User Acceptance of Biometric Payment Technologies
Summary
User acceptance of biometric payment technologies hinges on how individuals perceive the balance of convenience, security and privacy when using unique physiological or behavioural traits to authenticate transactions. As financial services integrate fingerprint, facial, iris and palm‐vein recognition into ATMs, point‐of‐sale terminals and mobile applications, research has explored factors that drive or hinder uptake. Perceived usefulness and ease of use remain central, while trust in the technology and its providers, concerns over data privacy, and perceived risks—financial, physical or reputational—shape users’ attitudes. Demographic attributes such as age, education and technology familiarity, along with cultural and contextual influences, further moderate acceptance. The COVID-19 pandemic has accelerated interest in contactless options, highlighting hygiene and convenience benefits but also magnifying anxieties around biometric data storage and misuse. Through theoretical lenses such as the Technology Acceptance Model and extensions incorporating privacy and trust constructs, studies reveal how positive drivers (security, speed, hygiene) and inhibitors (privacy invasion, error rates) combine to influence adoption and continued use worldwide.
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User Acceptance of Biometric Payment Technologies publication trend
The graph below shows the total number of articles in user acceptance of biometric payment technologies across all publications each year (not limited to Nature Index journals).
Technical terms
Biometric authentication: The verification of identity using unique biological or behavioural characteristics.
Perceived value: The user’s overall assessment of the benefit derived from a technology compared with its cost or risk.
Continuance intention: The user’s intention to continue using a technology after initial adoption.
Net valence framework: An analytical approach weighing positive and negative factors to predict technology acceptance.
Technology Acceptance Model: A theoretical model positing that perceived usefulness and ease of use govern technology adoption.
References
- Net valence analysis of iris recognition technology-based FinTech. Financial Innovation (2024).
- Disentangling facial recognition payment service usage behavior: A trust perspective. Telematics and Informatics (2023).
- Determinants of consumer adoption of biometric technologies in mobile financial applications. Economics and Business Review (2024).
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