Reports & Research

Wildfire Risk Is Rising Nationwide‍

Wildfire seasons are getting longer, more destructive, and harder to predict—and they’re no longer just a Western U.S. concern. From the Southeast to the Midwest, wildfire risk is emerging in places many insurers haven’t traditionally watched.

What the Latest Data Reveals About Wildfire Exposure

Drawing from the latest national datasets and insights from ZestyAI’s Z-FIRE™ model, this visual guide to wildfire risk in the U.S. shows:

• New wildfire hotspots: Discover where risk is rising fastest.
• Mitigation gaps: Learn how a lack of defensible space is putting thousands of homes in danger across the country.
• Top risk drivers: See how features like overhanging trees and wooden roofs are fueling destruction in high-risk areas.

Download Free Infographic

BONUS: You’ll also get access to our latest online event with IBHS and Western Fire Chiefs Association, The LA Fires in Focus: What Worked, What Didn’t, What’s Next for Insurers.

The Silent Peril Reshaping Homeowners Insurance

Non-weather water damage rarely makes headlines, but it’s quietly eroding profitability across the country.
It is now the fourth costliest peril in homeowners insurance, and claim severity has increased 80% in the last decade—a trend that’s accelerating even as frequency remains relatively flat.

Traditional risk models struggle to capture the early warning signs behind these losses, leading to mispriced policies, undetected exposure, and rising volatility for carriers.

Want the full analysis? Download the complete “Winning the Fight Against Non-Weather Water Losses” guide.

Why Loss Severity Keeps Rising

Aging homes and overlooked system failures

Many of the most expensive losses stem from aging plumbing, deteriorating materials, and slow-burn failures that often go undetected until damage is significant.

Frequency is flat—severity is not

Loss patterns suggest that while the number of events hasn’t surged, the financial impact of each event has—a signal that traditional models are not capturing the right property-level predictors.

The Property Features Most Predictive of Water Losses

The overlooked attributes that traditional models miss

Standard territory- or age-based assessments often ignore the property-specific details that meaningfully influence water loss risk, including:

• supply line material and age
• plumbing configuration
• occupancy patterns
• system maintenance and upgrades
• moisture exposure and prior loss indicators

These factors vary widely between neighboring homes—yet most models treat them as identical.

Where Traditional Underwriting Falls Short

ZIP-code and age-based proxies mask true risk

Legacy approaches rely heavily on broad territory-level assumptions that overlook structural vulnerabilities and system conditions.

Limited visibility creates mispriced policies

Without property-level insight, high-risk homes are often underpriced while lower-risk homes subsidize them—driving loss ratio volatility over time.

Get deeper insights on the drivers of water loss severity in our full guide → “Winning the Fight Against Non-Weather Water Losses”

How AI and Property-Level Data Are Changing the Landscape

AI models trained on real-world claims data can identify early signals of potential water loss by analyzing the interaction between:

• plumbing systems
• property attributes
• historical patterns
• material degradation
• repair history

This enables carriers to segment risk accurately, adjust pricing, and reduce preventable losses—long before small issues turn into major claims.

What Homeowners Actually Understand About Water Risk

Misconceptions around coverage and prevention

ZestyAI’s research shows that many policyholders:

• misunderstand what is and isn’t covered
• underestimate how much damage water can cause
• rarely take preventive actions unless prompted

This disconnect creates an opportunity for carriers to strengthen education, mitigation, and customer engagement.

Steps Carriers Can Take Today

Improve segmentation and rating accuracy

Property-level signals enable more precise risk tiers and more stable long-term portfolios.

Strengthen mitigation and reduce loss severity

Insights help identify which homes are at elevated risk and where targeted mitigation can reduce exposure.

Enhance underwriting workflows with explainable insights

Transparent, explainable AI helps underwriters understand the key drivers behind elevated risk—supporting both decision-making and regulatory review.

