The Impact of Credit Risk on Performance: A Case of South African Commercial Banks

Lawrence, Babatunde; Doorasamy, Mishelle; Sarpong, Prince

doi:10.1177/0972150920969927

Cited by 3 publications

(4 citation statements)

References 18 publications

(22 reference statements)

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“…Another comparison of the impact of CR on the profitability of large and small banks in South Africa indicated that the CR of smaller banks has a more significant effect on performance when proxied by ROA compared to larger banks. However, the CR of smaller banks exhibited a lesser impact on financial performance than larger banks, when measured by ROE during the period from 2008 to 2017 (Lawrence et al, 2020). Furthermore, research reveals that the profitability of the parent bank negatively affects the subsidiary's CR (Škrabić Perić et al, 2018).…”

Section: Literature Reviewmentioning

confidence: 96%

Determinants of credit risk: Empirical evidence from Indian commercial banks

Antony

Suresh

2023

Banks and Bank Systems

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Credit risk is a significant factor affecting the financial stability of banks. Keeping the credit risk under control is essential to maintain a bank’s cash flow. This paper examines the various profitability, microeconomic and macroeconomic indicators that affect a bank’s credit risk. The study uses the dataset of 31 banks from 2012 to 2021 and employs a panel data modelling approach to account for any variations in risk-taking behavior. The results revealed a statistically significant negative relationship between return on equity and credit risk when nonperforming loans proxy credit risk. This finding was consistent across fixed effect, random effect, and pooled OLS methods, at 1 percent significance (P value &lt; 0.00), indicating that the extent of credit risk decreases as profitability increases. It was further found that bank age and ownership type positively affect a bank’s credit risk, while factors such as bank size and operational efficiency negatively affect credit risk when nonperforming loans proxy credit risk. Further, macroeconomic variables showed that gross domestic product is positively associated with credit risk, while inflation negatively affects credit risk. Overall, the findings of this paper demonstrated that credit risk is affected by both micro and macroeconomic factors. The paper also addresses significant policy implications as it helps various stakeholders to examine the determinants of credit risk, make credit decisions, and ultimately lower their credit risk.

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Section: Literature Reviewmentioning

confidence: 96%

Determinants of credit risk: Empirical evidence from Indian commercial banks

Antony

Suresh

2023

Banks and Bank Systems

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“…RON-CHF exchange rate turned out to be the main factor affecting an increase in the NPL. Lawrence et al (2020) concluded that NPL, CAR, LR, LTDR and age of banks had a significant and greater impact on the ROA of small banks compared to the big ones. At the same time, NPL ratio affected the ROE of small banks to a relatively lower extent than it did in the case of big credit institutions.…”

Section: Literature Reviewmentioning

confidence: 99%

“…First, the number of banks under consideration is relatively small. However, the study took into account the majority of commercial banks that operate in Poland (assets of the banks analysed account for 84.90% of the assets of the banking sector in Poland) as well as some other studies based on relatively small samples, in fact, limited to commercial banks constituting specific banking sectors which is also the case of our research (Hada et al 2020;Lawrence et al 2020). The second limitation is connected with the relatively short horizon of the study.…”

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confidence: 99%

Determinants of Differentiation of Cost of Risk (CoR) among Polish Banks during COVID-19 Pandemic

Korzeb

Niedziółka

2021

JRFM

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The aim of the paper is to assess the evolution of the cost of credit risk (CoR) of Polish banks as a result of the COVID-19 pandemic in the first three quarters of 2020 as well as its microeconomic determinants. We analysed the structural diversity of the sample of the 13 largest Polish commercial banks in terms of the evolution of their CoR. For this purpose, a diagraphic method of Jan Czekanowski was used. It allowed us to distinguish two groups of banks displaying features characteristic of multi-object structures and three groups consisting of individual banks characterized by atypical CoR developments, significantly different from the structures of objects classified to the first and second groups. In the second part of the research, in order to identify the determinants of the observed trends, a multiple regression model was used in which the explanatory variable was the dynamics of CoR in the first three quarters of 2020. The parameters of return on capital (ROE) at the end of 2019, Non-Performing Loans (NPLs) at the end of 2019 and the dynamics of write-offs in the period 2017–2019 proved to be important explanatory variables.

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“…In addition, banks should prioritize female borrowers over males. Lawrence et al (2020) presented the effect of credit risk control on the financial performance of South African banks (i.e., for both big and small banks). For the research, the author collected data from 14 banks and then analyzed them using R-Studio software to evaluate the effect of capital adequacy ratio, non-performing loan to gross loan, loan-todeposit ratio, leverage ratio, board gender diversity, bank size, and age size as the control variables on performance based on return on asset and return on equity.…”

Section: A Credit Risk Control and Profitability Of Microfinance Banksmentioning

confidence: 99%

A Comparative Evaluation of the Effects of Credit Risk Control on the Profitability of Micro-Finance Bank

Enoch

Digil

Arabo

2021

EJBMR

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When assessing lending applications, banks face the problem of inadequate information needed to screen potential borrowers. The relevant information needed to evaluate the commitment of the entrepreneur and the likelihood of the business is challenging to interpret or even absent. This creates risk for the banks. Therefore, it is of paramount importance to give much consideration to credit management first before embarking on lending. In this research, we used both primary and secondary sources. We adopt a multi-stage sampling method by selecting a set of 21 respondents from a population of 52 credit officers. Questionnaires were used to collect data from the respondents while descriptive and inferential statistics were used to analyze the data collected and in testing the hypotheses. Specifically, we used simple percentage and regression analysis. We used the software SPSS (Statistical Package for Social Science) to implement the statistical techniques mentioned above. The results showed that microfinance banks need to strengthen their credit risk control measures to increase their profitability. This is because if properly adopted it helps to decrease the percentage of payments defaults. Credit management is important in improving the financial performance of microfinance banks and this is attributed to the fact that sounds and grounded credit management (client appraisal) allowed the bank to be efficient and have the availability of liquidity.

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The Impact of Credit Risk on Performance: A Case of South African Commercial Banks

Cited by 3 publications

References 18 publications

Determinants of credit risk: Empirical evidence from Indian commercial banks

Determinants of credit risk: Empirical evidence from Indian commercial banks

Determinants of Differentiation of Cost of Risk (CoR) among Polish Banks during COVID-19 Pandemic

A Comparative Evaluation of the Effects of Credit Risk Control on the Profitability of Micro-Finance Bank

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