Author: Ayushi

ABSTRACT

This study investigates how trust and perceived risk influence user satisfaction and continuance intention in AI-enabled FinTech platforms. Drawing on the Technology Acceptance Model (TAM), Unified Theory of Acceptance and Use of Technology (UTAUT), and Trust-Commitment Theory, we develop and test a structural model using primary survey data from 412 users of digital banking and payment applications. Structural equation modeling (SEM) reveals that trust positively influences user satisfaction (β = 0.47, p < 0.001) and continuance intention (β = 0.38, p < 0.001), while perceived risk negatively affects both satisfaction (β = −0.29, p < 0.01) and continuance intention (β = −0.24, p < 0.01). Trust also partially mediates the relationship between perceived risk and satisfaction. Perceived ease of use and AI service efficiency emerge as significant antecedents of satisfaction. The findings carry practical implications for FinTech platform design, regulatory policy, and strategies to enhance user engagement in AI-driven financial services