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Name: Martin Bladt

Talk Title: Phase-type distributions for Insurance pricing

Abstract: We address the task of modelling severity losses using segmentation when the distribution of the data does not fall into the usual regression frameworks, for instance in the presence of heavy tails. This is not an uncommon situation in lines of business such as third party liability insurance, where heavy-tails and multimodality more often than not hamper a direct statistical analysis. We propose to use regression models based on phase-type distributions, regressing on the intensity of their underlying inhomogeneous Markov intensity using an extension of the EM algorithm. These models are tailored for survival analysis, but are shown to be well suited for loss data modelling as well. We show that correct segmentation can be obscured or revealed depending on the quality of the baseline distribution.

This talk is an invited talk EVA 2021.