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Abstract

This paper describes a spatial-dynamic, stochastic optimization model that ta1ces account of the complexities and dependencies of catastrophic risks. Following a description of the general model, the paper briefly discusses a case study of earthquake risk in the Irkutsk region of Russia. For this purpose the risk management model is customized to explicitly incorporate the geological characteristics of the region, as well as the seismic hazards and the vulnerability of the built environment. In its general form, the model can analyze the interplay between investment in mitigation and risk-sharing measures. In the application described in this paper, the model generates insurance strategies that are less vulnerable to insolvency.

22. Catastrophic Risk Management: Flood and Seismic Risks Case Studies

“…This discussion closely follows the papers [1,2,14,15,17,18]. Section 22.2 illustrates the peculiarities of emerging stochastic optimization problems by using a typical model of risk theory.…”

“…To better understand the main features of the model described in the next section, let us sketch out some case studies [1,2,17] carried out at the International Institute for Applied Systems Analysis (IIASA). The main concern of these case studies is related to issues emphasized by Froot in [19].…”

“…The model emphasizes the cooperation of various agents in dealing with catastrophes. The solution to catastrophic risk management, especially for small economies with limited risk absorption capacity, cannot be accomplished (see [2,8,37]) without pooling of risk exposures. The proposed model involves pooling risks through mandatory flood insurance based on location-specific exposures, partial compensation to the flood victims by the central government, and a contingent credit to the pool.…”

“…For the seismic-prone Irkutsk region in Russia [2], the focus of the analysis was on the feasibility of an insurance pool to cover catastrophic losses subject to strong standard insolvency regulations. In contrast to the case study in Hungary, the contribution of different insurers to the stability of the pool was explicitly analyzed by taking into account the transaction costs and effects of mutual dependencies among claims from different locations (cells).…”

“…Such models can be even more critical for guidance and setting regulations in countries that are moving toward market economies. In Russia [2] new legislative instruments and government resolutions are creating a framework for risk management similar to that existing in the OECD countries. However, in Russia and other transition countries the emergence of a viable insurance industry is slow and subject to insolvency risks due to problems of the national economies, the lack of consolidated experience and practicable guidance, and the lack of sufficient risk reserves of the existing companies.…”