The Empirical Effectsof Credit Risk on Profitability of Commercial Banks: Evidence from Nigeria

Abstract

The study investigates the effect of credit risk on profitability of commercial banks in Nigeria. Specifically, this research is to determine the significant effects of credit risk and its measure indicators; and the relationship between the indicators which influence the profitability of banks. A total 8 commercial banks (SIBs) was selected for the study, from the period 2011-2014. A panel data analysis is employed for the study to provide a robustness to the analytical model which passes all validity and reliability test to be a good fit model for hypotheses testing. Diagnostic test is utilized to test for data reliability and validity. The result of the analysis has revealed that there is a negative and significant relationship between non-performing loan ratio and the profitability; negative and insignificant relationship between debts to total assets ratio and profitability, and a positive and insignificant relationship between debts to equity ratio and profitability of banks during the period of study. In general, the results propose that banks needs to refocus on the effective management of their inherent risk which often affects their profitability and financial viability. Therefore, the study concludes that credit risk impact on profitability of commercial banks in Nigeria.

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International Journal of Science and Research (IJSR)
ISSN (Online): 2319-7064
Index Copernicus Value (2013): 6.14 | Impact Factor (2015): 6.391
Volume 5 Issue 8, August 2016
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Licensed Under Creative Commons Attribution CC BY
The Empirical Effectsof Credit Risk on Profitability
of Commercial Banks: Evidence from Nigeria
Olalere Oluwaseyi Ebenezer1, Wan Ahmad Wan Omar2
1,2Universiti Malaysia Perlis, School of Business Innovation and Technopreneurship,
01000, Kangar, Perlis, Malaysia
Abstract:The study investigates the effect of credit risk on profitability of commercial banks in Nigeria. Specifically, this research is to
determine the significant effects of credit risk and its measure indicators; and the relationship between the indicators which influence
the profitability of banks. A total 8 commercial banks (SIBs) was selected for the study, from the period 2011-2014. A panel data analysis
is employed for the study to provide a robustness to the analytical model which passes all validity and reliability test to be a good fit
model for hypotheses testing. Diagnostic test is utilized to test for data reliability and validity. The result of the analysis has revealed that
there is a negative and significant relationship between non-performing loan ratio and the profitability; negative and insignificant
relationship between debts to total assets ratio and profitability, and a positive and insignificant relationship between debts to equity ratio
and profitability of banks during the period of study. In general, the results propose that banks needs to refocus on the effective
management of their inherent risk which often affects their profitability and financial viability. Therefore, the study concludes that
credit risk impact on profitability of commercial banks in Nigeria.
Keywords: Credit risk, profitability, commercial banks, systematically important banks (SIBs) and financial institutions
1. Introduction
The banking sector is considered to be an important means of
financing for most infant businesses. By its nature, banks
face numerous risks which arises as a result of its dynamic
operations, and the complexity of the economic environment
in which it operates. Thus, since the inception of financial
institutions in the early decades in a couple of developing
countries especially Nigeria, the studies on the effect of
credit risk on profitability of commercial banks and financial
institutions have been very active. There are numerous
reports on the study of credit risk and profitability in various
parts of the emerging economy including developed
economy (see [1], [2], [3], [4], [5], [6], [7] and others).
Albeit, some significant results is reported in the previous
studies but it lacks robustness in the modeling and most of
the results are inconclusive. The aim of this study is to
examine the effect of credit risk on the profitability of
commercial banks, specifically in Nigeria. The application of
the panel data analysis in the studies of credit risk on
profitability is to overcome the lack of robustness in the
modelling. The focus of the study is Nigeria, using recent
financial data and adopting the systematically important
banks in the country. By definition, theSystematically
Important Banks (SIBs) has categorized by Central Bank of
Nigeria based on four selection criteria: as defined by their
total assets, interconnectedness, substitutability and
complexity. Hence, these are the contributions of the study.
Adequate management of credit risk in financial institutions
is critical for the survival and growth of the Financial
Institutions. In the case of banks, the issue of credit risk is
even of greater concern because of the higher level of
perceived risks resulting from some of the characteristics of
clients and business conditions that they find themselves in.
