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Journal articles on the topic 'Management of credit risk'

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Published: 24 April 2022

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1

Spuchlakova, Erika, and Maria Misankova. "Risk management of Credit Default Swap." New Trends and Issues Proceedings on Humanities and Social Sciences 3, no. 4 (March 22, 2017): 229–34. http://dx.doi.org/10.18844/gjhss.v3i4.1573.

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2

Akram, Hassan, and Khalil ur Rahman. "Credit risk management." ISRA International Journal of Islamic Finance 10, no. 2 (December 10, 2018): 185–205. http://dx.doi.org/10.1108/ijif-09-2017-0030.

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PurposeThis study aims to examine and compare the credit risk management (CRM) scenario of Islamic banks (IBs) and conventional banks (CBs) in Pakistan, keeping in view the phenomenal growth of Islamic banking and its future implications.Design/methodology/approachA sample of five CBs and four IBs was chosen out of the whole banking industry for the study. Secondary data obtained from the banks’ annual financial reports for 13 years, starting from 2004 to 2016, were analyzed. Multiple regression, correlation and descriptive analysis were used in the examination of the data.FindingsThe results show that loan quality (LQ) has a positive and significant impact on CRM for both IBs and CBs. Asset quality (AQ), on the other hand, has a negative impact on CRM in the case of IBs, but has a significantly positive relation with CRM in the case of CBs. The impact of 16 ratios measuring LQ and AQ have also been individually checked on CRM, by making use of a regression model using a dummy variable of financial crises for robust comparison among CBs and IBs. The model proved significant, and CRM performance of IBs was observed to be better than that of CBs. Moreover, the mean average value of financial ratios used as a measuring tool for these variables shows that the CRM performance of IBs operating in Pakistan was better than that of CBs over the period of the study.Practical implicationsThe research findings are expected to facilitate bankers, investors, academics and policy makers to build a better understanding of CRM practices as adopted by CBs and IBs. The findings would be useful in formulating policy measures for the progress of the banking industry in Pakistan.Originality/valueThis research is unique in terms of its approach toward analyzing and comparing CRM performance of CBs and IBs. Such work has not been carried out before in the Pakistani banking industry.
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3

Freeman, Mark C., Paul R. Cox, and Brian Wright. "Credit risk management." Managerial Finance 32, no. 9 (September 2006): 761–73. http://dx.doi.org/10.1108/03074350610681952.

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4

Gazi, Boran. "Credit Risk Management." Journal of Applied Statistics 38, no. 6 (June 2011): 1314. http://dx.doi.org/10.1080/02664760903335083.

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5

Kealhofer, Stephen. "Credit Risk and Risk Management." AIMR Conference Proceedings 1999, no. 3 (August 1999): 80–91. http://dx.doi.org/10.2469/cp.v1999.n3.11.

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6

Boffey, R., and G. N. Robson. "Bank Credit Risk Management." Managerial Finance 21, no. 1 (January 1995): 66–78. http://dx.doi.org/10.1108/eb018497.

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7

Nayan J., Nayan J., and Dr M. Kumaraswamy Dr. M. Kumaraswamy. "Retail Credit Risk Management in Indian Public Sector Banks." Global Journal For Research Analysis 3, no. 8 (June 15, 2012): 31–37. http://dx.doi.org/10.15373/22778160/august2014/10.

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Tigges, Christoph. "Buchbesprechung: Die Optimierung der Performance im Credit Management. Verein für Credit Management e.V. (Hrsg.: Schneider-Maessen, Schumann, Skier, Weiß)." RISKNEWS 2, no. 6 (December 2005): 76. http://dx.doi.org/10.1002/risk.200590127.

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9

Gibson, Michael S. "Credit Derivatives and Risk Management." Finance and Economics Discussion Series 2007, no. 47 (2007): 1–20. http://dx.doi.org/10.17016/feds.2007.47.

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10

Kealhofer, Stephen. "Portfolio Management of Credit Risk." AIMR Conference Proceedings 2003, no. 5 (February 10, 2003): 19–29. http://dx.doi.org/10.2469/cp.v2003.n5.3318.

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11

Vu, Joseph. "Trends in Credit Risk Management." CFA Digest 29, no. 3 (August 1999): 34–35. http://dx.doi.org/10.2469/dig.v29.n3.515.

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12

Anna, Siekelova, Kollar Boris, and Weissova Ivana. "Impact of Credit Risk Management." Procedia Economics and Finance 26 (2015): 325–31. http://dx.doi.org/10.1016/s2212-5671(15)00860-6.

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13

Adam, Tim René. "Risk management and the credit risk premium." Journal of Banking & Finance 26, no. 2-3 (March 2002): 243–69. http://dx.doi.org/10.1016/s0378-4266(01)00221-7.

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14

Luo, Na, Jiayi Yang, Yuanfeng Zhu, and Yu Zhang. "The Risk Management of Commercial Banks——Credit-Risk Assessment of Enterprises." International Journal of Economics and Finance 8, no. 9 (August 24, 2016): 69. http://dx.doi.org/10.5539/ijef.v8n9p69.

