This analysis compares robust loss reserving models, suggesting enhanced accuracy in actuarial predictions.
Robust statistical procedures have a growing body of literature and have been applied to loss severity fitting in actuarial applications. An introduction of robust methods for loss reserving is presented in this paper. In particular, following Tampubolon (2008), reserving models for a development triangle are compared based on the sensitivity of the reserve estimates to changes in individual data points. This measure of sensitivity is then related to the generalized degrees of freedom used by the model at each point.
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Venter et al. (2010) studied this question.
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