Most (re)insurance companies invest a great deal of time and resources in understanding their catastrophe risk, but nowhere near as much in understanding their casualty risk—despite the fact that most write just as much in casualty insurance premiums as they do in property insurance premiums. Although there may be a perception that casualty risk cannot be modeled, or perhaps isn’t well understood, AIR’s casualty analytics platform, Arium can help (re)insurance companies and brokers understand and quantify their casualty risk.
What Is Catastrophe Modeling?
The majority of (re)insurance companies and brokers are very familiar with catastrophe modeling as it relates to property damage. Catastrophe models are widely used to help (re)insurers prepare for the most extreme events, ensuring they are able to manage their risk and pay their claims.
AIR models are built using the best scientific understanding of natural catastrophes and how homes and businesses respond to the impacts of these events. The models estimate how frequent and severe future catastrophes are likely to be, where they are likely to occur, and the damage they can inflict. So, when you enter information about assets that are potentially in harm’s way, the model will output a view of possible loss outcomes.
Instead of relying on limited historical experience or a handful of scenarios, you get a more accurate picture of risk from tens of thousands of years of simulated activity, in no time at all. The results allow you not only to visualize the most at-risk areas, but also to quantify the potential damage and financial losses.
How Does Nat Cat Modeling Relate to Casualty Modeling?
Similar to how property (re)insurance provides coverage in the case of a natural catastrophe, casualty (re)insurance provides coverage from liability in the case that a policyholder is found legally responsible for its actions.
Much like AIR’s ability to quantify risk from several different types of natural catastrophes, Arium can capture risk from a variety of different casualty events, such as product liability, financial misconduct, and industrial accidents. Just as geography is used to establish proximity between property insurance exposures, trading relationships are used by Arium to determine which liability policies within your portfolio are more likely to be implicated by a common trigger or event.
Each casualty event is different. While historical data can be used as a guide, the ever-changing landscape of economic, legal, and regulatory factors can have dramatic effects on how casualty liabilities will trigger and spread. The Arium approach uses supply chain relationships to build scenarios that reflect correlations between the casualty policies in your portfolio. This approach offers a transparent and flexible way to quantify the impact of liability accumulations across your organization.
Watch the video to learn how Arium can help you identify, measure, and mitigate your casualty risk: