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Journal articles on the topic 'Financial and credit risk'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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1

Redondo, Helena, and Elisa Aracil. "Climate‐related credit risk: Rethinking the credit risk framework." Global Policy 15, S1 (2024): 21–33. http://dx.doi.org/10.1111/1758-5899.13315.

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AbstractClimate change and the challenges associated with the transition to a zero‐carbon economy pose significant financial risks. Climate‐related risks (CRR) indirectly impact banks through their loan portfolios. To examine the integration of CRR into banks' credit risk assessment and monitoring, this article reviews academic and institutional literature using quantitative bibliometric techniques and content analysis of 145 academic documents from policymakers and financial supervisors. A framework emerges that incorporates CRR into credit risk management. We find four thematic areas in the

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BAVEENKUMAR, S. "Credit Risk Management." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 04 (2025): 1–9. https://doi.org/10.55041/ijsrem46201.

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ABSTRACT This study assesses the financial performance and credit risk management practices of select private sector banks in India between 2020 and 2024. In light of increasing competition and dynamic regulatory frameworks, it explores the importance of profitability and risk control as fundamental measures of a bank’s success.The research focuses on five key banks: HDFC Bank, ICICI Bank, Karur Vysya Bank, Federal Bank, and Tamilnad Mercantile Bank. The study is entirely based on secondary data collected from annual reports, financial portals, and scholarly sources.To evaluate financial stren

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Yadav, Sandeep. "Balancing Profitability and Risk: The Role of Risk Appetite in Mitigating Credit Risk Impact." International Scientific Journal of Engineering and Management 03, no. 12 (2024): 1–7. https://doi.org/10.55041/isjem01087.

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Balancing profitability and risk is a central challenge for financial institutions, especially in the context of managing credit risk. This paper explores the concept of risk appetite as a strategic framework for aligning an institution’s risk-taking activities with its financial objectives. By defining risk appetite in measurable terms, institutions can calibrate their credit risk strategies to ensure optimal decision-making that mitigates potential losses while maintaining profitability. The study examines how risk appetite influences credit decision-making processes, including credit underw

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Goodhart, C. A. E. "Financial Regulation, Credit Risk and Financial Stability." National Institute Economic Review 192 (April 2005): 118–27. http://dx.doi.org/10.1177/002795010519200111.

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In contrast to recent successful developments in macro monetary policies, the modelling, measurement and management of systemic financial stability has remained problematical. Indeed, the focus of most effort has been on improving individual, rather than systemic, bank risk management; the Basel II objective has been to bring regulatory bank capital into line with the (sophisticated) banks‘ assessment of their own economic capital. Even at the individual bank level there are concerns over (i) appropriate diversification allowances, (ii) differing objectives of banks and regulators, (iii) the n

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Herring, R. "Credit risk and financial instability." Oxford Review of Economic Policy 15, no. 3 (1999): 63–79. http://dx.doi.org/10.1093/oxrep/15.3.63.

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Niklis, Dimitrios, Michalis Doumpos, and Constantin Zopounidis. "Credit Risk Modelling." International Journal of Sustainable Economies Management 7, no. 3 (2018): 50–64. http://dx.doi.org/10.4018/ijsem.2018070105.

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The assessment of businesses' credit risk is a difficult and important process in the area of financial risk management. In a classical multivariate model, financial ratios are combined in order to achieve a credit risk score, which signals if a loan application is approved or discarded. Despite their good performance, the developed multivariate models using statistical methods have been widely criticized. They are based on models that use accounting data, which have the disadvantage of being static and so often fail to follow the changes in the economic and business environment. In recent yea

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Anwulika Ogechukwu Scott, Prisca Amajuoyi, and Kudirat Bukola Adeusi. "Advanced risk management solutions for mitigating credit risk in financial operations." Magna Scientia Advanced Research and Reviews 12, no. 1 (2024): 212–23. http://dx.doi.org/10.30574/msarr.2024.11.1.0085.

