Preview

Russian Journal of Economics and Law

Advanced search

Technological, organizational and financial features of using biometric services

https://doi.org/10.21202/2782-2923.2026.1.116-134

Abstract

Objective: to identify and analyze the technological, financial and organizational features of the use of biometric services by enterprises in the Russian economy.

Methods: general scientific methods (analysis, synthesis); case studies of the introduction of biometric services through GIS National Biometric System in 2024–2025; abstract-logical and correlation analysis of statistics of the Bank of Russia for the 1st quarter of 2024 – 2nd quarter of 2025; and a dialectical approach to considering biometrics as an evolving system.

Results: the research showed that the transition to a centralized model of working with biometric personal data through GIS National Biometric System and commercial biometric systems has formed the service architecture of the biometrics market in Russia. This architecture requires integration of software, hardware, information security and communication infrastructure at the levels of enterprises and macro-infrastructure. Correlation analysis of the statistical data of the Bank of Russia for 2024-2025 revealed a strong positive relationship between the dynamics of payments using biometrics with QR-code and mobile/Internet banking. The author interprets this as the inclusion of biometric payments in the general development of digital payment instruments in Russia.

Scientific novelty: the novelty of the work lies in the comprehensive characterization of the technological, organizational and financial configuration of the biometric services market in Russia under the centralization of working with personal databases. This allows considering biometrics not as an isolated innovation, but as a structural element of the digital service infrastructure. The author clarified the role of the service business model and system integrators as key nodes of the institutional and technological architecture of biometric solutions affecting the structure of transaction costs and operating costs of enterprises. The proposal is to interpret the dynamics of payments using biometrics by their statistically confirmed connection with other digital payment tools, regarding it as an indicator of the integration of biometrics into the economic agents’ daily practices.

Practical significance: the results will be useful for the development of the biometrics market in Russia, increasing its sustainability, as well as for interdisciplinary research using a combination of qualitative and quantitative methods.

About the Author

N. S. Seliverstova
Kazan (Volga region) Federal University
Russian Federation

Natalya S. Seliverstova, Cand. Sci. (Econ.), Associate Professor of the Department of Mathematical Methods and Information Technologies in Economics

Kazan



References

1. Agidi, R. C. (2018). Using biometric in solving terrorism and crime activities in Nigeria. Techsplend Journal of Technology, 1(12), 91–105.

2. Alfatni, M. S. M., Ebiad, A. M., Al-Bahbouh, M. A., & Esmeda, L. A. (2023). Electronic health file system based on fingerprint sensor technology. Journal of Advanced Research in Applied Sciences and Engineering Technology, 33(2), 209–224. https://doi.org/10.37934/araset.33.2.209224

3. Antonova, I. I., & Seliverstova, N. S. (2025). Trends in standardization of innovative domestic ict solutions. Competency (Russia), 5, 8–13. (In Russ.).

4. Belousov, A. L., & Levchuk, E. Yu. (2018). Digitalization of the banking sector. Finance and Credit, 24(2(770)), 455–464. (In Russ.). https://doi.org/10.24891/fc.24.2.455

5. Clodfelter, R. (2010). Biometric technology in retailing: will consumers accept fingerprint authentication? J. Retailing Consum. Serv., 17(3), 181–188.

6. Eksteen, C., & Humbani, M. (2021). Understanding proximity mobile payments adoption in South Africa: a perceived risk perspective. Journal of Marketing and Consumer Behaviour in Emerging Markets, 2(13), 4–21.

7. Hwang, J., Kim, J. S., Kim, H. M., & Kim, J. J. (2024). Effects of motivated consumer innovativeness on facial recognition payment adoption in the restaurant industry: a cross-cultural study. Int. J. Hospit. Manag., 117, Article 103646. https://doi.org/10.1016/j.ijhm.2023.103646

8. Kartsan, I. N. (2023). Biometric data: new opportunities and risks. Modern Innovations, Systems and Technologies, 3(3), 0201–0211. (In Russ.). https://doi.org/10.47813/2782-2818-2023-3-3-0201-0211

9. Khramov, E. N., & Vershinina, O. V. Biometric technologies as a factor in improving security and competitiveness in Russia’s financial infrastructure. Fundamental Research, 4, 69–79. (In Russ.). https://doi.org/10.17513/fr.43814

10. Kochetkov, E. P. (2019). Digital transformation of economy and technological revolutions: challenges for the current paradigm of management and crisis management. Strategic Decisions and Risk Management, 10(4), 330–341. (In Russ.). https://doi.org/10.17747/2618-947x-2019-4-330-341

11. Kotilko, V. V. (2024). Biometrics and the Russian economy. In Forming and developing a new paradigm of science in a post-industrial society: collection of articles of the International scientific-practical conference (June 7, 2024, Irkutsk) (pp. 93–100). Ufa: Omega Science. (In Russ.).

12. Krylova, I. Yu., & Rudakova, O. S. (2018). Biometric technologies as a mechanism for ensuring information security in the digital economy. Molodoy uchenyy, 45(231), 74–79. (In Russ.).

