基于RFM分析的银行信用卡客户的行为评分模型应用自组织映射神经网络SOM和Apriori方法.pdf

基于RFM分析的银行信用卡客户的行为评分模型——应用自组织映射神经网络SOM和Apfiod方法梁昌勇赵艳霞合肥工业大学管理学院,合肥230009 摘要t 本文应用数据挖掘工具分析银行的现有的信用卡客户的行为特性和信用,探讨了信用卡客户的行为评分模型。应用自组织映射神经网络分析其还款行为和近度R、频度F、值度M的行为特性, 应用这四个指标进行评分来识别不同的客户群。,形成客户轮廓。本文通过建立的客户行为评分模型有助于识别客户的特征,促进营销策略的实施. 关键词:行为评分模型;客户细分:神经网络:关联规则 The Behavioral Scoring Model ofCredit Card Customers in aBank Based onRFM ?一theApplication ofSOM andApriori Liang Changyong Zhao Yanxia School ofManagement,Hefei UniversityofTechnology,Hefei 230009 Abstract:This studyproposes anintegrated datamining analysis thebehavior oftheexisting credit card customers in abank andpresents abehavioral scoring anizing map work isused tO identifygroups ofcustomers based 011repayment behavior andrecency,frequency,ary behavioral scoring alsoclassifiedbank customers into threemajor profitablegroups ofcustomers and 作者简介:粱昌勇(1965一),男,安徽合肥人,合肥工业大学管理学院副院长,博士生导师,研究方向:信息管理、智能决策。赵艳霞(1978.),女,合肥工业大学硕士生,研究方向:信息资源管理、客户关系管理、数据挖掘,Emaihzhao ******@.∞ 347 identifiedthe most important resultinggroups ofcustomers were thenprofiledbycustomcr,s featureattributesdetermined using an Apriori association study demonst他teS that identifying customersby abehavioral scoring model ishelpful characteristicsofcustomer and facilitatcs marketing strategydevelopment. Keywords: Behavioral ScoringModel;Custom