Predictive Insights Into Digital-Only Banking Adoption in Malaysia using Artificial Neural Networks


Mashaal A. M. Saif and Nazimah Hussin, Universiti Teknologi Malaysia, Malaysia


This study employs an Artificial Neural Network (ANN) to predict the importance of various factors—convenience, economic efficiency, functional risk, security risk, critical mass, number of services, trust, environmental concern, and perceived value-in collectively determining the intention to adopt digital-only banks. The analysis involves 403 respondents in Malaysia, utilising both exploratory factor analysis and the ANN method. The results from the ANN highlight "environmental concern" as the most influential factor shaping individuals' intention to adopt digital-only banks. Additionally, "trust," "perceived value," and "convenience" emerged as crucial factors in predicting adoption intention. These findings not only provide valuable insights for fintech companies and banks aiming to attract new customers or enter new markets but also contribute to expanding knowledge in the field, particularly in the realm of non-linear methods such as ANN. This study enhances the understanding of the evolving landscape in digital-only banking.


Artificial Neural Network (ANN); Adoption Intention; Digital-only banks; Perceived Value; Environmental Concern.

Full Text  Volume 14, Number 6