Generalized linear models for dependent frequency and severity of insurance claims
| Autor: | Christian Genest, Juliana Schulz, José Garrido |
|---|---|
| Jazyk: | angličtina |
| Předmět: |
Statistics and Probability
Generalized linear model Economics and Econometrics Automobile insurance Poisson distribution 01 natural sciences Insurance claims Aggregate claims model 010104 statistics & probability symbols.namesake Simple (abstract algebra) 0502 economics and business Covariate Statistics Econometrics Economics 0101 mathematics Dependence Exponential dispersion models 050208 finance Loss cost 05 social sciences Term (time) Product (business) symbols Statistics Probability and Uncertainty Claim severity Claim frequency |
| Zdroj: | Insurance: Mathematics and Economics. :205-215 |
| ISSN: | 0167-6687 |
| DOI: | 10.1016/j.insmatheco.2016.06.006 |
| Popis: | Traditionally, claim counts and amounts are assumed to be independent in non-life insurance. This paper explores how this often unwarranted assumption can be relaxed in a simple way while incorporating rating factors into the model. The approach consists of fitting generalized linear models to the marginal frequency and the conditional severity components of the total claim cost; dependence between them is induced by treating the number of claims as a covariate in the model for the average claim size. In addition to being easy to implement, this modeling strategy has the advantage that when Poisson counts are assumed together with a log-link for the conditional severity model, the resulting pure premium is the product of a marginal mean frequency, a modified marginal mean severity, and an easily interpreted correction term that reflects the dependence. The approach is illustrated through simulations and applied to a Canadian automobile insurance dataset. |
| Databáze: | OpenAIRE |
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