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Yeh, C.-C., Lin, F.Y. and Hsu, C.-Y. (2012) A Hybrid KMV Model, Random Forests and Rough Set Theory Approach for Credit Rating. Knowledge-Based Systems, 33, 166-172.
https://doi.org/10.1016/j.knosys.2012.04.004

has been cited by the following article:

• TITLE: The Impact of Electronic Banking on the Credit Risk of Commercial Banks —An Empirical Study Based on KMV Model

  AUTHORS: Zheng Zhao, Yue Lan, Xiaoyu Wu

  KEYWORDS: Commercial Banks, Electronic Banking, Credit Risk, KMV Model, Default Distance

  JOURNAL NAME: Journal of Mathematical Finance, Vol.6 No.5, November 17, 2016

  ABSTRACT: Due to the birth of the age of Big Data and the development of Internet finance, electronic banking has been booming. With the application of descriptive statistics, KMV model, panel data regression and robustness testing, this paper examines the validity of KMV model as a measurement of the credit risk of financial institutions, and reveals the impact of electronic banking on the credit risk of commercial banks. The findings are as follows: First, the default distance based on the KMV model can well reflect the credit risk of banks; Second, the growing electronic banking may increase the credit risk, considering the lack of governmental and industrial regulation; At last, the credit risk of banks under different systems have their unique characteristics, so that a clearly defined division of responsibilities for risk control and supervision is needed.