method featured as a best
practice for which relative efficiency could be measured. In some recent research, cost
effectiveness and profits are also being taken to account. However, most studies place more
focus on cost efficiency rather than profit efficiency. Also, risk variables too are being
considered, for instance Rao (2005) shows liabilities owed by banks reduce its liquidity ratios
and consequently the interest rates that they can offer. He further asserts that accumulated risks
are like ‘black hole’ that throw financial institution in financial limbo and in the long run closure.
In summary, Bank efficiencies is usually measured relative to the best practices performed by
other bigger banks of the same kind,
Liquidity as defined by loan to deposit ratio

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The ratio of liquid assets to total assets is used in measurements of bank liquidity. Increased
liquidity ratio means that banks are more liquid and therefore, greater returns on capital could
arise as an opportunity cost, (Bougatef (2017); Chowdhury and Rasid (2017); Menicucci and
Paolucci (2016). Insufficient liquidity is seen as one of the principal causes of failure by banks.
Previous studies have shown both adverse and positive liquidity-profit interactions, (Ebenezer et
al., 2017).
Macroeconomic factors Influencing Performance in the Banking Industry
Problems of providing profitability and financial stability of commercial banks in the national
economy are highlighted in works of many leading domestic and foreign scientists, namely: A.
Alshatti [1], A. Banerjee, E. Duflo [2], P. Bustos, G. Garber, J. Ponticelli [3], F. Shamim, B.
Aktan, M. Abdulla, N. Yaseen Sakhi [4], E. Gilje, E. Loutskina, P. Strahan [5], R. Iyer, M. Puri
[6], L. Sloboda, N. Dunas, A. Limański [7], T. Alzoubi, O. Dzubluk [11], Ya. Tchaikovsky [12],
and others.
For example, T. Alzoubi explained that the size of a bank is directly proportional to its
profitability. This is because larger banks possess better opportunities to diversify their
investment portfolio, thus making generating safer and better profit generating opportunities. The
amount of capital and the efficiency of its using have a significant positive impact on a bank’s
profitability. Capital generates a direct source of funding on banking operations which cannot be
refused, as opposed to debt capital,, which will increase its profitability. Loans have little
positive impact on profitability of banks. Deposits posit a positive effect on bank profitability as
they serve as a cheaper and readily available source of financing.

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F. Shamim, B. Aktan, M. Abdulla and N. Yaseen Sakhi explain that bank financial performance
can be influenced by internal factors, which describe particular characteristics of the banking
institution, or external factors, which are factors within the business environment where a firm
operates. Further, they explain that internal factors can be controlled and managed by the bank,
and include bank ssize, cost and capital management and credit risk. On the other hand, external
factors are beyond the control of the banks management, thus necessitating the banking
institution to adopt their provisions. They include inflation rates, interest rates, market groth,
structure of the market, changes in bank regulation and alterations in business cycles. L. Sloboda,
N. Dunas and A. Limański state that the banking sector plays an important role in the
development of the financial sector, economic growth, formation of a business strategy, and
enhancement of investment competitiveness. At present, the Ukrainian banking sector faces
transformation and systemic risks in all types of banking services.
 Interest rate
Interest rates are profits bank acquire by offering credits. These rates are anticipated to have
positive effect on bank’s profitability. INTR’s empirical results on bank profitability from
previous research are not clear, for instance, Rashid and Jabeen (2016) discovered that the rates
affect the efficiency of banks negatively. On the other hand, Yahya, Akhtar, and Tabash (2017)
recorded a favourable effect of rates on banking profitability.
Firstly, the impact on the rates of interest on revenue growth in undetermined. Several researches
have proven of there being a positive correlation between these variables, this is demonstrated
through the increased revenue growth through high interest rates, (Javari 2016; Saeed 2014).
Some other studies, however, have pointed out on there being a negative association between

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rates and productivity. Noman et al. (2015) concluded interest rates had a negative effect on
profitability. The primary reason would be that maturation of deposit accounts is significantly
shorter than that of bank loans. As a result of this condition, deposits are affected sooner as
compared to loans; loan rates increase thus reducing margin on net interest rates.
The primary reason for this behaviour is that loans mature faster than deposits. Thus interests on
loans overshadows profit rates from deposits. The net effect being diminished interest margins
and value for money. In addition, the impact on profitability due to inflation rates is dependent
on whether or not it can be anticipated. Financial institutions can easily adjust their rates of
interest to the expected inflation rates if anticipated. In case of this scenario profitability will be
effected, (Molyneux and thornton (1992). In contrast, In the event of unexpected interest rates,
then these two factors will have a negative relation, (Noman et al.2015, Ariyadasa et al 2016).
Finally, as the growth in economy indicates economic development, profitability effects of this
parameter ought to be progressive, Djalilov and Piesse 2016)
 Inflation rate
This is the speed by which the overall price level of products and services increases. These
phenomenon results to a drop in currency’s purchasing power (singh and sharma 2016).
Implications of profitability of financial instituitions as a result of inflation has been supported
by several literatures on banking; i.e. Anbar and alpher 2011; massod and Ashraf 2012;
Chowdhury and Rasid 2017. Capital adequacy ratio reflects the capital amount of the bank with
regard to its risks. The impacts of the Capital adequacy ratio is unclear, some researchers have
shown that these two factors have a negative relationship. Buchory (2015) observes that the
greater the capital levels a customer receives, the less the credit he or she can receive. Other

