During recent years, increased competition among banks has caused many developments in banking experiences and technology, while leading to even more churning customers due to their desire of having the best services. Therefore, it is an extremely significant issue for the banks to identify churning customers and attract them to the banking system again. In order to tackle this issue, this paper proposes a novel personalized collaborating filtering recommendation approach joint with the user clustering technology. In the proposed approach, first a hybrid algorithm based on Particle Swarm Optimization (PSO) and K-mean cluster the loyal customers. The clusters of loyal customers are used to identify the features of the churning customers. Finally, the list of appropriate banking services are recommended for the churning customers based on a collaborative filtering recommendation system. The recommendation system uses the information of loyal customers to offer appropriate services for the churning customers. We applied successfully the proposed intelligent approach to return the churning customers of an Iranian bank.
Shafiei Gol, Elham, Abbas Ahmadi, and Azadeh Mohebi. 2016. Intelligent approach for attracting churning customers in banking industry based on collaborative filtering. Journal of Industrial and Systems Engineering ۹ (۴): ۹-۲۵.