Table Info

Table 2.

Characteristics summary of the 12 selected publications

Number	Title	Author	Date	Type	Study design	Identified applications of AI	Identified challenges facing AI	Identified opportunities
1	Legal status of artificial intelligence-based health insurance services: Challenges, opportunities for customer protection [8]	Riyanti R	2022	Cross-sectional	Quantitative study	N/A	Legal challenges Security Privacy	N/A
2	Explainable Artificial Intelligence (XAI) in Insurance [9]	Owens E, Sheehan B, Mullins M, Cunneen M, Ressel J, Castignani G	2022	Systematic review	Qualitative study	Fraud detection Claims reserving	N/A	Claims management Insurance fraud detection
3	AI Insurance: How Liability Insurance Can Drive the Responsible Adoption of Artificial Intelligence in Health Care [10]	Stern AD, Goldfarb A, Minssen T, Price II WN	2022	Literature review	Qualitative study	Insurance product pricing	Reliability Uncertainties	N/A
4	Blockchain and AI-Empowered Healthcare Insurance Fraud Detection: an Analysis, Architecture, and Future Prospects [11]	Kapadiya K, Patel U, Gupta R, Alshehri M, Tanwar S, Sharma G, Bokoro PN	2022	Cross-sectional	Quantitative study	Fraud detection	Security Privacy Fraud issues	N/A
5	Machine Learning-Based Regression Framework to Predict Health Insurance Premiums [12]	Kaushik K, Bhardwaj A, Dwivedi AD, Singh R	2022	Literature review	Qualitative study	Insurance pricing Use of chatbots Claim settlement Personalized health insurance policies Cost-effectiveness Underwriting	N/A	N/A
6	Key Principles of Clinical Validation, Device Approval, and Insurance Coverage Decisions of Artificial Intelligence [13]	Park SH, Choi J, Byeon JS	2021	Cohort study	Quantitative study	Insurance coverage decisions	N/A	N/A
7	Algorithms in future insurance markets [14]	Śmietanka M, Koshiyama A, Treleaven P	2021	Literature review	Qualitative study	Personalized product offerings Behavioral product pricing Risk assessment Fraud detection	Data strategy Inadequate technical knowledge Aversion towards AI	Automation Security
8	Improving the Accuracy and Transparency of Underwriting with Artificial Intelligence to Transform the Life-Insurance Industry [15]	Maier M, Carlotto H, Saperstein S, Sanchez F, Balogun S, Merritt S	2020	Cross-sectional	Quantitative study	Underwriting	N/A	N/A
9	Artificial Intelligence (AI) in Insurance: A Futuristic Approach [16]	Gupta R	2020	Review	Qualitative study	Chatbots, machine learning, robotic process automation (RPA), robo-advisors Fraud detection Accurate decisions Provide better coverage Price risk abilities	N/A	Cross-selling opportunities
10	Artificial Intelligence in Insurance Sector [17]	Kumar N, Srivastava JD, Bisht H	2019	Literature review	Quantitative study	TensorFlow, Fukoku, H2O.ai, Bots, APIs Portfolio innovations Optimizing sales and marketing Improving customer experience Insurance fraud	N/A	N/A
11	How AI is changing the insurance landscape [18]	Corea F	2019	Review	Qualitative study	Buying and pricing insurance products	N/A	N/A
12	Resolving asymmetry of medical information by using AI: Japanese people's change behavior by technology-driven innovation for Japanese health insurance [19]	Yamasaki K, Hosoya R	2018	Case study	Qualitative study	Data organization (resolving asymmetry) and analysis	N/A	Innovations

N/A: not applicable

Declarations

Author contributions

AAA: Conceptualization, Data curation, Methodology, Writing—original draft, Writing—review & editing. SA: Data curation, Writing—original draft, Writing—review & editing. Both authors read and approved the submitted version.

Conflicts of interest

The authors declare that they have no conflicts of interest.

Ethical approval

Not applicable.

Consent to participate

Not applicable.

Consent to publication

Not applicable.

Availability of data and materials

Data is available upon reasonable request.

Funding

Not applicable.

Copyright

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Stern AD, Goldfarb A, Minssen T, Price II WN. AI Insurance: How Liability Insurance Can Drive the Responsible Adoption of Artificial Intelligence in Health Care. NEJM Catal Innov Care Deliv. 2022;3:1–10. [DOI]

11.

Kapadiya K, Patel U, Gupta R, Alshehri M, Tanwar S, Sharma G, et al. Blockchain and AI-Empowered Healthcare Insurance Fraud Detection: an Analysis, Architecture, and Future Prospects. IEEE Access. 2022;10:79606–27. [DOI]

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13.

Park SH, Choi J, Byeon JS. Key Principles of Clinical Validation, Device Approval, and Insurance Coverage Decisions of Artificial Intelligence. Korean J Radiol. 2021;22:442–53. [DOI] [PubMed] [PMC]

14.

Śmietanka M, Koshiyama A, Treleaven P. Algorithms in future insurance markets. Int J Data Sci Big Data Anal. 2021;1:1–19.

15.

Maier M, Carlotto H, Saperstein S, Sanchez F, Balogun S, Merritt S. Improving the Accuracy and Transparency of Underwriting with Artificial Intelligence to Transform the Life-Insurance Industry. AI Mag. 2020;41:78–93. [DOI]

16.

Gupta R. Artificial Intelligence (AI) in Insurance: A Futuristic Approach. Shodh Drishti. 2020;11:6–10.

17.

Kumar N, Srivastava JD, Bisht H. Artificial Intelligence in Insurance Sector. J Gujarat Res Soc. 2019;21:79–91.

18.

Corea F. How AI is changing the insurance landscape. Applied artificial intelligence: where AI can be used in business. Cham: Springer; 2019. pp. 5–10. [DOI]

19.

Yamasaki K, Hosoya R. Resolving asymmetry of medical information by using AI: Japanese people's change behavior by technology-driven innovation for Japanese health insurance. 2018 Portland International Conference on Management of Engineering and Technology (PICMET). Honolulu: IEEE; 2018. pp. 1–5. [DOI]

20.

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