{"title":"Research on Credit Rating Method Based on BP NN","authors":"G. Jiang","doi":"10.1109/ICSSSM.2007.4280185","DOIUrl":null,"url":null,"abstract":"In the paper, a new subclass of credit rating model based on advanced BP artificial neural network (BP ANN) is introduced. Firstly, follow 6C principles (character, capacity, capital, collateral, condition, and continuity), the credit evaluation indicators are designed, and then credit rating model based on advanced BP artificial neural network (BP ANN) algorithm is proposed after selection of input dimensional of BP ANN. Finally the system architecture of credit rating decision supporting system is presented, and the two main system components have taken to demonstrated how to set up such kind of rating decision supporting system based on advanced BP ANN.","PeriodicalId":153603,"journal":{"name":"2007 International Conference on Service Systems and Service Management","volume":"18 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Service Systems and Service Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSSM.2007.4280185","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 8
Abstract
In the paper, a new subclass of credit rating model based on advanced BP artificial neural network (BP ANN) is introduced. Firstly, follow 6C principles (character, capacity, capital, collateral, condition, and continuity), the credit evaluation indicators are designed, and then credit rating model based on advanced BP artificial neural network (BP ANN) algorithm is proposed after selection of input dimensional of BP ANN. Finally the system architecture of credit rating decision supporting system is presented, and the two main system components have taken to demonstrated how to set up such kind of rating decision supporting system based on advanced BP ANN.