Using client’s characteristics and their financial products to predict their usage of banking electronic channels

Technology innovation and its impact on the progress of electronic banking establish the requirement for this research regarding customer demographics, their financial portfolio and banking preferences. In this research, banking financial data were collected from three Kuwaiti banks. The data included usage information in all electronic banking channels for each customer, their characteristics and financial portfolio. The aim of this study is to predict the customer use of electronic channels, treated as dependent variables, considering individual customer information, which is treated as independent variables. To bring the most benefit to bankers and financial analysts, machine learning techniques (ML), specifically multinomial logistic regression, were used to deal with the data from cleaning to analysing. The results disclosed that banks can determine the preferred electronic banking channel for each of their customers by knowing some information about their characteristics and financial product portfolio.