{"title":"分类模型在信用卡欺诈检测中的应用","authors":"Aihua Shen, Rencheng Tong, Yaochen Deng","doi":"10.1109/ICSSSM.2007.4280163","DOIUrl":null,"url":null,"abstract":"Along with the great increase in credit card transactions, credit card fraud has become increasingly rampant in recent years. This study investigates the efficacy of applying classification models to credit card fraud detection problems. Three different classification methods, i.e. decision tree, neural networks and logistic regression are tested for their applicability in fraud detections. This paper provides a useful framework to choose the best model to recognize the credit card fraud risk.","PeriodicalId":153603,"journal":{"name":"2007 International Conference on Service Systems and Service Management","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-06-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"216","resultStr":"{\"title\":\"Application of Classification Models on Credit Card Fraud Detection\",\"authors\":\"Aihua Shen, Rencheng Tong, Yaochen Deng\",\"doi\":\"10.1109/ICSSSM.2007.4280163\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Along with the great increase in credit card transactions, credit card fraud has become increasingly rampant in recent years. This study investigates the efficacy of applying classification models to credit card fraud detection problems. Three different classification methods, i.e. decision tree, neural networks and logistic regression are tested for their applicability in fraud detections. This paper provides a useful framework to choose the best model to recognize the credit card fraud risk.\",\"PeriodicalId\":153603,\"journal\":{\"name\":\"2007 International Conference on Service Systems and Service Management\",\"volume\":\"2 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-06-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"216\",\"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.2007.4280163\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2007 International Conference on Service Systems and Service Management","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICSSSM.2007.4280163","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Application of Classification Models on Credit Card Fraud Detection
Along with the great increase in credit card transactions, credit card fraud has become increasingly rampant in recent years. This study investigates the efficacy of applying classification models to credit card fraud detection problems. Three different classification methods, i.e. decision tree, neural networks and logistic regression are tested for their applicability in fraud detections. This paper provides a useful framework to choose the best model to recognize the credit card fraud risk.