Lasso-Cox模型在个人信用风险评估中的应用  

The Application of the Lasso-Cox Model in Personal Credit Risk Assessment

作　　者：李淑锦[1] 嵇晓佳 LI Shu-jin;JI Xiao-jia(School of Economics,Hangzhou Dianzi University,Hangzhou 310018,China)

机构地区：[1]杭州电子科技大学经济学院,浙江杭州310018

出　　处：《资源开发与市场》2021年第2期129-135,共7页Resource Development & Market

基　　金：国家社会科学基金项目“基于大数据的金融零售信用风险评估与智能决策研究”(编号:17BJY233);教育部人文社科青年项目“网络借贷信用风险评估的结构化方法及应用研究”(编号:16YJCZH031)。

摘　　要：借鉴Lasso模型和Cox模型的优点创建Lasso-Cox模型,用以评估个人借款者的信用风险,并利用个人借款者的数据进行实证分析,比较不同模型的预测精度。结果表明:(1)单一Cox模型的预测准确度高于Logistic回归模型,而Lasso-Cox模型的预测精度达95.76%,远高于单一Cox模型。(2)考虑宏观环境对个人经济的影响,发现将宏观变量纳入模型后预测精度有明显的提升,其中Lasso-Cox模型预测精度高达98.88%。Based on the advantages of Lasso model and Cox model,this paper effectively established the Lasso-Cox model to evaluate the credit risk of individual borrowers and compare the prediction accuracy of different models by using individual borrower′s data.The results showed that:(1)The prediction accuracy of the single Cox model was higher than that of the Logistic regression model,and the prediction accuracy of the Lasso-Cox model was 95.76%,which was higher than that of the single Cox model.(2)Taking the impact of macro variables on the individual financial situation into account,the prediction accuracy was significantly improved when macro variables was included in the models,such as the Lasso-Cox model with the accuracy up to 98.88%.

关 键 词：Lasso-Cox模型 信用风险 个人借款者 

分 类 号：F830[经济管理—金融学]