CREDIT RISK ASSESSMENT IN COMMERCIAL BANKS BASED ON SVM USING PCA

摘要：

According to analysis and practical situation of credit risk assessment in commercial banks, some indexes are selected to establish the index system. The credit risk classes are separated into two classes- normality and loss. To classify the credit risk data, support vector machines (SVM) model based on PCA (principal component analysis) is established. In order to verify the effectiveness of the method, a real case is given and SVM model without using PCA is also used to classify the same data. The experimental results show that SVM model based on PCA is effective in credit risk assessment and achieves better performance than SVM model without using PCA.

关键词： Credit risk Commercial banks SVM PCA

作者: CHEN-GUANG YANG XIAO-BO DUAN

作者单位: Power Grid Planning & Research Center, Hebei Electric Power Research Institute, Shijiazhuang 050021, China

会议类型: 国际会议

会议名称: 2008 International Conference on Machine Learning and Cybernetics(2008机器学习与控制论国际会议)

会议地点: 昆明

会议语种:英文

页码: 1207-1211

在线出版日期: 2008-07-12（万方平台首次上网日期，不代表论文的发表时间）