Artificial immune algorithm-based credit evaluation for mobile telephone customers

Abstract

The arrearage problem is a critical concern for China’s mobile communication services industry. Analysis of customer credit evaluation provides this study with a potential viable solution to the arrearage problem in China. By employing an artificial immune algorithm (AIA), a measure of customer credit based on customer attributes is proposed. This method was applied to one China mobile communication services company with approximately 400 000 customers yielding satisfying results. Utilizing traditional predictive accuracy and alternative metrics, performance comparisons of the proposed AIA were made using the feed-forward back propagation artificial neural network and the logistic regression model. A decision tree analysis of anticipated benefits was performed and indicates workability of the proposed method based on customer credit evaluation.

Keywords:

• mobile communication
• customer credit evaluation
• artificial immune algorithm
• analysis of expected benefit

Acknowledgements

The research was supported by the Scientific Research Fund of Hunan Provincial Science and Technology Department (2013GK3090) and the grants from the Guangdong Mobile Communication Corporation Key Item, China (GMCC 19901-02). The authors would like to extend their appreciation to the editor(s) and anonymous reviewers for their valuable suggestions, and Professor David J. Hand and Dr C. Anagnostopoulos at Imperial College London for their kind help in providing a program for statistical computing.