Skip to main content
Top

2024 | OriginalPaper | Chapter

Digital Transformation with Artificial Intelligence in the Insurance Industry

Author : Samet Gürsev

Published in: Advances in Intelligent Manufacturing and Service System Informatics

Publisher: Springer Nature Singapore

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

The chapter delves into the digital transformation of the insurance industry, driven by Artificial Intelligence. It begins by outlining the shift from traditional insurance models to fully digital business processes, facilitated by technologies like AI, IoT, and blockchain. The Covid-19 pandemic has accelerated this digitalization, with insurers adopting new channels such as online sales, mobile applications, and chatbots to enhance customer interaction. The research focuses on the application of AI in various insurance processes, including risk calculation, customer data analytics, and fraud detection. It presents a model based on real applications, highlighting the potential for personalized customer experiences and improved market adaptability. The chapter also discusses the implementation of this model in a case study, showcasing substantial improvements in customer demand fulfillment, satisfaction rates, and operational efficiency over a one-year period.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

Literature
1.
go back to reference Riikkinen, M., Saarijärvi, H., Sarlin, P., Lähteenmäki, I.: Using artificial intelligence to create value in insurance. Int. J. Bank Mark. (2018) Riikkinen, M., Saarijärvi, H., Sarlin, P., Lähteenmäki, I.: Using artificial intelligence to create value in insurance. Int. J. Bank Mark. (2018)
2.
go back to reference Kumar, N., Srivastava, J.D., Bisht, H.: Artificial intelligence in insurance sector. J. Gujarat Res. Soc. 21(7), 79–91 (2019) Kumar, N., Srivastava, J.D., Bisht, H.: Artificial intelligence in insurance sector. J. Gujarat Res. Soc. 21(7), 79–91 (2019)
3.
go back to reference Park, S.H., Choi, J., Byeon, J.S.: Key principles of clinical validation, device approval, and insurance coverage decisions of artificial intelligence. Korean J. Radiol. 22(3), 442 (2021)CrossRef Park, S.H., Choi, J., Byeon, J.S.: Key principles of clinical validation, device approval, and insurance coverage decisions of artificial intelligence. Korean J. Radiol. 22(3), 442 (2021)CrossRef
4.
go back to reference Ho, C.W., Ali, J., Caals, K.: Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance. Bull. World Health Organ. 98(4), 263 (2020)CrossRef Ho, C.W., Ali, J., Caals, K.: Ensuring trustworthy use of artificial intelligence and big data analytics in health insurance. Bull. World Health Organ. 98(4), 263 (2020)CrossRef
6.
go back to reference Gramegna, A., Giudici, P.: Why to buy insurance? An explainable artificial intelligence approach. Risks 8(4), 137 (2020)CrossRef Gramegna, A., Giudici, P.: Why to buy insurance? An explainable artificial intelligence approach. Risks 8(4), 137 (2020)CrossRef
8.
go back to reference Paul, L.R., Sadath, L., Madana, A.: Artificial intelligence in predictive analysis of insurance and banking. In: Artificial Intelligence, pp. 31–54. CRC Press (2021) Paul, L.R., Sadath, L., Madana, A.: Artificial intelligence in predictive analysis of insurance and banking. In: Artificial Intelligence, pp. 31–54. CRC Press (2021)
9.
go back to reference Stern, A.D., Goldfarb, A., Minssen, T., Price II, W.N.: AI insurance: how liability insurance can drive the responsible adoption of artificial intelligence in health care. NEJM Catal. Innov. Care Deliv. 3(4), CAT-21 (2022) Stern, A.D., Goldfarb, A., Minssen, T., Price II, W.N.: AI insurance: how liability insurance can drive the responsible adoption of artificial intelligence in health care. NEJM Catal. Innov. Care Deliv. 3(4), CAT-21 (2022)
