A Pioneering Vulnerability Functions Framework for Casualty CAT Models

By Silvia Yang, Ziqi He, Mehrdad Memari, Eric Gesick, Jay Guin

November 24, 2025 / 3 min read

Verisk Catastrophe and Risk Solutions has developed a first-of-its-kind framework of vulnerability functions for casualty catastrophe modeling—mirroring the analytical tools used in property CAT models to quantify how different structures or assets respond to natural perils. These functions define the relationship between hazard intensity, such as wind speed and ground shaking, to the expected level of damage to buildings or assets, typically expressed as a probability distribution of ground-up loss ratios known as secondary uncertainty. They are developed and calibrated through a combination of engineering principles, empirical loss data, and subject matter expert judgment.

Casualty CAT modeling is still in its early stages compared with property CAT modeling. Despite the increasing frequency and severity of systemic liability events (such as litigation over PFAS chemicals or addictive opioids), there is no standardized equivalent to vulnerability functions in casualty lines. This absence limits the industry's ability to quantify tail risk, price casualty insurance and reinsurance effectively, and build resilient portfolios.

group-of-coworkers-revewing-data-on-screens

The novel approach developed by Verisk simulates court verdicts, identifying liable defendants, and calculating their payout shares in large-scale litigation scenarios. The framework is grounded in two widely accepted assumptions in the insurance industry, backed by empirical evidence:

Plaintiffs are more likely to target larger enterprises because of their visibility and perceived financial capacity.
These enterprises tend to attract a greater share of payouts in verdicts, reflecting their market dominance and perceived relative responsibility.

By embedding these principles into a scalable, probabilistic model, the new framework introduces a structured way to quantify systemic liability risk.

This modeling approach offers a transparent, stable, and repeatable method to estimate financial exposure. It simulates how courts might apportion damages among defendants based on factors such as company size, industry revenue size and distribution, and historical litigation outcomes. The resulting vulnerability functions provide a probabilistic distribution of loss outcomes, enabling insurers and reinsurers to assess exposure across portfolios, jurisdictions, lines of business, and industries. This innovation brings the same level of sophistication to casualty CAT modeling that has long existed in property CAT.

Beyond its technical merits, this framework has profound strategic implications. It enables the development of next-generation casualty CAT models that are modular, scalable, and adaptable to emerging risks. It can support more accurate pricing of casualty insurance and reinsurance, enhance capital modeling, and improve portfolio optimization. It also lays the groundwork for regulatory engagement through which carriers demonstrate the robustness of their risk assessments using transparent, data-driven methodologies.

As systemic liability risks continue to evolve, driven by globalization, technological disruption, and shifting societal norms, this framework offers a critical foundation for building resilience in the face of uncertainty. The framework is a landmark advancement that is poised to revolutionize the industry’s approach to systemic liability risk and establish a new standard for enterprise-scale modeling in casualty lines.

The vulnerability framework will be incorporated into the next release of our casualty and liability analytics platform, Arium, in Q1 2026 - embedded directly within the platform to give clients a new way to quantify, model, and manage systemic casualty and liability risks. This enhancement enables deeper portfolio insights and analytics for more confident pricing, planning, and portfolio management.

Authors’ contribution:

Silvia Yang: Developing the foundational modeling architecture

Ziqi He: Laying the groundwork for the modeling framework and driving project execution

Mehrdad Memari: Shaping the innovation strategy and guiding the project to completion

Eric Gesick: Overseeing model development while integrating actuarial expertise

Jay Guin: Overseeing model development and guiding the integration of secondary uncertainty into the modeling framework

Contact our team today to explore how this capability can support your organization’s risk strategy.