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Advanced risk management solutions are essential for mitigating credit risk in financial operations, particularly in today's volatile economic environment. This Review explores the innovative approaches and technologies being utilized to enhance credit risk management and safeguard financial institutions against potential losses. Credit risk, the possibility that a borrower will default on their obligations, poses a significant threat to financial stability. Traditional methods of assessing and managing credit risk, such as credit scoring and historical data analysis, are no longer sufficient

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Qasem, Mais Haj, and Loai Nemer. "Extreme Learning Machine for Credit Risk Analysis." Journal of Intelligent Systems 29, no. 1 (2018): 640–52. http://dx.doi.org/10.1515/jisys-2018-0058.

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Abstract Credit risk analysis is important for financial institutions that provide loans to businesses and individuals. Banks and other financial institutions generally face risks that are mostly of financial nature; hence, such institutions must balance risks and returns. Analyzing or determining risk levels involved in credits, finances, and loans can be performed through predictive analytic techniques, such as an extreme learning machine (ELM). In this work, we empirically evaluated the performance of an ELM for credit risk problems and compared it to naive Bayes, decision tree, and multi-l

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Stępińska, Joanna. "Credit Borrower Sector of Economy and Credit Risk For Banks." Journal of Finance and Financial Law 4, no. 44 (2024): 95–128. https://doi.org/10.18778/2391-6478.4.44.06.

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The purpose of the article. Business entities in different industries operate differently. Therefore, different sectors are characterized, among other things, by different profitability, the need for external financing, and, consequently, a different level of risk of default on credit commitments to banks. Borrowers from specific industries may be, from the perspective of banks' interests, better or worse customers and contribute to strengthening or weakening the quality of their credit portfolios. The purpose of the article is to compare sections of the economy in terms of the credit risk acc

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Alam, MD Waquar. "INVESTIGATING THE IMPACT OF CREDIT RISK ON FINANCIAL PERFORMANCE OF COMMERCIAL BANK IN INDIA." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 08, no. 05 (2024): 1–5. http://dx.doi.org/10.55041/ijsrem33025.

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In this liberalization period, credit Risk Management has got much importance in the Indian Economy. The main challenges faced by the banking sector today are the challenge of identifying the risk and managing it. The risk is imbibed nature of the banking business. The main role of a bank is of intermediate for those having resources and requiring resources. For risk management various risks like credit risk, market risk or operational risk have to be converted into one composite measure. The importance of credit risk management and its impact on profitability has motivated us to pursue this s

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Moudud-Ul-Huq, Syed, Rabaka Akter, and Tanmay Biswas. "Impact of Financial Crisis on Credit Risk: Pre- and Post-financial Crises in an Emerging Economy." FIIB Business Review 9, no. 2 (2020): 118–32. http://dx.doi.org/10.1177/2319714520923952.

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This aim of the article is to establish a model to discuss the reasons for changing the level of credit risk among the commercial banks of Bangladesh during the global financial crisis (GFC). Credit risk has been remaining as the essential and core risk in commercial banking activities. Multiple regression analysis is used to test the relationship among the level of credit risk as a dependent variable and financial crisis, other bank-level variables and macroeconomic variables. The causes of the GFC revealed not only systematic or structural imbalances but also the necessity to keep and streng

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Anwulika Ogechukwu Scott, Prisca Amajuoyi, and Kudirat Bukola Adeusi. "Effective credit risk mitigation strategies: Solutions for reducing exposure in financial institutions." Magna Scientia Advanced Research and Reviews 12, no. 1 (2024): 198–211. http://dx.doi.org/10.30574/msarr.2024.11.1.0084.

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Credit risk remains a critical concern for financial institutions, especially in the context of economic uncertainties and volatile market conditions. This paper examines the importance of credit risk mitigation strategies and presents solutions for reducing exposure in financial institutions. The research focuses on various strategies employed by banks and other financial institutions to manage credit risk effectively. The paper begins with an overview of credit risk and its significance in the banking industry. It discusses the various types of credit risk faced by financial institutions, in

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Al-Shawabkeh, Abdallah, and Rama Kanungo. "Credit risk estimate using internal explicit knowledge." Investment Management and Financial Innovations 14, no. 1 (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 p

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., Gustriani, Imam Asngari, Suhel ., and Ana Yulianita. "Determinants of Financial Inclusion for MSMEs: Evidence from Indonesia." Journal of Economics, Business, & Accountancy Ventura 26, no. 2 (2023): 122. http://dx.doi.org/10.14414/jebav.v26i2.3381.

