Prediction of individual automobile RBNS claim reserves in the context of Solvency II
AbstractAutomobile bodily injury (BI) claims remain unsettled for a long time after the accident. The estimation of an accurate reserve for Reported But Not Settled (RBNS) claims is therefore vital for insurers. In accordance with the recommendation included in the Solvency II project (CEIOPS, 2007) a statistical model is here implemented for RBNS reserve estimation. Lognormality on empirical compensation cost data is observed for different levels of BI severity. The individual claim provision is estimated by allocating the expected mean compensation for the predicted severity of the victim’s injury, for which the upper bound is also computed. The BI severity is predicted by means of a heteroscedastic multiple choice model, because empirical evidence has found that the variability in the latent severity of injured individuals travelling by car is not constant. It is shown that this methodology can improve the accuracy of RBNS reserve estimation at all stages, as compared to the subjective assessment that has traditionally been made by practitioners.
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Bibliographic InfoPaper provided by University of Barcelona, Research Institute of Applied Economics in its series IREA Working Papers with number 200806.
Length: 23 pages
Date of creation: May 2008
Date of revision: May 2008
Automobile accident; Solvency II; bodily injury claims; individual RBNS reserve..;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2008-05-31 (All new papers)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Ayuso, Mercedes & Santolino, Miguel, 2007. "Predicting automobile claims bodily injury severity with sequential ordered logit models," Insurance: Mathematics and Economics, Elsevier, vol. 41(1), pages 71-83, July.
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