Policyholder Lifecycle Modelling and Offer Optimisation: AI-Driven Frameworks for Personalised Insurance Product Recommendation

Authors

  • Emily Chen Associate Professor of Computer Science, City College of New York

Keywords:

policyholder lifecycle modelling, offer optimisation, frameworks, personalised insurance product recommendation, machine learning

Abstract

Personalized insurance offers are increasingly gaining importance in today’s growing digital world. Insurance organizations aim to tailor their products and services to the increasing needs and requirements of their customers. The major objective is to maximize customer satisfaction and enhance customer retention and loyalty. Traditional insurance organizations operate on the premise that all clients have the same needs and requirements.

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Published

31-12-2025

How to Cite

[1]
“Policyholder Lifecycle Modelling and Offer Optimisation: AI-Driven Frameworks for Personalised Insurance Product Recommendation”, Human-Computer Interaction Persp., vol. 5, no. 2, pp. 1–13, Dec. 2025, Accessed: Jun. 04, 2026. [Online]. Available: https://thesciencebrigade.com/hcip/article/view/810