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Enhancing the financial sector is paramount, as it can bolster public trust in financial institutions and consequently expand financial inclusion, particularly within the MSMEs sectors. This study employs the ARCH Maximum Likelihood Model to examine the impact of the banking industry’s financial soundness and macroeconomic conditions on the financial inclusion of MSMEs. The financial soundness of banks is gauged through pertinent financial metrics, including capital adequacy, profitability, credit risk, and liquidity. Moreover, the financial inclusion metric employs the count of account credit

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

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Credit derivatives are an up to date innovation in financial markets. These financial instrument have a potential to allow enterprises to trade and manage the credit risks and market risks. The striking growth of credit derivatives suggest that participant of financial markets find them to be useful instrument for risk management. The most popular and fundamental credit derivatives is a credit default swaps (CDS). In the paper we detailed the risk management of the credit default swaps and quantified the credit risk of investors in two way: (i) calculate the term structure of default probabili

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Singh, Puneet, Shubha Mishra, Gargi Porwal, Prakhar Saxena, and Rishabh Tripathi. "Credit Risk Model: Research on Credit Risk Categorization model using XGBoost." INTERANTIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 03 (2025): 1–9. https://doi.org/10.55041/ijsrem43005.

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Machine Learning is a subset of Artificial Intelligence technology that enables systems to learn and make decisions on their own. These systems can make accurate decisions by analyzing datasets and information without the need for explicit programming. This paper mainly introduces the application of machine learning algorithm (XGBoost) in credit risk assessment in the financial industry. Credit risk assessment is a significant challenge for banks to assess credit worthiness among many applicants and plays a very crucial role in the profitability of banks. Our research paper addresses the limit

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Kim, Seil, Pepa Kraft, and Stephen G. Ryan. "Financial statement comparability and credit risk." Review of Accounting Studies 18, no. 3 (2013): 783–823. http://dx.doi.org/10.1007/s11142-013-9233-z.

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Akram, Hassan, and Khalil ur Rahman. "Credit risk management." ISRA International Journal of Islamic Finance 10, no. 2 (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

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Gusti Ngurah Agung Suaryana, I., Naniek Noviari, and I. Gusti Ayu Eka Damayanthi. "The impact of Indonesian financial accounting standard implementation, credit risk, and credit restructuring on allowance for credit losses in Indonesia." Banks and Bank Systems 17, no. 3 (2022): 177–87. http://dx.doi.org/10.21511/bbs.17(3).2022.15.

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This study examines the impact of the implementation of the Indonesian Financial Accounting Standard, credit risk, and credit restructuring on the formation of Allowance for Credit Losses (ACL) of commercial banks listed on the Indonesia Stock Exchange. The formation of ACL is regulated in PSAK 71 which is part of the Indonesian Financial Accounting Standard. The implementation of PSAK 71, and credit risk are expected to increase the ACL of commercial banks, however, credit restructuring programs will reduce the ACL. The research population is commercial banks listed on the Indonesia Stock Exc

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Hjouji, Zaynab, Imane Hasinat, and Amal Hjouji. "A New Method in Machine Learning Adapted for Credit Risk Prediction of Bank Loans." Statistics, Optimization & Information Computing 13, no. 3 (2024): 1209–32. https://doi.org/10.19139/soic-2310-5070-1476.

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The recent global financial crisis has significantly impacted the financial system, leading to major bank failures and prompting a reevaluation of credit risk management models. Given its critical role in maintaining banking stability, effective credit risk forecasting methods are essential. In light of this, various studies have introduced techniques to analyze, detect, and prevent bank credit defaults. In this paper, we present a new approach for predicting credit risk, known as the “Method of Separating the Learning Set into Two Balls.” This method involves partitioning a learning set into

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Li, Meiling. "Practice and Research on Enterprise Financial Credit Risk." Frontiers in Business, Economics and Management 19, no. 1 (2025): 138–45. https://doi.org/10.54097/9ybneg68.

