Research on the Personal Credit Risk Assessment Based on XGBoost and SHAP Methods
To achieve a comprehensive and accurate assessment of personal credit risk,firstly,the importance of various personal information indicators of borrowers in credit risk assessment is studied.Next,based on Python programming language and XGBoost integrated learning method,a personal loan credit assessment model is constructed.Subsequently,reasonable credit assessment indicators are selected by using the SHAP method to improve the assessment model.Finally,it develops a personal loan credit evaluation system based on the LabVIEW platform.The research results indicate that the final selected indicators can more effectively evaluate personal credit risk,and can provide a more effective personal credit risk assessment system for the financial industry.
国家科技期刊平台
NSTL
万方数据
维普
