An approach for personalization of banking services in multi-channel environment using memory-based collaborative filtering

Number of services that banks offer customers, has been increased significantly in recent years. There is a variety of services available through the different channels like internet bank, mobile bank, telephone bank, ATM and so forth. The need to personalize these services for customers is felt more than before since people are busier than ever and have a limited time to do their daily tasks. In addition, in some banking channels like telephone bank, giving a service in a high speed manner is very important since the user has to listen to a variety of menu items and select one he want. Having a personal bank for each customer is an interesting issue for customers that can save their time doing banking tasks and it will improve customer satisfaction. In this paper, we present an architecture for implementation of this service personalization in a multi-channel environment with the help of a powerful approach called memory-based collaborative filtering. It has the ability to process the information coming from different banking channels according to the recent services that a customer has previously used and services that other customers have used most frequently.