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Advances in Social Sciences Research Journal – Vol. 10, No. 6.2
Publication Date: June 25, 2023
DOI:10.14738/assrj.106.2.15014.
Sivarajan, L. S., Alyasa-Gan, S. S., Che-Yahya, N., & Salehuddin, S. (2023). Explaining Non-Performing Loans of Commercial Banks in
Malaysia. Advances in Social Sciences Research Journal, 10(6.2). 98-106.
Services for Science and Education – United Kingdom
Explaining Non-Performing Loans of Commercial Banks in
Malaysia
Leedya Sivalaxmi Sivarajan
Department of Accounting and Finance, Faculty of Business, Management and
Professional Studies, Management and Science University, Shah Alam, Malaysia
Siti Sarah Alyasa-Gan
Corresponding Author
sitisarahgan@msu.edu.my
Department of Accounting and Finance, Faculty of Business, Management and
Professional Studies, Management and Science University, Shah Alam, Malaysia
Norliza Che-Yahya
Department of Economics and Financial Studies, Faculty of Business Management,
Universiti Teknologi Mara, Puncak Alam Campus, Malaysia
Sharullizuannizam Salehuddin
Department of Accounting and Finance, Faculty of Business, Management and
Professional Studies, Management and Science University, Shah Alam, Malaysia
ABSTRACT
This study examines the influence of bank size, capital adequacy, profitability and
liquidity on non-performing loans (NPLs). The growing risk of non-performing
loans leading to banks’ potential losses motivates this study to be conducted. This
study includes commercial banks in the Main Market of Bursa Malaysia from 2010
to 2021. To test the hypotheses, this study employs a Fixed Effect model. The results
show that bank size and capital adequacy have a significant and negative
relationship with non-performing loans, indicating that larger banks and higher
capital adequacy have lower NPLs. Generally, this study found a limited number of
commercial banks listed in the Malaysian market, providing a smaller sample.
Nonetheless, the results of this study may benefit commercial banks in the
significant factors to prevent the occurrence of non-performing loans.
Keywords: Non- performing loan, Capital adequacy, Liquidity, Fixed effect model.
INTRODUCTION
The primary asset of commercial banks is disbursing loans and advances [19]. Generally, a drop
in the value or the worth of banks’ loan books (non-performing loans) is the primary reason for
the banking industry’s financial instability, eventually affecting the overall nation’s financial
system [22]. Non-performing loans occur everywhere worldwide and play a major part in
banks collapsing. In order to gauge a bank’s level of credit risk and the viability of its
outstanding loans, the law requires banks to disclose or declare their ratio of non-performing
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Sivarajan, L. S., Alyasa-Gan, S. S., Che-Yahya, N., & Salehuddin, S. (2023). Explaining Non-Performing Loans of Commercial Banks in Malaysia.
Advances in Social Sciences Research Journal, 10(6.2). 98-106.
URL: http://dx.doi.org/10.14738/assrj.106.2.15014
loans to total loans. A high ratio indicates that the bank is at a higher risk of loss. In another
way, if the bank cannot recoup the unsettled or unpaid loan balances, a low ratio specifies that
the bank faces risks from outstanding loans, commonly referred to as non-performing loans.
Non-performing loan occurs once the debtor owes a payment that is further than 90 days past
due, when the interest has been renegotiated to a different value, postponed, or endorsed for
more than 90 days, or when instalments are less than 90 days past due but are not ever again
anticipated [3]. Examples of non-performing loans include those where the principal has been
reimbursed, but a portion of the loan balance is still owed [16]. The negative implication of
enduring a high ratio of NPLs for commercial banks is a contraction of credit supply, distorted
credit allocation, and worsened market confidence, negatively affecting the banks’
performance. Worsening of non-performing loan levels might also imperil the bank stability,
negatively affecting the country’s economy. For instance, many financial crises that affected the
ASEAN countries have resulted from nonstandard credit growth that preceded an expansion in
financial institutions’ failures [6]. Understanding that banks are pertinent to economic
development, this study finds investigating the influences affecting banks’ non-performing
loans crucial.
Although past studies highlight the importance of macroeconomic factors [5, 23], this study
argues that past studies have yet thoroughly identified the potential of banks’ internal factors
and their relative role in overcoming the issue of non-performing loans. Specifically, this study
examines the potential roles of liquidity, profitability, size and capital adequacy of banks as
factors of banks’ non-performing loans in Malaysia.
