Exploring biometric identification in FinTech applications based on the modified TAM

Abstract In recent years, biometric technologies have been widely embedded in mobile devices; these were originally employed to enhance the security of devices. With rise financial technology (FinTech), which uses devices and applications as promotional platforms, biometrics has important role strengthening identification such for security. However, users still privacy trust concerns about biometrics. Previous studies demonstrated that acceptance model (TAM) can rigorously explain predict user new technologies. This study therefore modifies TAM a basic research architecture. Based on literature review, we add two variables, namely, “perceived privacy” trust,” extend traditional examine FinTech applications. First, apply analytic hierarchy process (AHP) evaluate defined objects relevant criteria framework. Second, use AHP results scenario analysis explore methods correspond criteria. The indicate face voice recognition are most preferred addition, there significant changes perceived dominant scenarios.