Commercial Banks Exceptional Client Distinguish Based on Data Mining

Abstract

The commercial banks need identify exceptional client in their large number of customers to prevent abnormal customer’s risk. In this paper, four types of abnormal data detection method is introduced, present a new method - the k-medoids clustering algorithm combining genetic algorithm to detect the outlier. Finally, apply the algorithm to analysis credit data sets, detect outlier and identify abnormal customer