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Relevant bibliographies by topics / Assessment of credit risk

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Academic literature on the topic 'Assessment of credit risk'

Author: Grafiati

Published: 28 May 2022

Last updated: 31 July 2025

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Journal articles on the topic "Assessment of credit risk"

1

Gustafson, Cole R., Glenn D. Pederson, and Brent A. Gloy. "Credit risk assessment." Agricultural Finance Review 65, no. 2 (2005): 201–17. http://dx.doi.org/10.1108/00214660580001173.

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Hamraevich, Tashmatov Shuhrat. "ASSESSMENT OF CREDIT RISK OF A COMMERCIAL BANK." International Journal Of Management And Economics Fundamental 3, no. 12 (2023): 92–97. http://dx.doi.org/10.37547/ijmef/volume03issue12-16.

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This article presents a method for assessing the risks of commercial banks, mainly analyzing the credit risk, interest rate risk and capital risk faced by commercial banks. A model for assessing the credit risk of commercial banks in Uzbekistan is also reviewed.

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LARIONOVA, K., and T. DONCHENKO. "ANALYSIS AND ASSESSMENT OF CREDIT RISK OF BANKS OF UKRAINE." Herald of Khmelnytskyi National University. Economic sciences 278, no. 1 (2020): 233–40. https://doi.org/10.31891/2307-5740-2020-278-1-41.

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The negative consequences of the financial crisis, political instability, which significantly weakened the banking system of Ukraine, revealed the unwillingness of most banking institutions to promptly and adequately adjust credit policy to find the optimal balance between customer needs for credit resources, lending risks, liquidity requirements, collateral requirements credit funds of business entities with real assets, etc. The processes of internationalization and globalization in the financial market exacerbate the need to reassess the role and place of credit risk management of banking i

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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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Xie, Xiaofeng, Fengying Zhang, Li Liu, Yang Yang, and Xiuying Hu. "Assessment of associated credit risk in the supply chain based on trade credit risk contagion." PLOS ONE 18, no. 2 (2023): e0281616. http://dx.doi.org/10.1371/journal.pone.0281616.

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Assessment of associated credit risk in the supply chain is a challenge in current credit risk management practices. This paper proposes a new approach for assessing associated credit risk in the supply chain based on graph theory and fuzzy preference theory. First, we classified the credit risk of firms in the supply chain into two types, namely firms’ “own credit risk” and “credit risk contagion”; second, we designed a system of indicators for assessing the credit risks of firms in the supply chain and used fuzzy preference relations to obtain the fuzzy comparison judgment matrix of credit r

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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 (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 establis

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Moolchandani, Sanjay. "Advanced Credit Risk Assessment Using Markov Chain Monte Carlo Techniques." International Journal of Science and Research (IJSR) 12, no. 12 (2023): 2160–63. http://dx.doi.org/10.21275/sr23127095329.

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Черниченко, Светлана, Svetlana Chernichenko, Роман Котов, Roman Kotov, Светлана Гильмулина, and Svetlana Gilmulina. ". Experimental synthetic approach to segment assessment of aggregate credit risk." Food Processing: Techniques and Technology 48, no. 1 (2019): 184–89. http://dx.doi.org/10.21603/2074-9414-2018-1-184-189.

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Multifaceted, multifactor and multicomponent nature of credit risk makes it possible to consider it as an integral hypothetical unit which consists of the autonomous diverse segments specifying risky situations. As the given article is focused on the mechanism of loan fund circulation within foreign currency loan the author considers the combination of credit, interest rate, foreign exchange and inflation risks within the aggregate (total, combined) credit risk. Foreign exchange and inflation risks generate special interest in relation to evaluation procedures as there can be statutory regulat

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Barth, Mary E., Gaizka Ormazabal, and Daniel J. Taylor. "Asset Securitizations and Credit Risk." Accounting Review 87, no. 2 (2011): 423–48. http://dx.doi.org/10.2308/accr-10194.

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ABSTRACT This study examines the sources of credit risk associated with asset securitizations and whether credit-rating agencies and the bond market differ in their assessment of this risk. Measuring credit risk using credit ratings, we find the securitizing firm's credit risk is positively related to the firm's retained interest in the securitized assets and unrelated to the portion of the securitized assets not retained by the firm. Measuring credit risk using bond spreads, we find the securitizing firm's credit risk is positively related to both the firm's retained interest in the assets an

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Arunkumar, Paramasivan. "Revolutionizing Credit Risk Assessment AI in Card Transaction Analytics." INTERNATIONAL JOURNAL OF INNOVATIVE RESEARCH AND CREATIVE TECHNOLOGY 6, no. 1 (2020): 1–9. https://doi.org/10.5281/zenodo.14551643.