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studies have highlighted the fact that a high adequacy ratio of capital helps improve the image of
a financial institution, this contributes positively to profitability, (Moline and Thornton 1992).
Credits on the deposit ratio and GDP loans are the next lender-specific factors. Quantity of
interests offered by banks is directly proportional to the banks revenue streams, Saeed 2014. This
situation shows that there should be a positive association between profitability and a company’s
loan quantity, (Duraj and Moci 2015). In contrast, it is contentious how credit affects
profitability, this primarily due to the quality of the loans, (Menicucci and Paolucci 2016). The
mark of the credit proportion to GDP demonstrates value of the credit in post-soviet. If, negative
the outcome is perceived as a poor lending performance. The opposite is also true if outcome is
favorable.
 GDP Growth

Gross domestic growth (GDP) refers to an increase in the economy, adjusted for inflation usually
between given time intervals, Marijana et al., 2012. GDP is the largest macroeconomic metric
used to access the effect of macroeconomic factors on a financial institution’s performance,
Francis, 2013. Moreover, it is a metric of all inclusive economic activities within an economy
(Ongore & Kusa, 2013) productivity is by far the largest determinant of gross domestic product,
(Singh & Sharma, 2016)
2.3.1 Capital Adequacy

Capital adequacy is the amount of capital held within a financial institutions based on the
provisions of financial regulators to manage for unprecedented losses, expressed in form of
capital adequacy ratio, CAR of the risk weighted risk. It serves as a strategy to enhance financial
stability and efficiency as it assists banking institutions to reduce risk of insolvency.

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Regulators would like to have a higher minimum requirement to lower instances of bank failure,
however, bankers argue its expensive and difficult to obtain additional capital and higher
restrictions reduces competitiveness (Koch, 2015). Capital adequacy is inversely related to
profitability since companies holding onto higher cash ratios tend to be risk averse as they evade
investing in high risk investment which posit higher returns, thus making investors to generate
low returns associated with little or no risk.
2.3.2 Liquidity

Liquidity in banking is the ability of banks to meet its financial obligations. Poor profit
generation in banking institutions have been associated with poor liquidity management. As
such, banks in some countries have a minimum liquidity requirement. For instance, French banks
are required to hold on at least 20% liquidity. This posits a tough responsibility to the
management as they have to avail cash for withdrawal, deposit and catering for short term
financial obligations while at the same time striving to maintain the liquidity levels.

The shift ability theory in banking provides that for an asset to be transferred from one bank to
the other, it has to be perfectly transferrable such that its shifting process does not incur any
capital losses. It stipulates that all banks in France should acquire such assets shifted to the
Central Bank of France as the lender’s last option. It is asserted that companies that maintain
strong liquidity, at the expense of certain investments can produce significant yields.
2.3.3 Asset Quality

Asset quality means assessing specific corporate property to help evaluate the magnitude and
amount of monetary dangers engaged by default during payments. Lending, which is one of the

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main sources of bank profits compromise a huge percentage of bank assets, thus positing huge
risk to the capital to cases of credit risks, which is the risk of capital loss due to delayed or failed
payment of a debtor’s loan.

Credit risks is one of the earliest and most common risks affecting the financial health of a
banking institution. Its extent is dependent on the value or quality of an asset based on the risk
exposure factor. Bank operations are guided by three prime objectives namely profit generation
increase in asset and heightened client base. As such, once a client fails to meet their loan
obligations, they increase credit risk, which results to a decline in assets. Banks would increase
profitability by improving screening and monitoring of credit risk.
2.3.4 Management Efficiency
Managerial efficiency is qualitative in nature, thus limiting the ability to measure its impact
through financial ratios. As such, operational management is adopted as an effective technique to
examine the efficiency of the management. The main role of the management in a commercial
bank is to facilitate smooth operations, effective risk control and quality delivery to consumers.
Various studies have proved that bank management impact positively on the financial
performance of banks. Further, effective management generates a strong client base through
improved customer relations, which is one of the prime objectives that a bank has to fulfil to
generate more profits.
2.3.5. Earnings Performance

For a business to generate profits, they must avail quality services thus satisfy consumer
demands so that they can increase generated funds. This can examined by reviewing the earning
performance of the institution. Efficiency among financial institutions is the ability to transform

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a certain amount of assets into revenue and to generate profit from a given source of income.
Traditionally, banks mainly depended on interest income as their main source of profits (Kumar
2006). However, with recent changes within the financial sector, bank consolidation,
universalization and globalization have created alternative income generating sources that assist
banking institutions to raise more capital.

