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Commercial Bank Lending: Process, Credit Scoring, and Costs of Errors in Lending

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  • Altman, Edward I.

Abstract

Despite the proliferation of banking services, the basic commercial and industrial lending process remains the lifeblood of commercial banks and other banking institutions. The lending process is a relatively straightforward series of activities involving two principal parties whose association ranges from the initial loan request to the successful or unsuccessful repayment of the loan. Most students of banking would agree that the process is an interdependent one, but the exact dependencies are rarely articulated in a rigorous manner. One of the purposes of this paper is to investigate the association between at least two important aspects of the lending process, namely, the credit evaluation stage and the sequence of events that describes and quantifies the charge-off and subsequent recovery experience.

Suggested Citation

  • Altman, Edward I., 1980. "Commercial Bank Lending: Process, Credit Scoring, and Costs of Errors in Lending," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 15(4), pages 813-832, November.
    • Handle: RePEc:cup:jfinqa:v:15:y:1980:i:04:p:813-832_01
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    1. Gabriela Kuvikova, 2015. "Does Loan Maturity Matter in Risk-Based Pricing? Evidence from Consumer Loan Data," CERGE-EI Working Papers wp538, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    2. Lang Zhang & Haiqing Hu & Dan Zhang, 2015. "A credit risk assessment model based on SVM for small and medium enterprises in supply chain finance," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 1(1), pages 1-21, December.
    3. Jialin Du & Eric Yanfei Zhao, 2023. "International expansion and home-country resource acquisition: A signaling perspective of emerging-market firms’ internationalization," Journal of International Business Studies, Palgrave Macmillan;Academy of International Business, vol. 54(9), pages 1642-1660, December.
    4. Yi Jiang & Stewart Jones, 2018. "Corporate distress prediction in China: a machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 58(4), pages 1063-1109, December.
    5. Zedda, Stefano & Modina, Michele & Gallucci, Carmen, 2024. "Cooperative credit banks and sustainability: Towards a social credit scoring," Research in International Business and Finance, Elsevier, vol. 68(C).
    6. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
    7. Hubert Ooghe & Christophe Spaenjers, 2010. "A note on performance measures for business failure prediction models," Applied Economics Letters, Taylor & Francis Journals, vol. 17(1), pages 67-70, January.
    8. Gabriela Kuvikova, 2015. "Loans for Better Living: The Role of Informal Collateral," CERGE-EI Working Papers wp541, The Center for Economic Research and Graduate Education - Economics Institute, Prague.
    9. Roy Cerqueti & Francesca Pampurini & Annagiulia Pezzola & Anna Grazia Quaranta, 2022. "Dangerous liasons and hot customers for banks," Review of Quantitative Finance and Accounting, Springer, vol. 59(1), pages 65-89, July.
    10. Rodríguez Guevara, David Esteban & Rendón García, Juan Fernando & Trespalacios Carrasquilla, Alfredo & Jiménez Echeverri, Edwin Andrés, 2022. "Modelación de riesgo de crédito de personas naturales. Un caso aplicado a una caja de compensación familiar colombiana [Natural People Credit Risk Modeling. An applied case in a Colombian Family Be," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 33(1), pages 29-48, June.
    11. Brad S. Trinkle & Amelia A. Baldwin, 2016. "Research Opportunities for Neural Networks: The Case for Credit," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 23(3), pages 240-254, July.
    12. Rodgers, Waymond, 1999. "The influences of conflicting information on novices and loan officers' actions," Journal of Economic Psychology, Elsevier, vol. 20(2), pages 123-145, April.
    13. Onur Boyabatlı & L. Beril Toktay, 2011. "Stochastic Capacity Investment and Flexible vs. Dedicated Technology Choice in Imperfect Capital Markets," Management Science, INFORMS, vol. 57(12), pages 2163-2179, December.
    14. Bitetto, Alessandro & Cerchiello, Paola & Filomeni, Stefano & Tanda, Alessandra & Tarantino, Barbara, 2023. "Machine learning and credit risk: Empirical evidence from small- and mid-sized businesses," Socio-Economic Planning Sciences, Elsevier, vol. 90(C).
    15. Adli Abouzeedan, 2003. "Financing Swedish Small and Medium-Sized Enterprises: Methods, Problems and Impact," ERSA conference papers ersa03p34, European Regional Science Association.
    16. Smith, L. Douglas & Lawrence, Edward C., 1995. "Forecasting losses on a liquidating long-term loan portfolio," Journal of Banking & Finance, Elsevier, vol. 19(6), pages 959-985, September.
    17. Hossein Rezayi Dolatabadi & Avaz Yari & Fatemeh Faghani & Ali Akbar Abedi Sharabiany & Mohammad Hossein Forghani & Mohammad Kazem Emadzadeh, 2013. "Prioritizing of Credit Ranking Criterions of Isfahan State banks' Costumers by Using AHP Fuzzy Method," International Journal of Academic Research in Accounting, Finance and Management Sciences, Human Resource Management Academic Research Society, International Journal of Academic Research in Accounting, Finance and Management Sciences, vol. 3(1), pages 303-313, January.
    18. Wayne Passmore & Roger Sparks, 1997. "The effect of automated underwriting on the profitability of mortgage securitization," Finance and Economics Discussion Series 1997-19, Board of Governors of the Federal Reserve System (U.S.).
    19. Piesse, J. & Wood, D., 1992. "Issues in assessing MDA models of corporate failure: A research note," The British Accounting Review, Elsevier, vol. 24(1), pages 33-42.
    20. Chen, Yenpao & Guo, Ruey-Ji & Huang, Rao-Li, 2009. "Two stages credit evaluation in bank loan appraisal," Economic Modelling, Elsevier, vol. 26(1), pages 63-70, January.
    21. Alessandro Bitetto & Paola Cerchiello & Stefano Filomeni & Alessandra Tanda & Barbara Tarantino, 2021. "Machine Learning and Credit Risk: Empirical Evidence from SMEs," DEM Working Papers Series 201, University of Pavia, Department of Economics and Management.
    22. Yubin Yang & Xuejian Chu & Ruiqi Pang & Feng Liu & Peifang Yang, 2021. "Identifying and Predicting the Credit Risk of Small and Medium-Sized Enterprises in Sustainable Supply Chain Finance: Evidence from China," Sustainability, MDPI, vol. 13(10), pages 1-19, May.
    23. Andreas Hoegen & Dennis M. Steininger & Daniel Veit, 2018. "How do investors decide? An interdisciplinary review of decision-making in crowdfunding," Electronic Markets, Springer;IIM University of St. Gallen, vol. 28(3), pages 339-365, August.

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