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This paper aims to explore the management and practice of enterprise's financial credit risk. Through systematic literature review, theoretical analysis and empirical research, a set of financial credit risk assessment and prevention and control system suitable for modern enterprises is constructed. Based on the definition, theoretical basis and classification of credit risk, combined with quantitative and qualitative research methods, this paper deeply analyzes the financial credit risk of enterprises. Through the analysis of actual cases, this paper reveals the causes, impacts and prevention

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Kalu, Emenike O., Bashabe Shieler, and Christian U. Amu. "Credit Risk Management and Financial Performance of Microfinance Institutions in Kampala, Uganda." Independent Journal of Management & Production 9, no. 1 (2018): 153. http://dx.doi.org/10.14807/ijmp.v9i1.658.

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The objective of this study was to evaluate whether relationship exist between credit risk management techniques and financial performance of microfinance institutions in Kampala, Uganda. Specifically, the study examined whether there is a relationship between credit risk identification, credit risk appraisal, credit risk monitoring, credit risk mitigation and financial performance of microfinance institutions in Kampala using sample of 60 members of staff in finance and credit departments of three licensed microfinance institutions in Kampala, Uganda namely Finca Uganda Ltd, Pride Microfinanc

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Chen, Fang, Xuanjuan Chen, Zhenzhen Sun, Tong Yu, and Ming Zhong. "Systemic Risk, Financial Crisis, and Credit Risk Insurance." Financial Review 48, no. 3 (2013): 417–42. http://dx.doi.org/10.1111/fire.12009.

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Tayachi, Tahar, and Ahmed BenSaïda. "Modeling SMEs Credit Default Risk: The Case of Saudi Arabia." Journal of Reviews on Global Economics 11 (November 21, 2022): 32–48. http://dx.doi.org/10.6000/1929-7092.2022.11.04.

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This study assesses the credit risk of small and medium-sized enterprises (SMEs) to minimize unexpected risk events. We construct a hybrid statistical model based on factor analysis and logistic regression to predict enterprise default on loans and determine the factors predicting SMEs default. We assess the credit risk of SMEs listed on the Saudi stock market. The results indicate that the SMEs acid-test ratios are the most influential factors in predicting SMEs credit risk. Therefore, the designed logistic model can be used by financial institutions during the decision-making process of gran

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Peng, Hua. "Research on Credit Risk Identification of Internet Financial Enterprises Based on Big Data." Mobile Information Systems 2021 (November 13, 2021): 1–8. http://dx.doi.org/10.1155/2021/1034803.

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The advent of the era of big data has provided a new way of development for Internet financial credit collection. The traditional methods of credit risk identification of Internet financial enterprises cannot get the characteristics of credit risk zoning, leading to large errors in the results of credit risk identification. Therefore, this paper proposes a new method of credit risk identification based on big data for Internet financial enterprises. According to the big data perspective, the credit risk assessment steps of Internet financial enterprises are analyzed and the weight of assessmen

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Chen, Yijun, Xiao Yan, and Qiuhong Jia. "Credit and Financial Risk Measurement of Financial Enterprises Based on PSM Model." Tobacco Regulatory Science 7, no. 5 (2021): 3710–23. http://dx.doi.org/10.18001/trs.7.5.1.147.

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With the rapid development of social economy and information technology, the credit risk and financial risk of my country’s financial enterprises are also facing severe challenges. In financial enterprises, credit is related to the survival of the enterprise. As the business volume and scale of financial enterprises continue to expand, financial risks are correspondingly increased. Therefore, the research on financial enterprise credit and financial risks is of great significance. The research on the credit and financial risks of financial enterprises is helpful to help financial enterprises h

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Mall, Sunita, Tushar R. Panigrahi, and Stephina Thomas. "Predicting Financial Solvency of Commercial Borrowers: The Case of Non-Banking Financial Companies." Accounting and Finance Research 8, no. 3 (2019): 61. http://dx.doi.org/10.5430/afr.v8n3p61.

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Credit risk can be effectively managed by evaluating and predicting the credit worthiness of a customer or a corporate. Credit scores are calculated to assess the credit worthiness. It helps the financial institutes to know the amount and dimensions of risk involved in different credit transactions. Credit scoring helps the financial institutes to decide whether or not to lend. It also helps in deciding the price of a particular exposure, the appropriate credit facility and different risk tools. This research paper focuses on identifying the triggers of credit default. It also focuses on check

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Stanley Isanzu, Juliana. "The Impact of Credit Risk on the Financial Performance of Chinese Banks." JOURNAL OF INTERNATIONAL BUSINESS RESEARCH AND MARKETING 2, no. 3 (2017): 14–17. http://dx.doi.org/10.18775/jibrm.1849-8558.2015.23.3002.