Research Framework
Figure 1: Theoretical Framework of the Determinants of Non-performing Loans
This study is expected to be significant to several parties, such as financial regulators and
commercial banks. This study can offer insights to Bank Negara Malaysia and commercial banks
in implementing initiatives to deepen and strengthen the commercial banks by reducing the
amount of non-performing loans. The significant variables (bank size and capital adequacy)
found in this study indicate that smaller commercial banks and lower capital funds should be
more cautious of the number of loans issued to reduce the possibilities of non-performing loans.
While loans may be one of the major assets of commercial banks, they may also be a liability if
poorly managed, especially low-quality loans. Thus, this study provides additional empirical
evidence that internal factors of commercial banks, specifically the bank size and capital
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adequacy, are worth examining in determining non-performing loans. The rest of this study is
sequenced accordingly: literature review, methodology, discussion and analysis, and
conclusion.
LITERATURE REVIEW
Non-Performing Loans
When the debtor has more or further than a certain number of days overdue on the loan’s
organized payments date, it is the most typical definition of a non-performing loan [15]. High
non-performing loan levels may compromise the stability of the banking system and its
capacity to lend to the actual economy [12]. Therefore, it is clear that dealing with large non- performing loan rates is necessary, especially for economies that rely heavily on banks, like the
Euro area [12]. To assess whether the banking institutions are handled effectively and to fortify
the Malaysian financial system, financial institutions must study bank efficiency [21], which in
this case is the performance of loans.
Numerous researches on the causes of non-performing loans have been conducted over the
years due to the negative impact non-performing loans have on the financial performance and
viability of commercial banks. Banks can control the rise of non-performing loans by being
aware of the main factors influencing them, limiting their negative effects on banks’
performance. Additionally, being aware of the effects of non-performing loans contributes to
maintaining a strong financial system that can foster economic expansion [23].
In a study by Zainol et al. [26], the macroeconomic variables determining the non-performing
loans of Malaysia’s banks and financial institutions were examined. GDP is substantial and has
a negative impact on non-performing loans. In contrast, base lending rate and household
income distribution are significant and have a favourable relationship with non-performing
loans. Another study by Zain et al. [25] found capitalization, net interest margin and real
exchange interest rate to significantly influence banks’ non-performing loans.
According to Wood and Skinner [23], gross domestic product growth negatively influences non- performing loans. Their result suggests an increase in the real economy strengthens the
borrower’s capability to pay off their debt, which in turn helps to reduce the amount of non- performing loans. On the other hand, unemployment has detrimental effects on households’
and businesses’ cash flow, increases their debt load, and makes it impossible for them to fulfil
their financial responsibilities [23]. Thus, the unemployment rate also is found to influence non- performing loans positively.
While macroeconomic factors have been vastly explained, the internal factors of commercial
banks have yet been thoroughly examined. This study intends to fill the gap by suggesting the
possible influence of commercial banks’ internal factors on higher or lower non-performing
loans. Specifically, this study proposes that banks’ size, profitability, capital adequacy and
liquidity can influence banks’ non-performing loans.
Bank Size
Enormous assets provide banks access to large amounts of credit, which allows them to lower
interest rates [2]. Due to the ease of credit payments made possible by such low-interest rates,
banks will have less troublesome loans to deal with. The sum of a bank’s assets can be used to
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Sivarajan, L. S., Alyasa-Gan, S. S., Che-Yahya, N., & Salehuddin, S. (2023). Explaining Non-Performing Loans of Commercial Banks in Malaysia.
Advances in Social Sciences Research Journal, 10(6.2). 98-106.
URL: http://dx.doi.org/10.14738/assrj.106.2.15014
determine its size. For instance, large asset banks can make more money if their operations are
monitored and would not be highly impacted by borrowers’ inability to repay their loans.
According to the findings of studies by Barus and Erick [2], larger banks should have lower non- performing loans. Another study by Jabbouri and Naili [13] also found a negative relationship
between bank size and non-performing loans, asserting that larger banks are more equipped
with risk management tools and resources, which can reduce information asymmetry and
moral hazard issues. Hence, non-performing loans will also decrease. Similarly, we hypothesize
that bank size has a negative relationship with NPLs.
➢ H1: There is a negative relationship between bank size and non-performing loans.
Profitability
Profitability-related factors examine whether more profitable banks are more likely to take
risks and have higher non-performing loan rates. A bank’s profitability suffers from non- performing loans because of provisions for such loans that might not be of the best quality [8].