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With the diversified developments of the financial market, commercial banks are confronted with various risks, among which the credit risk is the core, and thus the assessment of enterprises’ credit risks is especially important in the credit process of the commercial banks. Based on the relevant researches about commercial banks’ credit risk management, the paper carries out a deep analysis on the factors that may affect the credit risk assessment and then establishes a relatively comprehensive credit risk assessment system. In this paper, we apply our risk assessment model, which is established on the basis of GRNN neural network model, to make an empirical analysis with the selected sample data. And the results suggest that the hit rates of identifying high quality enterprises and low quality enterprises are 92.16 percent and 93.75 percent, respectively, indicating that the model has realized a good prediction.
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15

Pradhan, Shreya, and Ajay K. Shah. "Credit Risk Management of Commercial Banks in Nepal." Journal of Business and Social Sciences Research 4, no. 1 (June 30, 2019): 27–37. http://dx.doi.org/10.3126/jbssr.v4i1.28996.

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The study is primarily focused on credit risk assessment practices in commercial banks on the basis of their internal efficiency, assessment of assets and borrower. The model of the study is based on the analysis of relationship between credit risk management practices, credit risk mitigation measures and obstacles and loan repayment. Based on a descriptive research approach the study has used survey-based primary data and performed a correlation analysis on them. It discovered that credit risk management practices and credit risk mitigation measures have a positive relationship with loan repayment, while obstacles faced by borrowers have no significant relationship with loan repayment. The study findings can provide good insights to commercial bank managers in analysing their model of credit risk management system, policies and practices, and in establishing a profitable and sustainable model for credit risk assessment, by setting a risk tolerance level and managing credit risks vis-a-vis the prevailing market competition.
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16

Lin, Xi, Yafeng Yin, and Fang He. "Credit-Based Mobility Management Considering Travelers’ Budgeting Behaviors Under Uncertainty." Transportation Science 55, no. 2 (March 2021): 297–314. http://dx.doi.org/10.1287/trsc.2020.1014.

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This study analyzes the performance of a credit-based mobility management scheme considering travelers’ budgeting behaviors for credit consumption under uncertainty. In the scheme, government agencies periodically distribute a certain number of credits to travelers; travelers must pay a credit charge for driving to complete their trips. Otherwise, they can take public transit free of credit charge. Consequently, within a credit-releasing cycle, travelers must budget their credit consumption to fulfill their mobility needs. Such budgeting behaviors can be viewed as a multistage decision-making process under uncertainty. Considering a transportation system with a credit scheme, we propose parsimonious models to investigate how the uncertainty associated with individual mobility needs and the subsequent travelers’ credit-budgeting behavior influence the multistage equilibrium of the transportation system, as well as the performance of the credit scheme on managing the transportation system. Both analytical and numerical results suggest that travelers tend to restrict their credit consumption in the early stage of a credit-releasing cycle to hedge against the risks associated with using up all credits, which compromises the performances of credit-based schemes. Moreover, a negative attitude toward risk aggravates the discrepancy between the credit consumption of the early and late stages. Last, we propose a contingency credit scheme to mitigate the negative impact incurred by travelers’ budgeting behaviors.
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17

Moloi, Tankiso. "The nature of credit risk information disclosed in the risk and capital reports of the top-5 South African banks." Banks and Bank Systems 11, no. 3 (October 12, 2016): 87–93. http://dx.doi.org/10.21511/bbs.11(3).2016.09.

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This paper used the Credit Risk Disclosure Measurement Tool (CRDMT) constructed on the basis of six main areas, namely, banks own description of credit risk (i.e., as it applies to the banks operations), banks strategy of reducing credit risk exposure (i.e., objectives of credit management), banks approach to credit modelling or the internal rating system, banks approach and the manner in which they assess their exposure to credit risk, banks credit risk mitigation strategies employed (i.e., collateral and other credit enhancements), and banks approach to the valuation of pledged collateral and other credit enhancements to assess the information disclosed on the risk and capital management reports of the top-5 South African banks. Results demonstrated that the top-5 South African banks were fairly in line with the main six credit risk areas that would result in an informative risk and capital management report, as proposed by the CRMDT. It was observed that there were, however, pockets of information that could be improved to enhance these risk and capital management reports, particularly the credit risk information made available to public. These areas included the information relating to banks credit risk mitigation strategies employed and banks strategy of reducing credit risk exposure, as well as the information relating to banks approach to the valuation of pledged collateral and other credit enhancements. These areas were noted for their partial or non-disclosure of information. Keywords: banks, credit risk, Credit Risk Disclosure Measurement Tool (CRDMT), disclosure analysis and risk and capital reports. JEL Classification: G21, G32
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18

BROLL, UDO, B. MICHAEL GILROY, and ELMAR LUKAS. "MANAGING CREDIT RISK WITH CREDIT DERIVATIVES." Annals of Financial Economics 03, no. 01 (June 2007): 0750004. http://dx.doi.org/10.1142/s2010495207500042.