Get the Full Guide

Our new research paper, Winning the Fight Against Non-Weather Water Losses, breaks down the trends reshaping this growing peril—and the strategies carriers can use to get ahead of it.

Access the Guide

ZestyAI's analysis revealed that more than 12.6 million U.S. properties are at high risk of hail-related roof damage, representing $189.5 billion in potential replacement costs.

Powered by ZestyAI’s Z-HAIL™ model, the analysis underscores the growing financial threat of severe convective storms (SCS), including hail, tornadoes, and wind events. In 2024 alone, damages from SCS were estimated at $56 billion—surpassing losses from hurricanes.

Yet many insurers still rely on traditional models designed to estimate portfolio-level exposure, not property-level risk. As hail events increase in severity and frequency, these models often miss the structural and environmental conditions that drive real losses.

Kumar Dhuvur, Co-Founder and Chief Product Officer at ZestyAI said:

“Catastrophe models have helped insurers understand where storms may strike and how losses might add up at a portfolio level. But they weren’t built to assess risk at the individual property level, and they often miss the specific conditions that drive hail damage. By analyzing the interaction between structure-specific features and local storm patterns, we can distinguish risk between neighboring properties—enabling smarter underwriting, more precise pricing, and better protection for policyholders.”

Z-HAIL evaluates hail risk using a proprietary blend of climate, aerial, and property-specific data. By applying advanced machine learning to these inputs, Z-HAIL delivers highly granular predictions that reflect both the physical characteristics of a structure and the storm activity in its immediate surroundings.

Key findings from the analysis:

• 12.6 million U.S. structures flagged as high risk for hail-related roof damage
• $189.5 billion in total potential roof replacement exposure

Top five states by dollar exposure:

• Texas ($68B)
• Colorado ($16.7B)
• Illinois ($10.8B)
• North Carolina ($10.4B)
• Missouri ($9.5B)

States with the lowest dollar exposure:

• Maine ($4.7M)
• Idaho ($12.8M)
• New Hampshire ($18.5M)
• Nevada ($49.3M)
• Vermont ($64.7M)

In recent case studies, Z-HAIL has demonstrated the ability to pinpoint which properties are most susceptible to hail damage—even within the same neighborhood and exposed to the same storm. In one example from Allen, Texas, following a storm with 2.5-inch hailstones, Z-HAIL segmented risk across 483 policies, identifying no losses among properties rated “Very Low” by the model. This level of intra-territory precision gives insurers the ability to refine risk selection with confidence—even in the most hail-prone regions of the country.

Severe convective storms are becoming more frequent and costly, putting pressure on insurers to refine underwriting and risk management strategies. 

On April 2, our experts covered:

• Key drivers behind increasing severe storm losses
• What La Niña means for the 2025 season
• How AI-powered risk models improve risk segmentation
• Live Q&A – Get expert answers to your toughest questions!

Missed the live event? Stream now! 

Severe convective storms (SCS)—including tornadoes, hail, and damaging wind events—resulted in $58 billion in insured losses across the U.S in 2024.

Insurers face a dual challenge: navigating the uncertainty of storm patterns while ensuring their portfolios remain resilient enough to absorb the financial strain from clustered, high-loss events.

Research with IBHS confirms that SCS damage accumulates over time, particularly affecting rooftops after multiple exposures to intense storm activity. As housing stock deteriorates, insurers must reassess their portfolios to ensure underwriting, rating, and loss cost controls align with their risk appetite and maintain premiums that accurately reflect evolving exposure.

Get ahead of rising storm risks with expert insights that help you strengthen underwriting, risk assessment, and claims management.

Get our new report.

A staggering $2.15 trillion worth of U.S. residential property is at high risk of wildfire damage, according to a new AI-powered analysis from ZestyAI, the leader in climate and property risk analytics. The study, which assessed 126 million properties nationwide, found that 4.3 million individual homes face heightened wildfire risk—far beyond traditionally recognized high-risk areas.

