Decision Intelligence to Enhance Bank Profitability through Customer Promotion Path Design

Studying the behavior of a bank's customers over time to determine and monitor their position in a customer segmentation system (CSS) could be the basis for producing and proposing some paths to promote the customers to a preferred level in the CSS. It is mutually beneficial for both the bank and the customers. On the one hand, the bank increases its revenue by growing sales; on the other hand, the customers benefit from incentive allocation. In this research, with the help of the new concept of Decision Intelligence (DI) along with the machine learning modeling approach, customized paths were extracted that led to improving the level of the customers in the bank’s CSS. These paths are designed according to the specific circumstances of each customer and the scope of its business, which ensures its feasibility. The proposed method was implemented for ۴۲۲,۲۶۴ customers in a private bank, and the results show that this method has been successful in achieving successfully achieved the predefined goals.

Keywords:

Customer segmentation , Decision Intelligence , Machine learning , Customized Banking