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Credit risk is one of the most important forms of risk faced by national and international banks as financial intermediaries. Managing this kind of risk through selecting and monitoring corporate and sovereign borrowers and through creating a diversified loan portfolio has always been one of the predominant challenges in bank management. The aim of our study is to examine how a risky loan portfolio affects optimal bank behavior in the loan and deposit markets, when derivatives to hedge credit risk are available. In a stochastic continuous-time framework a hedging model is developed where the bank management can use derivatives to hedge credit risk. Optimal loan, deposit and hedging strategies are then studied. It is shown that the magnitude and the direction of hedging are determined by the bank manager's preferences, the corresponding risk premium and the variance of the loan rate and its hedging instrument respectively.
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19

Apanga, Michelle Ayog-Nying, Kingsley Opoku Appiah, and Joseph Arthur. "Credit risk management of Ghanaian listed banks." International Journal of Law and Management 58, no. 2 (March 14, 2016): 162–78. http://dx.doi.org/10.1108/ijlma-04-2014-0033.

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Purpose – The study aims to assess credit risk management practices within financial institutions in Ghana. Specifically, the study compares credit risk management practices of listed banks in Ghana with Basel II (1999). Design/methodology/approach – The analysis is based on data gathered from varied sources, namely, use of questionnaires, analysis of internal credit policies and procedure manuals and semi-structured interviews and discussions with credit risk managers of the selected banks in May 2007 and October 2014. Findings – Overall, the credit risk management practices within listed banks in Ghana are in line with sound practices. The only dissimilarity, however, is the role of the board of directors in defining acceptable types of loans and maximum maturities for the various types of loans. The listed banks in Ghana are also exposed to credit risks associated with granting both corporate and small business commercial loans and the use of collaterals to mitigate their credit risk exposures. Practical implications – Banks in Ghana should consider developing the skills of all their personnel and appropriately motivating those involved in the credit risk management processes to ensure that they carry out this process efficiently. Originality/value – Research into credit risk management in the banking industry from the Ghanaian perspective remains scant. This study is, therefore, timely, and its findings are invaluable for the efficient management of credit risk in the banking industry. This study provides policy recommendations which will enhance shareholder value and, in this way, contribute to greater stability in the banking sector in developing countries, in particular.
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20

Tchernykh, S. "Risk Management in Banks." Voprosy Ekonomiki, no. 8 (August 20, 2004): 120–27. http://dx.doi.org/10.32609/0042-8736-2004-8-120-127.

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Problems of managing risks of partnership in banks taking into account the new Central Bank of Russia document "On Organization of Internal Control in Credit Organizations and Bank Groups" are considered in the article. It is pointed out that effective bank risk management including risks of partnership сan be realized only under condition of bona fide competition. Functioning of banks in competitive environment is impossible without risks, their monitoring allows to become competitive on the banking services market if various "black lists" and other unsound negative information leading to lowering the level of liquidity of a credit organization are absent. Methods of managing risks of partnership that become all the more complex under the influence of technological innovations (in particular, the development of operations with credit derivatives) are also analyzed.
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21

Toufaili, Bilal. "THE IMPACT OF RISK MANAGEMENT ON FINANCIAL PERFORMANCE." EUrASEANs: journal on global socio-economic dynamics, no. 3(28) (May 31, 2021): 7–23. http://dx.doi.org/10.35678/2539-5645.3(28).2021.7-23.

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Commercial banks that control a large proportion of overall assets of the financial sector primarily rely on extending credits, and banks may raise their earnings through this function which constitutes one of the major functions of commercial banks. Consequently, and due to the wide multiple risk exposures of commercial banks, the issue of capital structure has become a vital element in determining the viability of banks and their ability to withstand various risks involved. Hence, risk management as such has become an essential part of evaluating various risks, including credit risks, liquidity risks, solvency risks and so forth. It is necessary to remember that banks differ from one to another in many respects, namely, their goals, services and strategies. Thus, banks are facing various risks in their day-to-day operations. The research here has implemented a quantitative methodology throughout distributing a survey over a defined number of respondents, and the results were viewed through the prism of regression analysis and Pearson correlations. The obtained results prove there is a direct relationship between market risk, liquidity risk, credit risk, and solvency risk. The results also prove that the higher the risk management ratios are managed, the higher the net income will be.
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22

Wang, Huibo. "Credit Risk Management of Consumer Finance Based on Big Data." Mobile Information Systems 2021 (July 22, 2021): 1–10. http://dx.doi.org/10.1155/2021/8189255.

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In recent years, China’s consumer finance has developed rapidly, but the foundation is unstable, and the industry has serious problems of violent competition, excessive credit, and fraud. Therefore, we should attach great importance to the healthy development of consumer finance, especially the management of its credit risk. The application of big data credit investigation can provide early warning of potential risks and prevent the risk of excessive credit investigation. This paper starts with the definition of basic core concepts, such as traditional credit investigation, big data credit investigation, and consumer finance, analyzes the performance and causes of consumer finance credit risk, and combs in detail the relevant theories of the application of big data credit investigation in consumer finance credit risk management. The application of big data credit investigation has optimized the risk management process of consumer financial institutions, deepened the concept of Internet consumer finance, improved the risk management system, created a diversified credit information system, and strengthened the innovation of Internet consumer finance products and services. For example, credit scores provide the most intuitive quantification of consumer credit risk. For consumers with different levels of credit scores, different credit approval processes can be matched. For customers with high scores, the work process can be simplified without affecting the work results. It can reduce the workload of employees by 20% and increase the accuracy of customer credit risk prediction by 16%.
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23

Chen, Jiongyong, and Li Ma. "Bank Credit Risk Avoidance and Countermeasures Based on Wireless Communication." Scientific Programming 2022 (March 17, 2022): 1–7. http://dx.doi.org/10.1155/2022/7793088.