3.0. DATA AND ITS SOURCES
The research study aims to examine and evaluate the determinants of the bank’s profitability in
France. Notably, within the context of the research study, annual data for the period between
2008 and 2018 is considered and evaluated. A panel data set of eight banks in France is provided
prom world bank as well as the annual financial reports of the respective banks. Consequently,
the data is obtained from the bankscope data base to define both specific/internal/microeconomic
factors and external/macroeconomic factors that affects banks profitability. However, the study
applies the following criteria to obtain the data from the bankscope database; the commercial
banks in France was considered, the chosen banks must be active and lived, the chosen banks
must have the accounting statements for the period of time being examined. The samples of the
eight major in France are: BNP Paribas SA, Credit Agricole, Groupe Credit Mutuel-CIC, Societe
Generale, AXA Banque, HSBC France, La Banque Postale and Banque Populaire (BP).

The analysis conducted in this study covers two key elements, first are the firm-specific factors
or the internal factors that influence profitability of the commercial banks in France. These
involve the internal or microeconomic factors. Here, the researcher concentrates on the most
recent data, ranging from 2009 to 2018 as recorded on the financial statements of the specific
banks involved in the study. The second section of this research discusses the external or macro-

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economic factors that influence bank financial performance. Here, the researcher reviewed the
most recent financial statements for the banks under study, for the years ranging from 2008 to
2017.
Variables used in the Analysis
There were eight test variables involved in the study, whose impact on a bank’s profitability was
examined. Based on the analysis from existing literature, the researcher narrowed down to five
microeconomic variables and three macroeconomic variables as listed in the table below:
Variable Details
Capital Capital adequacy ratio
Inflation rates (CPIt-CPIt-1)/CPIt-1)
Deposit to asset ratio Total loans/total deposits

Liquidity ratio Total loans/total assets
Interest rates Deposit interest rates
Loans/GDP ratio The total loans/GDP
Innovations Bank assurance and agency banking

3.1. Banks selected

 BNP Paribas SA
 Credit Agricole

 Groupe Credit Mutuel-
CIC

 Societe Generale
 AXA Banque

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 HSBC France:
 La Banque Postale:
 Banque Populaire (BP)

3.2. Profit factors
The profit factors are grouped into two parts; microeconomic factors and macroeconomic
factors.
3.3. Microeconomic factors

 Return on Assets
 Return on Equity
 Measures of capital
adequacy such as asset
ratio
 Management efficiency
as defined by cost to
income ratio
 Asset Quality
 Liquidity –as defined
by loans to deposit
ratio

3.4. Macroeconomic factors

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 Interest rates
 Inflation rates
 GDP growth
 Innovation such as
banc assurance and
Agency banking

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Return on assets –measure of profitability
According to Bose and Islam, 2017) return on assets is complete proportion debts to assets.
Usually there is reduced ROE’s but increased ROA in banks with greater stocks
(Athanasoglou et al., 2008).
 Return on equity – measure of profitability
 Capital adequacy such as equity to asset ratio
Model
Profitbaility (P: ROA) = a + a 1 BSP + a 2 MEF + uit
Profitbaility (P; ROE) = b + b 1 BSP + b 2 MEF + vit
Where P is profitability of Bank (x); BSP is bank specific factors; MEF is macro- economic
factors

Weakness of the data set
Legal and regulatory problems
The data set adopted for this study is limited in various ways. First, this data set is
categorized in terms of big data and small data, based on the study period. Also, most of the
data from the selected financial companies is biased due to legal and regulatory concerns that
are associated with complexity challenges due to the sheer data. Though the researcher noted
that most financial institutions had a definite control pattern in cases of small data, most
banks were observed to experience legal and regulatory challenges when analysing big data.
As such, these legal and regulatory limitations will lead to biasness in the data set thus
limiting the accuracy of the study results.
Privacy and security of the data