10.
go back to reference Mullins, M., Holland, C.P., Cunneen, M.: Creating ethics guidelines for artificial intelligence and big data analytics customers: the case of the consumer European insurance market. Patterns 2(10), 100362 (2021)CrossRef Mullins, M., Holland, C.P., Cunneen, M.: Creating ethics guidelines for artificial intelligence and big data analytics customers: the case of the consumer European insurance market. Patterns 2(10), 100362 (2021)CrossRef
11.
go back to reference Islam, M.M., Yang, H.C., Poly, T.N., Li, Y.C.J.: Development of an artificial intelligence–based automated recommendation system for clinical laboratory tests: Retrospective analysis of the national health insurance database. JMIR Med. Inform. 8(11), e24163 (2020)CrossRef Islam, M.M., Yang, H.C., Poly, T.N., Li, Y.C.J.: Development of an artificial intelligence–based automated recommendation system for clinical laboratory tests: Retrospective analysis of the national health insurance database. JMIR Med. Inform. 8(11), e24163 (2020)CrossRef
12.
go back to reference Herrmann, H., Masawi, B.: Three and a half decades of artificial intelligence in banking, financial services, and insurance: a systematic evolutionary review. Strateg. Chang. 31(6), 549–569 (2022)CrossRef Herrmann, H., Masawi, B.: Three and a half decades of artificial intelligence in banking, financial services, and insurance: a systematic evolutionary review. Strateg. Chang. 31(6), 549–569 (2022)CrossRef
13.
go back to reference Owens, E., Sheehan, B., Mullins, M., Cunneen, M., Ressel, J., Castignani, G.: Explainable Artificial Intelligence (XAI) in Insurance. Risks 10(12), 230 (2022)CrossRef Owens, E., Sheehan, B., Mullins, M., Cunneen, M., Ressel, J., Castignani, G.: Explainable Artificial Intelligence (XAI) in Insurance. Risks 10(12), 230 (2022)CrossRef
14.
go back to reference Keller, B.: Promoting responsible artificial intelligence in insurance. Geneva Association-International Association for the Study of Insurance Economics (2020) Keller, B.: Promoting responsible artificial intelligence in insurance. Geneva Association-International Association for the Study of Insurance Economics (2020)
16.
go back to reference Sinha, K.P., Sookhak, M., Wu, S.: Agentless insurance model based on modern artificial intelligence. In: 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI), pp. 49–56. IEEE (2021) Sinha, K.P., Sookhak, M., Wu, S.: Agentless insurance model based on modern artificial intelligence. In: 2021 IEEE 22nd International Conference on Information Reuse and Integration for Data Science (IRI), pp. 49–56. IEEE (2021)
17.
go back to reference Gupta, S., Ghardallou, W., Pandey, D.K., Sahu, G.P.: Artificial intelligence adoption in the insurance industry: evidence using the technology–organization–environment framework. Res. Int. Bus. Financ. 63, 101757 (2022)CrossRef Gupta, S., Ghardallou, W., Pandey, D.K., Sahu, G.P.: Artificial intelligence adoption in the insurance industry: evidence using the technology–organization–environment framework. Res. Int. Bus. Financ. 63, 101757 (2022)CrossRef
18.
go back to reference Yoshikawa, J.: Sharing the costs of artificial intelligence: universal no-fault social insurance for personal injuries. Vand. J. Ent. Tech. L. 21, 1155 (2018) Yoshikawa, J.: Sharing the costs of artificial intelligence: universal no-fault social insurance for personal injuries. Vand. J. Ent. Tech. L. 21, 1155 (2018)
19.
