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Bayesian modelling of outstanding liabilities incorporating claim count uncertainty. (English) Zbl 1084.62544

Summary: This paper deals with the prediction of the amount of outstanding automobile claims that an insurance company will pay in the near future. We consider various competing models using Bayesian theory and Markov chain Monte Carlo methods. Claim counts are used in order to add a further hierarchical stage in the model with log-normally distributed claim amounts and its corresponding state space version. By this way, we incorporate information from both the outstanding claim amounts and counts data resulting to new model formulations. We provide implementation details and illustrations with real insurance data.

MSC:

62P05 Applications of statistics to actuarial sciences and financial mathematics
62F15 Bayesian inference
65C40 Numerical analysis or methods applied to Markov chains
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