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ZestyAI Product Insights

Winter Storm Fern has evolved into a historic catastrophe for the U.S. insurance industry. Between January 23-27, 2026, the storm shattered records by placing over 230 million Americans under severe winter alerts, with a death toll of 85 as of February 3rd. 

Preliminary industry estimates place insured losses at $6.7 billion, potentially making Fern the third-costliest U.S. winter storm on record, trailing Elliott (2022) and Uri (2021). The crisis is far from over. The National Weather Service warns of a "historic duration" of extreme cold, with temperatures 15 to 25 degrees below average, that continues to hamper mitigation efforts.

For carriers, Fern is a complex, multi-peril challenge. Claims teams are navigating a surge of freeze-related losses, ice-driven structural damage, and widespread business interruptions across 34 states. 

To understand the stakes, one needs to look no further than February 2021, when Winter Storm Uri brought Texas to its knees and generated over $11 billion in insured losses from a single state. Fern’s footprint is broader, and its secondary effects are still unfolding.

The Cold Hard Numbers from Storm Uri: Why Claims Explode Below 5°F

Our analysis of the 2021 Storm Uri reveals a striking relationship between temperature deviation and claim frequency for the non-weather water and freeze perils. Using data from multiple carriers, we tracked daily claim rates against minimum temperatures: before, during, and after the storm window (February 11-20, 2021).

The results show how rapidly falling temperatures can transform a routine winter pattern into a systemic loss event, allowing us to monitor the market’s response in real-time as conditions deteriorated, peaked, and normalized.

The results are dramatic:

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Figure 1: Daily claim rates (blue line) surged 126X above the baseline in a temporal spike as temperatures (orange line) plunged below the 20-year average (dashed green line) during Winter Storm Uri.

The chart reveals a clear inverse relationship: as minimum temperatures dropped from the mid-40s°F to below 5°F, daily claim rates didn’t just rise, they increased 126X, from a baseline of 0.04% to 0.46% at the peak. This dramatic surge underscores the significant consequences of extreme cold events on insurance liability.

Figure 2: ZestyAI’s Z-WATER™ demonstrated an 11X increase in claim frequency between ‘Very High’ and ‘Very Low’ risk tiers during Winter Storm Uri

We used ZestyAI’s Z-WATER™ to segment the property-specific non-weather water risk across the 10-day storm window. Z-WATER™ is a risk model that accounts for how plumbing design, local climate, and infrastructure reliability interact to drive non-weather water and freeze losses. By capturing real-world dynamics, such as temperature swings that stress pipes and electrical grid failures that amplify claims, the model delivers a scientifically grounded view of property-level risk.

The results were definitive: properties that Z-WATER™ scored as ‘Very High’ risk filed 26 claims per 1,000, compared to just 2.2 claims per 1,000 for those scored as ‘Very Low’, an 11X increase in claim frequency.

This accurate segmentation reveals a clear path to managing volatility. Z-WATER™ provides a deep understanding of a home’s resilience across the full spectrum of loss mechanisms, from everyday plumbing failures to expensive outlier events like Storms Uri and Fern. By enabling precise intra-territory risk splitting, the model allows carriers to price and underwrite more reliably, ensuring premiums reflect the true risk profile while protecting the portfolio against systemic losses.

The January 2026 Storm: History Rhyming?

While we can already see the immediate impact of Winter Storm Fern, the primary difference between Fern and Winter Storm Uri is the duration of the freezing event itself, rather than any changes in how quickly policyholders are filing their claims.

As shown in Figure 1, NWW claims rise rapidly as temperatures fall and taper off quickly once conditions normalize. The risk in prolonged cold events lies in how long properties stay below the Plumbing Design Temperature; the longer the freeze, the greater the likelihood of systemic plumbing failure.