go back to reference Singh, S.K., Chivukula, M.: A commentary on the application of artificial intelligence in the insurance industry. Trends Artif. Intell. 4(1), 75–79 (2020) Singh, S.K., Chivukula, M.: A commentary on the application of artificial intelligence in the insurance industry. Trends Artif. Intell. 4(1), 75–79 (2020)
20.
go back to reference Ejiyi, C.J., et al.: Comparative analysis of building insurance prediction using some machine learning algorithms (2022) Ejiyi, C.J., et al.: Comparative analysis of building insurance prediction using some machine learning algorithms (2022)
21.
go back to reference Winston, P.H.: Artificial Intelligence. Addison-Wesley Longman Publishing Co., Inc., Boston (1984) Winston, P.H.: Artificial Intelligence. Addison-Wesley Longman Publishing Co., Inc., Boston (1984)
22.
go back to reference Boden, M.A. (ed.): Artificial Intelligence. Elsevier, Amsterdam (1996)MATH Boden, M.A. (ed.): Artificial Intelligence. Elsevier, Amsterdam (1996)MATH
23.
go back to reference Ramesh, A.N., Kambhampati, C., Monson, J.R., Drew, P.J.: Artificial intelligence in medicine. Ann. R. Coll. Surg. Engl. 86(5), 334 (2004)CrossRef Ramesh, A.N., Kambhampati, C., Monson, J.R., Drew, P.J.: Artificial intelligence in medicine. Ann. R. Coll. Surg. Engl. 86(5), 334 (2004)CrossRef
25.
go back to reference Gunning, D., Stefik, M., Choi, J., Miller, T., Stumpf, S., Yang, G.Z.: XAI—Explainable artificial intelligence. Sci. Robot. 4(37), eaay7120 (2019) Gunning, D., Stefik, M., Choi, J., Miller, T., Stumpf, S., Yang, G.Z.: XAI—Explainable artificial intelligence. Sci. Robot. 4(37), eaay7120 (2019)
26.
go back to reference Kelley, K.H., Fontanetta, L.M., Heintzman, M., Pereira, N.: Artificial intelligence: implications for social inflation and insurance. Risk Manag. Insur. Rev. 21(3), 373–387 (2018)CrossRef Kelley, K.H., Fontanetta, L.M., Heintzman, M., Pereira, N.: Artificial intelligence: implications for social inflation and insurance. Risk Manag. Insur. Rev. 21(3), 373–387 (2018)CrossRef
27.
go back to reference Sakthivel, K.M., Rajitha, C.S.: Artificial intelligence for estimation of future claim frequency in non-life insurance. Glob. J. Pure Appl. Math. 13(6), 1701–1710 (2017) Sakthivel, K.M., Rajitha, C.S.: Artificial intelligence for estimation of future claim frequency in non-life insurance. Glob. J. Pure Appl. Math. 13(6), 1701–1710 (2017)
28.
go back to reference Lior, A. (2022). Insuring AI: The role of insurance in artificial intelligence regulation. Harvard Journal of Law and Technology, 1 Lior, A. (2022). Insuring AI: The role of insurance in artificial intelligence regulation. Harvard Journal of Law and Technology, 1
29.
go back to reference Sufriyana, H., Wu, Y.W., Su, E.C.Y.: Artificial intelligence-assisted prediction of preeclampsia: development and external validation of a nationwide health insurance dataset of the BPJS Kesehatan in Indonesia. EBioMedicine 54, 102710 (2020)CrossRef Sufriyana, H., Wu, Y.W., Su, E.C.Y.: Artificial intelligence-assisted prediction of preeclampsia: development and external validation of a nationwide health insurance dataset of the BPJS Kesehatan in Indonesia. EBioMedicine 54, 102710 (2020)CrossRef
30.
go back to reference Murray, N.M., et al.: Insurance payment for artificial intelligence technology: methods used by a stroke artificial intelligence system and strategies to qualify for the new technology add-on payment. Neuroradiol. J. 35(3), 284–289 (2022)CrossRef Murray, N.M., et al.: Insurance payment for artificial intelligence technology: methods used by a stroke artificial intelligence system and strategies to qualify for the new technology add-on payment. Neuroradiol. J. 35(3), 284–289 (2022)CrossRef
31.