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Although big data posits effective potential on the progression of banking institutions, no
bank will accept to present or disclose all their financial reports to the public. As such, the
bank scope cannot access whole bank operation data despite its significance for this study.
This is because most banks have adopted hidden tax evasion techniques, whose exposure
would lead to over taxation.
Data quality
Data quality is crucial in describing the actual performance of banks under study, thus
increasing the accuracy of the study results. It is determined through proxies such as validity,
accuracy, timeliness and completeness of the data. However, most data from banking
institutions are limited in these qualities due to ineffective measurement and recording. This
in turn poses limitations to our study since the data used may be inaccurate, thus leading to
inaccurate study results.
Research methodology
This section entails a description of the research path adopted by the researcher to derive the
research conclusions. The chapter incorporates the research design, population of study, data
collection and analysis techniques. It also describes various statistical tests carried out on the
data such as the reliability and validity tests.
The primary purpose of the research study is that by analysing the indicators of financial
performance among financial institutions, the study will be able to explain on the factors
influencing bank’s profitability and the effect they have on the profit levels of 8 banks in
France for a period 2008-2017. The study will utilize a balanced panel as the data design for
the study in a bid to achieve the main objective if the study. The population under study
includes a sample of eight commercial banks from France.
Descriptive statistics, correlation coefficient analysis as well as the multiple regression
analysis will be the main techniques of data analysis in this study. The mean and the standard

27
deviation will be applied as indicators of the general trends of the data from 2008-2017 for
both specific and macroeconomic variables. Moreover, a correlation matrix will be used to
evaluate the relationship between the bank’s profitability (ROA) and the independent
variables. The correlation matrix will also be used to test for the existence of multicollinearity
among the study variables. According to Cresswell (2017) variables should be analysed in a
specified order to enable readers gain a clear understanding on groups that should need
further experimentation as well as the outcomes under investigation.
The study will employ the use of CAMEL model which is popularly used by scholars to
proxy the specific factors that affects the performance of banks. Perhaps, CAMEL stand for
the capital adequacy, asset quality, management efficiency, earning ability and liquidity ratio.
These are specific factors that represents banks internal factors in relation to the performance
of banks. For instance, the French central bank uses the CAMEL ratios to examine the
performance of the French commercial banks. Perhaps, the performance of banks is measured
in terms of ROA, ROE and NIM which are expressed as a function of both specific and
macroeconomic factors. The specific factors according to this research study are the capital
adequacy ratio, asset quality, management efficiency as well as the liquidity ratio. The
macroeconomic factors include the real GDP growth, the inflation rates and interest rates that
has an impact on the financial performance of banks in France. Therefore, in this research
study, both specific variables and macroeconomic variables are used to investigate the
determinants of commercial banks profitability and their impact on financial performance.
The research study will use three models to examine and measure the bank’s profitability
using regression analysis. For instance, the regression analysis will be used to determine the
significance and impact of each of the explanatory variable on the profitability of banks. The
p-value of the independent variable will be used to test the hypothesis at 5% level of

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significance. The following equations shows the multiple regression models for the ROA,
ROE and NIM.

Where:
Is the return on asset at time t, CAR t  = Capital adequacy ratio at time t, ASQ t  = Asset quality
at time t, MGE t  = Management efficiency at time t and LIQ t  = Liquidity of bank at time t.
also, RGD t  = Real GDP growth rate at time t, INF t  = Inflation rate at time t, INT=interest rate
at time t. the t =is the period of study 2008-2017. C=constant which shows the fixed effects.
α = Internal determinant factors regression coefficients; β = Macroeconomic factor regression
coefficients; ε = Error term.
Based on the literature review, the research study variables are calculated as follows;
 ROE = Net Income / Shareholders’ Equity.
 ROA = Net Income / Total Assets.
 NIM = A percentage of earns on loans in a time period and other assets minus the
interest paid on borrowed funds / Earning Assets.
 Capital adequacy ratio = Total capital / Risk Weighted Assets
 Asset quality = Non-performing Loans / Total Gross Loan measured into a
percentage.
 Management efficiency = Expenditures to Income Ratio.
 Liquidity ratio = Liquid Assets / Short-Term Liabilities
 GDP = Yearly Real GDP Growth Rate.
 Inflation = Yearly Average Inflation Rate
 Interest rate=yearly average interest rates.

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Data collection
Secondary data collection was the method of data collection adopted for thisstudy. Variables
were gathered from the financing statement of French commercial banks from the bankscope.
The data use will be entail total assets, total loans, and current liabilities, the total deposits of
customers, interest rates, interest rates as the variables of the research study.
Test of significance
The analysis of variance (ANOVA) technique will be applied to determine the significance of
the model. The test of significance for the regression model will be conducted at a 5%
significance level and 95% level of confidence interval (CI).R squared will be used to test for
the variation of the dependent variable to account for changes and disparity among the
independent variables involved in this study.

30

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