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Sébastien Farkas (LPSM, Sorbonne Université) "Cyber claim analysis through Generalized Pareto Regression Trees with applications to insurance"
1st Monday of each month
Time: 4:15 pm – 5:00 pm
Date: 03th of February 2020
Place: Room 3105
Sébastien Farkas (LPSM, Sorbonne Université) “Cyber claim analysis through Generalized Pareto Regression Trees with applications to insurance”
Abstract : With the rise of the cyber insurance market, there is a need of a better quantification of the economic impact of this new risk. Due to the relatively poor quality and consistency of databases on cyber events, and because of the heterogeneity of cyber claims, evaluating the appropriate premium and/or the required amount of reserves is a difficult task. In this paper, we propose a method based on regression trees to analyze cyber claims to identify criteria for claim classification and evaluation. We particularly focus on severe/extreme claims, by combining a Generalized Pareto modeling – legitimate from Extreme Value Theory – and the regression tree (CART) approach. We illustrate this methodology on a public database and briefly present an alternative methodology.
Joint work with : Olivier Lopez and Maud Thomas