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The study aim was to empirically examine the impact of credit risk on the financial performance of Chinese banks. Secondary data was collected from five largest commercial banks in the country for the period of 7 years from 2008 to 2014. The study used nonperforming loans, capital adequacy ratio, impaired loan reserve, and loan impairment charges as measures of credit risk and for a measure of financial performance return on asset was used. Data analysis was done using a balanced panel data regression model, and the study findings reveal nonperforming loan and Capital adequacy have a significa

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Amar, Siti Salama, and Bambang Tj Ahjadi. "Role of credit risk, market risk, liquidity risk, and operational risk on banking financial performance with good corporate governance as a moderating variable." International Journal of Innovative Research and Scientific Studies 8, no. 3 (2025): 5001–15. https://doi.org/10.53894/ijirss.v8i3.7700.

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The purpose of this study was to determine the effect of credit risk, market risk, liquidity risk, and operational risk on banking financial performance. Good corporate governance moderates the relationship between these variables and banking financial performance. The population in this study consisted of banking companies listed on the Indonesia Stock Exchange from 2020 to 2024. The technique for sampling was purposive sampling, and based on the criteria that have been used, the number of samples obtained was 20 banking companies. Research hypothesis testing utilized Multiple Linear Regressi

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Mwakiboko, Mwanaisha, and Tumaini Mutugi Mwikamba. "Financial Risk and Financial Performance of Listed Commercial Banks in Kenya." International Journal of Social Science and Humanities Research (IJSSHR) ISSN 2959-7056 (o); 2959-7048 (p) 3, no. 1 (2025): 233–46. https://doi.org/10.61108/ijsshr.v3i1.169.

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At its core, commercial banking is a business deeply entrenched in the dynamics of risk and reward. Financial risks, encompassing credit, liquidity, price and operational risks, serve as inherent components of banking activities. These risks are not only omnipresent but also inherently interconnected, creating a complex web that directly influences financial performance of commercial banks. The purpose of the study was to determine the effect of financial risk on financial performance of listed commercial banks in Kenya. The study was grounded on extreme value theory, credit risk theory, asymm

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Tsintsadze, Asie, Vladimer Glonti, Lela Oniani, and Tamar Ghoghoberidze. "Empirical Analysis of Financial and Non-Financial Risks of the Commercial Bank." European Journal of Sustainable Development 8, no. 2 (2019): 101. http://dx.doi.org/10.14207/ejsd.2019.v8n2p101.

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Background: Activities of commercial banks are connected with numerous risks, the source of which is the internal and external processes of the bank. Objectives: Risk management science has been studying the origins of the risks, determining their impact quality and avoiding expected loss models from the 1950s. Method/Approach: Credit risk regressive analysis is based on the selection of effective factors, determination of their influence and prediction of future according to the correlation coefficient. Results/Findings: In the article, it is discussed the regressive analysis of operational r

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Yangyudongnanxin, Guo. "Financial Credit Risk Control Strategy Based on Weighted Random Forest Algorithm." Scientific Programming 2021 (October 19, 2021): 1–9. http://dx.doi.org/10.1155/2021/6276155.

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In order to improve the effectiveness of financial credit risk control, a financial credit risk control strategy based on weighted random forest algorithm is proposed. The weighted random forest algorithm is used to classify the financial credit risk data, construct the evaluation index system, and use the analytic hierarchy process to evaluate the financial credit risk level. The targeted risk control strategies are taken according to different risk assessment results. We compared the proposed method with two other methods, and the experimental results show that the proposed method has higher

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Amijaya, Rachmania Nurul Fitri, and Rochmatulloh Alaika. "Does Financial Risk Matter for Financial Performance in Sharia Banks?" Jurnal Ilmu Ekonomi Terapan 8, no. 1 (2023): 24–40. http://dx.doi.org/10.20473/jiet.v8i1.44675.