go back to reference Amerirad, B., Cattaneo, M., Kenett, R.S., Luciano, E.: Adversarial artificial intelligence in insurance: from an example to some potential remedies. Risks 11(1), 20 (2023)CrossRef Amerirad, B., Cattaneo, M., Kenett, R.S., Luciano, E.: Adversarial artificial intelligence in insurance: from an example to some potential remedies. Risks 11(1), 20 (2023)CrossRef
32.
go back to reference Shi, Y., Sun, C., Li, Q., Cui, L., Yu, H., Miao, C.: A fraud resilient medical insurance claim system. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 30, no. 1 (2016) Shi, Y., Sun, C., Li, Q., Cui, L., Yu, H., Miao, C.: A fraud resilient medical insurance claim system. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 30, no. 1 (2016)
33.
go back to reference Sharma, V., Sood, D.: The role of artificial intelligence in the insurance industry of India. In: Big Data Analytics in the Insurance Market, pp. 287–297. Emerald Publishing Limited (2022) Sharma, V., Sood, D.: The role of artificial intelligence in the insurance industry of India. In: Big Data Analytics in the Insurance Market, pp. 287–297. Emerald Publishing Limited (2022)
34.
go back to reference Paruchuri, H.: The impact of machine learning on the future of insurance industry. Am. J. Trade Policy 7(3), 85–90 (2020)CrossRef Paruchuri, H.: The impact of machine learning on the future of insurance industry. Am. J. Trade Policy 7(3), 85–90 (2020)CrossRef
35.
go back to reference Massaro, A.: Implementation of a decision support system and business Intelligence algorithms for the automated management of insurance agents activities. Int. J. Artif. Intell. Appl. (IJAIA), 12(3) (2021) Massaro, A.: Implementation of a decision support system and business Intelligence algorithms for the automated management of insurance agents activities. Int. J. Artif. Intell. Appl. (IJAIA), 12(3) (2021)
36.
go back to reference Kaushik, K., Bhardwaj, A., Dwivedi, A.D., Singh, R.: Machine learning-based regression framework to predict health insurance premiums. Int. J. Environ. Res. Public Health 19(13), 7898 (2022)CrossRef Kaushik, K., Bhardwaj, A., Dwivedi, A.D., Singh, R.: Machine learning-based regression framework to predict health insurance premiums. Int. J. Environ. Res. Public Health 19(13), 7898 (2022)CrossRef
37.
go back to reference Lee, J., Oh, S.: Analysis of success cases of insurtech and digital insurance platform based on artificial intelligence technologies: focused on ping an insurance group ltd. in China. J. Intell. Inf. Syst. 26(3), 71–90 (2020) Lee, J., Oh, S.: Analysis of success cases of insurtech and digital insurance platform based on artificial intelligence technologies: focused on ping an insurance group ltd. in China. J. Intell. Inf. Syst. 26(3), 71–90 (2020)
38.
go back to reference Fung, G., Polania, L.F., Choi, S.C.T., Wu, V., Ma, L.: Artificial intelligence in insurance and finance. Front. Appl. Math. Stat. 7, 795207 (2021)CrossRef Fung, G., Polania, L.F., Choi, S.C.T., Wu, V., Ma, L.: Artificial intelligence in insurance and finance. Front. Appl. Math. Stat. 7, 795207 (2021)CrossRef
39.
go back to reference Cioffi, R., Travaglioni, M., Piscitelli, G., Petrillo, A., De Felice, F.: Artificial intelligence and machine learning applications in smart production: progress, trends, and directions. Sustainability 12(2), 492 (2020)CrossRef Cioffi, R., Travaglioni, M., Piscitelli, G., Petrillo, A., De Felice, F.: Artificial intelligence and machine learning applications in smart production: progress, trends, and directions. Sustainability 12(2), 492 (2020)CrossRef
40.
go back to reference Kusiak, A.: Smart manufacturing. Int. J. Prod. Res. 56(1–2), 508–517 (2018)CrossRef Kusiak, A.: Smart manufacturing. Int. J. Prod. Res. 56(1–2), 508–517 (2018)CrossRef
