Abstract
In property insurance, a contract often provides the policyholder with protection against damages to the insured properties that arise from a variety of perils. We propose a multivariate framework for pricing property insurance contracts with multiperil coverage in a longitudinal context. Specifically, a two-part model is employed to accommodate the excess of 0s and heavy tails in the insurance loss cost, and a Gaussian copula with a structured correlation is used to capture the dependence within and between perils, as well as their interaction. Using the government property insurance data from the state of Wisconsin in the USA, we show that the multiperil claim model has important implications in both experience rating and risk margin analysis.
Original language | English (US) |
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Pages (from-to) | 647-668 |
Number of pages | 22 |
Journal | Journal of the Royal Statistical Society. Series A: Statistics in Society |
Volume | 182 |
Issue number | 2 |
DOIs | |
State | Published - Feb 1 2019 |
Externally published | Yes |
Bibliographical note
Funding Information:We thank the Joint Editor and two reviewers for their comments that helped to improve the presentation of the paper. Peng Shi acknowledges the support by the Centers of Actuarial Excellence research grant from the Society of Actuaries and the Fall Research Competition from the University of Wisconsin–Madison.
Funding Information:
We thank the Joint Editor and two reviewers for their comments that helped to improve the presentation of the paper. Peng Shi acknowledges the support by the Centers of Actuarial Excellence research grant from the Society of Actuaries and the Fall Research Competition from the University of Wisconsin?Madison.
Publisher Copyright:
© 2018 The Authors Journal of the Royal Statistical Society: Series A (Statistics in Society) Published by John Wiley & Sons Ltd on behalf of Royal Statistical Society.
Keywords
- Gaussian copula
- Multiperil rate making
- Multivariate longitudinal data
- Predictive distribution
- Zero inflation