Understanding customer behaviours toward the use of electronic banking given customer characteristics and financial portfolios

The evolution of electronic banking demonstrates the need for research regarding demographics and banking preferences. In this study, financial data was collected from three Kuwaiti banks. The data included customer characteristics, product portfolios, and usage information in all electronic banking channels. This data was used to predict the use of electronic channels, treated as dependent variables in our study, based on individual customer’s information, that is treated as independent variables. Machine learning (ML) techniques, specifically multinomial logistic regression, were used to handle the data bearing in mind that these techniques would bring the most benefit to financial analysts and bankers. The results showed that one can determine the preferred electronic banking channel for each customer by knowing some of their characteristics and financial portfolio.