In the sixth part of our swan blog series, we take a look at the implications and challenges presented to life insurers when it comes to exploring climate risk through this lens.
What are gray rhinos?
Coined by author Michele Wucker, gray rhinos are highly probable, high-impact threats that are often overlooked. Imagine walking through a foggy morning in the savannah – you could spot a rhino if you were looking. But without paying attention, you might not notice it until it crashes into you, leaving no time to react.
Climate risk continues to evolve along a spectrum, from well-understood “white swans” to unknowable “black swans”, with “gray rhinos” representing high-probability, high-impact risks that are often insufficiently reflected in current practice. Across this series, we have observed how climate change is shifting risks along this spectrum, challenging traditional actuarial approaches. Events once considered remote are becoming more frequent, while more complex and systemic risks are emerging under conditions of deep uncertainty (part 1).
In financial markets, climate risks are increasingly observable and reflected in asset prices. While uncertainty remains high, particularly in relation to long-term transition pathways, these risks can be incorporated into valuation frameworks and capital models through the setting of best-estimate and shocked assumptions. Similarly, non-life underwriting risks have already materialised through rising catastrophe losses. These risks are identifiable, modelled, and priced, albeit with increasing volatility and structural uncertainty. In this sense, climate-related non-life risks sit midway on the black swan–gray rhino spectrum (part 2).
By contrast, life underwriting risks – mortality, morbidity – remain significantly more uncertain. Direct impacts such as heat or air pollution related to mortality and morbidity are increasingly observable. To the extent these risks are material, they can be allowed for in the best estimate and shocked assumptions, for example via a ‘climate term’.
However, the mechanisms through which climate change affects these risks are predominantly indirect, systemic, and long-term, with more material effects arising through second-order channels, including the spread of vector-borne diseases, pressure on food and water systems, strain on healthcare infrastructure, and widening socioeconomic inequality. These impacts are heterogeneous across regions and populations, contributing to a highly complex risk profile.
These indirect effects are not only difficult to quantify but are also highly interconnected. Climate change acts as a threat multiplier, amplifying existing vulnerabilities and creating feedback loops across health, economic, and social systems. As a result, these indirect impacts sit firmly within grey rhino territory – visible and developing, but not yet fully embedded within standard actuarial assumptions or models (part 4).
Policyholder behaviour introduces an additional layer of uncertainty. Climate-driven economic pressures, including inflation and reduced household income, may suppress demand for new business and increase lapse activity. Conversely, heightened awareness of emerging risks, such as the possibility of new diseases or higher prevalence of existing diseases, may support increased demand for protection products. These opposing effects create material uncertainty in both new business projections and in-force experience. Product design features, including guarantees and liquidity options, further increase exposure to behavioural risks and potential anti-selection. There is no clear best estimate to include in technical provisions or stressed assumptions (part 3).
Importantly, these risks should not be considered in isolation. Climate change is likely to alter the relationship between risks, reducing diversification benefits and increasing the potential for adverse co-movements. Risk aggregation, therefore, becomes critical in assessing overall exposure. Common climate drivers – such as extreme weather events and economic disruption – may increase correlations between market and demographic risks, leading to more pronounced tail outcomes.
For example, extreme weather events may simultaneously increase mortality rates and drive market volatility, impacting both liabilities and asset values. Similarly, economic stress may increase lapse rates at the same time as asset performance deteriorates, amplifying capital strain. Within demographic risks, shared drivers may strengthen dependencies between mortality, morbidity, and policyholder behaviour, while previously assumed relationships may weaken or reverse under systemic stress.
A key challenge in addressing these risks is the limited availability of relevant historical data. Climate change is altering the underlying risk environment in ways that reduce the relevance of experience. However, the absence of robust data does not justify inaction. Delaying recognition of these risks increases the likelihood that emerging grey rhinos remain unaddressed until their impacts are fully realised.
In response, life insurers may need to place greater emphasis on qualitative and exploratory approaches. Scenario analysis, expert judgement, and structured risk assessments can provide insight into potential future pathways and the evolution of risk relationships. Stress testing can be extended to consider the breakdown of diversification benefits, while monitoring frameworks can help identify early indicators of change (part 5).
Overall, the implications for actuarial practice are clear. Traditional approaches, grounded in historical data and stable relationships, may no longer be sufficient, and greater focus on forward-looking and adaptive methodologies may be required. Climate risk management should evolve to reflect the increasing importance of systemic, interconnected, and uncertain risks.
The central challenge is not the absence of signals, but the extent to which they are recognised and acted upon. As climate risks continue to transition along the swan–rhino spectrum, a proactive and holistic approach will be essential to ensure that emerging risks are identified and managed before they fully materialise.
