Thanks to its outstanding performances, boosting has rapidly gained wide acceptance among actuaries. Hainaut et al. (2022) established that boosting can be conducted directly on the response under Tweedie loss function and log-link, by adapting the weights at each step. This is particularly useful to analyze low counts (typically, numbers of reported claims at policy level in personal lines). Huyghe et al. (2022) adopted this approach to propose a new boosting machine with cost-complexity pruned trees. In this approach, trees included in the score progressively reduce to the root-node one, in an adaptive way. This paper reviews these results and presents the new BT package in R contributed by Willame (2022), which is designed to implement this approach for insurance studies. A numerical illustration demonstrates the relevance of the new tool for insurance pricing.
Keywords: Risk classification, Boosting, Adaptive Boosting, Regression Trees.
Sector: Insurance
Expertise: Insurance pricing
Authors: Gireg Willame,
Julien Trufin and Michel Denuit
Publisher: Detralytics
Date: April 2023
Language: English
Pages: 24
Reference : Detra Note 2023-3
Gireg a acquis d'importantes connaissances en matière d'assurance non-vie, telles que la gestion des risques, la tarification particuliers/PME et la réassurance. En outre, il a travaillé sur de nombreux projets internes allant du calcul des réserves aux applications de Machine Learning. Passionné par la modélisation, il a développé de solides compétences en codage au cours de ses différentes missions.
Julien est Scientific Advisor chez Detralytics et Professeur en sciences actuarielles au sein du département de mathématiques de l’Université Libre de Bruxelles. Il possède une expérience en tant que consultant et un solide parcours académique développé au sein d’institutions de renom, dont l’Université Laval (Canada), l’UCL et l’ULB (Belgique). Chez Detralytics, Julien encadre les jeunes talents, dispense des formations de pointe, stimule l’innovation et supervise les projets de R&D.
Michel is a Scientific Advisor at Detralytics, as well as a professor in actuarial science at the Université Catholique de Louvain. He has international experience as a visiting professor, and has promoted many projects in collaboration with the industry. At Detralytics, Michel coaches young talents, provides cutting-edge training, fosters innovation and oversees R&D projects.