According to [8] banks originates for the main purpose of
providing a safe storage of customer’s cash. He argued that
since this money received from the customers was always
available to the bank, they later put it to use by investing in
assets that are profit earning. Thus, the practice of advancing
credits. Banks are in the business of safeguarding money and
other valuables for their clients. They also provide loans,
credit and payment services such as checking accounts,
money orders and cashier’s checks. Credit risk is regarded as
the extent of value fluctuations in debt instruments as well as
derivatives due to variations in the underlying credit quality
of counterparties and borrowers [9]. Credit risk is the most
important source of risk for the capital adequacy of banking
institutions [10]. However, the net worth and profitability are
not only determined by default risk of assets but also on off
balance sheet items, re-pricing characteristics, liabilities, and
overall credit quality [11].Therefore, the management of
credit risk is very imperative to banks because it is an
essential part of the loan process, maximizes the risk of the
bank to increase their financial performance, adjust the risk
rate of return through shielding the bank from the adverse
effects of credit risk [12]. Thus, the paper examines the
effect of credit risk on profitability of commercial banks in
Nigeria.
2. Literature Review
According to the study of [13], it suggested that bank risk
taking has pervasive effects on bank profits and safety. The
study of [14] also asserts that the profitability of a bank
depends on its ability to foresee, avoid and monitor risk. It is
also observed that the weak management in banks has net
effect of increasing the ratio of substandard credits in the
bank’s credit portfolio and decreasing the bank’s
profitability. The bank supervisors are well aware of this
problem, it is however very difficult to persuade bank
managers to follow more prudent credit policies during an
economic upturn, especially in a highly competitive
environment. [15] observed that the increased number of
banks over-stretched their existing human resources capacity
which resulted into many problems such as poor credit
appraisal system, financial crimes, the accumulation of poor
asset quality among others and this led to increase in the
number of distressed banks. Other factors identified are bad
Paper ID: ART2016315
DOI: 10.21275/ART2016315
1645

International Journal of Science and Research (IJSR)
ISSN (Online): 2319-7064
Index Copernicus Value (2013): 6.14 | Impact Factor (2015): 6.391
Volume 5 Issue 8, August 2016
www.ijsr.net
Licensed Under Creative Commons Attribution CC BY
management, adverse ownership influences and other forms
of insider abuses coupled with political considerations and
prolonged court process especially as regards debt recovery.
Most recently, [16] examine the impact of credit risk
management on the commercial banks performance in
Nigeria. Financial reports of seven commercial banking
firms were used to analyze for seven years (2005 – 2011). In
the model, Return on Equity (ROE) and Return on Asset
were used as the financial performance indicators while Non-
performing loans (NPL) and Capital Adequacy (CAR) as
credit risk indicators. Using a panel regression model, the
findings of the study revealed that credit risk management
has a significant impact on the profitability of commercial
banks’ in Nigeria.
On the contrary [17] also examined the effect of credit risk
on the banking profitability: A case of Bangladesh. The
study uses annual reports of 18 banks from 2003 to 2013;
ROA, ROE and NIM were used as profitability indicators
while NPL, LLRGL (ratio of loan loss reserve to gross loan),
LLRNPL (ratio of loan loss reserve to non-performing loan)
and CAR as credit risk indicators. However, using OLS
random effect model and GLS, the findings of the study
revealed that non-performing loans and LLRGL as a
negative and significant effect on all profitability indicators.
In addition, [18] equally examined credit risk management
and profitability in Commercial Banks in Sweden. Using the
regression model for the empirical analysis, the study found
that credit risk indicator (Non-performing loans) has an
effect on profitability as measured by (ROE) more than
capital adequacy ratio, and the effect of credit risk
management on profitability was not the same for all the
banks included in their study. However, a significant
relationship between credit risk and financial performance
were also established by the studies of [19], [20], [21], [22],
and [23]. Therefore, previous studies on the relationship
between credit risk and profitability are discuss thus;
[19] adopt the NPLs ratio & LATD, the study found that
Credit risk has a positive relationship with banks financial
performance.
