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How Well Do Banks Manage Their Credit Risk? A Data Envelopment Analysis (DEA) Approach

Advances in Pacific Basin Business, Economics and Finance

ISBN: 978-1-83753-865-2, eISBN: 978-1-83753-864-5

Publication date: 4 April 2024

Abstract

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

Keywords

Citation

Chen, R.-R. and Kuei, C.-H. (2024), "How Well Do Banks Manage Their Credit Risk? A Data Envelopment Analysis (DEA) Approach", Lee, C.-F. and Yu, M.-T. (Ed.) Advances in Pacific Basin Business, Economics and Finance (Advances in Pacific Basin Business, Economics and Finance, Vol. 12), Emerald Publishing Limited, Leeds, pp. 125-163. https://doi.org/10.1108/S2514-465020240000012006

Publisher

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Emerald Publishing Limited

Copyright © 2024 Ren-Raw Chen and Chu-Hua Kuei. Published under exclusive licence by Emerald Publishing Limited