A DEALG methodology for prediction of effective customers of internet financial loan products

Abstract

It is becoming more crucial nowadays for researchers to objectively utilize reasonable and effective methods to choose a key customer index and analyze a wealth of data, with the aim of setting up precision marketing of Internet financial products. This paper thus considers pre-process data via DEA and adds the DEA efficiency value into the logistic regression model, which can improve accuracy of the basic logistic regression model. This novel data analytics approach, termed DEALG, significantly enhances the customer response rate of Internet loan products according to its results. The goal is to effectively identify those customers who are more likely to show their interests on the loan products in order to achieve the goal of precision marketing, thus reducing supply-side costs. The results of the DEALG method are very promising, and in the real world it can be applied as an actual marketing method like sending text messages to potential clients. Finally, the results show that this method can generate high profits for the Internet financial industry.

Keywords:

• Data envelopment analysis (DEA)
• logistic regression (LG)
• internet loan products
• precision marketing

Acknowledgements

The authors thank the two anonymous reviewers for their insightful comments and suggestions in an earlier version of the paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This research is supported by National Natural Science Funds of China (No. 71771126, 71801133, 71871105, 71701059), Jiangsu Social Science Fund (17GLB013), Project of Jiangsu Qing Lan and Jiangsu Social Science Excellent Young Scholars. This research was also supported by The Postgraduate Research & Practice Innovation Program of Jiangsu Province (KYCX18_0945) and The Excellent Innovation Teams of Philosophy and Social Science in Jiangsu Province (2017ZSTD022), as well as The Major Research Plan of National Social Science Foundation (18ZDA052).