[21] use capital asset ratio and Cost of bad & doubt loans,
and the study found that Capital asset ratio & cost of bad
loans have effect on banks financial performance
[23] employ the NPLs ratio in his study, the study found that
Non-performing loan ratio has positive effect on banks
profitability
[18] use NPLs ratio, and the study found that Credit risk has
effect on profitability of banks
[16] employ NPLs ratio & CAR in his study, and found that
Credit risk has significant impact on profitability of
commercial banks
[20] use NPLs ratio & Net charge-off rate in his study, and
found that credit risk has positive relationship with banks
performance.
[26] employ NPL/LA, ratio of total loan to deposit, and the
study concluded that the effect of credit risk on bank
performance measure by ROA of banks is cross-sectional
invariant; and that the nature and managerial pattern of
individual firms do not determine the impact.
[24] use NPL/total loan, Operating cost/total amount of
loans, capital fund/risk weighted assets to measure credit
risk. The study revealed that credit risk management is an
important predictor of banks financial performance.
[5] employs the amount of credit, level of NPLs. The study
revealed that the bulk of the profits of commercial banks are
not influenced by the amount of credit and non-performing
loans, therefore suggesting that other variable other than
credit and NPLs impact on profits.
The above discovery shows that related studies have
investigated the effect of credit risk on financial
performance; while some of the studies were conducted in
Sweden, Bangladesh, Nepal etc. [18], [23], [24] etc. and to
lesser extent, for emerging markets in Africa such as Ghana
and Kenya [20], [5]. However, quite a number of researchers
in Nigeria amongst others have carried out extensive studies
on credit risk, and they have produced mixed results [25],
[21], [19], [16], and [26] etc. Apart from the oversight role of
the regulating authorities’ (CBN), there is still paucity of
robustness, conclusive and empirical studies on the effect of
credit risk on profitability of commercial banks in Nigeria.
The study therefore aimed at contributing to the literature
gap by examining the effects of credit risk on profitability
using recent financial report to capture the impact on the
systematically important banks (SIBs).
2.1 Profitability
Mostly, profitability has been arguably the most paramount
and continuous monitored aspect of commercial banks. It has
gained attention from the last couple of years, reason been
that the banking sector is considered as the main engine of
economic growth [27]. Technically, profitability can be
defined as the assessing of a bank policy and operation in a
monetary form. It also shows a banks overall financial health
over a period of time. In this study, return on equity will be
employed as a proxy for profitability. The reason for
choosing return on equity is that it reveals how much profits
or income a firm earned in comparison to the total amount of
shareholders equity found in the balance sheet. A financial
institution that has a high return on equity is more likely to
be capable of generating cash internally. Therefore, in order
for banks to increase or maximize its profit, it should engage
in more transaction by increasing its risk or reduce its
operating cost.
3. Research Methodology
3.1 Empirical Investigation and Methodology
Data for this study consists of annual observations on 8
Nigeria commercial banks between 2011 and 2014. The
commercial banks chosen are Systematically Important
Banks (SIBs) has categorized by Central Bank of Nigeria
based on four selection criteria: as defined by their total
Paper ID: ART2016315
DOI: 10.21275/ART2016315
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International Journal of Science and Research (IJSR)
ISSN (Online): 2319-7064
Index Copernicus Value (2013): 6.14 | Impact Factor (2015): 6.391
Volume 5 Issue 8, August 2016
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assets, interconnectedness, substitutability and complexity.
They are term as “too big to fail” because of their critical
functions such that, should the firm go unexpectedly into
liquidation, the rest of the financial system and the economy
would face severe adverse consequence. The data was
obtained from annual reports and financial statement of the
banks. Because the data contains information on cross
sectional units observed over time, a panel data estimation
technique is adopted. This allows us to perform statistical
analysis and apply inference techniques in either the time
series or the cross−section dimension. The model takes the
form:
𝑌
𝑖𝑡 = 𝛼0 + 𝛽𝑋𝑖𝑡 +𝜀𝑖𝑡 (1)
Therefore, moving a step further, the regression model of the
study takes the form of;
𝑅𝑂𝐸𝑖𝑡 = 𝛽0+ 𝛽1𝑇𝐷𝑇𝐴𝑖𝑡 + 𝛽2𝑁𝑃𝐿𝐺𝐿𝐴𝑖𝑡 +𝛽3𝑇𝐷𝑇𝐸𝑖𝑡
+𝜀𝑖𝑡 (2)
Where i is 8 cross sections and periods t is 2011....2014. Yit
is a dependent variable which represents bank profitability
measured by the return on equity (ROE); ROE is use because
it reveals how much profits a firm earned in comparison to
the total amount of shareholders equity found in the balance
sheet and Xit is a vector of the independent variables which
represent credit risks. The variables are debt-total asset ratio,
non-performing loan ratio, and debt-equity ratio. They have
been selected on the basis of their potential relevance to this
model, and because of their importance in depicting a bank’s
real financial position. Some of the independent variables
will vary over time and cross sections, whereas others will
only vary across sections. The intercept α i varies across
banks to capture the specific effects for each country. In
what follows we discuss the three broad explanatory
variables of the model. Thus, the hypotheses of the study
postulates that credit risk impact on profitability of
commercial banks in Nigeria.
