No More Guessing Your Portfolio's Risk with CAT Modeling

Guest Post by Lindsay Young (Shapiro), CSP, Assistant Vice President, Senior Risk Consultant, Hub International

In 2022, you would be hard-pressed to find any area of the country that hasn’t experienced a severe weather event within the last couple of years.

The U.S. alone saw more than 17,500 severe weather events in 2021, inclusive of floods, heat waves, wildfires, hurricanes, and droughts. Along with the number of events, the geographical reach of these events is expanding as well, with wildfires spreading wider and tropical storms making their way farther inland.

Other than human safety, one of the largest concerns for people in areas impacted by severe weather is the damage they inflict on property and real estate. Many real estate owners and operators now experiencing the profound effects of climate change and severe weather have never had to cope with this type of property damage threat before. It’s estimated that 1 in 10 homes were impacted by natural disasters in 2021, totaling nearly $57 billion in property damage.

These conditions have turned tools like catastrophe (CAT) modeling into essential resources for the real estate industry.

CAT modeling has been long used by insurers and risk managers to determine accurate risk management strategies and as a crucial tool in their underwriting process. But now real estate operations and owners are investing in CAT modeling to calculate the risk of a weather or natural disaster before investing in new property.

Here’s what you need to know about CAT modeling.

A quick history lesson

The first CAT model was introduced in 1987 by AIR Worldwide. However, it wasn’t until August of 1992 when Hurricane Andrew wreaked $15.5 billion of havoc across South Florida that the insurance industry truly transformed the way it predicted risk and implemented widespread use of CAT modeling.

Prior to Hurricane Andrew, many insurers relied on traditional actuarial techniques to estimate risk and losses. With these techniques, it wasn’t uncommon for losses to far exceed estimates. CAT, along with leaps in the sophistication of our ability to collect accurate data on weather variables and general increases in computer processing power, allows a more granular level of risk assessment based on detailed location and property information.

How CAT modeling works

In its simplest form, CAT modeling uses data to evaluate risk in specific geographic locations based on common perils in that area. For example, flood modeling for coastal regions or wildfire modeling for California residents. It converts immense amounts of geographical and property data, from soil samples to construction dates, into actionable information that predicts the severity and frequency of major events, such as earthquakes, flood, hurricanes, and wildfires and what that would mean for invested parties such as insurance companies and real estate owners.

There are four basic modules to CAT models, regardless of which peril is being analyzed: event, intensity, vulnerability, and financial modules. Each of these modules provides specific insight into your property or portfolio’s risk.

The event module uses historical data to generate possible and random event scenarios for the geographical location.

The intensity module determines the level of physical hazard that these events could carry based on location-specific risk characteristics for each simulated event.

The vulnerability module quantifies the expected damage based on the event and intensity modules, and the financial module measures the damage in monetary loss. When financial influencers such as primary insurance carrier information are provided, these modules can provide estimates based on policy conditions such as deductibles and limits.

For example, output from an earthquake analysis would include something along the lines of, “There is a X% chance of an earthquake occurring within the policy year of such magnitude as to cause $Y (or greater) losses to the property.”

The benefits of these modules can extend beyond a single property as well. CAT modeling can take the existing data in a given area and extend it across the entire geographic spread of insurable properties, giving insight into determining the right level of coverage for a given type of weather event for a specific location or an entire real estate portfolio.

Why is CAT modeling so important?

There is no way to precisely predict when the next catastrophic event is going to strike. As we’ve learned year over year, the timing and severity of natural events will always find a way to surprise us. But CAT modeling offers us the opportunity to make business decisions based on a range of potential outcomes. This is why accurate and detailed data is crucial to the usefulness of CAT modeling.

With the right information, you can take proactive measures to mitigate your exposure to risk. For some, this may mean choosing locations with less risk based on CAT model results. For others, CAT models will arm them with the right information to protect themselves from being under- or over-insured for specific properties. As mentioned earlier, insurers and risk managers have already been using CAT modeling to determine coverage strategies for quite some time. These same CAT models and probable maximum loss studies can provide owners and operators with insight to improve decision making as well.