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Credit risk management refers to the main operating risks faced by banks, and its effective management is directly related to the bank’s operating performance. The main link of the credit risk management system is the measurement of bank credit risk, and this connection will run through the entire process of the bank’s credit risk management system. The measurement results directly affect the actual operation of the bank and therefore also affect risk management and business management. This article aims to study bank credit risk management in the context of wireless communication and big data. Based on the analysis of the characteristics of credit risk, the theory of credit risk and information asymmetry, and the credit risk measurement model, Bank S is taken as an example to construct Bank S’s credit risk influencing factor model. Finally, the bank is compared with three banks.
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24

Al-Shawabkeh, Abdallah, and Rama Kanungo. "Credit risk estimate using internal explicit knowledge." Investment Management and Financial Innovations 14, no. 1 (March 31, 2017): 55–66. http://dx.doi.org/10.21511/imfi.14(1).2017.06.

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Jordanian banks traditionally use a set of indicators, based on their internal explicit knowledge to examine the credit risk caused by default loans of individual borrowers. The banks are reliant on the personal and financial information of the borrowers, obtained by knowing them, often referred as internal explicit knowledge. Internal explicit knowledge characterizes both financial and non-financial indicators of individual borrowers, such as; loan amount, educational level, occupation, income, marital status, age, and gender. The authors studied 2755 default or non-performing personal loan profiles obtained from Jordanian Banks over a period of 1999 to 2014. The results show that low earning unemployed borrowers are very likely to default and contribute to non-performing loans by increasing the chances of credit risk. In addition, it is found that the unmarried, younger borrowers and moderate loan amount increase the probability of non-performing loans. On the contrary, borrowers employed in private sector and at least educated to a degree level are most likely to mitigate the credit risk. The study suggests improving the decision making process of Jordanian banks by making it more quantitative and dependable, instead of using only subjective or judgemental based understanding of borrowers.
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25

Erben, Roland Franz. "Buchbesprechung: Standortbestimmung im Credit Management - Der Credit Manager als der Erfolgsfaktor zur Steigerung des Unternehmenswertes vom Verein für Credit Management e. V.; Jan Schneider-Maessen; Matthias Schumann und Bernd Weiß (Hrsg.)." RISKNEWS 2, no. 2 (March 24, 2005): 79. http://dx.doi.org/10.1002/risk.200590044.

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26

Elgharbawy, Adel. "Risk and risk management practices." Journal of Islamic Accounting and Business Research 11, no. 8 (January 13, 2020): 1555–81. http://dx.doi.org/10.1108/jiabr-06-2018-0080.

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Purpose This study aims to compare types and levels of risk and risk management practices (RMPs) including the recognition, identification, assessment, analysis, monitoring and control of risk in both Islamic and conventional banks. Design/methodology/approach A questionnaire survey was conducted among the Islamic and conventional banks in Qatar, together with an analysis of archival data extracted from the Thomson Reuters Eikon database for the period 2009-2018. Data were analysed using descriptive statistics, ANOVA and regression analysis. Findings Islamic banks encounter unique types and levels of risk that are not encountered by conventional banks. In Islamic banks, risks such as those of operation and Sharia non-compliance are perceived to be higher, while in conventional banks other risks such as those of credit and insolvency are higher; other risks, for example, liquidity risk, are faced by both. RMPs are determined by understanding risk and risk management, risk identification, risk monitoring and control and credit risk analysis, but not by risk assessment and analysis. However, the RMPs of the two types of bank are not significantly different, except in the analysis of credit risk. Research limitations/implications The study contributes to the debate in the literature by developing a better understanding of the dynamism of risk management in Qatari banks, which can be extended to similar contexts in the region. However, the relatively small sample size in only one country limits the possibility of generalizing the findings. The survey methodology is based on the perception of bankers rather than their actual actions and does not provide in-depth analysis for each type of risk, especially credit risk. However, using archival data, in addition to those from the survey, minimises the bias that would result from depending on one source of data. Practical implications The study provides valuable insights into the different types and levels of risk, as well as the RMPs in Islamic and conventional banks, which can help in guiding the future development and regulation of risk management in the banking sector of Qatar and its region. Originality/value The study helps to explain the mixed results of previous studies that compare types and levels of risk and RMPs in Islamic and conventional banks. Using different types of data and analysis, it provides evidence from one of the fastest growing economies in the world. It also addresses the concerns over RMPs in banks since the global financial crisis.
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27

Панова and T. Panova. "Determination of Credit Border – Basis of Credit Risk Management of Consumer Credit." Economics of the Firm 4, no. 3 (September 17, 2015): 44–48. http://dx.doi.org/10.12737/17595.

