Artificial intelligence and personalization of insurance

Failure or delayed ignition

Bibliographic Data

ID5260356
AuthorsArthur Charpentier (0000-0003-3654-6286, Université du Québec à Montréal), Xavier Vamparys (0009-0004-4640-2408, Télécom Paris, corresponding author)
Year2025
Volume12
Issue1
Publication date2025-03-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueBig Data & Society (JOURNAL)
Journal identifiersISSN: 2053-9517 • E-ISSN: 2053-9517
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/20539517241291817
OpenAlexW4407397349
LanguageEN
Citations received2
References cited23

In insurance, there is still a significant gap between the anticipated disruption, due to big data and machine learning algorithms, and the actual implementation of behaviour-based personalization, as described by Meyers (2018). Here, we identify eight key factors that serve as fundamental obstacles to the radical transformation of insurance guarantees, aiming to closely align them with the risk profile of each policyholder. These obstacles include the collective nature of insurance, the entrenched beliefs of some insurance companies, challenges related to data collection and use for personalized pricing, limited interest from insurers in adopting new models as well as policyholders' reluctance towards embracing connected devices. Additionally, the hurdles of explainability, insurer inertia and ethical or societal considerations further complicate the path toward achieving highly individualized insurance pricing

Business · Computer security · Internet privacy · Personalization · World Wide Web · Computer Science · Insurance and Financial Risk Management

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