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• W2007604013 abstract "Modeling insurance claim counts is a critical component in the ratemaking process for property and casualty insurance. This article explores the usefulness of copulas to model the number of insurance claims for an individual policyholder within a longitudinal context. To address the limitations of copulas commonly attributed to multivariate discrete data, we adopt a jittering method to the claim counts which has the effect of continuitizing the data. Elliptical copulas are proposed to accommodate the intertemporal nature of the jittered claim counts and the unobservable subject-specific heterogeneity on the frequency of claims. Observable subject-specific effects are accounted in the model by using available covariate information through a regression model. The predictive distribution together with the corresponding credibility of claim frequency can be derived from the model for ratemaking and risk classification purposes. For empirical illustration, we analyze an unbalanced longitudinal dataset of claim counts observed from a portfolio of automobile insurance policies of a general insurer in Singapore. We further establish the validity of the calibrated copula model, and demonstrate that the copula with jittering method outperforms standard count regression models." @default.
• W2007604013 created "2016-06-24" @default.
• W2007604013 creator A5001221706 @default.
• W2007604013 creator A5086867154 @default.
• W2007604013 date "2011-01-01" @default.
• W2007604013 modified "2023-09-25" @default.
• W2007604013 title "Longitudinal Modeling of Insurance Claim Counts Using Jitters" @default.
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• W2007604013 doi "https://doi.org/10.2139/ssrn.1926237" @default.
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