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This Article examines the transformative impact of artificial intelligence (AI) on credit risk assessment within card transaction analytics. By harnessing AI's advanced capabilities in data analysis and pattern recognition, financial institutions can now conduct more nuanced and accurate evaluations of an individual’s creditworthiness, identify potential defaults, and detect early signs of financial distress in real time. Traditional credit scoring models, previously limited by static data and periodic assessments, are significantly enhanced by AI’s ability to analyze vast transact

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Dissertations / Theses on the topic "Assessment of credit risk"

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Patricio, Antonio Pires. "Credit risk assessment in Macau." Thesis, University of Macau, 2004. http://umaclib3.umac.mo/record=b1636249.

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Mu, Yuan. "Chinese bank's credit risk assessment." Thesis, University of Stirling, 2007. http://hdl.handle.net/1893/210.

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This thesis studies the Chinese banks’ credit risk assessment using the Post Keynesian approach. We argue that bank loans are the major financial sources in emerging economies and it is uncertainty, an unquantifiable risk, rather than asymmetric information about quantifiable risk, as held by the mainstream approach, which is most important for the risk attached to credit loans, and this uncertainty is particularly important in China. With the universal existence of uncertainty, borrowers and lenders have to make decisions based on convention and experience. With regard to the nature of decisi

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Desrosiers, Mary Elizabeth. "Prices of credit default swaps and the term structure of credit risk." Link to electronic thesis, 2007. http://www.wpi.edu/Pubs/ETD/Available/etd-050107-220449/.

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Curti, Filippo. "The Rating Game: an Empirical Assessment." Diss., The University of Arizona, 2014. http://hdl.handle.net/10150/323225.

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The question of whether ratings agencies convey new information to financial markets when they assign new ratings or change previous ratings has been debated for at least 40 years. In this study I first examine equity market, bond market and CDS market reactions to long and short term rating changes from S&P, Fitch and Moody's. I find that not all the credit rating changes affect the market but only those classified as unanticipated. Subsequently, I study whether the regulatory setting, in which the Credit Ratings Agencies work, can possibly affect the financial markets reactions. Lastly I sho

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Henley, William Edward. "Statistical aspects of credit scoring." Thesis, Open University, 1994. http://oro.open.ac.uk/57441/.

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This thesis is concerned with statistical aspects of credit scoring, the process of determining how likely an applicant for credit is to default with repayments. In Chapters 1-4 a detailed introduction to credit scoring methodology is presented, including evaluation of previous published work on credit scoring and a review of discrimination and classification techniques. In Chapter 5 we describe different approaches to measuring the absolute and relative performance of credit scoring models. Two significance tests are proposed for comparing the bad rate amongst the accepts (or the error rate)

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Boscolo, Chio Michele <1995&gt. "The assessment of credit risk in international trade: country risk and enterprise specific risk." Master's Degree Thesis, Università Ca' Foscari Venezia, 2020. http://hdl.handle.net/10579/16864.

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International Trade and export are fundamental activities for companies that want to compete in a globalised market. This descriptive-analytical study has the goal to define the risks that companies must consider operating beyond the domestic boundary. The main risk analysed in this thesis is the credit risk, that in international trade transactions must be seen as a binomial composed of the specific risk of the buyer enterprise and the risk of the country the buyer enterprise is located in. This thesis is divided into two parts. The first part is intended to introduce the definition and the l

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Pershad, Rinku. "A Bayesian belief network for corporate credit risk assessment." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0022/MQ50360.pdf.

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Hellström, Ängerud Linnéa. "Credit Risk Assessment of Real Estate Companies : How does the Credit Assessment of Banks and Bond Investors Differ?" Thesis, KTH, Fastigheter och byggande, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-211143.

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The vast majority of the Swedish real estate companies are to some extent financed by debt and are dependent on external capital when expanding their business. Swedish real estate companies have traditionally financed their business through bank loans, but as a result of – among other things – stricter regulations, an increasing share of the Swedish real estate companies seek funding in the capital market, and corporate bonds in particular have emerged as an alternative to bank loans. In all types of lending, whether it is a bank loan or an investor who buys a bond, the lender must assess the

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Hrdová, Edita. "Risk Assessment." Master's thesis, Vysoká škola ekonomická v Praze, 2012. http://www.nusl.cz/ntk/nusl-194193.

