基于Lasso-Logistic模型的个人信用风险预警方法

将lasso-logistic模型引入到个人信用评估中，通过模拟实验发现，逐步回归法倾向于保留一些不重要的变量，而且选出正确模型的概率较低，而Lasso不仅计算更加快捷、同时进行变量选择和参数估计，而且能更准确筛选出重要变量。此外，本文以信用卡消费信贷违约数据为例对我国个人信用评估进行了实证分析，发现相对于全变量Logistic模型和逐步回归Logistic模型，lasso-logistic模型更能抓住影响消费信用风险的关键因素，而且预测准确率也更高。

Individual Credit Risk Prediction Method: Application of a Lasso-Logistic Model

This article apply lasso-logistic model to the individual credit risk prediction, the simulation suggests that stepwise method is apt to keep nonzero variable and the probability to select correct model is low, while lasso has the advantages over other methods in computation, variable selection and parameter estimation simultaneously and grasping key factors. In additional, this article give an empirical analysis of individual credit evaluation using credit cards data from a famous bank in China, finding that lasso-logistic model relative to full logistic model and stepwise logistic model can select key factors and the predict accuracy is much higher.