Presenter: Melanie Averhoff, AU

Title: Experience Rating in the Cramér-Lundberg Model

Abstract: This paper provides a study of how experience rating on both claim frequency and severity impacts the solvency of an insurance business in the continuous-time Cramér Lundberg model. This is done by treating the claim parameters as random outcomes and continuously updating the premiums using Bayesian estimators. In the analysis, the claim sizes conditional on the severity parameter are assumed to be light-tailed. The main contributions are large deviation results, where the asymptotic ruin probabilities are found for a model updating the premium based upon both frequency and severity. This asymptotic ruin probability is compared to the one of a model, which updates the premium solely based on claim frequency. Our findings are illustrated with a parametric example, where the conditional claim size are exponentially distributed, and the severity parameter is the outcome of gamma distribution.

PhD presentation as part of mandatory 1st or 3rd year presentation. The time is extended to one hour; the presenter has 40 minutes for the presentation, 5-10 minutes for the discussant, and 5-10 minutes for questions.

Organizers: Stefan Hirth and Anders Merrild Posselt