During Winter Storm Uri, extended sub-freezing conditions significantly increased the number of days in which vulnerable properties were exposed to frozen pipe failures, driving aggregate losses to historic levels. Fern is now exhibiting a similar duration profile, with sub-freezing conditions persisting for up to 10 consecutive days across parts of the Northeast. The National Weather Service has warned this “could be the longest duration of cold in several decades,” raising the likelihood of elevated losses even if individual claims remain tightly clustered in time.

For carriers, the warning signs are already flashing:

• The Power Failure Multiplier: During the storm's peak, over 1 million customers lost power. In the South, where homes lack the heavy thermal insulation of northern properties, a power outage is the primary driver of catastrophic pipe bursts. Without active heating, a property can reach the "burst threshold" within hours.
• The $30,000 Claim Severity Benchmark: Recent State Farm data underscores the high stakes of these events. Winter water damage claims totaled over $628 million, with the average claim payment now exceeding $30,000. For carriers, this high per-claim severity means even a moderate frequency surge can quickly erode Q1 margins.
• Regional Fragility in the South: While the initial assessments are still surfacing, early industry estimates for privately insured losses from Winter Storm Fern puts the damage at $4 billion to $7 billion. With Texas and Tennessee identified as the hardest-hit states, carriers are facing a "Uri-style" scenario in which infrastructure wasn't designed for a 10-day deep freeze.

From Reactive to Predictive: Solving the $6.7 Billion Freeze Risk Equation

The 2021 Texas freeze taught us that traditional approaches to freeze risk are highly insufficient. Many properties that experienced burst pipes were in areas that rarely see extended freezing temperatures, meaning they lacked adequate winterization. 

This is where predictive analytics becomes essential. By modelling the interaction between property-level vulnerabilities and local temperature thresholds, carriers can better identify which properties are most vulnerable to freeze events before the damage actually occurs.

Key Risk Drivers Identified in Our Latest Analysis:

• The Design Mismatch: The greatest risk isn't just the cold; it's the sudden change in temperature. Properties in states like Texas or Tennessee face a higher risk because they are built to release heat, not trap it. They lack the heavy insulation and deep-buried pipes needed to survive a 10-day freeze.

• The Power Grid Vulnerability: Our analysis shows that areas prone to power outages face a compounded risk. In the South, a home’s primary defense is its heating system so when the power fails and the heater stops, the "burst threshold" can be reached in just a few hours.

• Building Vulnerabilities: Our analysis shows that older homes and properties with plumbing routed through exterior walls are disproportionately represented among $30,000 non-weather water losses.

The Bottom Line for Carriers

The 2021 Texas freeze was a pivotal moment for the industry, generating more than 500,000 claims and $11.2 billion in insured losses in a single state. Today, Winter Storm Fern represents an even broader systemic threat, with weather alerts impacting 230 million people across more than 30 states.

While the final tally for Fern is still developing, the data is already clear: temperature shocks drive claims at exponential rates. With early industry assessments estimating privately insured losses between $4 billion and $7 billion, it is evident that the prolonged duration and geographic anomaly of extreme weather events are the primary drivers of this volatility.

For carriers looking to protect their Q1 margins, predictive analytics are no longer a luxury; they are a requirement. By analyzing property-level characteristics, regional vulnerabilities, and historical temperature deviations, you can move from reactive claims handling to proactive risk management. 

The question isn't whether another major freeze will occur, but whether your portfolio is prepared for the next 126-fold surge.

Learn More About Z-WATER 

ZestyAI’s Z-WATER™ provides the industry’s most granular view of interior water risk, helping carriers accurately and reliably assess properties in areas prone to temperature shock events. By analyzing detailed property-level characteristics alongside historical weather patterns and regional risk factors, our advanced models predict the likelihood of Non-Weather Water (NWW) and freeze claims as well as their associated severity. This deeper level of analysis empowers carriers to make smarter pricing decisions before the next major storm hits.

Methodology: Analysis based on aggregated claims from multiple Texas carriers during Winter Storm Uri (February 2021). Temperature data reflects mean daily minimums across the exposure footprint, weighted by ZIP Code to account for geographic density. The claim/exposure ratio was calculated by dividing daily claims by the average policy-day exposure.

