Evaluating User Satisfaction in AI-Powered Digital Banking: An Expectation Confirmation Model Approach

Abstract

This study assesses user satisfaction with AI-Banking services by integrating artificial intelligence features into an expectation confirmation model. Using a quantitative approach, data was obtained from 124 bank customer respondents in Indonesia using a questionnaire, then analyzed using PLS-SEM approach. The analysis results indicate that expectation confirmation has a significant influence on performance perceptions. Furthermore, the variables of trendiness, visual attractiveness, problem-solving ability, and customization positively influence user satisfaction. These findings suggest that banking service providers should prioritize these aspects. Improvements in these factors have the potential to strengthen userr satisfaction in AI-based digital banking services.