Major part of African economy such as Nigerian economy has been experiencing high rate of adult financial exclusion, and poor usage of novel financial technologies. Several factors have been shown from developed nations to have significant effect on how customers use and adopt financial innovations. The study investigates the acceptance and use of fingerprint biometric authentication in an African context. This is critical because of the driving cashless policies of most African nations like Nigeria and the proliferation of different financial innovations to which a significant few have gained user traction. The paper is centered on advancing structural model to fit the African context of fingerprint authentication, and assess how customers’ perception of its usefulness can have mediating influence on its adoption. Thus, how do customers perceive usefulness of fingerprint authentication in adopting the device when associated with other determinant factors? Cross-sectional design was adopted while adapted structured questionnaire was used to pool 311 responses using snowball sampling. Confirmatory factor analysis was carried out while structural equation modeling was used to prove the hypotheses. Convenience, perceived security, personal innovativeness, perceived usefulness and subjective norm are the key drivers of fingerprint biometric authentication in Africa. However, convenience is the key contributor in deepening the cashless market while perceived usefulness partially mediate behavioral intention. The predictive power of 76% intention to use biometric authentication indicates inclusion of major factors that enables understanding of the implications while the mediation analysis portrays the value of such factors in deepening cashless market. Also it is one of scarce literature on deepening cashless market in African context through biometric authentication. Therefore, it is concluded that in African context of customer reaction to biometric authentication, convenience has paramount influence while customers significantly value usefulness as it mediates the relationship of other factors to the adoption of the innovation.

Ajzen, I. (1991). The theory of planned behavior, Organizational Behavior and Human Decision Processes, 50, 179–211.

Buckley, O., & Nurse, J. (2019). The language of biometrics: Analysing public perceptions, Journal of Information Security and Applications, 47, 112-119

Chen, L., & Nath, R. (2008). Determinants of Mobile Payments: An Empirical Analysis, Journal of International Technology and Information Management, 17(1), 9-20

Davis, F.D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology, MIS Quarterly, 13, 319–340.

Duarte, P.E. Silva, S.C., & Ferreira, M.B. (2018). How convenient is it? Delivering online shopping convenience to enhance customer satisfaction and encourage e-WOM, Journal of Retailing and Consumer Services, 44, 161–169

Fornell, C., & Larcker, D.F. (1981). Evaluating structural equation models with unobservable variables and measurement error, Journal of Marketing Research 18(1), 39–50.

Iloduba, S.C. Muhammad, S., & Ebelogu, C.U. (2019). Secure ATM and Bank Transactions using Biometric and Blockchain, International Journal of Advances in Scientific Research and Engineering (IJASRE), 5(10), 301-313

Hair, J. Black, W. Babin, B., & Anderson, R. (2014). Multivariate data analysis. Harlow: Pearson

Hayes, A.F. (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis:

Lara-Rubio, J. Villarejo-Ramos, A.F., & Liébana-Cabanillas, F. (2020). Explanatory and predictive model of the adoption of P2P payment systems, Behaviour & Information Technology, 40(6), 524-541, https://doi.org/10.1080/0144929X.2019.1706637

Muñoz-Leiva, F. Climent-Climent, S., & Liébana-Cabanillas, F. (2017). Determinants of intention to use the mobile banking apps: An extension of the classic TAM model, Spanish Journal of Marketing – ESIC, 21, 25-38

Oliveira, T. Thomas, M. Baptista, G., & Campos, F. (2016). Mobile payment: Understanding the determinants of customer adoption and intention to recommend the technology, Computers in Human Behavior, 61, 404–414.

Pal, D. Vanijja, V., & Papasratorn, B. (2015). An empirical analysis towards the adoption of NFC mobile payment system by the end user, Procedia Computer Science, 69, 13–25.

Rosén, A. Sondell, E., & Khalil, E. (2021). The case of biometric payment cards: A quantitative study of the behavioural intention to use biometric payment cards among Swedish consumers. Available at: https://www.diva-portal.org (accessed 7 May 2021)

Shankar, A. and Rishi, B. (2020), Convenience matter in mobile banking adoption intention? Australasian Marketing Journal, Vol.28, pp.273–285

Verkijika, S.F. (2018). Factors influencing the adoption of mobile commerce applications in Cameroon, Telematics and Informatics, 35(6), 1665–1674.

Xu, F., & Du, J.T. (2018). Factors influencing users’ perceived satisfaction and loyalty to digital libraries in Chinese universities, Computers in Human Behavior, 83, 64–72.

Zhao, X. Lynch, J.G. Jr, & Chen, Q. (2010). Reconsidering Baron and Kenny: Myths and truths about mediation analysis, Journal of Consumer Research, 37, 197–206.