现代信息科技2024，Vol.8Issue(8)：146-150,155,6.DOI:10.19850/j.cnki.2096-4706.2024.08.032
基于XGBoost和SHAP方法的个人信贷风险评估研究
Research on the Personal Credit Risk Assessment Based on XGBoost and SHAP Methods
摘要
Abstract
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.关键词
信贷风险/XGBoost算法/SHAP/信用评估/PythonKey words
credit risk/XGBoost algorithm/SHAP/credit evaluation/Python分类
信息技术与安全科学引用本文复制引用
伍洁,陈迪芳,李瑞彤,石景阳..基于XGBoost和SHAP方法的个人信贷风险评估研究[J].现代信息科技,2024,8(8):146-150,155,6.基金项目
湖北省大学生创新创业训练计划项目(S202210525055) （S202210525055）
教育部产学合作协同育人项目(202101087049) （202101087049）
湖北省大学生创新创业训练计划项目(S202210525056) （S202210525056）
