Sam Haynes, Vice President of Data and Analytics at Verisk, outlines how insurers are adapting their approach to strikes, riots, and civil commotion (SRCC), and political violence, as the frequency of riots increases and conflict zones expand
SRCC risk has moved rapidly up the agenda for insurers and reinsurers over the past few years. What key global trends are driving this heightened focus today?
SRCC has rapidly moved up the agenda for insurers and reinsurers since 2019, when five major events resulted in combined insured losses exceeding $10bn. More broadly, riots that impact commercial or municipal property were twice as common in 2025 as they were in 2022.
The mix of political, economic, and social factors that make countries prone to bouts of violent unrest, resulting in damage and business interruption remain present in dozens of countries globally. In 2025, according to our analysis, nearly 12,000 commercial or municipal properties were impacted by riots. This is up 20% from 2023 and 2024, despite each including a major insured loss event.
Given the combination of around 100 countries per year seeing riots that result in damage to commercial or municipal property, and the diffuse global footprint of SRCC and political violence books of business, it is no surprise that insurers are focusing more on the issue.
How are insurers leveraging the Verisk SRCC model to adjust pricing, underwriting strategies, or reserve allocations in the face of elevated global instability?
Verisk's SRCC catastrophe model for the United States applies rigorous probabilistic methods from natural catastrophe modelling to human-driven perils. By simulating 500,000 stochastic years of events, the model integrates political, social, and economic indicators to estimate event frequencies and severities, and produce high-resolution ZIP code-level losses for damage and business interruption for a set of exposures.
Outputs, including average annual loss, exceedance probabilities, and scenario-specific losses, allow insurers to quantify SRCC exposure with actuarial credibility. This supports precise underwriting, pricing, portfolio analysis, and capital allocation, moving beyond qualitative assessments to actionable insights.
In practice, insurers using the Verisk SRCC model can better anticipate emerging threats, identify high-risk exposures, and strengthen portfolio resilience to severe SRCC loss scenarios, enabling risk-adjusted pricing that better reflects the dynamics and possibilities that SRCC events can bring.
Unlike natural catastrophe events, which are a function of physical laws and for which, in most cases, rich datasets of historic events are available, SRCC is a human-driven issue and presents some unique challenges.
Firstly, while it may be easy to point to the large loss events of recent years, that is not nearly enough information on which to build a robust framework for assessing future SRCC insured losses. Secondly, the dynamics of SRCC events are inherently complex; there are the underlying conditions that make a country more prone to SRCC; thirdly, there are the sparks that set off an event, and finally, there are the many ways in which an event can play out. Through data collection, analysis, and cutting-edge modelling, we have taken the science-based principles of natural catastrophe modelling and applied them to SRCC.
This year, we've already seen significant political volatility around the world, including continued armed conflict, geopolitical tension, and protests. How do events like these influence the way the insurance industry thinks about SRCC and political violence more broadly?
In times of heightened uncertainty and a seemingly endless stream of geopolitical events, one can be forgiven for seeing political violence as a complex hazard that is impossible to manage.
It is important to remember that political violence is made up of distinct types of events, each with different actors, means, and paths to insured losses. Let's take SRCC, terrorism, and conflict as an example. Ultimately, the outcome of each event could be an insured asset being destroyed or damaged, but the drivers are very different, and the risk a given exposure faces will vary significantly depending on where they are in the world.
Those drivers can be measured and developed into transparent, validated, and comprehensive models that help insurers make better-informed decisions around underwriting and exposure management through accumulation analysis and scenario-based loss estimation. As loss estimation for political violence perils increasingly becomes an industry expectation, early adopters will be ahead of the game.