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The article discusses the problem of determining the boundaries of credit and credit risk management. Defining the boundaries of reasonable use of credit and compliance is of great importance for the economy as a whole. Only with an optimal level of credit investments of credit impact on the economy can be positive.
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28

Agaba, Francis, Caleb Tamwesigire, and Marus Eton. "Credit Risk Management Practices and Loan Performance of Commercial Banks in Uganda." Business Perspective Review 4, no. 1 (March 31, 2022): 16–28. http://dx.doi.org/10.38157/bpr.v4i1.394.

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Purpose: The study examined the relationship between Credit Risk Management Practices and Loan Performance of Commercial Banks in Mbarara City. The study covered 19 commercial banks. Method: A correlational design was used to establish the relationship between different credit risk management practices and Loan Performance in selected commercial banks in the city. The study used a structured questionnaire to collect numerical data from the credit staff and management of 19 commercial banks. Correlation and regression tests to analyze the relationships and effects of Credit risk management and Loan Performance of commercial banks in Mbarara city Findings: The study found a significant relationship between credit risk identification and loan performance; credit risk assessment and loan performance; credit risk monitoring and loan performance; and credit risk control and loan performance. The study also found that some commercial banks did not have experts to accurately predict credit risks nor evaluate the consequences of the decisions taken by loan officers. Implication: Banks should source experts who can analyze and predict risks and evaluate their consequences on the bank. The bank should adopt the tool of 5cs of credit management, with this it will develop a good loan book that shall lead to good loan performance. Limitations: We still don't know clients' perceptions of the different credit risk management practices. Therefore, a qualitative study to assess clients' perception of the credit management practices in commercial banks should be conducted.
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Konovalova, Natalia, Ineta Kristovska, and Marina Kudinska. "CREDIT RISK MANAGEMENT IN COMMERCIAL BANKS." Polish Journal of Management Studies 13, no. 2 (June 2016): 90–100. http://dx.doi.org/10.17512/pjms.2016.13.2.09.

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30

Beatty, Nigel. "Credit risk management with EMV cards." Card Technology Today 18, no. 5 (May 2006): 9. http://dx.doi.org/10.1016/s0965-2590(06)70486-8.

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31

MACLACHLAN, IAIN. "RECENT ADVANCES IN CREDIT RISK MANAGEMENT." Economic Papers: A journal of applied economics and policy 18, no. 4 (December 1999): 92–106. http://dx.doi.org/10.1111/j.1759-3441.1999.tb01165.x.

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32

Srikanth, Maram, and Braj Kishore. "Credit Risk Management in Indian Banks." Indian Economic Journal 62, no. 1 (April 2014): 751–67. http://dx.doi.org/10.1177/0019466220140104.

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33

Acharya, Viral. "Credit Risk: Pricing, Measurement, and Management." Economica 72, no. 285 (February 2005): 181–82. http://dx.doi.org/10.1111/j.0013-0427.2005.408_3.x.

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34

Ofoeda, Isaac. "Credit risk management and NBFI profitability." International Journal of Financial Services Management 8, no. 3 (2016): 195. http://dx.doi.org/10.1504/ijfsm.2016.080100.

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Ofoeda, Isaac. "Credit risk management and NBFI profitability." International Journal of Financial Services Management 8, no. 3 (2016): 195. http://dx.doi.org/10.1504/ijfsm.2016.10000996.

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36

Lekpek, Ahmedin. "Credit risk management in Islamic banking." Bankarstvo 47, no. 1 (2018): 32–51. http://dx.doi.org/10.5937/bankarstvo1801032l.

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37

Byström, Hans. "Credit risk management in Greater China." Journal of Futures Markets 28, no. 6 (2008): 582–97. http://dx.doi.org/10.1002/fut.20320.

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38

Sahani, Kalpana, Soni Sahani, Sundip Bansal, Deepak Shakya, and Binay Shrestha. "Credit Risk Management of Kumari Bank Ltd. Nepal." International Journal of Emerging Research in Management and Technology 7, no. 4 (April 20, 2018): 14. http://dx.doi.org/10.23956/ijermt.v7i4.2.

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Banks are always faced with different types of risks that may have a potentially negative effect on their business. Risk-taking is an inherent element of banking and, indeed, profits are in part the reward for successful risk taking in business. On the other hand, excessive and poorly managed risk can lead to losses and thus endanger the safety of a bank's depositors. Risks are considered warranted when they are understandable, measurable, controllable and within a bank’s capacity to readily withstand adverse results. Sound risk management systems enable managers of banks to take risks knowingly, reduce risks where appropriate and strive to prepare for a future, which by its nature cannot be predicted.Financial institutions are subject to a number of risks such as Credit risk, Market risk management, Foreign exchange risk, Operational risk, and Liquidity risk. Although credit risk has always been of primary concern to these institutions, its importance became paramount during the recent financial crisis. The crisis exposed the shortcomings of existing risk management systems, and several firms saw significant losses resulting from failure of their counterparties to deliver on contracts. Firms may also be worried about a second recession, which makes credit risk a top priority.
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39

Bouslama, Ghassen, and Christophe Bouteiller. "Human capital and credit risk management: training is more valuable than experience." Problems and Perspectives in Management 17, no. 1 (February 13, 2019): 67–77. http://dx.doi.org/10.21511/ppm.17(1).2019.07.