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¹CNN Weather, "More than 230 million people under alerts for potential ice, heavy snow and extreme cold," January 2026. [link]

²Fox News, "Noem coordinates with Mississippi officials as state recovers from deadly winter storm," January 2026. [link] 

³Insurance Innovation Reporter, “KCC Estimates $6.7 Billion in Insured Losses from Winter Storm Fern,“ February 2026 [link]

⁴Texas Department of Insurance, "Insured Losses Resulting from the February 2021 Texas Winter Weather Event," March 2022. [link]

 ⁵Fox Business, “More than 1 million Americans lose power as monster winter storm sweeps across the US,” January 2025 [link]

 ⁶Carrier Management, “Frozen Pipes Lead to $628M in Losses for State Farm,” January, 2026 [link]

⁷ Barrons, “Winter Storm Fern Packed a Wallop. Now the Cost Estimates Are Rolling In.,“ February 2026 [link]

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Wildfire risk in the United States is no longer confined to the edges of forests or traditionally high-risk zones. New analysis using ZestyAI’s property-level wildfire models shows that millions of homes classified as low or no wildfire risk under federal assessments face elevated wildfire danger when evaluated at the property level.

This analysis was recently featured in Vox, which examined how wildfire behavior is evolving — and why broad, backward-looking risk maps are increasingly misaligned with how fires spread today.

👉 Read the full article on Vox → https://www.vox.com/climate/476932/california-wildfire-los-angeles-risk-ai-housing-climate

Wildfire risk is closer — and more granular — than most maps show

Many homes damaged or destroyed in the 2025 Los Angeles wildfires were still classified as “low risk” under federal wildfire assessments. ZestyAI’s property-level analysis provides a different perspective.

By evaluating individual structures — including vegetation proximity, defensible space, building characteristics, and neighborhood-level fire dynamics — ZestyAI identified more than 3,000 properties worth approximately $2.4 billion in areas impacted by the Palisades and Eaton fires that showed elevated wildfire risk despite being classified as low or no risk under FEMA’s census-level assessments.

Across California, the classification gap is even broader. Approximately 1.2 million properties, representing roughly $940 billion in residential property value, are designated as low or no wildfire risk under federal maps, despite AI-driven property-level models indicating elevated wildfire danger.

Why census-level wildfire maps fall short

Wildfires do not spread evenly across census tracts or counties. Ember-driven ignition, structure-to-structure spread, wind conditions, and localized vegetation patterns create uneven outcomes, where one home survives and the next is destroyed.

Federal wildfire assessments are designed to provide a baseline view of community-level risk. FEMA has noted that its National Risk Index is not intended to serve as a property-specific risk assessment. When risk is evaluated at the individual property level, meaningful differences emerge that aggregated maps are not designed to capture.

What more granular wildfire risk intelligence enables

More detailed wildfire risk data can support:

• Targeted mitigation efforts at the property and neighborhood level
• More informed rebuilding and land-use decisions
• Clearer, more defensible underwriting and portfolio strategies
• Improved dialogue between insurers, regulators, and communities

A shift in how wildfire risk is understood

Wildfire risk is evolving faster than the systems built to measure it. Homes are no longer just adjacent to wildfire hazards; they increasingly influence how fires ignite, spread, and intensify, even in dense urban environments.

Property-level risk intelligence does not remove hard decisions. But without it, those decisions are made using an incomplete picture of where wildfire risk truly exists.

Read the full Vox article here.

In property insurance, roof age is one of the most critical factors in assessing risk. Yet too often, carriers rely on self-reported or agent-supplied data that is incomplete or inaccurate.

ZestyAI’s recent analysis of 500,000+ properties revealed widespread discrepancies in reported roof age. The result? Mispriced policies, unexpected losses, and operational inefficiencies that impact the bottom line.

As climate volatility grows and reinsurance pressure intensifies, overlooking the true condition and age of a home’s largest, most exposed surface is a risk no carrier can afford.

