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Validation of a probabilistic model for hurricane insurance loss projections in Florida

Author

Listed:
  • Pinelli, J.-P.
  • Gurley, K.R.
  • Subramanian, C.S.
  • Hamid, S.S.
  • Pita, G.L.

Abstract

The Florida Public Hurricane Loss Model is one of the first public models accessible for scrutiny to the scientific community, incorporating state of the art techniques in hurricane and vulnerability modeling. The model was developed for Florida, and is applicable to other hurricane-prone regions where construction practice is similar. The 2004 hurricane season produced substantial losses in Florida, and provided the means to validate and calibrate this model against actual claim data. This paper presents the predicted losses for several insurance portfolios corresponding to hurricanes Andrew, Charley, and Frances. The predictions are validated against the actual claim data. Physical damage predictions for external building components are also compared to observed damage. The analyses show that the predictive capabilities of the model were substantially improved after the calibration against the 2004 data. The methodology also shows that the predictive capabilities of the model could be enhanced if insurance companies report more detailed information about the structures they insure and the types of damage they suffer. This model can be a powerful tool for the study of risk reduction strategies.

Suggested Citation

  • Pinelli, J.-P. & Gurley, K.R. & Subramanian, C.S. & Hamid, S.S. & Pita, G.L., 2008. "Validation of a probabilistic model for hurricane insurance loss projections in Florida," Reliability Engineering and System Safety, Elsevier, vol. 93(12), pages 1896-1905.
  • Handle: RePEc:eee:reensy:v:93:y:2008:i:12:p:1896-1905
    DOI: 10.1016/j.ress.2008.03.017
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    Cited by:

    1. Sangki Park & John Lindt & Yue Li, 2013. "Application of the hybrid ABV procedure for assessing community risk to hurricanes spatially," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 68(2), pages 981-1000, September.
    2. Hong, Xu & Wan, Zhiqiang & Chen, Jianbing, 2023. "Parallel assessment of the tropical cyclone wind hazard at multiple locations using the probability density evolution method integrated with the change of probability measure," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    3. Wei-ping Lou & Hai-yan Chen & Xin-fa Qiu & Qi-yi Tang & Feng Zheng, 2012. "Assessment of economic losses from tropical cyclone disasters based on PCA-BP," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 60(3), pages 819-829, February.
    4. Erdem Karaca & Hesaam Aslani, 2016. "Review of two Japan Typhoon catastrophe models for commercial and industrial properties," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 83(1), pages 19-40, August.

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