文献类型：会议论文

中文题名：CREDIT EVALUATION MODEL OF CREDIT CARD BY USING THE HYBRID MODEL OF NEURAL NETWORK AND LOGISTIC REGRESSION

作者：HAIYING MA[1];

机构：[1]DEPARTMENT OF MANAGEMENT SCIENCE AND ENGINEERING,EAST CHINA UNIVERSITY OF SCIENCE TECHNOLOGY,SHANGHAI 200237,CHINA;

会议论文集：THE SEVENTH WUHAN INTERNATIONAL E-BUSINESS CONFERENCE(第七届武汉电子商务国际会议)论文集

会议日期：2008年1月1日

会议地点：武汉

主办单位：中国地质大学

语种：英文

中文关键词：NEURAL NETWORKS;LOGISTIC REGRESSION;CREDIT CARD;CREDIT SCORING

摘要：IT IS URGENT FOR BANKS TO SOLVE PROBLEMS IN HOW TO IDENTIFY AND JUDGE APPLICANTS OF CREDIT CARD, AND IMPROVE CAPABILITY OF PREVENTING AND RESISTING RISK OF CREDIT CARD. TO PROVIDE EFFECTIVE DECISIVE SUPPORT TO POLICYMAKER, TO JUDGE THE CREDIT CARD EFFICIENTLY AND INTELLECTUALLY WILL INCREASE ACCURACY AND EFFICIENCY OF CREDIT EVALUATION IN PROCESS OF CREDIT CARD APPROVAL. THIS TEXT SUGGESTS TO EVALUATE CREDIT CARD BY USING HYBRID MODEL OF NEURAL NETWORKS AND LOGISTIC REGRESSION WITH THEIR CHARACTERS OF HIGH ACCURACY OF NEURAL NETWORKS AND HIGH STABILITY OF LOGISTIC REGRESSION. REAL CASE SHOWS THAT THE ACCURACY OF HYBRID MODEL IS HIGHER THAN USING NEURAL NETWORKS AND LOGISTIC REGRESSION SEPARATELY. THEREFORE, THIS METHOD IS FEASIBLE AND EFFECTIVE.