The purpose of the paper is to use the age of claims in the prediction of risks. A dynamic random effects model on longitudinal count data is presented...

We design a system for improving the calculation of the price to be charged for an insurance product. Standard pricing techniques generally take into account the expected severity of potential losses. However, the severity of a loss can be extremely high and the risk of a severe loss is not...

This paper presents an analysis of motor vehicle insurance claims relating to vehicle damage and to associated medical expenses. We use univariate severity distributions esti- mated with non-parametric methods. The methods are implemented using the statistical package R. The nonparametric...

In this paper, we illustrate the use of the Conditional Tail Expectation (CTE) risk measure on a set of bivariate real data consisting of two types of auto insurance claim costs. Several continuous bivariate distributions (normal, lognormal, skew-normal with the alternative log-skew-normal) are...

We present an overview of methods to estimate risk arising from operational losses. Our approach is based on the study of the statistical severity distribution of a single loss. We analyze the fundamental issues that arise in practice when modeling operational risk data. We address the...

In this paper we concentrate on the estimation of loss functions using nonparametric methods. We focus on the parametric transformation approach to kernel smoothing introduced by Wand, Marron and Ruppert (1991) and compare it with the standard kernel estimator and the multiplicative bias...