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This diploma thesis is focused on companies risk evaluation before endorsement of Loan deriving from business relationships. The aim of this thesis is not only to describe individual steps of risk assessment, but also perfom analysis of particular companies based on available data, i.e. Balance sheet, Profit and Loss statement and external rating and after that propose solution for each company. My analysis will be based on theoretical knowledge, further on experience related to my job role as credit analyst. The aim will be to perform objective analysis of real companies and determine financi

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Claesson, Johan. "Credit Risk Assessments of Swedish RealEstate Companies." Thesis, KTH, Fastigheter och byggande, 2013. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-124335.

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The real estate industry is a sector where the companies generally have a capital structure which is high leveraged. The financing – with the related terms – is therefore specifically of high importance for the companies in the sector. Traditionally, the way of obtain financing is by borrowing from the bank. Lately, due to new bank regulations, the banks have become more restrictive in their lending which have lead to a growth of other financing alternatives. For instance, the corporate bond market has grown rapidly. The development has increased the number who acts as lenders. Institutional i

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Books on the topic "Assessment of credit risk"

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Abrahams, Clark R. Credit Risk Assessment. John Wiley & Sons, Ltd., 2009.

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Lowe, Philip. Credit risk measurement and procyclicality. Bank for International Settlements, Monetary and Economic Dept., 2002.

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Doumpos, Michalis, Christos Lemonakis, Dimitrios Niklis, and Constantin Zopounidis. Analytical Techniques in the Assessment of Credit Risk. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-99411-6.

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Altay, Osman. Sovereign credit rating system and determinants of short term soverign risk: Evidence from Turkey. Nobel Bilimsel Eserler, 2020.

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Pershad, Rinku. A Bayesian belief network for corporate credit risk assessment. National Library of Canada, 2000.

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Avery, Robert B. Consumer credit scoring: Do situational circumstances matter? Bank for International Settlements, 2004.

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Ganguin, Blaise. Fundamentals of corporate credit analysis. McGraw-Hill, 2005.

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Dermine, Jean. Deposit insurance, credit risk and capital adequacy: A note. INSEAD, 1992.

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Somerville, Andrew A. The reliability of banker judgement in LDC credit-risk assessment. City University Business School, Centre for Empirical Research in Finance and Accounting, 1994.

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Bohn, Jeffrey R. Active Credit Portfolio Management in Practice. John Wiley & Sons, Ltd., 2009.

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Book chapters on the topic "Assessment of credit risk"

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Assefa, Samson, Tomasz R. Bielecki, Stéphane Crépey, and Monique Jeanblanc. "CVA Computation for Counterparty Risk Assessment in Credit Portfolios." In Credit Risk Frontiers. John Wiley & Sons, Inc., 2012. http://dx.doi.org/10.1002/9781118531839.ch12.

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Lewis, Mervyn K., Per Lundberg, M. Sc Lars Silver, et al. "Risk Assessment and Credit Management." In Risk Behaviour and Risk Management in Business Life. Springer Netherlands, 2000. http://dx.doi.org/10.1007/978-94-017-2909-3_2.

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Poncet, Patrice, and Roland Portait. "Modeling Credit Risk (1): Credit Risk Assessment and Empirical Analysis." In Springer Texts in Business and Economics. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-84600-8_28.

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Moliterni, Francesco. "Credit Risk Transfer and Systemic Risk." In New Economic Windows. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64916-5_7.

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AbstractThis chapter investigates the relationship between the banking and insurance industry by focusing on systemic risk. The concept of credit risk transfer stems from banks’ inclination to offload credit risks. Insurance companies, particularly those specializing in risk transfer services, emerge as natural recipients for these risks. Notably, credit insurance firms are equipped with specialized expertise in risk assessment and selection. Banks seek to mitigate their exposure to credit risks by transferring them to insurance companies. This transfer occurs because insurance companies, part

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Koulafetis, Panayiota. "Chapter 5: Credit Risk Assessment of Structured Finance Securities." In Modern Credit Risk Management. Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-52407-2_5.

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Koulafetis, Panayiota. "Chapter 4: Credit Risk Assessment of Sovereigns, Banks and Corporates." In Modern Credit Risk Management. Palgrave Macmillan UK, 2017. http://dx.doi.org/10.1057/978-1-137-52407-2_4.

