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Defining and estimating stochastic rate change in a dynamic general insurance portfolio

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  • Roland R. Ramsahai

Abstract

Rate change calculations in the literature involve deterministic methods that measure the change in premium for a given policy. The definition of rate change as a statistical parameter is proposed to address the stochastic nature of the premium charged for a policy. It promotes the idea that rate change is a property of an asymptotic population to be estimated, not just a property to measure or monitor in the sample of observed policies that are written. Various models and techniques are given for estimating this stochastic rate change and quantifying the uncertainty in the estimates. The use of matched sampling is emphasized for rate change estimation, as it adjusts for changes in policy characteristics by directly searching for similar policies across policy years. This avoids any of the assumptions and recipes that are required to re-rate policies in years where they were not written, as is common with deterministic methods. Such procedures can be subjective or implausible if the structure of rating algorithms change or there are complex and heterogeneous exposure bases and coverages. The methods discussed are applied to a motor premium database. The application includes the use of a genetic algorithm with parallel computations to automatically optimize the matched sampling.

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  • Roland R. Ramsahai, 2018. "Defining and estimating stochastic rate change in a dynamic general insurance portfolio," Papers 1810.10970, arXiv.org.
    • Handle: RePEc:arx:papers:1810.10970
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    References listed on IDEAS

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    7. Sekhon, Jasjeet S., 2011. "Multivariate and Propensity Score Matching Software with Automated Balance Optimization: The Matching package for R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 42(i07).
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