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In recent years, one of the major challenges for financial institutions isthe retention of their customers using new methodologies of reliable andprofitable segmentation. In the field of banking, the approach of offering allof the services to all the existing customers at the same time does not alwayswork. However, being aware of what to sell, when to sell and whom to sell makesa huge difference in the conversion rate of the customers responding to newservices and buying new products. In this paper, we used RFM technique andvarious clustering algorithms applied to the real customer data of one of thelargest private banks of Azerbaijan.

Segmenting Bank Customers via RFM Model and Unsupervised Machine Learning