The bivariate Sarmanov distribution for insurance claim frequencies and average severities

Abstract

Real data studies emphasized situations where the classical independence assumption between the frequency and the severity of claims does not hold in the collective model. Therefore, there is an increasing interest in defining models that capture this dependence. In this paper, we introduce such a model based on Sarmanov’s bivariate distribution, which has the ability of joining different types of marginals in flexible dependence structures. More precisely, we join the claims frequency and the average severity by means of this distribution. We also suggest a maximum likelihood estimation procedure to estimate the parameters and illustrate it both on simulated and real data.