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This study seeks to examine the impact of operational, liquidity, and credit risks on financial performance (ROA) at national Islamic commercial banks from 2015 to 2021. The model includes control variables such as technological risk (E-Banking) and macroeconomic variables (BI rate and inflation). This study used seven national Islamic banking businesses as examples. This work employs the panel data regression technique to investigate a mixture of time series from 2015 to 2021. In this study, the independent variables are credit risk as measured by Non-Performing Finance (NPF), liquidity risk

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Santana, Patricia Jimbo, Laura Lanzarini, and Aurelio F. Bariviera. "Fuzzy Credit Risk Scoring Rules using FRvarPSO." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 26, Suppl. 1 (2018): 39–57. http://dx.doi.org/10.1142/s0218488518400032.

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There is consensus that the best way for reducing insolvency situations in financial institutions is through good risk management, which involves a good client selection process. In the market, there are methodologies for credit scoring, each analyzing a large number of microeconomic and/or macroeconomic variables selected mostly depending on the type of credit to be granted. Since these variables are heterogeneous, the review process carried out by credit analysts takes time. The objective of this article is to propose a solution for this problem by applying fuzzy logic to the creation of cla

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Stanley Chidozie Umeorah, Adesola Oluwatosin Adelaja, Bibitayo Ebunlomo Abikoye, Oluwatoyin Funmilayo Ayodele, and Yewande Mariam Ogunsuji. "Data-driven credit risk monitoring: Leveraging machine learning in risk management." Finance & Accounting Research Journal 6, no. 8 (2024): 1416–35. http://dx.doi.org/10.51594/farj.v6i8.1399.

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This review explores the evolution of credit risk monitoring, tracing its journey from traditional qualitative assessments to the current integration of machine learning (ML). It highlights how the integration of ML and big data has introduced unprecedented capabilities for analyzing extensive datasets and detecting subtle patterns beyond human capacity. These advanced technologies enable more accurate, efficient and dynamic credit risk predictions through techniques such as random forests, gradient boosting and decision trees. The transformative potential of these methodologies in credit risk

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Faria Rahman Annasha, Sabbir Hossen, Monoara Sultana Morzina, Md. Solaiman Kabir, and Md. Showrov Hossen. "Credit Card Client’s Payment Prediction for Next Month Using Machine Learning Algorithms." Journal of Computer Science and Technology Studies 6, no. 3 (2024): 76–85. http://dx.doi.org/10.32996/jcsts.2024.6.3.8.

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With the quick growth of the credit card system, there is a rising number of misconduct rates on credit card loans, which creates a financial risk for commercial banks. Thus, successful resolutions of the risks are significant for the sound advancement of the industry in the long term. Numerous financial banks and organizations become more and more attentive to the issue of credit card default because it brings about a high probability of financial risks. Credit risk plays a significant part in the financial business. One of the main functions of a bank is to issue loans, credit cards, investm

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Geng, Xinpeng, Bing Han, Debao Yang, and Junren Zhao. "Credit risk contagion of supply chain finance: An empirical analysis of supply chain listed companies." PLOS ONE 19, no. 8 (2024): e0306724. http://dx.doi.org/10.1371/journal.pone.0306724.

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With the gradual rise of the supply chain financial model and the expansion of scale, credit risk and contagion effects are gradually strengthened as business and financial links between upstream and downstream enterprises in the supply chain. The traditional credit risk contagion assessment model based on the financial status of an enterprise and the pledging of fixed assets has been unable to meet the basic needs of modern supply chain companies and financial institutions for risk control. Therefore, this paper introduces the Cox-Copula model to comprehensively assess a company’s financial s

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Setiadi, Fahmi, and Y. Anni Aryani. "Political Connection and Credit Risk Management: Its Effect on Bank’s Performance." Riset Akuntansi dan Keuangan Indonesia 4, no. 3 (2019): 112–21. http://dx.doi.org/10.23917/reaksi.v4i3.8520.

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The present study examines the effect of political connection and credit risk management on Indonesian bank’s performance during the declining credit growth period. The present study involved 258 banks that registered in the Indonesian Stock Exchange from 2012 to 2017 as the sample of the study. Company political connection was measured using headcount index, credit risk management was measured by its credit risk value or NPL, and the company financial performance was measured based on Return on Asset. The data of the study were obtained from banks and Indonesian Stock Exchange annual report.

