Finding the Hidden Pattern of Credit Card Holder's Churn: A Case of China

  • Authors:
  • Guangli Nie;Guoxun Wang;Peng Zhang;Yingjie Tian;Yong Shi

  • Affiliations:
  • Research Center on Fictitious Economy and Data Science, CAS, Beijing, China 100190;Research Center on Fictitious Economy and Data Science, CAS, Beijing, China 100190 and School of Computer science and information engineering, Henan University, Kaifeng, China 475001;Research Center on Fictitious Economy and Data Science, CAS, Beijing, China 100190;Research Center on Fictitious Economy and Data Science, CAS, Beijing, China 100190;Research Center on Fictitious Economy and Data Science, CAS, Beijing, China 100190 and College of Information Science and Technology, University of Nebraska at Omaha, Omaha, USA NE 68182

  • Venue:
  • ICCS 2009 Proceedings of the 9th International Conference on Computational Science
  • Year:
  • 2009

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Abstract

In this paper, we propose a framework of the whole process of churn prediction of credit card holder. In order to make the knowledge extracted from data mining more executable, we take the execution of the model into account during the whole process from variable designing to model understanding. Using the Logistic regression, we build a model based on the data of more than 5000 credit card holders. The tests of model perform very well.