What’s Inside

• Uncover the biggest myths and blind spots in roof age records.
• Understand why traditional data sources, like claims systems and permits, fall short in providing accurate roof age.
• Learn how a multi-source verification strategy, combining aerial imagery, permits, tax records, and AI, offers a blueprint for improvement and 97% national coverage.
• Explore why roof age is a predictor of losses across multiple perils, not just wind and hail.
• Discover the one-two punch of verified roof age and real-time condition insights, delivering a complete view of risk, even for young roofs with hidden problems.
• Align your roof age data with growing regulatory expectations, particularly in states like Florida.

Access the Guide.

New research from ZestyAI reveals that 62% of U.S. homeowners are deferring critical home maintenance, adding up to $317 billion in potential claims exposure for insurers.

These findings come as Severe Convective Storms (SCS) caused an estimated $58 billion in insured losses in 2024, surpassing hurricane-related losses and marking the second-costliest SCS year on record.

Tornadoes, hail, and wind events now account for over 60% of all U.S. catastrophe claims, and research from the Insurance Institute for Business & Home Safety (IBHS) shows that roof damage accounts for up to 90% of residential catastrophe losses.

Key Findings from ZestyAI’s Homeowner Survey

According to ZestyAI’s nationally representative survey, 62% of homeowners have delayed essential repairs due to budget constraints, representing nearly 59 million U.S. homes with unaddressed vulnerabilities. Forty percent said they would rely on an insurance claim to cover major repairs like roof replacement, adding up to an estimated $317 billion in potential exposure for carriers.

Alarmingly, 63% of homeowners who weren’t living in their home at the time of the last roof replacement don’t know how old their roof is, making it even harder to detect aging systems before they fail. Meanwhile, 12% admitted they would delay repairs indefinitely, further increasing their risk of property damage.

Severe Convective Storms: The Growing Catastrophe Risk

This blind spot compounds known risks: prior ZestyAI analysis has identified over 12.6 million U.S. properties at high risk for hail-related roof damage, representing $189.5 billion in potential roof replacement costs.

“Deferred maintenance has long been a known risk factor, but today the stakes are higher than ever,” said Kumar Dhuvur, Co-Founder and Chief Product Officer of ZestyAI. "With claim severity rising and storm losses compounding, insurers need more than hazard maps to navigate this landscape."

"Property-level insights allow carriers to proactively address known vulnerabilities, improve underwriting precision, and work with homeowners to reduce losses before they happen.”

ZestyAI’s findings support a growing push toward data-driven, preventative underwriting strategies, especially as carriers face rising claim severity and pressure to improve combined ratios across storm-prone states.

With insured losses projected to exceed $30 billion, the recent Los Angeles wildfires rank among the costliest in U.S. history—reshaping how insurers think about risk, resilience, and readiness.

Watch the Full Webinar → LA Fires in Focus: What Insurers Need to Know

In this on-demand webinar, experts from the Insurance Institute for Business & Home Safety (IBHS), the Western Fire Chiefs Association, Cal Poly’s WUI Fire Institute, and ZestyAI unpack what really happened—from frontline response to lab-based research and model performance—and share critical strategies insurers can use to prepare for what’s next.

Watch this session if you’re a Product Managers, Underwriters, Actuaries, and Risk & Innovation leaders looking to make informed decisions in an increasingly volatile wildfire landscape.

What You’ll Learn

• Key takeaways from the Los Angeles wildfires
• Research on structure-to-structure fire spread and resilience factors
• How wildfire risk models performed—what we got right (and wrong)
• Practical strategies to reduce exposure and strengthen resilience

Meet the Experts

• Anne Cope, Chief Engineer, IBHS
• Bob Roper, CEO, Western Fire Chiefs Association
• Frank Frievalt, Director, WUI Fire Institute at Cal Poly
• Kumar Duhvur, Co-Founder & CPO, ZestyAI

With insured losses projected to exceed $30 billion, the recent Los Angeles wildfires rank among the costliest in U.S. history—reshaping how insurers think about risk, resilience, and readiness.

