基于支持向量机的商业银行信用评级研究——来自中国上市商业银行的数据佐证  

Research on Credit Rating of Commercial Banks Based on Support Vector Machine—Data from China’s Listed Commercial Banks as Evidence

作　　者：朱顺泉 

机构地区：[1]广州华商学院数字金融学院,广东 广州

出　　处：《金融》2025年第2期423-429,共7页Finance

基　　金：本研究为广东省重点建设学科科研能力提升项目(项目编号2024ZDJS113)、广州华商学院应用型示范专业-金融科技专业建设项目HS2024SFZY08、广州华商学院金融科技专业核心课程教研室建设项目HS2024ZLGC43等阶段性成果。

摘　　要：在当今的大数据和人工智能时代,机器学习在信用评级领域应用是一个热门的问题之一。论文在梳理国内外信用评级法文献的基础上,运用机器学习的支持向量机(SVM)法建立了中国上市商业银行的3分类信用评级模型,与现有文献的信用评级方法相比,支持向量机法对中国上市商业银行的信用评级有较好的识别,具有广泛的适用性和较好的推广价值。论文丰富传统的信用评级法,对规范金融市场的健康发展有重要的意义。In today’s era of big data and artificial intelligence, the application of machine learning in the field of credit rating is one of the hot issues. Based on a review of domestic and international literature on credit rating methodologies, this paper employs the Support Vector Machine (SVM) approach from machine learning to establish a three-category credit rating model for listed commercial banks in China. Compared with credit rating methods found in existing literature, the SVM approach demonstrates better recognition accuracy in credit rating for listed commercial banks in China, exhibiting broad applicability and significant promotion value. The paper enriches the traditional credit rating method, which is of great significance in regulating the healthy development of the financial market.

关 键 词：中国上市商业银行 支持向量机 信用评级 数据佐证 

分 类 号：F832.33[经济管理—金融学] F832.2