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di Tollo, Giacomo, and Marianna Lyra. "Elman Nets for Credit Risk Assessment." In New Economic Windows. Springer Milan, 2010. http://dx.doi.org/10.1007/978-88-470-1778-8_8.

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Yhip, Terence M., and Bijan M. D. Alagheband. "The Criteria-Based Approach to Credit Risk Assessment and Credit Risk Rating." In The Practice of Lending. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-32197-0_3.

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Doumpos, Michalis, Christos Lemonakis, Dimitrios Niklis, and Constantin Zopounidis. "Introduction to Credit Risk Modeling and Assessment." In EURO Advanced Tutorials on Operational Research. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-99411-6_1.

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Ferretti, Paola. "Credit Risk Assessment: The Internal Rating Systems." In New Perspectives on the Bank-Firm Relationship. Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40331-1_3.

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Conference papers on the topic "Assessment of credit risk"

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Tofayel Gonee Manik, Mia Md, Abu Saleh Muhammad Saimon, Md Shafiqul Islam, Mohammad Moniruzzaman, Evha Rozario, and Md Ekrim Hossin. "Big Data Analytics for Credit Risk Assessment." In 2025 International Conference on Machine Learning and Autonomous Systems (ICMLAS). IEEE, 2025. https://doi.org/10.1109/icmlas64557.2025.10967667.

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Paul, Mutambuze, Margaret Nagwovuma, Barbara Nansamba, Nakayiza Hellen, Daudi Jingo, and Ggaliwango Marvin. "Trustworthy Deep Learning Techniques for Credit Risk Assessment." In 2024 5th International Conference on Electronics and Sustainable Communication Systems (ICESC). IEEE, 2024. http://dx.doi.org/10.1109/icesc60852.2024.10689741.

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Srikanteswara, Ramya, Krinal Naghera, Shashank Balnad Kukkaje, Adarsh Kumar, and Shrey P. "Credit Risk Assessment using Ensemble Models and Explainable AI." In 2025 3rd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT). IEEE, 2025. https://doi.org/10.1109/idciot64235.2025.10914916.

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Palaiokrassas, Georgios, Sandro Scherrers, Eftychia Makri, and Leandros Tassiulas. "Machine Learning in DeFi: Credit Risk Assessment and Liquidation Prediction." In 2024 IEEE International Conference on Blockchain and Cryptocurrency (ICBC). IEEE, 2024. http://dx.doi.org/10.1109/icbc59979.2024.10634435.

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Zhang, Hanyin, Facheng Dai, and Xiangguang Dai. "Personal Credit Risk Assessment Based on Swarm Intelligence and Random Forest." In 2024 6th International Conference on Electronic Engineering and Informatics (EEI). IEEE, 2024. http://dx.doi.org/10.1109/eei63073.2024.10696656.

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Gupta, Vishan Kumar, Paras Jain, Darpan Anand, Gamini Dhiman, Sarvesh Vishwakarma, and Anurag Aeron. "A Credit Risk Assessment System for Financial Institutions Utilizing Deep Learning." In 2024 1st International Conference on Advanced Computing and Emerging Technologies (ACET). IEEE, 2024. http://dx.doi.org/10.1109/acet61898.2024.10729899.

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Jiang, Mohan, Jiating Lin, Hongju Ouyang, Jingming Pan, Siyuan Han, and Bingyao Liu. "Wasserstein Distance-Weighted Adversarial Network for Cross-Domain Credit Risk Assessment." In 2024 3rd International Conference on Cloud Computing, Big Data Application and Software Engineering (CBASE). IEEE, 2024. https://doi.org/10.1109/cbase64041.2024.10824619.

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Yu, Guanfang. "Intelligent Credit Assessment and Risk Prediction Model based on Machine Learning." In 2025 3rd International Conference on Data Science and Information System (ICDSIS). IEEE, 2025. https://doi.org/10.1109/icdsis65355.2025.11070653.

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Sizykh, Dmitry, Roman Kovalev, and Natalia Sizykh. "Improving the Credit Risk Assessment Model Using Forecasting and Monte Carlo Methods." In 2024 17th International Conference on Management of Large-Scale System Development (MLSD). IEEE, 2024. http://dx.doi.org/10.1109/mlsd61779.2024.10739527.

