This paper addresses the Bayesian estimation of the shape parameter of Pareto distributions, and its application to premium calculation of large claims excess of loss (XL) reinsurance contracts. It studies the use of the generalized inverse Gaussian (GIG) as a Pareto prior conjugate, a family that contains as a particular case the gamma distribution. An exact credibility formula is deduced allowing the calculation of individual reinsurance premiums. These are premiums suited to the excesses history of a sole portfolio. A family of predictive distributions for the excesses is derived. We apply our exact credibility model to a sample of excesses arisen in ten Spanish portfolios of liability motor insurance from year 1992 to year 2001.

Some reasons are given for paying special attention to the gross cost of catastrophe claims in planning and control. A method is then described of defining catastrophe claims and estimating their expected cost. The various steps in applying the method to real data and its performance for planning and control are discussed and illustrated in conjunction with an investigation carried out on a company portfolio.