According to Ghosh [7], there is an inverse relationship between profitability and NPLs. Banks
with higher income and revenues have lower chances of experiencing NPLs. This is because
they try to be more careful to reduce the risk of operation by investing lesser in high-risk
investments. Similarly, Louzis et al. [9] also found a negative relationship between banks’
earnings and NPLs. Thus, this study hypothesizes that banks with higher profitability face lower
non-performing loans.
➢ H2: There is a negative relationship between profitability and non-performing loans.
Capital Adequacy
The capital adequacy ratio assesses a bank’s solvency and risk-aversion capacity. It is used to
safeguard customers and encourage financial system stability and efficiency. In theory, the
impact of CAR on non-performing loans is unknown. On the one hand, banks with high CAR may
pursue opportunities more aggressively, resulting in increased risk-taking and more hazardous
credit portfolios [4]. Consider raising the capital requirement. This increases capital costs,
causing banks to choose lower deposit and loan volumes. The decrease in aggregate loan
volume leads to increased loan rates and increased risk-taking by entrepreneurs. As a result,
tighter capital regulation raises the risk of individual loans by reducing competition for loans
and exacerbating the entrepreneurs’ moral hazard problem [11]. Therefore, this study
proposes that a higher capital adequacy ratio should increase banks’ non-performing loans.
➢ H3: There is a positive relationship between capital adequacy and non-performing
loans.
Liquidity
This study proposes the potential relationship between banks’ liquidity and non-performing
loan. Excess liquidity among banks is the concept in an economy where financial institutions
have excess cash but insufficient investment opportunities. According to Mahyoub and Said
[17], the importance of liquidity in ensuring commercial banks can face difficulties, such as
potentially increasing non-performing loans, is substantial. The revamp of Basel III, aiming to
enhance the ability of banking sectors to overcome economic or financial crises, proves that
banks’ liquidity plays a vital role in a sound financial institution’s operation. However, it is
difficult for banks to transfer money from surplus to deficit units while keeping enough liquidity
to pay the depositors. Banks face opportunity costs and the burden of paying interest on funds
collected from depositors [14]. Due to the excess cash, the banks are willing to supply a higher
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number of loans regardless of borrowers’ borrowing capacity to utilize the excess liquidity.
Thus, this study hypothesizes that higher liquidity will increase banks’ non-performing loans.
➢ H4: There is a positive relationship between liquidity and non-performing loans.
METHODOLOGY
Research Design and Data Collection
This study examines the impact of bank size, capital adequacy, profitability and liquidity on
non-performing loans that are in Malaysia. The sample period ranges from January 2010 until
December 2021. Since 2010 was the year following the financial crisis, this time frame was
chosen to prevent data biases. 10 commercial banks are listed in Bursa Malaysia. However, this
study excludes 2 commercial banks due to data availability issues. The final sample of this study
is 8 commercial banks listed in the Main Market of Bursa Malaysia. The multiple regression
analysis of this study employs the ordinary least square (OLS) method to examine the
relationship between non-performing loans and the key determinants, which are the bank size,
capital adequacy, profitability and liquidity. All of the data are acquired from Thomson Reuters
Datastream. Table 1 explains the measurement of each variable. Prior to the multiple regression
analysis, several diagnostic tests have been conducted. The tests include a normality test,
multicollinearity test, heteroscedasticity test, stationary test to fulfil the panel regression
analysis assumption. Referring to Table 2, this study employs the Hausman test to identify the
suitable model [10]. Considering the p-value is lesser than 0.05, this study concludes that the
null hypothesis is rejected and that the Fixed Effect model is preferred. Equation 1 indicates the
regression model of this study.
NPLit = β0 + β1Sizeit + β2CAPit + β3PROFit + β4Liquidityit + εit (1)
Table 1. Measurement of Variables.
Variable Proxy Measurements
Non-performing loans NPL =
Non − performing Loans
Total Loans
Bank Size SIZE = Natural Logarithm of Total Assets
Profitability PROF =
Net Income
Total Assets
Capital Adequacy CAP =
Total Equity
Total Assets
Liquidity LIQ =
Total Assets
Total Liabilities
Table 2. Hausman Test.
Test Summary Chi-Square Stats. P-value
Period Random 86.274 0.000***
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Sivarajan, L. S., Alyasa-Gan, S. S., Che-Yahya, N., & Salehuddin, S. (2023). Explaining Non-Performing Loans of Commercial Banks in Malaysia.
Advances in Social Sciences Research Journal, 10(6.2). 98-106.
