Article ID: | iaor201526799 |
Volume: | 66 |
Issue: | 9 |
Start Page Number: | 1533 |
End Page Number: | 1541 |
Publication Date: | Sep 2015 |
Journal: | Journal of the Operational Research Society |
Authors: | Zong-Chang Yang, Hong Kuang, Ji-sheng Xu, Hong Sun |
Keywords: | finance & banking, forecasting: applications, statistics: regression, neural networks |
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 400000 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.