4. Research Findings and Analysis
4.1 Data Preliminaries
The main aim is to show the pattern of the collected dataset
in the study. The variables (ROE, TDTA, NPLGLA and
TDTE) represents the profitability and credit risk indicators
collected from the annual time series reports of eight (8)
systematically important banks in Nigeria. The screening and
testing of the dataset confirms that the data is clean.
Figure 2: Financial performance ratio of selected banks in
Nigeria for the period of 2011 to 2014 (Return on equity).
Figure 3: Financial performance and financial risk ratio of
selected banks in Nigeria for the period of 2011 to 2014
(Return on equity and total debt to asset ratio)
As depicted in Figure 2 and 3 above, at initial stage, the
return on equity of selected banks is time variant during the
period of study. This implies that there is a difference
between commercial banks in Nigeria in terms of return on
equity. Similarly, the total debt to asset ratio is time variant
during the period of study. This suggest that there is a
difference between commercial banks in Nigeria in terms of
debt to asset ratio.
Figure 4: Financial risk ratio of selected banks in Nigeria for
the period of 2011 to 2014 (Non-performing loan to total
gross loan ratio and total debt to equity ratio)
As depicted in Figure 4 above, at initial stage, the non-
performing loan ratio of selected banks is also time variant
during the period of study. This implies that there is a
difference between commercial banks in Nigeria in terms of
non-performing loan ratio. In other words, the study can
suggest that the non-performing loan ratio of banks change
over time. Also, the debt to equity ratio of selected banks is
time variant during the period of study. This suggest that
there is a difference between commercial banks in Nigeria in
terms of total debt to equity ratio.
4.2 Descriptive Statistics
The descriptive results in Table 2 indicate that ROE has a
mean of 18.9 percent with minimum and maximum value of
6.9 and 29.5 percent (i.e. 0.069 and 0.295) respectively. This
indicates that the use of shareholders fund to generate
earning is averagely low in this period of study. Also, TDTA
has a mean of 85.3 percent, with the minimum and maximum
value of 80.3 and 91.4 percent (i.e. 0.803 and 0,914)
respectively. This implies that most of the Nigerian banks
Paper ID: ART2016315
DOI: 10.21275/ART2016315
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International Journal of Science and Research (IJSR)
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averagely rely on debt to finance their operations. NPLGLA
has a mean of 2.4 percent, with the minimum and maximum
value of 0.2 and 10 percent (0.002 and 0.1) respectively. This
implies a relatively low concentration of non-performing
loan ratio among the Systematically Important Banks in
Nigeria. Finally, TDTE has a mean of 616.6 percent, with the
minimum and maximum value of 409.0 and 1076 percent
(i.e. 4.090 and 10.760) respectively. This implies that the
Systematically Important Banks are aggressive in financing
their growth with debt. Aggressive leveraging practices are
often associated with high level of risk. This may result in
volatile earnings as a result of the additional interest expense.
Table 2: Descriptive statistics
N
Mean
Std. Dev.
Min.
Max.
ROE
32
0.189
0.065
0.069
0.295
TDTA
32
0.853
0.029
0.803
0.914
NPLGLA
32
0.024
0.019
0.002
0.1
TDTE
32
6.166
1.706
4.090
10.760
Source: Authors computation
4.3 Correlation
The correlation matrix of the variable included in the model
is presented in Table 3. The correlation matrix is to show that
the data is random, implying that it is reliable and stable.
