A Recommendation System For Car Insurance - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Journal Articles European Actuarial Journal Year : 2020

A Recommendation System For Car Insurance

Abstract

We construct a recommendation system for car insurance, to allow agents to optimize up-selling performances, by selecting customers who are most likely to subscribe an additional cover. The originality of our recommendation system is to be suited for the insurance context. While traditional recommendation systems, designed for online platforms (e.g. e-commerce, videos), are constructed on huge datasets and aim to sug- gest the next best offer, insurance products have specific properties which imply that we must adopt a different approach. Our recommendation system combines the XGBoost algorithm and the Apriori algorithm to choose which customer should be recommended and which cover to rec- ommend, respectively. It has been tested in a pilot phase of around 150 recommendations, which shows that the approach outperforms standard results for similar up-selling campaigns. Recommendation system Up-selling Car insurance XGBoost algorithm Apriori algorithm
Fichier principal
Vignette du fichier
car_recommandation_final.pdf (341.79 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02420954 , version 1 (20-12-2019)
hal-02420954 , version 2 (06-07-2020)

Identifiers

Cite

Laurent Lesage, Madalina Deaconu, Antoine Lejay, Jorge Augusto Meira, Geoffrey Nichil, et al.. A Recommendation System For Car Insurance. European Actuarial Journal, 2020, 10, pp.377-398. ⟨10.1007/s13385-020-00236-z⟩. ⟨hal-02420954v2⟩
336 View
3855 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More