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The aim of this article is to assess how human capital, and more specifically training and experience, helps in forecasting and monitoring credit risk. It uses a survey of a sample of loan officers in a major French mutualist bank and applies analysis of variance and correlation to determine the relationships among variables. The study of these two components of human capital in SME loan officers shows that their ability to anticipate risk depends above all on their training rather than on their experience. Some methods of anticipating risk are more important than others. Loan officers monitor their clients in similar ways, whatever the degree and nature of their experience. The findings have two important implications for credit risk management and human capital: first, both technical and regulatory training is crucial to enable loan officers to anticipate bank credit risk, second, experience, whether in banking or as a loan officer, only makes a difference in monitoring risk. These results will be useful when banks are planning recruitment, career management and resource and skills allocation. They also suggest that staff knowledge management will enable banks to use their human capital effectively to reach their own objectives with regard to risk control, and those fixed by the regulators. This work is, as far as it is known, the first to study the role of human capital in managing credit risk. The authors show that training is more important than experience in default risk anticipation, but that experience is useful in risk monitoring.
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Bilal, Ahmad Raza, and Mirza Muhammad Ali Baig. "Transformation of agriculture risk management." Agricultural Finance Review 79, no. 1 (February 4, 2019): 136–55. http://dx.doi.org/10.1108/afr-05-2018-0038.

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Purpose The purpose of this paper is to investigate the balanced role of internal and external compliance in risk evaluation process of specialized agriculture financing. The authors examine the adaptive behavior of risk managers to determine the role of proposed transformation for risk monitoring (RM) and control process in risk mitigation and avoidance of agriculture credit failure. Design/methodology/approach A self-administered survey was conducted to collect data from 353 risk-related officers and managers in Zarai Taraqiati Bank Limited (ZTBL) Pakistan. The authors used a previously tested scale for the main constructs. The descriptive analyses were used to gauge the model capacity for determining the strength of proposed risk patterns in agriculture risk management. Findings The results reveal that risk evaluation process in ZTBL is reasonably efficient in mitigating risks. Given the sensitive nature of farm credit, there is a need of fundamental reforms in risk policy manuals in line with central bank’s agriculture prudential regulations and Basel-III standards. The results fully support H1 and H2, while H3 is partially validated. The result patterns indicate serious issues in risk evaluation process in agriculture finance that is causing higher delinquency in farm credit. Research limitations/implications Based on highlighted issues, the authors recommend valuable guidelines in the RM review system for agriculture financing products at ZTBL. Practical implications The authors propose remodeling of agriculture risk management and offer valuable insights to the agriculture financial regulators and government in taking policy initiatives in the pre-and-post agriculture risk evaluation process. The proposed model enables RM process to improve farm credit delinquency, particularly in ZTBL and other agriculture banking networks in commercial banks. Originality/value This is the first study to empirically investigate RM evaluation process in agriculture risk management of ZTBL in Pakistan, thus, offers new horizon of farm credit regulatory compliance in agricultural sector of Pakistan.
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41

Liu, Wenjuan. "Enterprise Credit Risk Management Using Multicriteria Decision-Making." Mathematical Problems in Engineering 2021 (November 24, 2021): 1–10. http://dx.doi.org/10.1155/2021/6191167.

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The purpose of this study is to reduce the rate of multicriteria decision-making (MCDA) errors in credit risk management and to weaken the influence of different attitudes of enterprise managers on the final decision when facing credit risk. First, several solutions that are suitable for present enterprise credit risk management are proposed according to the research of enterprise risk management in the world. Moreover, the criteria and matrix are established according to the general practice of the expert method. A decision-making method of enterprise credit risk management with trapezoidal fuzzy number as the criteria of credit risk management is proposed based on the prospect theory; then, the weight is calculated based on G1 weight calculation, G2 weight calculation method, and the method of maximizing deviation; finally, the prospect values of the alternatives calculated by each method are adopted to sort and compare the proposed solutions. Considering the difference of risk degree of managers in the face of credit risk management, the ranking results of enterprise credit risk management solutions based on three weight calculation methods are compared. The results show that as long as the quantitative value of the risk attitude of the enterprise credit risk manager meets a certain range, the final choice of credit risk management scheme ranking is consistent. This exploration provides a new research direction for enterprise credit risk management, which has reference significance.
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Liu, Ming, Jie Zhu, Yuanchao Bian, and Liping Chen. "Comprehensive Credit Risk Management of Policy Export Credit Insurance Institutions." Journal of Accounting, Business and Finance Research 4, no. 2 (2018): 66–73. http://dx.doi.org/10.20448/2002.42.66.73.

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43

Yanenkova, Iryna, Yuliia Nehoda, Svetlana Drobyazko, Andrii Zavhorodnii, and Lyudmyla Berezovska. "Modeling of Bank Credit Risk Management Using the Cost Risk Model." Journal of Risk and Financial Management 14, no. 5 (May 7, 2021): 211. http://dx.doi.org/10.3390/jrfm14050211.