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Gunnlaugsson, Stefán B. "CREDIT RISK OF ICELANDIC MUNICIPALITIES." Oradea Journal of Business and Economics 2, no. 2 (2017): 7–15. http://dx.doi.org/10.47535/1991ojbe022.

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In this article the results of an extensive research on the credit risk of Icelandic municipalities are presented. The methodology named after Altman was applied and the credit risk of Icelandic municipalities was assessed according to his model. In addition the relationship between financial health and the size of municipalities was examined. Finally a small study was conducted where the financial health of municipalities around the capital area was different from other. The results are that this methodology is useful when evaluating the credit risk of Icelandic municipalities. The findings i

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Apochi, James George, and Asma’u Mahmood Baffa. "Credit Risk and Financial Performance of Deposit Money Banks in Nigeria: Moderating Role of Risk Management Committee." European Journal of Accounting, Auditing and Finance Research 10, no. 10 (2022): 98–115. http://dx.doi.org/10.37745/ejaafr.2013/vol10n1098115.

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The global financial crisis of 2008 and the economic dislocation that followed the emergence of COVID 19 adversely affected financial institutions leading to debt crisis in the Nigerian banking sector. Despite the risk management framework within the banking sector, credit still remains a crucial factor in comparison to other driving factors in the bank, due to its attendant risk and the effect on the economy. This study examined the risk management committee’s role on the effect of credit risk on financial performance of 13 deposit money banks in Nigeria from 2012 to 2021. Finance distress th

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Ogunwale, Olurotimi, and Isibor Areghan. "Impact of Credit Risk Management on the Performance of Nigerian Deposit Money Banks: An Analysis from 2010 to 2020." Asian Journal of Advanced Research and Reports 18, no. 10 (2024): 28–41. http://dx.doi.org/10.9734/ajarr/2024/v18i10752.

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This study examined the impact of credit risk management on the financial performance of Nigerian deposit money banks over a 10-year period from 2010 to 2020. Understanding the relationship between credit risk management and bank performance is crucial for the stability and growth of the Nigerian banking sector. The Five deposit money banks used were First Bank Plc, Zenith Bank Plc, Access Bank Plc, Guarantee Trust Bank Plc, with United Bank of Africa (UBA) Plc. Equity returns measured bank performance while credit risk was explained using non-performing credits, capital adequacy ratio, plus p

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Guan, Shuyin, Yuang Hu, and Ziyi Xu. "Research on the Influencing Factors of Corporate Credit Default Risk." Highlights in Business, Economics and Management 35 (June 16, 2024): 130–35. http://dx.doi.org/10.54097/69k2d202.

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This paper takes corporate financial indicators and the impact of corporate credit risk as the research object. This paper firstly introduces and analyses the relevant literature on enterprise financial indicators and credit risk, then classifies and analyzes the financial indicators of enterprises, and establishes the assessment model of enterprise financial indicators and credit risk on this basis. By analyzing the financial indicators of enterprises, this paper finds that the financial indicators of enterprises, such as quick ratio, cash flow position and net interest, have an important imp

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Vasilieva, Alfia. "Approaches to Building Default Probability Models for Financial Instruments of Project Financing at Long Time Horizons." Journal of Corporate Finance Research / Корпоративные Финансы | ISSN: 2073-0438 15, no. 4 (2021): 66–87. http://dx.doi.org/10.17323/j.jcfr.2073-0438.15.4.2021.66-87.

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 Project financing is one of the priority tools for stimulating the country's economic growth around the world, which allows the implementation of large-scale and capital-intensive projects, providing favorable credit conditions with insufficient creditworthiness of the project beneficiaries [1]. As a rule, project financing instruments are long-term (10-30 years, depending on the type of transaction), so this asset class is interesting for the implementation of the task of building long-term models for assessing credit risk associated with the introduction in 2018 of the new inter

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Sovilj, Ranko. "The challenges of credit risk management in the investment firms in crisis." Strani pravni zivot, no. 3 (2020): 43–56. http://dx.doi.org/10.5937/spz64-28148.