Watch the Full Webinar → LA Fires in Focus: What Insurers Need to Know

In this on-demand webinar, experts from the Insurance Institute for Business & Home Safety (IBHS), the Western Fire Chiefs Association, Cal Poly’s WUI Fire Institute, and ZestyAI unpack what really happened—from frontline response to lab-based research and model performance—and share critical strategies insurers can use to prepare for what’s next.

Watch this session if you’re a Product Managers, Underwriters, Actuaries, and Risk & Innovation leaders looking to make informed decisions in an increasingly volatile wildfire landscape.

What You’ll Learn

• Key takeaways from the Los Angeles wildfires
• Research on structure-to-structure fire spread and resilience factors
• How wildfire risk models performed—what we got right (and wrong)
• Practical strategies to reduce exposure and strengthen resilience

Meet the Experts

• Anne Cope, Chief Engineer, IBHS
• Bob Roper, CEO, Western Fire Chiefs Association
• Frank Frievalt, Director, WUI Fire Institute at Cal Poly
• Kumar Duhvur, Co-Founder & CPO, ZestyAI

ZestyAI, the leading provider of AI-powered property and climate risk analytics, today announced a strategic partnership with NEXT Insurance, a top commercial insurer specializing in small to medium-sized businesses.

Under this agreement, NEXT will adopt ZestyAI’s Z-PROPERTY™ and Z-FIRE™ models to enhance its underwriting processes with precise, property-level risk insights. Z-PROPERTY uses high-resolution aerial imagery and AI-powered analytics to assess roof condition, structural risks, and environmental hazards, helping insurers make more informed underwriting decisions.

Z-FIRE, adopted by over one-third of California’s insurance market, delivers highly accurate wildfire risk assessments based on 2,000+ historical wildfires, satellite imagery, and topographic data, ensuring that premiums reflect true wildfire exposure.

Lance Poole, Head of AI Underwriting at NEXT Insurance, said:

“ZestyAI’s peril-based risk models stood out for their ability to provide precise, actionable insights at scale, perfectly complementing our mission to help entrepreneurs thrive. This partnership strengthens our underwriting capabilities by delivering advanced data analytics that allows us to offer a faster, fully digital purchasing experience while maintaining best-in-class underwriting. By streamlining workflows and enhancing decision-making, we’re able to create innovative, tailored insurance solutions that meet the unique needs of small business owners, all while staying true to our commitment to simplicity and excellence."

Attila Toth, CEO of ZestyAI said:

"At ZestyAI, we are committed to bringing the power of AI-driven risk intelligence to the insurance industry. NEXT Insurance is redefining small business insurance with a fully digital experience, and we are proud to support that vision by providing precise, property-specific risk insights. With Z-PROPERTY and Z-FIRE, NEXT can enhance underwriting efficiency, optimize risk selection, and ultimately deliver smarter, more tailored coverage to small business owners across the country."

ZestyAI today announced its partnership with Safepoint Holdings, a regional property insurance group operating Safepoint, Cajun, and Manatee. Together, these platforms manage over 200,000 policyholders across Florida, Louisiana, Texas, Mississippi, and Alabama.

By leveraging ZestyAI’s advanced risk platform, Safepoint Holdings can analyze a high volume of properties with precision, enhancing underwriting accuracy and improving access to coverage for homeowners. Additionally, Safepoint Holdings is strengthening its loss cost control program by utilizing ZestyAI’s property insights to better predict and manage risk.

The partnership also enables Safepoint Holdings to optimize its inspection strategy, reducing costs and streamlining operations through high-resolution aerial imagery.

David Flitman, CEO of Safepoint Holdings. said:

“ZestyAI’s property insights have set a new benchmark for accuracy and innovation. The flexibility of their solutions and the ability to evaluate large insured portfolios in a matter of days provide tremendous value to us. This partnership will allow us to better serve our policyholders by proactively managing risk while making our operations more efficient.”

