Science, Technology, Engineering and Mathematics.
Open Access

AN ANALYSIS OF EARLY WARNING FOR CREDIT CARD CUSTOMER CHURN

Download as PDF

Volume 2, Issue 4, Pp 18-21, 2024

DOI: 10.61784/tsshr3005

Author(s)

ChangFu Yang

Affiliation(s)

School of Mathematics and Statistics, Guangxi Normal University, Guilin 541006, Guangxi, China.

Corresponding Author

ChangFu Yang

ABSTRACT

This paper aims to explore the development of credit cards in the Chinese market and the challenges posed by the rise of internet finance, while also analyzing customer churn issues and their management strategies. Since the introduction of credit cards to China in 1986, despite the initial lack of supporting facilities such as POS machines, credit cards have served as a monetary credit voucher, facilitating the small loan business of commercial banks. Over time, the credit card market has experienced rapid growth, becoming a vital channel for personal consumer loans. However, the emergence of internet finance has had a profound impact on the traditional banking business model, with customer churn becoming an increasingly prominent issue.

KEYWORDS

Credit cards; Internet finance; Customer churn; Data mining; Risk management

CITE THIS PAPER

ChangFu Yang. An analysis of early warning for credit card customer churn. Trends in Social Sciences and Humanities Research. 2024, 2(4): 18-21. DOI: 10.61784/tsshr3005.

REFERENCES

[1] Xu, Y., Rao, C., Xiao, X., Hu, F. Novel Early-Warning Model for Customer Churn of Credit Card Based on GSAIBAS-CatBoost. CMES-Computer Modeling in Engineering & Sciences, 2023, 137(3).

[2] Nie, G., Rowe, W.G., Zhang, L., Tian, Y., Shi, Y. Credit card churn forecasting by logistic regression and decision tree. Expert Syst. Appl., 2011, 38: 15273-15285.

[3] Lin, C. S., Tzeng, G. H., Chin, Y. C. Combined rough set theory and flow network graph to predict customer churn in credit card accounts. Expert Systems with Applications, 2011, 38(1): 8-15.

[4] De Caigny, A., Coussement, K., De Bock, K. W. A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees. European Journal of Operational Research, 2018, 269(2): 760-772.

[5] De Bock, K. W., & Van den Poel, D. An empirical evaluation of rotation-based ensemble classifiers for customer churn prediction. Expert Systems with Applications, 2011, 38(10): 12293-12301.

All published work is licensed under a Creative Commons Attribution 4.0 International License. sitemap
Copyright © 2017 - 2024 Science, Technology, Engineering and Mathematics.   All Rights Reserved.