TITLE:
Research on Credit Risk Rating of Commercial Banks Based on Support Vector Machine—Data from China’s Listed Commercial Banks
AUTHORS:
Shunquan Zhu
KEYWORDS:
Chinese Listed Commercial Banks, Support Vector Machine, Credit Risk Rating, Data Supporting
JOURNAL NAME:
Journal of Financial Risk Management,
Vol.14 No.1,
February
28,
2025
ABSTRACT: In the era of big data and artificial intelligence, machine learning is one of the hot issues in the field of credit rating. On the basis of combing the literature on credit rating methods at home and abroad, this paper uses the support vector machine (SVM) method of machine learning to set up a three-classification credit rating model for Chinese listed commercial banks, which is compared with the existing methods of credit rating, the data show that the model classification accuracy on the test set is 80%. The support vector machine (SVM) method can identify the credit rating of Chinese-listed commercial banks, and it has wide applicability and good promotion value. The paper enriches the traditional credit rating method and has important significance in standardizing the healthy development of the financial market.