However, since the number of significant exceeds the
insignificant, we can proceed for hypothesis testing.
Table 3: Correlation matrix of variables
ROE
TDTA
NPLGLA
TDTE
ROE
1.0000
TDTA
-0.6022*
1.0000
NPLGLA
-0.3696*
-0.2432
1.0000
TDTE
-0.5985*
0.9989*
0.2546
1.0000
Note: **, significant at the 0.05 level (2-tailed)
4.4 Data Reliability Tests
The study conducted a reliability test on the data starting
with ADF-Fisher to test for the presence of unit root in the
data. The results indicated that all the variables passed the
unit root test at level (i.e. stationary at level and at 1%
significant level). Also, Breusch-Pagan / Cook-Weisberg test
for heteroskedasticity was performed. The outcome of the
test indicates that there is no presence of heteroskedasticity
in the model. That is to say, since the p-value is greater than
0.05, we accept the null hypothesis supporting the absence of
heteroskedasticity in the model. In the same vein,
Wooldridge test was conducted to detect whether there is an
autocorrelation problem in the model. It is assume that if p-
value is less than 0.05, reject H0. However, the result shows
that the p-value is greater than 0.05. Therefore, we accept the
null, i.e. there is no autocorrelation problem.
Table 4: ADF-Fisher Unit Root Test with AIC Criteria.
Variables
Intercept only at level
p-value
I(d)
ROE
-5.40969
0.0000***
I(0)
TDTA
-6.17195
0.0000***
I(0)
NPLGLA
-6.38276
0.0014***
I(0)
TDTE
-6.55636
0.0000***
I(0)
Note: *** indicates significant at 1% level.
4.5 Panel Data Analysis
The study applies panel data analysis for its estimations,
which requires special techniques to account for time-series
and cross-sectional dimension of the data. So, the study
adopt the fixed effect and random techniques for estimation
and choose among them based on specific econometric test
to find a model which fits our data best. However, as was
discussed earlier, we should account for individual effects of
cross-section units (banks) and use panel data techniques to
obtain higher precision of the estimates. The fixed effects
model accounts for difference in the cross-section units by
assuming different constant term for each banks. Thus,
random effect model assumes that individual specific effects
vary randomly across cross-sections. Therefore, the summary
of the analysis is shown in Table 5 below.
Table 5: Summary of panel data analysis using ROE as
dependent variable
Variable Effect
Fixed Effect
Random Effect
Coef.
t-stats
Coef.
t-stats
TDTA
-1.452
-1.32
-1.681
-1.54
NPLGLA
-1.099*
-2.80
-1.247***
-3.25
TDTE
.0188
0.91
.01586
0.80
_cons
1.338
1.61
1.5553
1.89
R-squared
0.2749
0.6049
Adj. R-sqd
0.4368
0.4724
F-stat
2.65
13.94
Prob > F
0.075*
0.0030***
Hausman Test
0.2684 (REM)
No. of Obs.
32
32
Note: TDTA = Total debt to total assets. NPLGLA = Non-
performing loan to gross loan and advances. TDTE = Total
debt to total equity.
*** indicates significant at 1%, ** indicates significant at
5%, * indicates significant at 10%.
4.6 Random Effect Model
The study applies the random effect model has it is found to
be suitable for the analysis through the Hausman
Specification test. Hence, since p-value for the test is > 5%,
we accept the null (indicating that the random effects model
is efficient, consistent and appropriate for our analysis).
Table 6: Panel data analysis (random effect regression
model)
Variable
Coef.
Std. Error
t-Stat
Prob.
TDTA
-1.681
1.0929
-1.54
0.124
NPLGLA
-1.247
0.3839
-3.25
0.001**
TDTE
0.0158
0.0197
0.80
0.422
_cons
1.555
0.8226
1.89
0.059
R-squared
0.6049
F-statistic
13.93
Prob (F-statistic)
0.003**
n
32
Note: ** significant at 1% level.
