Applying TwoStep Cluster Analysis for Identifying Bank Customers ’ Profile
Applying TwoStep Cluster Analysis for Identifying Bank Customers ’ Profile
复制标题
应用两步聚类分析来识别银行客户档案
DOI：
--
复制
发表时间：
2010
期刊：
影响因子：
--
通讯作者：
D. Schiopu
中科院分区：
文献类型：
--
作者：
D. Schiopu
本文利用SPSS两步聚类方法对某银行的客户信息进行分析，将其分为三类。该方法非常适合我们的案例研究，因为与其他经典聚类方法相比，TwoStep使用混合数据（连续变量和分类变量），并且还可以找到最佳聚类数。TwoStep创建三个客户的配置文件。最大的群体是有技能的客户，他们的贷款目的是教育或商业。第二类是拥有真实的财产的人，但大多数是失业者，他们要求获得再培训或购买家庭用品的信贷。第三类人聚集了一些属性未知的人，他们要求一辆车或一台电视机，然后要求接受教育。这项研究的好处是通过更有效地管理客户来加强公司的利润。
In this paper we analyze information about the customers of a bank, dividing them into three clusters, using SPSS TwoStep Cluster method. This method is perfect for our case study, because, compared to other classical clustering methods, TwoStep uses mixture data (both continuous and categorical variables) and it also finds the optimal number of clusters. TwoStep creates three customers’ profiles. The largest group contains skilled customers, whose purpose of the loan is education or business. The second group consists in persons with real estate, but mostly unemployed, which asked for a credit for retraining or for household goods. The third profile gathers people with unknown properties, who make a request for a car or a television and then for education. The benefit of the study is reinforcing the company’s profits by managing its clients more effectively.