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Cracking the CAT Modeling Code
As storms grow more unpredictable, the insurance industry is reassessing how we analyze and underwrite property risks.
When the remnants of Hurricane Helene struck the Carolinas in September 2024, its devastation extended over 500 miles inland — well beyond the areas initially predicted to be at risk. Shortly after, Hurricane Milton made landfall with unprecedented force, causing both wind damage and widespread flooding that models hadn’t anticipated. California wildfires raged in unprecedented ways, causing massive devastation. These events underscore a growing reality: our current approach to risk modeling isn’t exactly working.
With climate change introducing new variables and unpredictable storm behaviors, traditional CAT models face limitations. Now is the time for a fresh perspective — one that blends data, human expertise, and collaboration to improve risk assessment and deliver stronger outcomes for clients.
Jencap’s team of experts explore the following topics:
What CAT Models Do Well — and Where They Fall Short
CAT models are advanced tools designed to predict potential losses from catastrophic events like hurricanes, wildfires, and earthquakes. They rely on historical data, geospatial information, and simulations to help insurers assess risk and set premiums. However, these models are relatively new and continuously evolving. Their effectiveness depends on accurate inputs, and while they provide a strong foundation for decision-making, they can’t account for every real-world complexity.
“In CAT modeling, data tells us the what, but human insight tells us the why and how. Together, they create a comprehensive picture.”
CAT models are powerful tools that help insurers and brokers make informed decisions. Here’s where they help:
Pinpointing Loss Drivers
Aggregating Portfolio Risk
Scenario Simulations
By modeling hypothetical events, CAT models allow insurers to prepare for extreme but plausible scenarios, offering insights for reinsurance and premium pricing.
Standardizing Risk Evaluation
Despite their strengths, CAT models have significant limitations that require human expertise to bridge the gap.
Data Quality Dependence
Lack of Contingency Modeling
Emerging Trends and Events
Simplistic Outputs
Words Matter
Why Definitions Make All the Difference in Coverage
In insurance, the way we define and categorize events directly affects whether a policy covers them — or doesn’t. There are different deductibles, limits, and exclusions depending on categorization. As we continue to use CAT modeling as a tool, agreeing on language is extremely important, especially when it comes to complex, multi-layered risks.
Storm Surge vs. Flood vs. Named Windstorm
Storm surge is one of the most ambiguous perils in insurance coverage because it involves both wind-driven water and flooding, blurring the lines between traditional definitions. Some insurers categorize storm surge as part of a “named windstorm,” making it eligible for windstorm coverage. Others classify it as “flood damage,” which may require separate flood insurance to be covered. This key distinction significantly affects a policyholder’s ability to make a claim.
Adding to this complexity is the constantly shifting nature of flood risk. Changes in infrastructure — like the construction of a new levee, dam, or large-scale development — can alter flood zones and render past models inaccurate. That’s why it’s so important to regularly reassess policies to make sure they align with current risks, a challenge Jencap is uniquely positioned to navigate.
Imagine This:
A hurricane strikes a coastal area, generating a powerful storm surge that inundates a neighborhood. A homeowner’s property sustains significant damage from the surge.
Policy A: Covers storm surge under named windstorm coverage, recognizing the role of the hurricane in creating the surge. The homeowner’s claim is approved.
Policy B: Classifies storm surge as flood damage, requiring separate flood insurance for coverage. The homeowner’s claim is denied because the property, originally in a low-risk Flood Zone X when the policy was written, was recently reclassified as Flood Zone A due to infrastructure changes in the area.
Mudslide vs. Flood vs. “Acts of Nature”
Mudslides and debris flows often result from heavy rainfall or flooding, but they are not universally categorized as “flood” events. Insurers may define them differently based on the peril’s specific triggers, leading to confusion about coverage eligibility. These events frequently fall into the gaps between risk models and real-world complexities, as CAT models often fail to account for nuanced scenarios like debris flows carrying additional hazards. The classification can vary widely, and without clear definitions, claims can become contentious.
Picture This:
A severe rainstorm causes property damage to a homeowner in a mountainous region. Mud carrying rocks, trees, and debris flows downhill, crashing into their garage and ultimately destroying part of their home. The event becomes even more complicated when a large tree swept up by the mudslide destroys an entire section of the house.
Policy A: Covers the event as a flood-related peril because the mudslide was triggered by heavy rainfall. The claim is approved.
Policy B: Denies the claim, arguing that the damage resulted from a landslide or “act of nature,” which is excluded under the policy. Additionally, the involvement of the tree creates further ambiguity, as the insurer might categorize it as structural damage unrelated to the flood event.
Tsunami: Earthquake or Flood?
Tsunamis are unique catastrophes triggered by underwater earthquakes, yet their classification depends on how insurers define the event. Some policies treat tsunamis as “flood damage,” while others consider them part of “earthquake damage,” creating potential coverage gaps for businesses and homeowners.
What If:
A coastal resort is devastated by a tsunami caused by a powerful underwater earthquake. The damage includes both structural destruction from the initial wave and water damage from flooding.
Policy A: Categorizes the tsunami as part of an earthquake event, covering damages under an earthquake rider. The claim is approved.