URL: http://dx.doi.org/10.14738/assrj.106.2.15014
FINDINGS AND DISCUSSIONS
Descriptive Statistics Analysis
Table 3. Descriptive Statistics.
Variable NPL SIZE CAP PROF LIQ
Mean 2.044 25.920 9.405 1.100 183.607
Median 1.855 25.942 9.115 1.115 1.816
Maximum 6.140 27.617 13.860 2.000 3346.138
Minimum 0.610 24.522 5.130 0.190 0.630
Jarque-Bera 23.417 6.118 1.736 17.480 1105.808
P-value 0.000 0.047 0.420 0.000 0.000
Concerning Table 3, the mean for non-performing loans is 2.04. Comparing the NPL ratio mean
with Zain et al. [25], a recent study in Malaysia reported an NPL ratio of less than 1 from 2009
to 2018. The increasing value of NPL ratio indicates that a higher number of borrowers cannot
repay their loans in recent years. The mean for other variables, such as bank size is reported at
25.92 (log), capital adequacy at 9.41 %, profitability at 1.1 % and liquidity at 183.61 times. The
median for non-performing loan is 1.855. The highest median for independent variable is bank
size, capital adequacy, liquidity and profitability. The maximum value for non-performing loan
is 6.140, capital adequacy is 13.860, liquidity is 3346.138, bank size is 27.617, and profitability
is 2.000. Moreover, the minimum value for non-performing loan is 0.610, capital adequacy is
5.130, liquidity is 0.630, bank size is 24.522 and profitability is 0.190. The p-value of Jarque
Bera test also shows that this study is not normally distributed. However, according to Asteriou
and Hall [1], financial variables are non-normally distributed. Thus, following the study, the
existence of non-normally distributed data should be permissible to be employed for the
regression analysis.
Correlation Analysis
Table 4. Pearson Correlation Coefficient.
Variables NPL SIZE CAP PROF LIQ
NPL 1.000
SIZE 0.140 1.000
CAP -0.046 0.145 1.000
PROF -0.267 0.144 -0.279 1.000
LIQ 0.374 0.287 0.019 -0.281 1.000
A high correlation between independent variables makes it easy to estimate the regression
coefficients, but doing so comes with huge standard errors, making it impossible to estimate
the population values of the coefficients correctly. Thus, before estimating the regression
model, the study performed a correlation analysis and the result is presented as in Table 4. This
study found that the highest correlation between independent variables in the model is
between liquidity and non-performing loans, at 37.4%. However, there is no value surpassing
0.8, which according to Asteriou and Hall [1], any value below 0.9 is considered low correlation.
Thus, this study concludes that the model is free from multicollinearity issues.
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Sivarajan, L. S., Alyasa-Gan, S. S., Che-Yahya, N., & Salehuddin, S. (2023). Explaining Non-Performing Loans of Commercial Banks in Malaysia.
Advances in Social Sciences Research Journal, 10(6.2). 98-106.
URL: http://dx.doi.org/10.14738/assrj.106.2.15014
➢ Fourthly, liquidity is found to have a positive but insignificant relationship with non- performing loans. According to Martiningtiyas and Nitinegeri [18], with ample liquidity,
banks may be tempted to engage in high-risk lending. This can lead to overfunding
existing customers or funding new customers with poor credit. The bank’s overall credit
quality will suffer because of this. However, once again, without significance, the
relationship between liquidity and non-performing loans is inconclusive, and this study
is unable to support its H4.
CONCLUSION
This study investigated the determinants of non-performing loans in Malaysia’s commercial
banks. This study was also a direct result of realizing that internal factors can be an issue for
non-performing loans to occur. The data from the result of descriptive statistics shows this
study is not normally distributed. After correlation analysis is completed, thus it is concluded
that this research has no multicollinearity issue as no values have surpassed 0.9. To answer the
research questions, the data was examined using a Fixed Effect Regression Model to determine
the relationship between the dependent variable (non-performing loan) and all of the
independent variables (bank size, capital adequacy, profitability and liquidity). The Multiple
Regression Model discovered that only bank size and capital adequacy significantly affect the
level of NPLs in Malaysian commercial banks.
The limitation of this research is the number of banks. There were 10 listed companies in Bursa
Malaysia, but this research manages to investigate only 8 commercial banks. Due to data
constraints, the study was unable to include a large number of publicly listed banks in Malaysia.
Thus, this study suggests that other potential researchers extend the examination to non-public
listed banks and the time frame of studies to ensure the findings is robust and improve the
outcome.
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