Application of KMV Model in Credit Risk Management in Banking Industry

Authors

  • Junchao Shen Nanfang College of Sun Yat-sen University, Guangzhou, Guangdong, China
  • Jiayan Chen Nanfang College of Sun Yat-sen University, Guangzhou, Guangdong, China

DOI:

https://doi.org/10.53469/jtpms.2024.04(05).01

Keywords:

Financial Engineering, Banking, Risk Management, KMV Mode

Abstract

As an important part of the national financial system, the banking industry bears important responsibilities for the national economy. In addition, the banking industry is considered an area full of high risks. The risk management of banks not only involves the national finance, economy and national security, but also directly affects the national financial system and the stability of the global financial order. Credit risk has always been one of the risks that domestic and foreign banking banks pay special attention to. Effectively identifying and preventing credit risk is the key to ensure the smooth operation of banks. In order to better identify and manage the credit risk of the listed banks in China, this study uses the KMV model to measure the default distance of the sample banks. Will default distance as assessment of China listed commercial Banks credit risk agent variables, using before 2019 in China's a-share market listed commercial Banks build panel data, empirical analysis, and discuss the analysis results, put forward relevant policy Suggestions, model support for the healthy and steady development of the banking industry. This paper analyzes the current situation of the application of modern credit risk measurement model in the risk management of the banking industry. Meanwhile, combining with the data of some listed banks in China, discusses the credit risks and challenges faced by banks through in-depth analysis, and provides development suggestions with the data analysis of financial model.

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Published

2024-05-31

How to Cite

Shen, J., & Chen, J. (2024). Application of KMV Model in Credit Risk Management in Banking Industry. Journal of Theory and Practice of Management Science, 4(05), 1–12. https://doi.org/10.53469/jtpms.2024.04(05).01