Bayesian Modelling of Outstanding Liabilities in Non-Life Insurance

This dissertation focuses on the stochastic modelling of outstanding liabilities in non-life insurance, using Bayesian Statistics. Credible intervals and various statistical estimates can then be derived, whereas this is not the case with the numerical methods commonly used in the industry, such as the Chain Ladder, which only give point estimates. We ignore the claim numbers and concentrate only on claim amounts. The modelling requires intensive use of Bayesian methodology and Monte Carlo Markov chain (MCMC) techniques through the WinBUGS package. We also show that the results obtained are quite different from those with the Chain Ladder method, however there is no obvious way to define which method is better as more data would be necessary.