Artificial Intelligence and Personalization of Insurance: Failure or Delayed Ignition?

Charpentier, Arthur et Vamparys, Xavier (2025). « Artificial Intelligence and Personalization of Insurance: Failure or Delayed Ignition? ». Big Data and Society.

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Résumé

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 behavior-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.

Type:	Article de revue scientifique
Mots-clés ou Sujets:	insurance, auto insurance, health insurance, artificial intelligence
Unité d'appartenance:	Faculté des sciences > Département de mathématiques
Déposé par:	Arthur Charpentier
Date de dépôt:	27 janv. 2025 17:24
Dernière modification:	27 janv. 2025 17:24
Adresse URL :	http://archipel.uqam.ca/id/eprint/18446

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