Applied Research on Data Mining in Bank Customer Churn

Abstract:

With the increasing competition in the banking sector, banks make every effort to compete for valuable customer resources in order to get more benefits, but how to make customers to retain, or reduce the loss of customers is become the key issues for the banks. In this paper, using theoretical research and practical method to discusses how to use data mining techniques to predict the bank's customer churn. Identifying risky customers and taking certain measures before customers really lost .The research will provide a reliable basis for decision-making of banks.

• Periodical: Applied Mechanics and Materials (Volumes 687-691)
• Pages: 5023-5027
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.687-691.5023
• Online since: November 2014
• Authors: Shou Xiang Zhao, Qing Yue Tai
• Keywords: Customer Churn, Data Mining (DM), Neural Network

References

[1] Lin rui, Bank Customer Churn Analysis Model Based on Artificial Neural Networks: Computer Knowledge and Technology: Vol. 8(2012),P. 665－666.

[2] Zhao yan, Zhao hui, Data Mining Theory and Technology: Fujian Computer, Vol. 2(2006),P. 22-24.

[3] Sun bo, The Analysis Framework of Bank Customers Based on Data Mining: Mechanical Management and Development, Vol. 2 (2006), P. 63-65.

[4] He xingshi, Liu yu, BP Neural Network Algorithm Used in Digital Recognition : Journal of Northwest Institute of Textile, Vol. 4(2000),P. 356-362.

[5] Han liqun, Artificial Neural Network Theory, Design and Application: Science Press, Vol. 9 (2011), P. 46-63.

[6] Liu lan, Risk Prediction of Credit Card Consumer Behavior Based on BP Neural Network Mixed Algorithm: Technology Management Research, Vol. 17 (2011), P. 207-210.

[7] Zeng zhezhao, Application of Neural Network Algorithm in Nonlinear Systems: Natural Science of Hunan Normal University, Vol. 2 (2007), P. 57-60.

[8] Liu chunlin, Analysis and Research of Bank Customers Behavior Based on Data Mining: Electronic World Series, Vol. 6 (2013), P. 78-79.

[9] Yu caixian, Mathematical Modeling and Analysis of Bank Customer Churn Prediction: Changchun University of Technology, Vol. 1 (2013), P. 6-8.

[10] Petar Miladin, Seizure of Credit Claims on Bank Accounts: Collected Papers of Zagreb Law Faculty, Vol. 5 (2006), P. 1568-1606.

[11] LisbetBerg, Loyalty, Naivety and Powerlessness among Norwegian Bank Customers: International Journal of Consumer Studies, Vol. 3 (2008), P. 222-231.

DOI: 10.1111/j.1470-6431.2008.00668.x

[12] Zhang defeng, The Application and Design of MATLAB Neural Network: Machinery Industry Press, Vol. 3 (2011), P. 45-80.

[13] Jiang yu, The Establish of Research and Prediction Model of Commercial Bank: Market Modernization , Vol. 3(2007),P. 219-220.