Credit Risk Model Based on Logistic Regression and Weight of Evidence

被引：0

作者：

Yang, Xiang ^{[1
]}

Zhu, Yongbin ^{[1
]}

Yan, Li ^{[1
]}

Wang, Xin ^{[1
]}

机构：

[1] Honghe Univ, Sch Engn Technol, Mengzi 661100, Peoples R China

来源：

PROCEEDINGS OF THE 2015 3RD INTERNATIONAL CONFERENCE ON MANAGEMENT SCIENCE, EDUCATION TECHNOLOGY, ARTS, SOCIAL SCIENCE AND ECONOMICS (MSETASSE 2015) | 2015年 / 41卷

关键词：

Credit Risk; Logistic Regression; Weight of Evidence; Scorecard;

D O I：

暂无

中图分类号：

C [社会科学总论];

学科分类号：

03 ; 0303 ;

摘要：

Many techniques have been used to build credit risk model. Among them, logistic regression is a more appropriate technique due to its desirable features (e.g., interpretability and prediction accuracy). In this paper, toimplement credit risk assessment quickly, a method for constructing credit risk model (in the form of a scorecard) based on logistic and weight of evidence is proposed.

引用

页码：810 / 814

页数：5

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