ZestyAI’s Advanced Risk Solutions Adopted by Safepoint:

• Z-PROPERTY Digital Roof™: Analyzes key drivers of roof-related risk—including material, shape, pitch, and condition—using AI-powered 3D modeling of high-resolution aerial imagery. These insights improve Safepoint’s risk selection process and optimize inspections by identifying properties requiring on-site evaluations, ensuring underwriting and renewals are both accurate and efficient.
• Z-PROPERTY Location Insights: Delivers detailed, property-specific risk insights for over 150 million properties across the U.S. Combining computer vision, machine learning, and high-resolution imagery,
  Location Insights provides critical risk insights on overhanging vegetation, lot debris, and more, enabling Safepoint uncover hidden risks, streamline workflows, and better align premiums to risk.
• Roof Age: Combines over 20 years of historical aerial imagery with verified building permit data to determine the accurate age of a roof with 92%+ accuracy. By eliminating reliance on self-reported or incomplete data, Safepoint can enhance pricing precision, reduce claims exposure, and make informed decisions about eligibility and coverage.

“By integrating our solutions, Safepoint Holdings can make better risk decisions, reduce costs, and expand coverage in states with high climate risk like Florida, Louisiana, Texas, Mississippi, and Alabama,” said Attila Toth, Founder and CEO of ZestyAI. “We’re excited to support Safepoint Holdings with the insights they need to serve their policyholders.”

This partnership comes at a pivotal time as Safepoint Holdings focuses on expanding its portfolio. With ZestyAI’s property-specific data, Safepoint Holdings can scale efficiently while maintaining reliable, cost-effective coverage for its policyholders. Safepoint Holdings operates with a combined policyholder surplus of approximately $150 million, with Safepoint Insurance Co. holding $70 million.

ZestyAI, the leader in AI-powered climate and property risk analytics, announced that Z-FIRE™, its advanced wildfire risk model, is filing-ready in California.

Z-FIRE can continue to be filed for rate segmentation and underwriting without further review under the Pre-Application Required Information Determination (PRID) process, which is currently focused on models that determine a catastrophe load factor.

Z-FIRE was last included in an approved California rate filing in 2024.

Z-FIRE leverages AI-driven analysis of over 2,000 historical wildfires, integrating satellite and aerial imagery, topography, and property-level characteristics to provide precise risk assessments. This approach is rooted in decades of science and experimentation by researchers, including the Insurance Institute for Business & Home Safety (IBHS).

With coverage spanning nearly 100% of U.S. properties, Z-FIRE is already trusted by more than one-third of California’s insurance market, including the California FAIR Plan, the state's insurer of last resort, to refine underwriting, enhance risk segmentation, and ensure that premiums accurately reflect the true wildfire exposure and vulnerability of each individual structure.

"For years, leading insurers have trusted ZestyAI to manage wildfire exposure in California and refine pricing segmentation with precision," said Attila Toth, Founder and CEO of ZestyAI. "Now, insurers can continue to confidently integrate it into their rate filings."

They can trust that Z-FIRE meets the highest actuarial and scientific standards, ensuring transparency and reliability for regulators, carriers, and policyholders alike.

ZestyAI continuously validates Z-FIRE’s performance through post-event analyses, assessing how well its risk designations align with real-world fire impacts.

Following the recent Los Angeles wildfires, preliminary analysis indicates that Z-FIRE’s highest-risk ratings closely correspond with the hardest-hit areas, with 94% and 87% of the areas affected by the Palisades and Eaton fires rated as high or very high risk by the model.

The model also captured how property-specific characteristics influenced damage patterns, even within the same fire perimeter, reinforcing the importance of granular, structure-level insights in wildfire risk assessment. Z-FIRE’s data also reveals more than 1.5 million structures in California face a high or very high risk of being within a wildfire perimeter.

With granular, property-specific insights, Z-FIRE allows insurers to move beyond binary "insure or drop" decisions. Instead, they can work with policyholders to reduce vulnerability—whether through defensible space measures, fire-resistant roofing, or other mitigation efforts.