13. Liang, Y., Samtani, S., Guo, B. & Yu, Z. (2020) Behavioral biometrics for continuousauthentication in the internet-of-things era: An artificial intelligence perspective, IEEE Internet of Things Journal, 7(9), 9128–9143. https://doi.org/10.1109/jiot.2020.3004077

14. Mizinov, P. V., & Konnova, N. S. (2023). On the meaning of the term “biometrics”. Humanities Bulletin of BMSTU, 5(103). (In Russ.).

15. Morake, А., Khoza, L., & Bokaba, T. (2021). Biometric technology in banking institutions: “The customers” perspectives”. SA Journal of Information Management, 23(1). https://doi.org/10.4102/sajim.v23i1.1407

16. Promyslov, V. G., Semenkov, K. V., & Mengazetdinov, N. E. Assessment of operator authentication methods in industrial control systems. Problemy Upravlenia, 3, 40–54. (In Russ.).

17. Seliverstova, N. S. (2024). Directions of emerging structural changes in the use of biometric data in Russia. Russian Journal of Economics and Law, 18(4), 912–925. (In Russ.). https://doi.org/10.21202/2782-2923.2024.4.912-925

18. Seliverstova, N. S., & Grigoryeva, O. V. (2025). Methodology of technological development research in modern Russia. Bulletin Tver State University. Series: Economics and Management, 2(70), 60–69. (In Russ.). https://doi.org/10.26456/2219-1453/2025.2.060-069

19. Shiau, W.-L., Liu, C., Zhou, M., & Yuan, Y. (2023). Insights into customers' psychological mechanism in facial recognition payment in offline contactless services: integrating belief–attitude–intention and TOE–i frameworks, Internet Research, 33(1), 344–387. https://doi.org/10.1108/intr-08-2021-0629

20. Smirnov, N. A., & Anisimova, E. S. (2025). Biometric system for identifying users by handwritten signature based on convolutional neural networks. In KAZAN DIGITAL WEEK – 2025 International Forum: a collection of works (Vol. 1, pp. 818–823). Kazan: GBU “NCBZhD”. (In Russ.).

21. Sulaiman, S. N. A., & Almunawar, M. N. (2022) The adoption of biometric point-of-sale terminal for payments. Journal of Science and Technology Policy Management, 13(3), 585–609. https://doi.org/10.1108/jstpm-11-2020-0161

22. Tiwari, Sh., Raja, R., Wadawadagi, R. S., Naithani, K., Raja, H., & Ingle, D. (2024). Emerging Biometric Modalities and Integration Challenges. In Online Identity – An Essential Guide. IntechOpen.

23. Venkatesh, V., Thong, J. Y., & Xu, X. (2012). Consumer acceptance and use of information technology: extending the unified theory of acceptance and use of technology. MIS Quarterly, 36, 157–178. https://doi.org/10.2307/41410412

24. Vishnyakova, O. N. (2025). Digital integration as a tool of sustainable development. In KAZAN DIGITAL WEEK – 2025 International Forum: a collection of works (Vol. 1, pp. 265–271). Kazan: GBU “NCBZhD”. (In Russ.).

25. Wang, Y. D., & Emurian, H. H. (2005). An overview of online trust: concepts, elements, and implications. Computers in Human Behavior, 21(1), 105–125. https://doi.org/10.1016/j.chb.2003.11.008

26. Wayman, J. L., Jain, A. K., Maltoni, D., & Maio, D. (2005). Biometric systems: Technology, design and performance evaluation. Springer Science & BusinessMedia, London, United Kingdom.

27. Wu, X., Zhou, Z., & Chen, S. (2024). A mixed-methods investigation of the factors affecting the use of facial recognition as a threatening ai application. Internet Research, 34(5), 1872–1897. https://doi.org/10.1108/intr-11-2022-0894

28. Zakhmatov, D. Yu., Kirshin, I. A., & Kokh, I. A. (2025). Construction of financial time series using neural networks in relation to enterprise forecast indicators. Kant, 1(54), 51–62. (In Russ.).

29. Zarco, C., Giráldez-Cru, J., Cordón, O., & Liébana-Cabanillas, F. (2024). A comprehensive view of biometric payment in retailing: A complete study from user to expert. Journal of Retailing and Consumer Services, 79, 103789. https://doi.org/10.1016/j.jretconser.2024.103789

30. Zhang, X., & Zhang, Z. (2024) Leaking My Face via Payment: Unveiling the Influence of Technology Anxiety, Vulnerabilities, and Privacy Concerns on User Resistance to Facial Recognition Payment. Telecommunications Policy, Article 102703. https://doi.org/10.1016/j.telpol.2023.102703

31. Zhu, Y., Tan, T., & Wang, Y. (2000). Biometric personal identification based on irispatterns. In Proceedings 15th International conference on pattern recognition, ICPR (Vol. 2, pp. 801–804). IEEE. https://doi.org/10.1109/icpr.2000.906197


Review

For citations:


Seliverstova N.S. Technological, organizational and financial features of using biometric services. Russian Journal of Economics and Law. 2026;20(1):116-134. (In Russ.) https://doi.org/10.21202/2782-2923.2026.1.116-134

Views: 410

JATS XML

ISSN 2782-2923 (Print)