Press to pay: The power of biometrics in financial transactions investigated by PLS-SEM, fsQCA, and NCA

Abstract

The financial sector is undergoing rapid transformation driven by technological innovation and the digitization of financial transactions. Biometric Payment Cards (BPCs) represent a disruptive solution that combines traditional payment methods with biometric authentication—primarily through fingerprints—to improve security and the user experience. This study explores the adoption of BPCs using an integrated theoretical framework that combines the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2), Perceived Risk Theory (PRT), and Trust Theory (TT). Data were collected from 342 users a tripartite approach using Partial Least Squares Structural Equation Modelling (PLS-SEM), fuzzy-set Qualitative Comparative Analysis (fsQCA), and Necessary Condition Analysis (NCA). The results reveal that effort expectation is the strongest positive predictor of adoption, followed by trust and hedonic motivation, while perceived risk acts as a significant inhibitor. The fsQCA analysis identifies multiple sufficient configurations—such as high trust combined with low perceived risk—that lead to high usage intention, and the NCA confirms that trust is a necessary condition. These findings contribute to both theory and practice by integrating linear and configurational approaches to technology adoption. In practical terms, the study highlights the importance of simplifying user interfaces, improving biometric reliability, and fostering user trust to promote widespread adoption of biometric payment technologies.