Since its adoption, Z-FIRE has helped insurers confidently write hundreds of thousands of policies that might have otherwise been non-renewed or declined. By incorporating vegetation density, roof materials, and structural characteristics, the model enhances risk segmentation, reduces volatility, and strengthens market stability.

ZestyAI has engaged with the California Department of Insurance (CDI) over the years, including discussions during the early regulatory considerations of Z-FIRE. After an independent actuarial review in 2020, multiple carrier rate and underwriting filings leveraging Z-FIRE have been approved by the CDI. Moreover, ZestyAI participated in seven CDI workshops in 2023-24 and co-hosted a January 2025 webinar on the new regulatory framework.

Artificial intelligence is reshaping the P&C insurance industry, offering new ways to streamline underwriting, enhance risk management, and navigate evolving regulations.

But as AI adoption accelerates, insurers must ensure they’re using these technologies effectively—balancing innovation with compliance.

Our latest guide explores the most impactful AI applications in insurance, including:

• AI-powered underwriting and predictive analytics
• How regulators are shaping the future of AI in insurance
• Best practices for integrating AI while ensuring fairness and transparency

As AI-driven tools become the new standard, insurers who adapt early will gain a competitive edge.

Download our free guide to leverage these innovations while staying aligned with evolving regulations.

For insurers, accurate roof age data is essential. Yet, self-reported information often falls short.

Our research shows that 1 in 5 homeowners underreport roof age by an average of 8 years. These discrepancies create hidden risks that can impact underwriting, pricing, and overall portfolio performance.

How can insurers get a more accurate picture?

AI-driven insights provide 97% nationwide coverage, combining verified roof age with real-time condition data for a more comprehensive risk assessment.

Download our latest research for a breakdown of five critical insights that every insurer should know about roof age. 

Plus, get access to The Roof Age Advantage, an exclusive video that unveils how AI is setting a new standard for risk evaluation.

                           The property and casualty (P&C) insurance industry has always been about protecting people and property against the unexpected. But in 2024, U.S. insured catastrophe losses reached $113 billion—nearly double the 25-year average of $58 billion.

For many carriers, the gap between collected premiums and total payouts, including operating costs, continues to widen, underscoring the growing financial strain of climate-driven risks. At ZestyAI, we can’t control the forces of nature, but we’re helping insurers adapt.

From Franklin’s Fire Policies to AI-Powered Resilience

The concept of insurance dates back to the Middle Ages, when merchants sought protection from unpredictable events like storms and piracy. Over time, the practice evolved into today’s property and casualty insurance, safeguarding homes, businesses, and communities.

In the United States, Benjamin Franklin advanced the industry by founding the nation’s first fire insurance company in 1752. By refusing to insure fire-prone buildings, his company not only mitigated risk but also set new safety standards. This principle of risk reduction has guided the industry ever since.

Today, ZestyAI is building on that foundation with AI-driven risk models that help insurers address modern challenges. While the tools have changed, the mission remains the same: to protect people, property, and the future.

Modern Tools for Today’s Challenges

At ZestyAI, we’re helping insurers address modern challenges with solutions designed to fit seamlessly into their workflows. Our AI-driven platform combines high-resolution aerial imagery, proprietary data, and advanced modeling to provide a clearer, more reliable view of risk.

Unlike broad, traditional approaches, we focus on delivering actionable insights at the property level, helping insurers:

• Modernize outdated processes without overhauling their systems,
• Improve underwriting precision,
• Optimize inspections and resources, and
• Strengthen their portfolios.

A key example of this is our work in wildfire risk modeling. ZestyAI’s proprietary wildfire loss database—built using data from 1,500 events over the last 20 years—helps insurers predict property-specific risks with precision. By understanding wildfire risk at this granular level, insurers can proactively reduce losses, guide mitigation strategies, and protect their customers with greater confidence.

Discover how ZestyAI’s regulator-approved solutions set new standards for accuracy, compliance, and fairness in insurance.