Forecasting the maximum compensation offer in the automobile BI claims negotiation process

Most motor bodily injury (BI) claims are settled by negotiation, with fewer than 5% of cases going to court. A well-defined negotiation strategy is thus very useful for insurance companies. In this paper we assume that the monetary compensation awarded in court is the upper amount to be offered by the insurer in the negotiation process. Using a real database, a log-linear model is implemented to estimate the maximal offer. Non-spherical disturbances are detected. Correlation occurs when various claims are settled in the same judicial verdict. Group wise heteroscedasticity is due to the influence of the forensic valuation on the final compensation amount. An alternative approximation based on generalized inference theory is applied to estimate confidence intervals on variance components, since classical interval estimates may be unreliable for datasets with unbalanced structures.

Prediction of individual automobile RBNS claim reserves in the context of Solvency II

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.

[Automobile à 3 roues] : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58397

Monaco, [avril] 1920, [le pilote ou le constructeur de canot automobile Victor] Despujols : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58817

Monaco, [avril] 1920, [le canot automobile] Sunbeam Despujols II : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58850

Monaco, [avril] 1920, [le canot automobile] Sunbeam Despujols I : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58852

Monaco, [avril] 1920, [le canot automobile] Sunbeam Despujols I : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58856

[Monaco, avril 1920, le canot automobile] Sunbeam Despujols I : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58858

Monaco, [avril] 1920, [le canot automobile] Vicuna IV : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58884

Monaco, [avril] 1920, [le canot automobile] Sunbeam Despujols II : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58889

Monaco, [avril] 1920, [le canot automobile] Sunbeam Despujols I : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58892

Monaco, [avril] 1920, [le canot automobile] Crusader : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58897

Monaco, [avril] 1920, [le canot automobile] Sunbeam Despujols I : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58902

Monaco, [avril] 1920, [le canot automobile] Sunbeam Despujols I : [photographie de presse] / [Agence Rol]

Référence bibliographique : Rol, 58904