Exploring College Students’ Adoption Behavior of Intelligent Wealth Management Applications: An Extended TAM Approach with Trust as a Mediator

As artificial intelligence-based Financial Technology (Fintech) increases at an astonishing speed, users of Intelligent Wealth Management (IWM) applications are enticing the "digital natives" i.e., university students, who are also potential future customers and early adopters of new technology. This paper combines the three exogenous variables—Perceived Risk (PR), Financial Literacy (FL), and AI Transparency (AIT)—implied by the original TAM and introduces Trust (TR) as the inner mostmediating variable connecting exogenous variables with Behavioral Intention (BI), thus developing an advanced SEM with second-order structure. Contrary to the typical TAM-based studies, this model also incorporates the interaction terms (AIT × FL) to investigate the moderation effects, and PLS-SEM with Multi-Group Analysis (MGA) is used to validate the questionnaires data from multi-discipline university students so that the effectiveness in the lasted hypothesis across gender, educational background, and investment experience is controlled. The data supports the argument that Trust significantly mediates the relationship between AI Transparency and Behavioral Intention, and Perceived Risk and Behavioral Intention.