The Role of Behavioural Intention to Use AI, Self Efficacy, and Risk Perception to Susceptibility of Social Engineering Attack

The global growth of digital finance has made banking more accessible but also exposed users to new dangers, especially social engineering attacks that target human behavior rather than technical weaknesses. This study explores how people’s confidence, awareness, and understanding of cyber risks—specifically self-efficacy, perceived severity, knowledge of threats, and risk perception—affect their vulnerability in AI-powered mobile banking. Data were gathered from 523 Indonesian mobile banking users through a structured survey in April 2025 using purposive sampling. Most respondents were women (62.9%) and active digital users who frequently conducted online transactions. Using the Partial Least Squares Structural Equation Modeling (PLS-SEM) method, the study examined seven key factors: attitude toward AI, self-efficacy, perceived severity, risk perception, knowledge of threats, susceptibility to scams, and behavioral intention to use AI. Results show strong links (p < 0.05): attitude toward AI drives intention, risk perception increases vulnerability, and knowledge reduces it. These findings reveal that human psychology—not technology alone—defines safety in digital finance.