But some warning signs are already starting to emerge. Insurance costs have been increasing rapidly in recent years due to a number of expensive disasters, growing concerns about climate change, and above-average reconstruction inflation. This has created a particularly challenging market for primary insurers, who have been struggling to secure sufficient reinsurance for their riskiest exposures. These factors have contributed, in part, to some firms withdrawing cover from high-risk areas such as Florida and California. Given these recent trends, it is not difficult to envision a situation in which the rate of change causes significant market dislocation that cannot easily be addressed as part of the annual policy cycle.
This scenario is made all the more challenging by uncertainty. Where there is ambiguity in the magnitude of the contribution of climate change to increasing claims (e.g., due to the lack of enough historical data to detect a statistically significant trend), insurance markets are susceptible to contagion. Similar to the social contagion Malcolm Gladwell wrote about, small behavioral changes could accumulate until there is a moment of critical mass. In other words, if the concerns about the future impacts of climate change grow large enough, rapid changes in insurance markets could happen over a short period of time, inducing tipping points before the actual impacts are fully realized.
Trend risk scenarios
The real question for insurance companies is how to assess the risks from rate-induced tipping points. Physical climate risk scenarios currently used by insurers are usually designed as instantaneous shocks, whereby a future climate state is applied to present-day market conditions, exposures, and business models (Figure 1a). While this approach is valuable for exploring a range of hypothetical futures, it does not easily allow us to consider the pace at which climatic or market variables will evolve over time.
To explicitly examine the rate of change, one option is to use trend risk scenarios (Figure 1b). Trend scenarios were first pioneered by Pierre Wack in the 1970s, who led the scenario analysis team at Royal Dutch Shell to analyze how the rate of change in a variable, such as market volatility, influences business outcomes. The same approach could be used by insurers to explore the implications of rate-based changes in weather-related claims, and potential thresholds at which market dislocation could occur.
To be useful for decision-making, these scenarios should focus on individual insurers’ exposures, business models, and objectives. One way to conduct such an exercise is via a normative (or reverse stress test) approach, which would allow an insurer to first specify an undesirable rate of change that is relevant for their business, before then exploring the different ways in which that change may materialise.
Incorporating rates of change into insurance decision-making has the potential to revolutionize the way that many firms think about, analyze, and manage climate change risks. As a result, it is vital that insurers begin to explore the potential risks posed by rate-induced tipping in both physical systems and insurance markets.