Dynamic segmentation and ranking approach of customers and identifying their behavioral mobility using data mining techniques in Kargaran Welfare Bank

Nowadays, identifying, determining the value and segmentation of customers is essential for a bank. Dynamic classification of workers' welfare bank customers and identification of their behavioral mobility between different departments in a specific period of time using data techniques Kaveh. In this regard, transaction data of customers of this bank was considered as a statistical community. In six time periods and on a monthly basis with the aim of segmentation and dynamic ranking of customers by K MEAN algorithms and self-organized neural networks SOM was performed. Based on the results of this study, customers were divided into three main sections and their dynamics were studied. Marketing is provided.