基于线性回归的个人信用报告信用评价研究  

Study on Linear Regression-based Credit Evaluation of Personal Credit Report

作　　者：姚路 

机构地区：[1]中国人民银行西宁中心支行,青海西宁810000

出　　处：《征信》2017年第12期33-35,共3页Credit Reference

摘　　要：在信息共享的大潮流下,缓解纵向信息不对称所带来的矛盾,只是通过信息要素的交换、汇总来提升对完整信息集的有效识别,并不能使信用报告使用者准确预判信用风险。个人征信报告正是在纵向信息不对称的大环境下,用来构建的可供金融机构共享的个人信用信息媒介。研究发现,信贷人员依据信用报告上的信息要素,在对个人基本信息、借贷担保交易信息、公积金信息、查询记录信息等认知的基础上,可以构建多元线性回归模型,间接得出对信息主体的信用评价,最终促进G2B共享信息的应用。In the context of the tide of information sharing, it is imperative to alleviate the contradiction resulted from the vertical information asymmetry. It cannot make the credit report users accurately predict the credit risk to enhance the effective identification of the complete information collection through the exchange and summary of information elements. Personal credit report is used as a media for financial institutions to share personal credit information in the vertical information asymmetry environment. The study shows that the credit officer, based on the information elements of the credit report, can establish a multiple linear regression model and indirectly obtain the credit evaluation of information subjects through the cognition of individual basic information, loan guarantee transaction information, provident fund information, and inquiry record information, and finally promotes the G2B application of information sharing.

关 键 词：信用报告 信用评价 多元线性回归模型 信息不对称 

分 类 号：F832.479[经济管理—金融学] O212.1[理学—概率论与数理统计]