Working Group II: Impacts, Adaptation and Vulnerability

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8.3.3. Insurers' Vulnerability and Capacity to Absorb Losses

A central component of vulnerability for public and private insurers alike is actuarial uncertainty in the dimensions, location, or timing of extreme weather events. This is particularly true for insurance where the rate of damage rises faster than the driving weather phenomenon. Examples include the relationships between peak wind speeds and structural damages (Dlugolecki et al., 1996), average temperature changes and lightning strokes (Price and Rind, 1994; Dinnes, 1999; Reeve and Toumi, 1999), extreme temperature events and electric power reductions or crop damages (Colombo et al., 1999) and heat stress mortality (see Chapter 9), and precipitation and flooding (White and Etkin, 1997).

Changes in the spatial distribution of natural disasters pose special risks and challenges for the insurance sector. Localities to which risks shift will tend to be relatively inexperienced and unprepared to handle such risks, potentially resulting in a net societal increase in losses. A given insurer's vulnerability often extends internationally. For example, U.S. insurers collected nearly 15% of their premiums overseas in 1997, and the ratio has been growing (III, 1999). Reinsurers have a particularly high degree of international exposure.

Figure 8-5: Global insured natural catastrophe losses (right-hand scale) vs. property/casualty premium income (left-hand scale), using a 5-year running mean. Global losses are from Munich Re (2000) and premiums from Swiss Re (1999b and earlier years). Note that these data include only major weather-related losses (approximately half of total weather-related losses). Premiums include considerable revenues (and associated reserves and surplus, not usable to pay catastrophe losses) from non-weather-related business segments and from self-insurers. The numbers generally include "captive" self-insurers but not the less-formal types of self-insurance. Exposure—measured as the ratio of premiums to losses—increased by a factor of 2.9 between the endpoints and by 5.2 in the worst single year (1993) within this time interval.

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