Facial Recognition Resistance in Banking: Analyzing Risk Through Technology Readiness, Regulation and Trust - Rika Ayu Haryanti; Dewi Hanggraeni (Green Publisher Indonesia, 2025)
The rapid digitalization of Indonesia's banking sector has driven widespread adoption of biometric authentication, particularly facial recognition (FR) technology, to enhance security and user experience. However, user resistance remains a barrier, especially in light of concerns about privacy, regulatory trust, and technological readiness. This study investigates the influence of individual technology readiness, perceived risk, perceived trust, and regulation and compliance on resistance to FR technology in mobile banking. Using a quantitative survey method and Partial Least Squares Structural Equation Modeling (PLS-SEM), data were collected from 200 Indonesian mobile banking users familiar with FR technology. The findings reveal that digital literacy and personal innovativeness significantly enhance technology readiness, which, in turn, increases users’ sensitivity to perceived risk. Perceived risk was found to be the strongest predictor of resistance, while trust reduced perceived risk but did not directly reduce resistance. Regulatory compliance directly enhanced trust and reduced resistance but did not moderate the influence of risk or trust. Mediation analysis showed that perceived risk fully mediates the relationship between technology readiness and resistance. These findings highlight the paradox that tech-ready users may still resist FR due to heightened awareness of data security concerns. The study suggests that reducing perceived risk and reinforcing data transparency through effective regulatory frameworks are critical to fostering public trust and adoption of FR technologies in digital banking.