Policy B: Classifies the tsunami as a flood event, requiring separate flood insurance to pay for damages. Without this additional policy, the resort’s claim is denied.
The Power of Parametric Insurance
Ambiguity is the last thing anyone wants during a disaster. It leaves businesses grappling with coverage disputes and lengthy claims processes. Parametric insurance eliminates the guesswork by offering clear, pre-defined payouts based on objective triggers — no loss adjustment process is required.
Unlike traditional insurance, which requires physical damage to trigger a payout, parametric policies account for broader economic losses. For example, a wildfire on Santa Catalina Island might never touch a hotel, but the resulting smoke and ash could drive wedding cancellations, leading to lost revenue. With parametric coverage, businesses can proactively secure protection against these indirect financial impacts.
How it Works
Defined Triggers
Coverage is activated if a specific event — such as a hurricane, earthquake, or wildfire — meets agreed-upon parameters like intensity, location, or duration.
Customizable Coverage Area
Your client defines the geographic boundary around the property, ensuring protection against relevant risks, whether it’s a five-mile radius or an entire region.
Pre-Set Payouts
Policyholders work with capital providers to determine the payout structure, such as $25 million for wildfire or $100 million for earthquake and windstorm.
Immediate Claims & Payments
Once the trigger event occurs, the payout is issued — no need to prove direct property damage. Funds can be used to cover any economic loss resulting from the event.
Parametric insurance puts control in your clients’ hands. What risks are they most concerned about? How much protection do they need? Once you work with them to define the parameters, they can gain peace of mind knowing that when disaster strikes, their coverage will activate seamlessly.
From Data to Decisions
The Ideal Risk Assessment Process
By integrating accurate data, advanced modeling, and expert insights, Jencap offers a comprehensive approach to risk management — tailored to meet the challenges of an unpredictable world for your specific insured and their needs.
Step 1: Accurate Data Collection & Valuation
Description: A CAT model is only as good as the data it’s built on. There’s limited fact-checking to validate inaccuracies, so data quality is critical to producing meaningful results.
Key Inputs Provided by Underwriter:
- Construction materials
- Occupancy
- Property valuation
Model Uses That Data to Generate:
- Historical storm patterns
- Climate projections
- Geographic risk factors
Because the data provided by the underwriter informs the model, it’s incredibly important that the underwriter’s data is accurate.
Step 2: CAT Model Data Analysis
Description: Use CAT models to analyze potential risks, generate probabilistic scenarios, and identify primary perils.
Key Outputs:
- Probable Maximum Loss (PML): an estimate of the largest loss a policyholder or insurer could face from a single insured event
- Return Period: the estimated frequency at which a specific PML event is expected to occur (most underwriters look at 250 years)
- Maximum foreseeable loss (MFL): the worst-case financial loss estimate for a property or portfolio during a catastrophic event
- Hazard mapping: visualizes potential risk zones and illustrates where mitigation efforts or additional coverage might be needed
- Event triggers: all relevant risks within a specific geographic area, including overlapping hazards (like a mudslide after a fire)
- Average annual loss (AAL): dictates the premium the market should charge, usually 2-5x the AAL
Step 3: Expert Interpretation
Description: Carriers use CAT model outputs to assess portfolio risk, balancing capacity, aggregate limits, and regional exposures. If a risk nears its aggregate limit, they may raise prices or decline coverage. At Jencap, we leverage this data and our expertise to place risks with the right market — whether it’s a carrier with higher wildfire tolerance or one suited to a specific peril — ensuring optimal coverage and terms. We also provide clients with their modeling results, helping them make informed decisions when allocating premiums across their portfolio.
Economic Considerations:
- Unmodeled risks like inland flooding or storm surge
- Site-specific vulnerabilities such as building materials and geography
- Economic considerations like reconstruction costs and inflation
Step 4: Comprehensive Risk Assessment
Description: Our actionable recommendations don’t just close coverage gaps — they help clients improve outcomes. By evaluating secondary modifiers, like roof construction standards adopted by the builder on a given risk or structural plans for high-risk areas, Jencap identifies ways to enhance insurability. Asking the right questions and leveraging engineering insights can significantly impact a carrier’s willingness to underwrite the risk and even reduce premiums, ensuring clients get tailored solutions for comprehensive protection.
What Jencap Provides:
- Customized policy solutions
- Client-specific coverage recommendations
- Transparent communication of risks and limitations
Why Disaster Risk Management Matters for Agents
Balancing the interests of insureds with the profitability of an insurance portfolio is a complex and delicate task. Achieving this balance requires innovative solutions that optimize for precision and transparency, even if it means challenging traditional approaches. While these advancements may limit the volume of business written, they provide more accurate pricing and robust portfolios that can withstand catastrophic events.
Jencap shares this commitment to precision and resilience, empowering agents with the information needed to navigate today’s dynamic risk landscape confidently. Connect with our CAT Modeling specialists to see how our data-driven and expert-led process turns insights into protection, so nothing is left to chance.
*A special thanks to Stephanie Kuczynski and all of our partners at Zesty AI for their insightful contributions to the videos in this piece.
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