Behavioral Intention and User Behavior Toward AI-Based Features in Mobile Banking: Evidence from Indonesia

Abstrak

The rapid development of technology, particularly Artificial Intelligence (AI) forces industries to adapt and utilize it as it makes operations efficient. In the Indonesian banking industry, AI has increasingly been implemented in several features such as AI Chatbots for Customer Service, AI-Based Personal Financial Assistant, AI Credit Scoring and Loan Approval, AI Security Systems, and Robo Advisors for Investment to improve user experience and company performance. This study aims to examine customer behavior towards AI based features in mobile banking applications by using a UTAUT (Unified Theory of Acceptance and Use of Technology) model with data collected from 305 respondents, gathered using a quantitative method-based questionnaire that was distributed through social media platforms. The findings indicate that Performance Expectancy, Social Influence, and Trust have a positive and significant influence on Behavioral Intention, while Financial Risk has a negative and significant influence on Behavioral Intention, Meanwhile, Effort Expectancy, Financial Knowledge, and Financial Efficacy do not significantly influence Behavioral Intention. Furthermore, User Behavior is influenced by Behavioral Intention and Facilitating Condition indicating that the user’s adoption of AI-based features in mobile banking is driven more by Performance Expectancy, Social Influence, Trust, Financial Risk, Behavioral Intention, and Facilitating Condition than by Effort Expectancy, Financial Knowledge, and Financial Efficacy. This study primarily consists of digitally literate respondents recruited through various social media platforms, therefore these findings should be interpreted within the context of the sample.

Identifier

• OpenAlex: https://openalex.org/W7167203538
• DOI: https://doi.org/10.54392/ajir26222