Demonstrates the integration of expert opinion into predictive distributions for loss reserving, suggesting improved adaptability in practice.
This paper shows how expert opinion can be inserted into a stochastic framework for loss reserving. The reserving methods used are the chain-ladder and Bornhuetter-Ferguson, and the stochastic framework follows England and Verrall. Although stochastic models have been studied, there are two main obstacles to their more frequent use in practice: ease of implementation and adaptability to user needs. This paper attempts to address these obstacles by utilizing Bayesian methods, and describing in some detail the implementation, using freely available software and programs supplied in the Appendix.
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R. J. Verrall (2007) studied this question.
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