Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location-Specific Premiums in the Netherlands

Ermolieva, T., Filatova, T., Ermoliev, Y., Obersteiner, M. ORCID: https://orcid.org/0000-0001-6981-2769, de Bruijn, K. M., & Jeuken, A. (2016). Flood Catastrophe Model for Designing Optimal Flood Insurance Program: Estimating Location-Specific Premiums in the Netherlands. Risk Analysis 1-17. 10.1111/risa.12589.

Preview

Text Flood catastrophe model.pdf - Accepted Version Available under License Creative Commons Attribution. Download (1MB) | Preview

Abstract

As flood risks grow worldwide, a well-designed insurance program engaging various stakeholders becomes a vital instrument in flood risk management. The main challenge concerns the applicability of standard approaches for calculating insurance premiums of rare catastrophic losses. This article focuses on the design of a flood-loss-sharing program involving private insurance based on location-specific exposures. The analysis is guided by a developed integrated catastrophe risk management (ICRM) model consisting of a GIS-based flood model and a stochastic optimization procedure with respect to location-specific risk exposures. To achieve the stability and robustness of the program towards floods with various recurrences, the ICRM uses stochastic optimization procedure, which relies on quantile-related risk functions of a systemic insolvency involving overpayments and underpayments of the stakeholders. Two alternative ways of calculating insurance premiums are compared: the robust derived with the ICRM and the traditional average annual loss approach. The applicability of the proposed model is illustrated in a case study of a Rotterdam area outside the main flood protection system in the Netherlands. Our numerical experiments demonstrate essential advantages of the robust premiums, namely, that they: (1) guarantee the program's solvency under all relevant flood scenarios rather than one average event; (2) establish a tradeoff between the security of the program and the welfare of locations; and (3) decrease the need for other risk transfer and risk reduction measures.

Item Type:	Article
Uncontrolled Keywords:	Flood risk; loss-sharing programs; quantile-related stochastic optimization; spatial catastrophe model
Research Programs:	Ecosystems Services and Management (ESM)
Depositing User:	Michaela Rossini
Date Deposited:	29 Mar 2016 12:33
Last Modified:	02 Feb 2022 14:11
URI:	https://pure.iiasa.ac.at/12333

Actions (login required)

View Item