%0 Journal Article
%T 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
%A 朱顺泉
%J Finance
%P 423-429
%@ 2161-0975
%D 2025
%I Hans Publishing
%R 10.12677/fin.2025.152044
%X 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.
%K 中国上市商业银行，
%K 支持向量机，
%K 信用评级，
%K 数据佐证
China Listed Commercial Banks
%K Support Vector Machine
%K Credit Rating
%K Data Evidence
%U http://www.hanspub.org/journal/PaperInformation.aspx?PaperID=109137