Research on Application of Personal Credit Scoring based on BP-Logistic Hybrid Algorithm

摘要：

In order to improve the robustness and accuracy of the credit evaluation model, we study on individual credit risk, select a statistical method of Logistic regression and a non-statistical method of neural network BP algorithm, which are most frequently used methods by domestic and foreign banks. Furthermore, we separately improve these two methods to some degrees, using Clementine tools to build Personal Credit evaluation model based on BP-Logistic mixed strategy, which improves the accuracy and robustness of the assessment model.

关键词： personal credit scoring BP network factor analysis Logistic regression

作者: Huang Weidong Zhu Xiangwei SuQingling

作者单位: Nanjing University of Posts and Telecommunications, Nanjing 210003, China Suzhou Campus, Nanjing Institute of Railway Technology, Suzhou, 215137, China

会议类型: 国际会议

会议名称: The 2010 International Conference on Computer Application and System Modeling(2010计算机应用与系统建模国际会议 ICCASM 2010)

会议地点: 太原

会议语种:英文

页码: 735-739

在线出版日期: 2010-10-22（万方平台首次上网日期，不代表论文的发表时间）