42.
go back to reference Zhang, L., Zhou, L., Ren, L., Laili, Y.: Modeling and simulation in intelligent manufacturing. Comput. Ind. 112, 103123 (2019)CrossRef Zhang, L., Zhou, L., Ren, L., Laili, Y.: Modeling and simulation in intelligent manufacturing. Comput. Ind. 112, 103123 (2019)CrossRef
43.
go back to reference Banjanović-Mehmedović, L., Mehmedović, F.: Intelligent manufacturing systems driven by artificial intelligence in Industry 4.0. In: Handbook of Research on Integrating Industry 4.0 in Business and Manufacturing, pp. 31–52. IGI global (2020) Banjanović-Mehmedović, L., Mehmedović, F.: Intelligent manufacturing systems driven by artificial intelligence in Industry 4.0. In: Handbook of Research on Integrating Industry 4.0 in Business and Manufacturing, pp. 31–52. IGI global (2020)
44.
go back to reference Yang, S., Wang, J., Shi, L., Tan, Y., Qiao, F.: Engineering management for high-end equipment intelligent manufacturing. Front. Eng. Manag. 5(4), 420–450 (2018)CrossRef Yang, S., Wang, J., Shi, L., Tan, Y., Qiao, F.: Engineering management for high-end equipment intelligent manufacturing. Front. Eng. Manag. 5(4), 420–450 (2018)CrossRef
45.
go back to reference Zhong, R.Y., Xu, X., Klotz, E., Newman, S.T.: Intelligent manufacturing in the context of Industry 4.0: a review. Engineering, 3(5), 616–630 (2017) Zhong, R.Y., Xu, X., Klotz, E., Newman, S.T.: Intelligent manufacturing in the context of Industry 4.0: a review. Engineering, 3(5), 616–630 (2017)
46.
go back to reference Liang, S., Rajora, M., Liu, X., Yue, C., Zou, P., Wang, L.: Intelligent manufacturing systems: a review. Int. J. Mech. Eng. Robot. Res. 7(3), 324–330 (2018) Liang, S., Rajora, M., Liu, X., Yue, C., Zou, P., Wang, L.: Intelligent manufacturing systems: a review. Int. J. Mech. Eng. Robot. Res. 7(3), 324–330 (2018)
47.
go back to reference McFarlane, D., Sarma, S., Chirn, J.L., Wong, C., Ashton, K.: Auto ID systems and intelligent manufacturing control. Eng. Appl. Artif. Intell. 16(4), 365–376 (2003)CrossRef McFarlane, D., Sarma, S., Chirn, J.L., Wong, C., Ashton, K.: Auto ID systems and intelligent manufacturing control. Eng. Appl. Artif. Intell. 16(4), 365–376 (2003)CrossRef
48.
go back to reference Wan, J., Yang, J., Wang, Z., Hua, Q.: Artificial intelligence for cloud-assisted smart factory. IEEE Access 6, 55419–55430 (2018)CrossRef Wan, J., Yang, J., Wang, Z., Hua, Q.: Artificial intelligence for cloud-assisted smart factory. IEEE Access 6, 55419–55430 (2018)CrossRef
49.
go back to reference Gray-Hawkins, M., Lăzăroiu, G.: Industrial artificial intelligence, sustainable product lifecycle management, and internet of things sensing networks in cyber-physical smart manufacturing systems. J. Self-Gov. Manag. Econ. 8(4), 19–28 (2020)CrossRef Gray-Hawkins, M., Lăzăroiu, G.: Industrial artificial intelligence, sustainable product lifecycle management, and internet of things sensing networks in cyber-physical smart manufacturing systems. J. Self-Gov. Manag. Econ. 8(4), 19–28 (2020)CrossRef
50.
go back to reference Zhou, G., Zhang, C., Li, Z., Ding, K., Wang, C.: Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing. Int. J. Prod. Res. 58(4), 1034–1051 (2020)CrossRef Zhou, G., Zhang, C., Li, Z., Ding, K., Wang, C.: Knowledge-driven digital twin manufacturing cell towards intelligent manufacturing. Int. J. Prod. Res. 58(4), 1034–1051 (2020)CrossRef
Metadata
Title
Digital Transformation with Artificial Intelligence in the Insurance Industry
Author
Samet Gürsev
Copyright Year
2024
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-99-6062-0_30

Premium Partners