Insurers, reinsurers, and brokers need to understand their potential liability risks resulting from the changing climate. Fortunately, the tools insurers, reinsurers, and brokers need to help them understand their exposures are available. Let’s discuss two distinct (but related) approaches for quantifying some climate change liability–related impacts.
Direct Developments and the Single Scenario Approach
There are new types of litigation, alleged harms, and damages sought because of climate change–specific developments that can be captured by a single scenario. These can be considered new liability events that require specific footprints and specific quantification frameworks to derive losses in the absence of historical precedents.
For example, consider “direct causal contribution” scenarios, where specific plaintiffs might argue that they suffer harms and damages due to specific defendants contributing to climate change, such as sea level rise potentially leading to more frequent and more severe flooding. We may not necessarily have seen these types of claims in past liability events. Modeling this potential event requires the development of a framework to quantify potential losses around sea level rise liability absent the existence of similar types of loss scenarios occurring in the past.
This single scenario approach might, however, only capture a slice of the full universe of potential climate change impacts on liability.
Indirect Risks
Instead, many new liability exposures resulting from climate change may be due to systemic changes to underlying conditions that can increase the frequency and/or severity of known or recurring types of events. These would not be new events, per se, requiring a novel approach to parameterization. Rather, they would be events that had already happened but that may happen more often and/or with greater damages than before because of climate change (or social/political responses to climate change).
To illustrate, let’s look for a moment at a similar issue—recessions and their relationship to liability. A recession doesn’t itself trigger liability losses; rather, it impacts the types of events that typically trigger liability losses. So, a recession isn’t a peril per se, but an increase in company bankruptcies due to a recession could lead to an increased exposure to director and officer liability (D&O) policies. A recession changes the underlying conditions such that certain events happen more often, or are more likely to come to light. In some cases events may be even more severe or even may begin to implicate new industries and supply chains. Bankruptcies happen in non-recessionary years, but in a recessionary year we might expect more of them to happen and perhaps cluster in certain industries.
Similar thinking applies to climate change liability and is best illustrated when we consider corporate risks from climate change, such as disclosures. A corporate failing to disclose certain information or misleading investors may lead to stock price declines that then trigger shareholder lawsuits. In the past, these have often become significant liability loss events. Arium, Verisk’s data-driven liability risk modeling solution, captures many of these events in its scenario catalog. These lawsuits historically have had nothing to do with climate change. This type of litigation could, however, also arise claiming that corporates misled investors about the risks of climate change or even their contributions to climate change. A wide range of industries could be implicated, including energy, manufacturing, and even financial institutions. As scrutiny from regulators, policymakers, and the investing public into corporate climate risk disclosures grows, perhaps we might anticipate more management/professional liability scenarios related to “failing to disclose” climate change issues in certain industries than in a non-climate change conditioned world.
This is very similar to the approach for handling recessions described above—there are known events that occur at some frequency, but now the underlying conditions have changed; there might now be more of these events—and perhaps more severe events—due to climate change itself or social/political responses to climate change. Essentially this approach provides insurers, reinsurers, and brokers with a comparative view of each type of event in a world without climate change concerns, and then a view of a world where climate change concerns/risks begin to impact how often these events could occur—or if they’re more clustered in certain corporate sectors.
This principle can be applied to events beyond corporate misrepresentation. For example, consider utilities and wildfires. In California, utilities are held strictly liable for contributing to or causing wildfires. But it appears that climate change is changing certain underlying climatic conditions that could increase the risk of more and bigger fires. To reflect this changing reality, we applied an event set approach to modeling how climate change may impact this type of liability event: using Arium, we took historical wildfire liability scenarios and adjusted them to provide a view of how this type of liability event might change as the climate changes. Essentially, this approach provides a view of how wildfire liability event frequency and severity may change, and even how culpability may spread differently, in a world where wildfires may be more likely to happen and may be significantly more destructive.
Perturbed Events and the Multiple Scenario Approach
This, then, is the two-fold approach Verisk is taking to quantify potential climate change liability for Arium: (1) developing new single scenarios to capture direct climate change impacts on liability; and (2) adjusting liability event catalogs to provide an updated view of how these events might change as the climate changes or as the response to climate changes starts to gain momentum. As we’ve seen, there’s value in both approaches for quantifying the climate change liability–related impacts discussed here, and both approaches can be accounted for using Arium.