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This article deals with the issue of managing bank credit risk using a cost risk model. Modeling of bank credit risk management was proposed based on neural-cell technologies, which expand the possibilities of modeling complex objects and processes and provide high reliability of credit risk determination. The purpose of the article is to improve and develop methodical support and practical recommendations for reducing the level of risk based on the value-at-risk (VaR) methodology and its subsequent combination with methods of fuzzy programming and symbiotic methodical support. The model makes it possible to create decision support subsystems for nonperforming loan management based on the neuro-fuzzy approach. For this paper, economic and mathematical tools (based on the VaR methodology) were used, which made it possible to analyze and forecast the dynamics of overdue payment; assess the quality of the credit portfolio of the bank; determine possible trends in bank development. A scientific and practical approach is taken to assess and forecast the degree of credit problematicity by qualitative criteria using a mathematical model based on a fuzzy technology, which can forecast the increased risk of loan default at an early stage in the process of monitoring the loan portfolio and model forecasting changes in the degree of credit problematicity on change of indicators. A methodology is proposed for the analysis and forecasting of indicators of troubled loan debt, which should be implemented as software and included in the decision support system during the process of monitoring the risk of the bank’s credit portfolio.
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44

Kogeda, Okuthe Paul, and Nicknolt N. Vumane. "A Model Augmenting Credit Risk Management in the Banking Industry." International Journal of Technology Diffusion 8, no. 4 (October 2017): 47–65. http://dx.doi.org/10.4018/ijtd.2017100104.

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A lack of reliable credit risk measurements and poor control of credit risks has caused massive financial losses across a wide spectrum of business. Financial institutions like banks have not been able to control and contain the rapid increases of the credit defaulting. In this paper, we address the credit lending challenges by eliminating credit defaulting faced by the banking industry. Data from bank of previously accepted and rejected loan applicants was used to construct a credit risk evaluation network. The artificial neural network technique with back-propagation algorithm was applied to develop a model that supports the banks in the credit granting decision-making. The model was trained to categorize applicants as either good (credit granted) or bad (credit denied) based on the credit record. The model was able to predict whether a particular applicant is likely or unlikely to repay the credit. The training of neural network model and validation testing was done using data obtained from the bank. The results show a greater performance, classification and prediction accuracy.
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45

Permatasari, Ika. "Does corporate governance affect bank risk management? Case study of Indonesian banks." International Trade, Politics and Development 4, no. 2 (October 23, 2020): 127–39. http://dx.doi.org/10.1108/itpd-05-2020-0063.

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PurposeThe purpose of this study is to examine the relationship between corporate governance and risk management of Indonesian banks.Design/methodology/approachImplementation of good corporate governance is measured by good corporate governance composite rating, which is the result of bank's self-assessment. Bank risk managements are measured by market risk, credit risk, liquidity risk and operational risk.FindingsThe study results showed that good corporate governance implementation in Indonesia was able to influence bank risk. There were differences in credit risk, liquidity risk and operational risk in banks with different governance ratings, but not at market risk.Originality/valueThe effectiveness of risk management and good corporate governance implementation is needed to enable banks to identify problems early, to follow up on rapid improvements and to be more resilient to crises. This study is an analysis of the relationship between corporate governance and banks' risk management in Indonesia. In particular, risk management is measured by four risks: market risk, credit risk, liquidity risk and operation risk.
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46

Ndegwa, Michael K., Apurba Shee, Calum G. Turvey, and Liangzhi You. "Uptake of insurance-embedded credit in presence of credit rationing: evidence from a randomized controlled trial in Kenya." Agricultural Finance Review 80, no. 5 (June 22, 2020): 745–66. http://dx.doi.org/10.1108/afr-10-2019-0116.

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PurposeDrought-related climate risk and access to credit are among the major risks to agricultural productivity for smallholder farmers in Kenya. Farmers are usually credit-constrained due to either involuntary quantity rationing or voluntary risk rationing. By exploiting randomized distribution of weather risk-contingent credit (RCC) and traditional credit, the authors estimate the causal effect of bundling weather index insurance to credit on uptake of agricultural credits among rural smallholders in Eastern Kenya. Further, the authors assess farmers' credit rationing, its determinants and effects on credit uptake.Design/methodology/approachThe study design was a randomized controlled trial (RCT) conducted in Machakos County, Kenya. 1,170 sample households were randomly assigned to one of three research groups, namely control, RCC and traditional credit. This paper is based on baseline household survey data and the first phase of loan implementation data.FindingsThe authors find that 48% of the households were price-rationed, 41% were risk-rationed and 11% were quantity-rationed. The average credit uptake rate was 33% with the uptake of bundled credit being significantly higher than that of traditional credit. Risk rationing seems to influence the credit uptake negatively, whereas premium subsidies do not have any significant association with credit uptake. Among the socio-economic variables, training attendance, crop production being the main household head occupation, expenditure on food, maize labour requirement, hired labour, livestock revenue and access to credit are found to influence the credit uptake positively, whereas the expenditure on non-food items is negatively related with credit uptake.Research limitations/implicationsThe study findings provide important insights on the factors of credit demand. Empirical results suggest that risk rationing is pervasive and discourages farmers to take up credit. The study results also imply that credit demand is inelastic although relatively small sample size for RCC premium subsidy groups may be a limiting factor to the authors’ estimation.Originality/valueBy implementing a multi-arm RCT, the authors estimate the factors affecting the uptake of insurance bundled agricultural credits along with eliciting credit rationing among rural smallholders in Eastern Kenya. This paper provides key empirical findings on the uptake of RCC and the effect of credit rationing on uptake of agricultural credits, a field which has been majorly theoretical.
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HORODETSKA, Tetiana, Kateryna ZAICHENKO, and Alla IVASHCHENKO. "Methodical approaches for reducing the credit risk." Economics. Finances. Law 11/1, no. - (November 26, 2021): 16–20. http://dx.doi.org/10.37634/efp.2021.11(1).3.

