8.3.4.2. Adaptation Mechanisms: Risk Reduction

Although risk-spreading is largely an economic and distributional process, risk reduction focuses more on technology, environmental management, land-use planning, engineered disaster preparedness/ recovery, and predictive modeling. Hooke (2000) provides a good overview of the challenges facing risk-reduction initiatives. The UN's International Decade for Natural Disaster Reduction (IDNDR) is a leading example of international cooperation in this area.

The insurance industry is an important participant in partnership with other public and private entities (Ryland, 2000). Examples include the use of geographic information systems to better understand and pinpoint risks, land-use planning, flood control programs, early warning systems, sustainable forest management, coastal defense, and wind-resistant construction techniques supported by building codes (Bourrelier et al., 2000; Davenport, 2000; Hamilton, 2000; Hooke, 2000; Sudo et al., 2000). However, the scale of effort has been much smaller than that anticipated for global climatic changes, and loss prevention generally has focused on fortifying the individual against perils, rather than reducing the peril itself (Kunreuther and Roth, 1998) and on post-disaster actions (Ryland, 2000).

Any discussion of vulnerability, impacts, and adaptation also should include insurance brokers, agents, risk managers, and trade associations. In 1998, there were more than 750,000 such workers in the United States alone (III, 1999).
A key but often untapped opportunity is to rebuild damaged structures in a more disaster-resistant fashion following loss events, as in the U.S. National Flood Insurance Program. Pervasive problems with building code enforcement and compliance have emerged following natural disasters. For example, 70% of the losses from Hurricane Alicia were traced to lax code enforcement (III, 2000a). Building industry stakeholders often resist new codes. Reinvigorating businesses and other forms of economic activity also is central to disaster recovery (Carrido, 2000).

Energy systems can have important implications for economic and insured losses through the vulnerability (reliability and/or physical damage) of energy generation, transmission, and distribution technologies (Epps, 1997; Keener, 1997; Deering and Thornton, 2000). Hydroelectric power resources, for example, are weather sensitive (see Chapter 15). Climate change may confound the actuarial basis for weather-related insurance provided to energy producers and for utility interruption insurance provided to energy users. Energy-related business interruption (via lightning damages, interrupted operations, inventory spoilage, event cancellation, disrupted tourism, etc.) is a significant weather-related exposure faced by the insurance sector (as evidenced by the extended power failure faced by Auckland, New Zealand, following a major heat wave in 1998). The North American ice storm of 1998 offers another dramatic example of the role of power disruption in disaster-related insurance losses (Lecomte and Gahagan, 1998; Table 15-5). Improved appraisal of the physical vulnerability of existing energy systems and of new technologies deployed for emission-reduction projects (e.g., as part of Clean Development Mechanism or Joint Implementation) would help to reduce vulnerability to extreme weather events and other losses (World Bank, 1999; Zwirner, 2000). The aftermath of Hurricane Andrew illustrated the complex nature of losses caused by natural disasters. About 20% of insured economic losses were related to business interruption (40% in the case of Hurricane Hugo) (Mills, 1996).

Effective risk reduction requires foresight. The insurance sector participates in a limited way in weather- and climate-related research and modeling (Kelly and Zeng, 1999). The Risk Prediction Initiative and the World Institute for Disaster Risk Management are two examples of insurer-funded research centers. Insurers' catastrophe models are not presently used in association with climate-prediction tools such as general circulation models (Peara and Mills, 1999). Their predictive power is poorly validated (Pielke, 1998; Pielke et al., 1999) and often exhibits significant unexplained model-to-model variation (Matthews et al., 1999; GAO, 2000a). Insurance regulators in the United States have resisted efforts to include them in ratemaking proceedings (III, 2000b). Thus, the insurance community may stand to benefit from analytical collaboration with the natural sciences community (Nutter 1996; Changnon et al., 1997; Zeng, 2000; Mills et al., 2001). Formal solvency analyses conducted by insurance regulators also could benefit from more explicit treatment of future climate scenarios.

Although much progress has been made in risk-reduction technology per se, attention is increasingly focused on problems of implementation. Key issues identified by IDNDR include public awareness of risks, training of practitioners, commitment by public officials, and justification and financing of risk-reduction strategies (Hamilton, 2000; Hooke, 2000)—all areas where the financial services sector can play a part.

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