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Paper ID:IJSREM66127

Understanding User Adoption of Immersive FinTech in Banking: A Conceptual Framework Integrating Trust and Perceived Risk

Stream/Area:

-

Subject:

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Paper ID:

IJSREM66127

Volume:

10 |

7 |

Jul 2026

Pages:

1-10

Publication Frequency:

Monthly (12 issues per year)

DOI
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Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Deepika

Deepika

Department of Management Studies

Deenbandhu Chhotu Ram University of Science and Technology

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Abstract

The advancement of Financial Technology (FinTech) has significantly transformed the global banking industry, accelerated digital transformation, and reshaped the way customers interact with financial services (Gomber et al., 2017; Lee & Shin, 2018). Among recent innovations, immersive technologies such as Augmented Reality (AR) and Virtual Reality (VR) are emerging as powerful tools for delivering engaging, interactive, and personalized banking experiences. Despite their transformative potential, the adoption of AR/VR-based banking services remains limited due to concerns related to trust, perceived risk, privacy, and security (Kim et al., 2008; Stewart & Jürjens, 2018). This conceptual review critically synthesizes the existing literature on FinTech adoption, digital trust, and perceived risk to examine their influence on user acceptance of immersive banking technologies. Drawing on established behavioral theories, including the Technology Acceptance Model (Davis, 1989) and the Theory of Planned Behavior (Ajzen, 1991), the paper integrates trust and perceived risk into a comprehensive conceptual framework to explain customers' adoption intentions toward AR/VR-enabled financial services. The review identifies significant research gaps, particularly the limited empirical evidence on immersive banking adoption in developing economies and the need for integrated theoretical approaches. The paper highlights future research opportunities related to sustainability-driven innovation, digital governance, and user-centric cybersecurity strategies. By consolidating fragmented research, this study contributes to the growing body of knowledge on immersive FinTech and provides a theoretical foundation for future empirical investigations into responsible digital transformation in the banking sector.

KEYWORDS

FinTech Immersive Banking Augmented Reality Virtual Reality Trust Perceived Risk

Cite This Article

Deepika, "Understanding User Adoption of Immersive FinTech in Banking: A Conceptual Framework Integrating Trust and Perceived Risk," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 7, pp. 1-10, Jul 2026.

Full Article/Conclusion

The rapid evolution of Financial Technology (FinTech) has positioned immersive technologies, particularly Augmented Reality (AR) and Virtual Reality (VR), as promising innovations capable of transforming the future of digital banking. By delivering interactive, personalized, and engaging financial experiences, immersive banking has the potential to enhance customer engagement, improve financial decision-making, and support broader objectives of digital transformation. Nevertheless, technological innovation alone is insufficient to ensure widespread customer acceptance. Psychological factors—especially trust and perceived risk—remain fundamental determinants of users' willingness to adopt immersive financial services (Gefen et al., 2003; Kim et al., 2008). This conceptual review integrates the Technology Acceptance Model (TAM) (Davis, 1989), the Theory of Planned Behavior (TPB) (Ajzen, 1991), and trust–risk theory to propose the Trust–Risk–Adoption Framework for understanding customer adoption of AR/VR-enabled banking services. By synthesizing fragmented literature, the study identifies critical research gaps related to immersive banking adoption, trust formation, sustainability, and digital governance while highlighting opportunities for future empirical investigation. Overall, this study contributes to the growing body of knowledge on immersive FinTech by providing a comprehensive theoretical foundation for understanding customer behaviour in emerging digital financial environments. The proposed framework offers valuable guidance for researchers, financial institutions, technology developers, and policymakers seeking to foster secure, trustworthy, and sustainable immersive banking ecosystems. As AR/VR technologies continue to evolve, understanding the interplay between technological innovation, trust, and perceived risk will be essential for achieving responsible digital transformation and promoting the successful adoption of next-generation banking services.

References

Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211. https://doi.org/10.1016/0749-5978(91)90020-T   Bauer, R. A. (1960). Consumer behavior as risk taking. In R. S. Hancock (Ed.), Dynamic Marketing for a Changing World (pp. 389–398). American Marketing Association.   Bhattacherjee, A. (2001). Understanding information systems continuance: An expectation-confirmation model. MIS Quarterly, 25(3), 351–370. https://doi.org/10.2307/3250921   Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008   Davis, F. D., Bagozzi, R. P., & Warshaw, P. R. (1989). User acceptance of computer technology: A comparison of two theoretical models. Management Science, 35(8), 982–1003. https://doi.org/10.1287/mnsc.35.8.982   Dwivedi, Y. K., Rana, N. P., Jeyaraj, A., Clement, M., & Williams, M. D. (2019). Re-examining the unified theory of acceptance and use of technology (UTAUT): Towards a revised theoretical model. Information Systems Frontiers, 21(3), 719–734. https://doi.org/10.1007/s10796-017-9774-y   Featherman, M. S., & Pavlou, P. A. (2003). Predicting e-services adoption: A perceived risk facets perspective. International Journal of Human-Computer Studies, 59(4), 451–474. https://doi.org/10.1016/S1071-5819(03)00111-3   Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. MIS Quarterly, 27(1), 51–90. https://doi.org/10.2307/30036519   Gomber, P., Kauffman, R. J., Parker, C., & Weber, B. W. (2017). On the FinTech revolution: Interpreting the forces of innovation, disruption, and transformation in financial services. Journal of Management Information Systems, 35(1), 220–265. https://doi.org/10.1080/07421222.2018.1440766   Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications.

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Publication Date

7/18/2026

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