From Table 6, the R-squared of the model indicated that 60%
of the variability in the financial performance (ROE) is
explained by the independent variables. The Prob (F-
statistic) of the study also indicates that the model is
statistically significant at 1% level. However, one of the
major financial risk of a banking business is credit risk [29].
Paper ID: ART2016315
DOI: 10.21275/ART2016315
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As a result, bank specific factors can enhance probability of
credit risk at higher side. The total debt to asset ratio is
negatively insignificant with ROE during the period. On the
contrary, non-performing loan ratio is negatively significant
with ROE during the period. This implies that a unit increase
in non-performing loan ratio results in the decrease of banks
profitability by 12.4% during the period under study, and
vice-versa. However, total debt to total equity ratio show a
positive but no significant relationship with the profitability
of banks. Therefore, based on the coefficient value shown in
Table 6 above, this study argue that non-performing loan
ratio is one of the major determining factor of return on
equity among the systematically important banks (SIBs) in
Nigeria.
5. Discussion of findings
The management of credit risk is crucial to financial
institutions survival, owner’s interest and ultimately, their
profitability as well. From the analysis, credit risk indicators
(total debt to total asset ratio) is negatively insignificant with
ROE. The profitability of banks will be affected negatively if
banks rely mostly on heavy debt to finance its operations,
and an increase in debt ratio of the banks implies high debt
value on the liability side of their balance sheet and
ultimately leading to lower profit margin during the period.
Consequently, the non-performing loan ratio has a negative
and significant relationship with profitability under ROE.
The plausible reason for this is that most of the
systematically important banks have a fairly bad credit
management policies because it reflect a negative influence
on their return on equity, and this implies that they are
exposed to greater risk of illiquidity and distress. The
implication is that, the increasing bad loans in banks occurs
as a result of poor credit policies in banks, bad management
and this reduces the bank’s profitability significantly. This
negative and significant relationship is in agreement with the
findings of [30], [26], [17], [25], [6], and [29]. Subsequently,
the debt to equity ratio show a positive and no significant
relationship with profitability under ROE. The implication is
that, despite the dependence of the banks on debt, there is
only 0.015% significant increase in the profitability of banks
during the period under study. Hence, this study argues that
credit risk impact on the profitability of commercial banks in
Nigeria.
However, it is a major concern for bank customers to be
aware of the safety of their deposits in any given banks. For
this reason, it is very essential for banks to critically assess
the customers who demand the extension of credit or loan
facility before granting such. This is because a weak and
poorly administered credit policy would lead to bad debt in
the loan portfolio of banks. If credit risks increase with the
growing volume of credit transactions in the banks, bad and
doubtful debts will claim the bulk of the supposed profit
estimated to be earned by banks. As these risks remain
unchecked, the profitability of banks reduces with each
transaction. This also reduces the operational performance of
banks.
6. Conclusion
The importance of the study is to fill the gap of empirical
evidence on credit risk practices in banking sector of Nigeria.
The study cover the period of 2011 – 2014, using the report
of the Systematically Important Banks (SIBs). This study has
successfully identified the factors that are significantly
affecting the profitability of the banks. The study employs
panel data analysis to examine the relationship between
credit risk and profitability of commercial banks in Nigeria,
using Hausman test in realizing the robust model for testing.
The diagnostic test (Breusch-Pagan and Wooldridge test)
indicates that there is no autocorrelation and
heteroskedasticity problem in the dataset and that the
variables are independent and identically distributed.
The relationship of debt to asset ratio is found to have
negative and insignificant effect on profitability. The non-
performing loan ratio established the negative and significant
relationship with profitability. This can be explained with the
fact that the unusual lending of loans and advances is found
to be the major portion of financial risk faced by the banks.
The relationship of gearing ratio (debt to equity ratio) with
profitability is positive and insignificant. The high geared
ratio is attributed to the fact that the banks relies heavily on
borrowing because their major source of finance contains
debt financing with the combination of equity finance. The
findings suggest that commercial banking institutions need to
refocus on the effective management of its financial risks; in
today’s dynamic environment of intense competitive
pressures, volatile economic conditions, rising default rates
and increasing levels of consumer and commercial, an
organization ability to effectively monitor and manage its
financial risk could mean the difference between success and
survival.
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Paper ID: ART2016315
DOI: 10.21275/ART2016315
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