基于电信大数据的信用卡精准营销算法研究及应用

Research and Application of Precision Marketing Algorithms for Credit Card Based on Telecom Big Data

信用卡业务是银行零售业务利润贡献的重要组成部分,基于运营商大数据可以对用户进行全面立体的刻画,进而分析信用卡潜在用户的特征。提出了基于人工蜂群算法的K-means聚类算法,可以提升K-means算法的簇头初始化水平,提升K-means算法性能。同时,将该算法运用在信用卡精准营销场景中,可以获取影响客户办理信用卡的关键要素,从而更加有效地发掘潜在用户,为垂直行业发展带来新思路和新动能。

Credit card business is an important part of the profit contribution of bank retail business.Users can be depicted in a compre?hensive and three-dimensional way based on the telecom big data,and then the characteristics of potential users can be ana?lyzed.K-means clustering algorithm based on artificial bee colony algorithm is proposed,which modifies the level of clustering head initialization and improves the performance of K-means algorithm.By applying the algorithm in the precision marketing scenario of credit card,the key factors affecting customers can be obtained,which will contribute to exploring potential cus?tomers and bringing new ideas and driving force for the development of vertical industry.