A Dynamic Recurrent Neural Networks-Based Recommendation System for Banking Customers
Hasan Avcı C. Okan Sakar · 2021
In recent years, machine learning approaches are replacing traditional methods in many industries. In parallel with these developments, marketing operations in banking started to be supported with machine learning based applications. In this study, a highly applicable product recommendation approach for banking customers was implemented using deep learning techniques. For this purpose, the dynamic recurrent neural network (DREAM) architecture, which was previously applied to e-commerce data, has been applied to banking customer data for recommendation system design. Comparative experiments with long short term memory and multilayer perceptron-based solutions have shown that the DREAM based recommendation approach has significant potential to be used in product proposal in the banking sector.