Determinants of the application of artificial intelligence in the insurance market
Keywords:
artificial intelligence, machine learning, insurance, insurance services, underwriting, generative artificial intelligenceSynopsis
This research is devoted to current issues related to the use of artificial intelligence technologies by insurers in providing insurance services. The characteristic features of digital insurance regarding the orientation of the insurer's business processes to the client, multi-channel and platformization of customer service were identified. The dynamics of artificial intelligence usage in the global insurance market have been analyzed. The regional structure of artificial intelligence application in the global insurance market has been studied.
The opportunities for the use of artificial intelligence in various segments of insurance activities such as risk assessment and underwriting, claims processing, marketing, fraud detection, billing, and payroll calculation have been identified. The consequences of implementing artificial intelligence technologies in underwriting, risk assessment, marketing activities, and claims processing by insurance providers have been characterized. Problems related to the application of artificial intelligence in the insurance market have been identified, such as the difficulties in integrating AI technologies with outdated information systems of insurance providers and with diverse sources of fragmented and contradictory data, the need to comply with regulatory requirements for the protection of clients' personal data, the necessity of carefully calculating the effectiveness of investments in AI technologies, and overcoming biases in AI algorithms related to unfair treatment of policyholders.
The trends in the development of artificial intelligence usage in the insurance market have been outlined, such as the activation of Internet of Things (IoT) devices, the integration of conversational AI into chatbots for insurance providers, the broader implementation of generative AI, the intensification of the development of agency networks based on the use of AI technologies, deeper penetration of AI into digital banking insurance, and the strengthening of insurers' integration into ecosystems to improve customer satisfaction. The use of artificial intelligence technologies will allow for the consideration of individual consumer needs, accelerate customer service, ensure rapid data collection and quality analysis, assess insurance risks and demand for specific insurance products, minimize the risks of insurance providers, and enhance the competitiveness of insurance service sellers.
The synergistic effect of the interaction of generative artificial intelligence and other financial technology tools on the development of digital insurance was revealed.
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Eling, M., Nuessle, D., Staubli, J. (2022). The impact of artificial intelligence along the insurance value chain and on the insurability of risks. The Geneva Papers on Risk and Insurance – Issues and Practice, 47 (2), 205–241. https://doi.org/10.1057/s41288-020-00201-7
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Nimmagadda, V. S. P. (2024). Artificial Intelligence for Dynamic Pricing in Insurance: Advanced Techniques, Models, and Real‑World Application. Hong Kong Journal of AI and Medicine, 4 (1), 258–297. Available at: https://hongkongscipub.com/index.php/hkjaim/article/view/43
Gupta, S., Ghardallou, W., Pandey, D. K., Sahu, G. P. (2022). Artificial intelligence adoption in the insurance industry: Evidence using the technology–organization–environment framework. Research in International Business and Finance, 63, 101757. https://doi.org/10.1016/j.ribaf.2022.101757
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Jorzik, P., Klein, S. P., Kanbach, D. K., Kraus, S. (2024). AI-driven business model innovation: A systematic review and research agenda. Journal of Business Research, 182, 114764. https://doi.org/10.1016/j.jbusres.2024.114764
Kalia, S. (2023). Potential Impact of Generative Artificial Intelligence (AI) on the Financial Industry. International Journal on Cybernetics & Informatics, 12 (6), 37–51. https://doi.org/10.5121/ijci.2023.120604
Bokka, V. V. R. M. (2025). Transforming mobile insurance through generative AI: A technical analysis of innovation in the U.S. market. International Research Journal of Modernization in Engineering Technology and Science, 7 (2), 633–642. https://doi.org/10.56726/irjmets67275
Adavelli, S. R. (2024). Generative AI in Digital Insurance: Redefining Customer Experience, Fraud Detection, and Risk Management. International Journal of Computer Science and Information Technology Research, 5 (2), 41–60.
Fedyshyn, M., Abramova, A., Morozova, L., Lavrov, R., Kovalova, O., Malin, O. (2022). Development fintech ecosystem: Evidence of European countries for Ukraine. International Journal of Computer Science and Network Security, 22 (2). https://doi.org/10.22937/IJCSNS.2022.22.2.5
Kurmaiev, P., Seliverstova, L., Bondarenko, O., Husarevych, N. (2020). Cyber insurance: the current situation and prospects of development. Revista Amazonia Investiga, 9 (28), 65–73. https://doi.org/10.34069/ai/2020.28.04.8
Kate, P., Ravi, V., Gangwar, A. (2022). FinGAN: Chaotic generative adversarial network for analytical customer relationship management in banking and insurance. Neural Computing and Applications, 35 (8), 6015–6028. https://doi.org/10.1007/s00521-022-07968-x
Volosovych, S., Gumynska, M. (2024). Artificial intelligence in the market of insurance services. Economy and Society, 70.