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Banking is inevitably associated with risks. No matter what efforts the bank makes to minimize risks, they will always exist – the only question is to what extent. Lending operations are among the most profitable types of banking, but they are associated with a high level of risk. The instability of the economic situation in the country, the imperfection of the legal framework in this area necessitate a detailed study of the problems of minimizing credit risks. It should be noted that the choice of methods of credit risk management in the bank is quite relevant today. Credit risk management is the most important task of any bank, and choosing the right method of credit risk management will increase the stability, reliability and competitiveness of the banking system, which will positively affect the overall economic condition of the country. Credit risk is the oldest in the system of banking risks and occupies a prominent place. It is necessary to work out an effective system of using the tools recognized by the world banking community to minimize risks, given the possibility of their transfer from the bank to investors. The starting point in the development of the latest risk management tools of the bank should be the creation of a regulatory framework that will regulate this process. It is necessary to improve the existing methodological framework and develop a new methodological framework for credit risk management of the bank, concentrating the advantages of existing assessment methods, create a single method of assessing the borrower's creditworthiness, not to mention a certain algorithm for banks to form credit procedures. It is necessary to adopt the experience of foreign banks in credit risk management. The experience of foreign banks in developed countries, based on a detailed study of all credit procedures, multifactor analysis of the creditworthiness of potential borrowers.
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Nayak, Bhabani Shankar, and Jia Xu. "Historical Trends and Transitions in Credit Risk Management of Chinese Commercial Banks." International Journal of Business Administration 9, no. 5 (August 3, 2018): 96. http://dx.doi.org/10.5430/ijba.v9n5p96.

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The paper outlines different trends and transitions in the history of credit risk management of Chinese commercial banks. By critically reviewing different stages of credit management and its historical evolution, it helps in understanding the nature of subjective challenges faced by Chinese commercial banks to manage credit risks. It reviews post reform policies in particularly after 1978 to locate the policy transitions and trajectories of credit risk management of commercial banks in China. It helps to understand the problems and prospects of effective credit management of risks by Chinese commercial banks. It argues that Chinese commercial banks are facing greater challenges in managing risk after the entry of foreign banks to China. Therefore, it is important for the commercial banks in China to develop its own credit management mechanisms within the context of Chinese banking environment.
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Jalilian, Negar, Seyed Mahmoud Zanjirchi, and Mark Goh. "Interactive scenario analysis of banking credit risks in intuitive fuzzy space." Journal of Modelling in Management 15, no. 1 (November 18, 2019): 257–75. http://dx.doi.org/10.1108/jm2-01-2019-0011.

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Purpose The purpose of the paper is to bring attention to documentary credits and the efforts to reduce debt obligations in credit history is recognized as an important source of uncommitted bank earnings. Credit risk has a significant impact on the stability of the banking system. This paper identifies the types of credit risk in the banking supply chain. Design/methodology/approach The authors model the types of credit risk using the intuitive fuzzy failure modes and effects analysis (IFMEA) and intuitive fuzzy cognitive mapping. The population of the study that is needed for the interviews and expert panels comprises senior managers and experts of a leading bank in Iran. The respondents are experienced in credit and banking risk and were selected through judgment sampling and snowballing. Findings The findings suggest that reducing the risks of the foreign letters of credit contracts can mitigate the risk in the agricultural sector, the specific risks of rent-to-own contracts, the risk of the long-term facilities and the specific risk of the domestic letter of credit contracts. Originality/value This research investigates Iran Tejart Bank’s credit risk, formulates a model of the types of credit risk present and analyzes them using the intuitive fuzzy failure modes and effects analysis and intuitive fuzzy cognitive map. Through this credit risk model, one can then facilitate risk management for better financial stability. Also, the model can be used to evaluate the risk indicators.
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Bilginci, Mehmet Resul, Gamze Ogcu Kaya, and Ali Turkyilmaz. "Decision Support System for Credit Risk Management." International Journal of Information Systems in the Service Sector 11, no. 2 (April 2019): 18–31. http://dx.doi.org/10.4018/ijisss.2019040102.

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Risk is an integrated part of the banking functions, which cannot be eliminated completely but it can be reduced by employing appropriate techniques. Credit processing is one of the core functions in the banking system, and its performance is closely related to management of the risks. The aim of this article is to develop a credit scorecard model which can be used as decision support system. A logistic regression with stepwise selection method is used to estimate the model parameters. The data that is used to construct the credit scorecard model is obtained from one of the pioneering banks in Turkish Banking Sector. The performance of the developed model is tested using statistical metrics including Receiver Operator Characteristic (ROC) curve and Gini statistics. The result reveals that the model performs well and it can be used as a decision support system for managing the credit risk by managers of the banks.
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