Combating Insurance Fraud in the Age of Digitalization: New Challenges for Law Enforcement and Insurance Companies

Insurance fraud poses a threat to the stability of market relations, having a devastating impact on the operational efficiency of insurance companies and exacerbating the financial burden on bona fide policyholders. At the same time, rapid digitalization, which brings unprecedented opportunities for optimizing operational processes and expanding customer service, is also radically transforming the nature of fraudulent activity, equipping attackers with fundamentally new tools and channels for implementing more sophisticated, scalable, and difficult-to-detect schemes, such as manipulating digital traces and data, staging events using deepfake technologies, or exploiting vulnerabilities in complex information systems and distributed ledgers. This fundamentally changes the conditions for counteraction and, as a result, creates new challenges for insurance companies and law enforcement agencies, necessitating a fundamental restructuring of their strategies and tactics. The paper presents innovative solutions for effectively combating insurance fraud in the context of digitalization.

1. Afanasev S. F., Borisova V. F., Zarubina M. N. i dr. Preimushchestva i riski primeneniya sovremennykh tekhnologiy v grazhdanskom protsesse // Vestnik grazhdanskogo protsessa. — 2020. — T. 10. — № 4. — S. 270–294.

2. Berdnikova O. P., Andronik N. A. Otdelnye aspekty rassledovaniya moshennichestva v sfere strakhovaniya // Vestnik Uralskogo yuridicheskogo instituta MVD Rossii. — 2019. — № 4. — S. 57–61.

3. Borovskikh R. N. Tipovye mekhanizmy i praktika protivodeystviya organizovannoy prestupnoy deyatelnosti v sfere strakhovaniya // Lex russica. — 2017. — № 8 (129). — S. 119–134. — DOI: 10.17803/17295920.2017.129.8.119-135.

4. Vinokhodova I. G. Metody protivodeystviya moshennichestvu v sfere strakhovaniya // Izvestiya Velikolukskoy gosudarstvennoy selskokhozyaystvennoy akademii. — 2020. — № 1. — S. 27–32. — URL: https://vgsa.ru/ nir/ivgsa/numbers/vgsa2020-1-5.pdf.

5. Zhuykova A. A. Protsessualnye osobennosti elektronnykh tekstovykh dokazatelstv kak sredstv dokazyvaniya po grazhdanskim delam, svyazannykh s zashchitoy intellektualnykh prav // Aktualnye problemy gosudarstva i prava. — 2020. — T. 4. — № 16. — S. 530–540. — DOI: 10.20310/2587-9340-2020-4-16-530-540.

6. Kovaleva E. R., Fukina S. P. Strakhovoe moshennichestvo kak faktor, prepyatstvuyushchiy razvitiyu strakhovogo rynka Rossii // Azimut nauchnykh issledovaniy: ekonomika i upravlenie. — 2019. — T. 8. — № 2 (27). — S. 160–164.

7. Milova I. E., Khachatryan R. E. Problemy privlecheniya k ugolovnoy otvetstvennosti za strakhovye moshennichestva // Pravo i gosudarstvo: teoriya i praktika. — 2025. — № 2. — S. 597–600. — DOI: 10.47643/1815-1337_2025_2_597.

8. Okhrimenko I. V., Tsyganov A. A. Vzglyad praktikov: kak povysit effektivnost protivodeystviya strakhovomu moshennichestvu // Vestnik Prikamskogo sotsialnogo instituta. — 2024. — № 1 (97). — S. 35–39.

9. Okhrimenko I. V., Tsyganov A. A. O problemakh protivodeystviya strakhovomu moshennichestvu // Vserossiyskiy kriminologicheskiy zhurnal. — 2023. — № 5. — S. 432–442.

10. Sultaniev I. S. Problemy protivodeystviya strakhovomu moshennichestvu v period tsifrovoy transformatsii rynka strakhovykh uslug // Vestnik Moskovskogo gumanitarno-ekonomicheskogo instituta. — 2024. — № 3 (95). — S. 53–61.

11. Burnett S., Kinder K. Insurance Fraud Detection Statistics 2025: Data-Driven Insights and Detection Techniques // URL: https://coinlaw.io/insurance-fraud-detection-statistics/.

12. Cude B. J., Zhang H. Factors That Influence Willingness to Commit Insurance Fraud // Journal of consumer affairs. — 2025. — Vol. 59. — Iss. 2. — DOI: 10.1111/JOCA.70015.

13. Ebinezer M. J. D., Krishna B. C. Life Insurance Fraud Detection: A Data-Driven Approach Utilizing Ensemble Learning, CVAE, and Bi-LSTM // Applied Sciences. — 2025. — Vol. 15 (16). — P. 8869–8899. — DOI: 10.3390/app15168869.

14. Insurance Fraud: Impacts on Premiums, Claim Costs, and the Public — Washington: American Academy of Actuaries, 2024. — 11 p. — URL: https://actuary.org/wp-content/uploads/2024/10/casualty-brief-insurancefraud.pdf.

15. Kumar S. K., Venkata Gummadi. Advancing insurance fraud detection: Leveraging machine learning and AI techniques // International Research Journal of Modernization in Engineering Technology and Science. — 2024. — August. — DOI: 10.15680/IJIRSET.2024.1308151.

16. Óskarsdóttir M., Ahmed W., Antonio K., et al. Social Network Analytics for Supervised Fraud Detection in Insurance // Risk Analysis. — 2021. — Vol. 42 (8). — DOI: 10.1111/risa.13693.

17. Pandya S. Transforming Claims Processing: The Role of Artificial Intelligence in Enhancing Efficiency and Fraud Detection in the Insurance Industry // International Journal of Emerging Trends in Computer Science and Information Technology. — 02.07.2025. — URL: https://ijeret.org/index.php/ijeret/article/view/174.

18. Schalck M. Y. Auto insurance fraud detection: Leveraging cost sensitive and insensitive algorithms for comprehensive analysis // Insurance: Mathematics and Economics. — 2025. — Vol. 122. — P. 44–60. — DOI: 10.1016/j.insmatheco.2025.02.001.

19. Sidorova E. Current Methods to Combating Insurance Fraud // Accounting. Analysis. Auditing. — 2024. — Vol. 11. — P. 93–103. — DOI: 10.26794/2408-9303-2024-11-5-93-103.