The Role of AI in Insurance. Snowflake. Available at: https://www.snowflake.com/trending/digital-insurance Last accessed: 15.03.2025
Volosovych, S., Nezhyva, M., Sirenko, N., Mykytiuk, I. (2024). Financial services in the development of the bigtech ecosystem. Financial and Credit Activity Problems of Theory and Practice, 4 (57), 55–66. https://doi.org/10.55643/fcaptp.4.57.2024.4454
Grobelnik, M., Perset, K., Russell, S. (2024). What is AI? Can you make a clear distinction between AI and non‑AI systems? OECD. Available at: https://oecd.ai/en/wonk/definition
Gupta, M. (2023). Harnessing The Power of AI In the Insurance Sector. Forbes. Available at: https://www.forbes.com/councils/forbestechcouncil/2023/04/17/harnessing-the-power-of-ai-in-the-insurance-sector/
Chung, V., Jain, P., Purushothaman, K. (2023). Insurer of the future: Are Asian insurers keeping up with AI advances? McKinsey & Company. Available at: https://www.mckinsey.com/industries/financial-services/our-insights/insurer-of-the-future-are-asian-insurers-keeping-up-with-ai-advances
Zhuravel, H. (2024). How AI is transforming the insurance industry. Binariks. Available at: https://binariks.com/blog/artificial-intelligence-ai-in-insurance-market/
Madiega, T., Ilnicki, R. (2024). AI investment: EU and global indicators. European Parliamentary Research Service. Available at: https://epthinktank.eu/2024/04/04/ai-investment-eu-and-global-indicators/
Thormundsson, B. (2024). Private artificial intelligence (AI) investment in the United States, China, and worldwide from 2015 to 2025. Statista. Available at: https://www.statista.com/statistics/1424667/ai-investment-growth-worldwide/#statisticContainer
Global investment in generative AI. Our World in Data. Available at: https://ourworldindata.org/grapher/global-investment-in-generative-ai
Generative AI – Munich Re is driving automation in the insurance industry (2024). Munich Re. Available at: https://www.munichre.com/en/insights/digitalisation/generative-ai-munich-re-is-driving-automation-in-the-insurance-industry.html
Saldanha, K., Lahraoui, K. (2024). The guide to generative AI for insurance. Accenture. Available at: https://insuranceblog.accenture.com/guide-generative-ai-insurance
Ozsevim, I. (2023). Lemonade sets world record with 2-second AI insurance claim. AI Magazine. Available at: https://aimagazine.com/articles/lemonade-sets-world-record-with-2-second-ai-insurance-claim
Generative AI in insurance: Trends, benefits, and challenges. Sprout.ai. Available at: https://25544903.fs1.hubspotusercontent-eu1.net/hubfs/25544903/Sprout%20Generative%20AI%20Report%20-%20FINAL.pdf?__hstc=193991410.f7b820ad5c6e4160d827239f1a0a957e.1743439269851.1743439269851.1743439269851.1&__hssc=193991410.1.1743439269852&__hsfp=1875071619&hsCtaTracking=643fb0f0-dcf8-41b0-a7de-920904b6e5fc%7C213bec2a-4071-417b-847e-290d66c6a4e3 Last accessed: 17.03.2025
Ding, N., Ruan, X., Wang, H., Liu, Y. (2025). Automobile Insurance Fraud Detection Based on PSO-XGBoost Model and Interpretable Machine Learning Method. Insurance: Mathematics and Economics, 120, 51–60. https://doi.org/10.1016/j.insmatheco.2024.11.006
Dimitrieska, S. (2024). Generative Artificial Intelligence and Advertising. Trends in Economics, Finance and Management Journal, 6 (1), 23–34. https://doi.org/10.69648/eyzi2281
Volosovych, S., Vasylenko, A., Mykytiuk, I., Yanchevs'ka, K. (2022). Insurance ecosystems under conditions of the pandemic. Investytsiyi: praktyka ta dosvid, 2, 30–35. https://doi.org/10.32702/2306-6814.2022.2.30
Volosovych, S., Vasylenko, A., Napadovs'kyj, І. (2023). Virtual assets market in the financial ecosystem. Investytsiyi: praktyka ta dosvid, 13, 47–52. https://doi.org/10.32702/2306-6814.2023.13.47
Text Identifier of this Chapter
Chapter 1
Published
August 26, 2025
Copyright (c) 2026 Svitlana Volosovych, Liudmyla Morozova, Nataliia Husarevych
How to Cite
Volosovych, S., Morozova, L., & Husarevych, N. (2025). Determinants of the application of artificial intelligence in the insurance market. In In Press. Digital intelligence: AI in industry and business. Scientific Route OÜ®. https://monograph.route.ee/rout/catalog/book/digital_intelligence_ai_in_industry_and_business/chapter/167