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Liu, Bingyao, Iris Li, Jianhua Yao, Yuan Chen, Guanming Huang, and Jiajing Wang. "Unveiling the Potential of Graph Neural Networks in SME Credit Risk Assessment." In 2024 5th International Conference on Intelligent Computing and Human-Computer Interaction (ICHCI). IEEE, 2024. https://doi.org/10.1109/ichci63580.2024.10808129.

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Reports on the topic "Assessment of credit risk"

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Gómez, Camilo, and Daniela Rodríguez-Novoa. Firm Support Measures, Credit Payment Behavior, and Credit Risk. Banco de la República, 2024. http://dx.doi.org/10.32468/be.1277.

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This paper examines the relationship between three government support measures (debt moratorium, credit guarantee programs, and payroll subsidies) and the firm's payment behavior on loans in Colombia. To do so, we use the COVID-19 pandemic episode as a case study. Using highly granular data at the bank-firm level and a difference-in-difference approach, we find that firms subject to debt reliefs and government guarantee programs experienced a lower probability of default while these policies were in force. Subsequently, once the programs ended, the dynamic of the payment behavior of these firm

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Soriano, Alejandro. Oversight Note on Credit Risk Management. Inter-American Development Bank, 2011. http://dx.doi.org/10.18235/0010447.

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This evaluation examines IDB's management of credit risk of Non-Sovereign Guaranteed Operations. Although the IDB is not subject to the Principles for the Management of Credit Risk issued by the Basel Committee for Banking Supervision, these principles have been used as guidelines for this assessment. It can be concluded that the IDB largely complies with Basel's credit risk management principles. To further develop what is already a solid foundation for its credit risk management system, it is recommended that the IDB adopts a comprehensive Credit Risk Framework that clearly defines its risk

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Yaroshchuk, Svitlana O., Nonna N. Shapovalova, Andrii M. Striuk, Olena H. Rybalchenko, Iryna O. Dotsenko, and Svitlana V. Bilashenko. Credit scoring model for microfinance organizations. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3683.

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The purpose of the work is the development and application of models for scoring assessment of microfinance institution borrowers. This model allows to increase the efficiency of work in the field of credit. The object of research is lending. The subject of the study is a direct scoring model for improving the quality of lending using machine learning methods. The objective of the study: to determine the criteria for choosing a solvent borrower, to develop a model for an early assessment, to create software based on neural networks to determine the probability of a loan default risk. Used rese

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Suarez, David, Juan Manuel Puerta, Thomas Reichmann, Juan Carlos Di Tata, and Cheryl Gray. IDB-9: Macroeconomic Sustainability Assessments. Inter-American Development Bank, 2013. http://dx.doi.org/10.18235/0009099.

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One of the most debated parts of the IDB-9 Agreement was the requirement that the Inter-American Development Bank (IDB or Bank) enhance its macroeconomic analysis and link it to its country programming to avoid lending in unsustainable macroeconomic situations. The IDB-9 Agreement mandated that the Chief Economist prepare annual Macroeconomic Sustainability Assessments for each borrowing country and that a positive judgment on sustainability is one of the prerequisites, among others, for maintaining the Bank's aggregate exposure with the country including both sovereign and non-sovereign opera

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Gourio, Francois. Credit Risk and Disaster Risk. National Bureau of Economic Research, 2011. http://dx.doi.org/10.3386/w17026.

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He, Zhiguo, and Wei Xiong. Rollover Risk and Credit Risk. National Bureau of Economic Research, 2010. http://dx.doi.org/10.3386/w15653.

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Galaasen, Sigurd, Rustam Jamilov, Ragnar Juelsrud, and Hélène Rey. Granular Credit Risk. National Bureau of Economic Research, 2020. http://dx.doi.org/10.3386/w27994.

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Patil, Gitesh. Credit Credit Risk Management Using Hybrid Methodologies. Iowa State University, 2020. http://dx.doi.org/10.31274/cc-20240624-448.

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Berndt, Antje, Rohan Douglas, Darrell Duffie, and Mark Ferguson. Corporate Credit Risk Premia. National Bureau of Economic Research, 2018. http://dx.doi.org/10.3386/w24213.

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López-Piñeros, Martha Rosalba, Fernando Tenjo-Galarza, and Hector Manuel Zárate-Solano. Credit cycles, credit risk and countercyclical loan provisions. Banco de la República, 2013. http://dx.doi.org/10.32468/be.788.

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