Analysis for Clients Churn of Credit Cards in Model Construction in Banking Industry
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DOI

10.26689/pbes.v3i2.1165

Submitted : 2020-03-18
Accepted : 2020-04-02
Published : 2020-04-17

Abstract

Data mining technology has been more and more important in the economics and financial market. Helping the banks to predict a customers’ behavior, which is that whether the existing customers will continue use their credit cards or not, we utilize the data mining technology to construct a convenient and effective model, Decision Tree. By using our Decision Tree model, which can classify the customers according to different features step by step, the banks are able to predict the customers’ behavior well. The main steps of our experiment includes collecting statistics from the bank, utilizing Min-Max normalization to preprocess the data set, employing the training data set to construct our model, examining the model by testing data set, and analyzing the results.