基于模糊理论的关联规则及其在财险交叉销售中的应用研究  

Study of Fuzzy Association Rules and Cross Selling toward Property Insurance Customers Based on FARMA

作　　者：闫春[1] 孙海棠[1] 李亚琪[1] 

机构地区：[1]山东科技大学数学与系统科学学院,山东青岛266590

出　　处：《金融理论与实践》2017年第5期100-105,共6页Financial Theory and Practice

基　　金：国家自然科学基金项目(61502280;61472228);青岛市应用基础研究计划项目(青年专项)(14-2-4-55-jch);山东省自然科学基金面上项目(ZR2014FM009);山东科技大学研究生教育创新计划项目(KDYC14016)

摘　　要：大量的客户信息数据给客户管理带来一定的困难,有效地借助数据挖掘工具,深入分析现有客户的个性化需求,维持重要客户并开展更广泛的交叉销售业务,对我国财险公司的发展具有重大意义。结合模糊集理论,探讨模糊关联规则在财险客户交叉销售中的应用,将模糊C均值算法引入到关联规则挖掘中,提出改进的Apriori算法—FARMA算法。借助SPSS、Clementine、R语言数据挖掘工具对算例数据进行挖掘,建立交叉销售模型,并进行算例分析,验证新算法的有效性。After many years’development,property insurance companies in China have accumulated certain customer resources.At the meanwhile,these companies will face greater competitive challenges with the acceleration of the marketization process.In view of this,it is very important for these companies to deeply analyze the existing customers’individual demands to develop a broader cross selling business based on effective means of data mining tools,which is of great significance to the development of them.In our study,FCM(fuzzy c-means algorithm)is introduced to association rules mining.And we present the improved Apriori algorithm-FARMA based on fuzzy set theories.With the help of data mining tools SPSS,Clementine16.0,R Language,we dig out12fuzzy association rules about customers’data given in Clementine16.0.Further we establish cross selling model based on those rules.

关 键 词：客户维持 交叉销售 数据挖掘 FARMA算法 

分 类 号：F840.65[经济管理—保险]