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The global financial crisis has given rise to legislative activity on the international level, with the adoption of numerous legal regulations, in order to improve the ability of financial participants, among others, investment firms to absorb losses arising from economic and financial stress situations. Credit risk is one of the dominant risk in the finance and business of investment firms, and consequently, the exposure to credit risk is present in almost all financial transactions. Therefore, the paper points out that the application of adequate methods of credit risk management can contrib

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Rozmetova, Umida Yuldashevna. "MONITORING OF CREDIT RISKS AS FINANCIAL RESOURCES IN COMMERCIAL BANKS." International journal of trends in business administration International journal of trends in business administration 12, no. 1 (2022): 106–11. https://doi.org/10.5281/zenodo.6683264.

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Credit risk analysis can be thought of as an extension of the credit allocation process. After an individual or business applies to a bank or financial institution for a loan, the lending institution analyzes the potential benefits and costs associated with the loan. Credit risk analysis is used to estimate the costs associated with the loan. Credit risk or credit default risk associated with a financial transaction is simply the expected loss of that transaction. In commercial banks, risk has always been one of the most basic concepts. This article examines the measurement and monitoring of t

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Liu, Yinuo. "Research On The Identification And Evaluation Of Supply Chain Finance Credit Risk." E3S Web of Conferences 275 (2021): 01069. http://dx.doi.org/10.1051/e3sconf/202127501069.

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Narrow financing channels and high costs have gradually become the main factors restricting the development of small and medium-sized enterprises. The break of the capital chain will restrict the development of the overall supply chain. The emergence of supply chain finance has brought good news for solving the problem of limited capital of small and medium-sized enterprises. However, affected by many factors such as the imperfection of the existing regulatory system, the inefficiency of the credit rating work of financial institutions, and the low moral standards of supply chain member compan

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BROLL, UDO, B. MICHAEL GILROY, and ELMAR LUKAS. "MANAGING CREDIT RISK WITH CREDIT DERIVATIVES." Annals of Financial Economics 03, no. 01 (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 b

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Wang, Wenhao, Xiyi Zuo, and Dantong Han. "Predict credit risk with XGBoost." Applied and Computational Engineering 74, no. 1 (2024): 164–77. http://dx.doi.org/10.54254/2755-2721/74/20240462.

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The risk of credit loan exists when the bank issues a loan to the borrower, because the borrower has no way to repay the amount or defaults, which exposes the financial institution to the risk of loss. This causes financial institutions to suffer from effects that affect their creditworthiness, loss of capital and increased management and collection of loans. Factors of such risk include, but are not limited to, the creditworthiness of the borrower, the repayment ability of the borrower, and fluctuations in interest rates. With the development of economy, the credit loan risk of financial indu

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Löschenbrand, Stefan, Martin Maier, Laurent Millischer, and Florian Resch. "Credit Risk Where It’s Due." IMF Working Papers 2025, no. 062 (2025): 1. https://doi.org/10.5089/9798229005777.001.

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This study investigates carbon pricing-induced credit risk, the potential negative impact of carbon pricing on firms’ ability to meet their financial obligations. Applying a well-established credit assessment model to a novel data set combining financial statements and emissions data, we subject the over 2.5 million borrowers of the euro area’s largest banking groups to two carbon pricing stress scenarios. Our findings reveal a notable variation in impacts between and within sectors. However, even under the conservative scenario, many firms experience only a minimal increase in their probabili

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Olaoye, F. O., and T. C. Ojuolape. "Credit Risk Disclosure Compliance And Bank Performance In Nigeria: A Case Study Of Zenith Bank PLC." Archives of Business Research 7, no. 8 (2019): 109–13. http://dx.doi.org/10.14738/abr.78.4055.

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The study examined the influence of credit risk disclosure compliance on bank performance in Nigeria. IFRS 7 state that entity should disclose credit risk in their financial report. Credit risk may affect going concern concept and audit report is silent about it. The specific objective of the study is to ascertain the influence of credit risk disclosure on bank profitability. Linear regression analysis was used to analyse the data collected from financial reports, with the help of SPSS 20.0 version. The study discovered that there is positive relationship between credit risk disclosure and ban

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