Using advanced AI models trained on over 2,000 historical wildfires, ZestyAI mapped wildfire exposure at the property level, integrating satellite and aerial imagery, topography, and structure-specific characteristics. While California leads the nation with $1.16 trillion in wildfire-exposed property, other states such as Colorado ($190.5 billion), Utah ($100.3 billion), and North Carolina ($71.2 billion) also face significant risk.

Wildfire Risk is a Nationwide Challenge

While the Western U.S. has historically seen the most severe wildfire activity, ZestyAI’s findings confirm that high-risk properties exist across the country. States like North Carolina (4.6% of homes at high risk), Kentucky (2.9%), Tennessee (2.3%), and even South Dakota (11.0%) are now seeing increased wildfire exposure.

As more homes and businesses are built in fire-prone landscapes, the Wildland-Urban Interface (WUI) continues to expand. This, combined with intensifying climate conditions, is driving higher insurance costs and growing availability concerns. Today, one in eight U.S. homeowners already lacks adequate insurance coverage, and that number is expected to rise.

AI Expands Insurance Access in High-Risk Areas

Attila Toth, Founder and CEO of ZestyAI said:

"Wildfires are threatening more properties than ever before, with billions of dollars in exposure even in areas many people don’t associate with fire risk. Yet, too many homeowners are finding themselves uninsured or underinsured just as these disasters become more frequent and severe. Insurers have traditionally relied on broad, regional models that don’t account for individual property characteristics."

"That means some homeowners are denied coverage even when their true risk is much lower than their neighbors'.’"

AI-driven risk analytics are reshaping the way insurers assess wildfire exposure. By providing granular, property-specific insights, we’re helping insurers make smarter underwriting decisions—keeping coverage available in high-risk areas while ensuring that homeowners who take mitigation steps are recognized.

Last year, our models helped insurers extend coverage to 511,000 properties that had previously struggled to secure insurance due to outdated risk models. In 2025, we expect that number to reach a million, ensuring that even in high-risk areas, responsible homeowners have access to protection when disaster strikes.

Severe convective storms (SCS)—including tornadoes, hail, and damaging wind events—resulted in $58 billion in insured losses across the U.S in 2024.

Insurers face a dual challenge: navigating the uncertainty of storm patterns while ensuring their portfolios remain resilient enough to absorb the financial strain from clustered, high-loss events.

Research with IBHS confirms that SCS damage accumulates over time, particularly affecting rooftops after multiple exposures to intense storm activity. As housing stock deteriorates, insurers must reassess their portfolios to ensure underwriting, rating, and loss cost controls align with their risk appetite and maintain premiums that accurately reflect evolving exposure.

Get ahead of rising storm risks with expert insights that help you strengthen underwriting, risk assessment, and claims management.

Get our new report.

A staggering $2.15 trillion worth of U.S. residential property is at high risk of wildfire damage, according to a new AI-powered analysis from ZestyAI, the leader in climate and property risk analytics. The study, which assessed 126 million properties nationwide, found that 4.3 million individual homes face heightened wildfire risk—far beyond traditionally recognized high-risk areas.

Using advanced AI models trained on over 2,000 historical wildfires, ZestyAI mapped wildfire exposure at the property level, integrating satellite and aerial imagery, topography, and structure-specific characteristics. While California leads the nation with $1.16 trillion in wildfire-exposed property, other states such as Colorado ($190.5 billion), Utah ($100.3 billion), and North Carolina ($71.2 billion) also face significant risk.

Wildfire Risk is a Nationwide Challenge

While the Western U.S. has historically seen the most severe wildfire activity, ZestyAI’s findings confirm that high-risk properties exist across the country. States like North Carolina (4.6% of homes at high risk), Kentucky (2.9%), Tennessee (2.3%), and even South Dakota (11.0%) are now seeing increased wildfire exposure.

