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Title: | Prediction of individual automobile RBNS claim reserves in the context of Solvency II |
Author: | Ayuso, Mercedes Santolino, Miguel |
Keywords: | Accidents de circulació Víctimes d'accidents de circulació Assegurances d'automòbils Assistència hospitalària Empirisme Traffic accidents Traffic accident victims Automobile insurance Hospital care Empiricism |
Issue Date: | 2008 |
Publisher: | Universitat de Barcelona. Institut de Recerca en Economia Aplicada Regional i Pública |
Series/Report no: | [WP E-IR08/06] |
Abstract: | Automobile 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. |
Note: | Reproducció del document publicat a: http://www.ub.edu/irea/working_papers/2008/200806.pdf |
It is part of: | IREA – Working Papers, 2008, IR08/06 |
URI: | http://hdl.handle.net/2445/62288 |
ISSN: | 2014-1254 |
Appears in Collections: | Documents de treball (Institut de Recerca en Economia Aplicada Regional i Pública (IREA)) |
Files in This Item:
File | Description | Size | Format | |
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IR08-006_Ayuso.pdf | 127.41 kB | Adobe PDF | View/Open |
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