As more homes and businesses are built in fire-prone landscapes, the Wildland-Urban Interface (WUI) continues to expand. This, combined with intensifying climate conditions, is driving higher insurance costs and growing availability concerns. Today, one in eight U.S. homeowners already lacks adequate insurance coverage, and that number is expected to rise.

AI Expands Insurance Access in High-Risk Areas

Attila Toth, Founder and CEO of ZestyAI said:

"Wildfires are threatening more properties than ever before, with billions of dollars in exposure even in areas many people don’t associate with fire risk. Yet, too many homeowners are finding themselves uninsured or underinsured just as these disasters become more frequent and severe. Insurers have traditionally relied on broad, regional models that don’t account for individual property characteristics."

"That means some homeowners are denied coverage even when their true risk is much lower than their neighbors'.’"

AI-driven risk analytics are reshaping the way insurers assess wildfire exposure. By providing granular, property-specific insights, we’re helping insurers make smarter underwriting decisions—keeping coverage available in high-risk areas while ensuring that homeowners who take mitigation steps are recognized.

Last year, our models helped insurers extend coverage to 511,000 properties that had previously struggled to secure insurance due to outdated risk models. In 2025, we expect that number to reach a million, ensuring that even in high-risk areas, responsible homeowners have access to protection when disaster strikes.

Property and climate risk analytics leader ZestyAI today announced regulatory approval of its Severe Convective Storm Suite in Oklahoma, North Carolina, Louisiana, Wisconsin, and Arkansas—covering more than 12 million residential and commercial properties. 

Severe convective storms caused $58 billion in insured losses in 2024, marking the second-costliest year on record. A recent ZestyAI analysis revealed that in these five newly approved states, more than 2.1 million properties face a high risk of filing a hail claim—putting over $31 billion in potential roof replacement costs on the line. 

Unlike traditional models, ZestyAI’s AI-driven risk models predict the likelihood and severity of claims at the individual property level by analyzing the interaction of local climatology with property-specific characteristics.

Built, tested, and validated on an extensive claims database, the models provide a granular, transparent understanding of risk—delivering the top risk factors for each property, and equipping insurers with the accuracy needed to improve underwriting, optimize pricing, and reduce preventable losses.

“Severe convective storms now cost insurers more than hurricanes, yet traditional underwriting tools don’t provide the precision needed to keep pace with rising losses,” said Bryan Rehor, Director of Regulatory Affairs at ZestyAI.

“These approvals reinforce the insurance industry’s shift toward data-driven, property-level risk assessment."

ZestyAI’s SCS models have now been thoroughly vetted and approved by regulators across 14 states—covering more than 44 million properties across the Midwest, Great Plains, and South.

ZestyAI announced today that Lemonade, the digital insurance company powered by AI and social impact, has adopted the ZestyAI platform to further optimize underwriting for key catastrophe perils in the U.S., building on the company’s existing technology and underwriting operations.

ZestyAI’s predictive analytics platform leverages advanced AI models to analyze the interplay of climatology, geography, and the unique characteristics of each structure and roof, enabling precise and transparent property risk assessments.

By leveraging unique risk insights, Lemonade can make smarter catastrophe risk mitigation decisions. Additionally, ZestyAI’s proactive regulatory approach, with approvals in key states, simplifies compliance and enables Lemonade to implement these models faster.

“Since our launch, we've always been committed to using technology to create smarter, more accessible insurance products,” said Ori Hanani, Senior Vice President of Insurance at Lemonade.

“In leveraging ZestyAI’s advanced risk models, we're able to further support homeowners in securing comprehensive coverage for their most valuable assets, while also continuing to strengthen our underwriting capabilities as we continue to grow." 

Attila Toth, Founder and CEO of ZestyAI, said:

Lemonade is a natural partner for ZestyAI.

“Their innovative approach to insurance and customer-centricity aligns perfectly with our commitment to provide actionable insights that drive smarter risk decisions.”

This partnership reflects a shared vision for addressing increasing climate risks and sets a new standard for resilience, efficiency, and innovation in the insurance industry. 

ZestyAI today announced a partnership with the Colorado FAIR Plan to expand insurance access for homeowners facing coverage challenges.

The partnership leverages ZestyAI’s AI-driven risk models—Z-FIRE™, Z-HAIL™, and Z-WIND™—to deliver property-specific risk assessments for wildfire, hail, and wind. These insights will support risk-based pricing and help the Colorado FAIR Plan guide homeowners on mitigation strategies.

“Our mission is to ensure every Coloradan has access to insurance that reflects their property’s actual risk, not outdated assumptions,” said Kelly Campbell, Executive Director of the Colorado FAIR Plan.

“ZestyAI’s models will help us bring greater fairness and resilience to the market while equipping homeowners with practical mitigation guidance.”

Over the next year, Colorado FAIR Plan expects to provide coverage to nearly 30,000 families previously classified as high-risk under traditional models.

By incorporating granular risk data, the plan can better align premiums with actual risk while offering homeowners actionable steps to protect their properties.

Those who invest in mitigation may also transition back to the standard insurance market over time.

Colorado regulators have prioritized risk-based pricing and transparency to stabilize the insurance market. Colorado Insurance Commissioner Michael Conway has led efforts to integrate mitigation into coverage decisions, aligning with the FAIR Plan’s adoption of ZestyAI’s AI-driven insights.

“This partnership ensures risk assessments reflect real property conditions—not just broad classifications—so homeowners can access both coverage and meaningful mitigation guidance,” said Bryan Rehor, Director of Regulatory Affairs at ZestyAI.

“Through AI-powered insights, we’re helping homeowners secure risk-aligned coverage options.”

ZestyAI’s risk platform integrates aerial imagery, historical building permits, geospatial data, and structural attributes to provide precise, property-level risk insights.

Insurers using ZestyAI’s models can assess key risk factors—including vegetation proximity, roof condition, and building materials—to inform underwriting, pricing, and mitigation recommendations to policyholders.

The collaboration builds on ZestyAI’s success with the California FAIR Plan, which expanded coverage for hundreds of thousands of homeowners in 2024.

We’re excited to share that, for the second year in a row, ZestyAI has been named one of America’s best startup employers by Forbes. This recognition highlights our commitment to fostering an exceptional workplace culture while fostering a healthier insurance market. 

What It Means to Be a Top Startup Employer

Forbes, in partnership with research firms, evaluated over 20,000 U.S. startups based on three key factors: employer reputation, employee satisfaction, and business growth. Only 500 companies made the final cut, and we’re incredibly proud to be among them.

At ZestyAI, we believe that fostering a collaborative and supportive work environment isn’t just beneficial for our team—it’s essential to our mission. By enabling insurers to make more precise, data-driven decisions, we help drive resilience across communities, ultimately benefiting the homeowners and business owners they serve.

A Remote-First, People-First Culture

As a fully remote company, ZestyAI gives team members the flexibility to design a work-life balance that fits their needs. We go beyond traditional benefits by offering an unlimited time-off policy, which includes vacation and mental health days to support well-being and prevent burnout.

For team members across North America, our local hubs bring “Zesties” together for in-person events and networking, fostering connection and collaboration.

“Culture is not just a buzzword at ZestyAI—it’s the glue that holds our team together,” said Attila Toth, Founder and CEO of ZestyAI.

“Like a great sports team, we believe that the whole is greater than the sum of its parts. Our commitment to collaboration and well-being empowers us to deliver exceptional results.”

Industry Recognition

This honor joins a list of awards celebrating our work. ZestyAI has also been recognized by Inc. 5000 as one of America’s fastest-growing private companies, included in the Deloitte Technology Fast 500, and named to the CB Insights Insurtech 50. We have also received an AI Breakthrough Award for Machine Learning and a PropertyCasualty360 Insurance Luminary award for Risk Management Innovation.

Interested in joining us? Check out our careers page!