Reports & Research

A Data-Driven Conversation about the US West’s Megadrought

Current climate conditions in the West reveal that 2021 may have a higher than normal risk for wildfire losses. While much of this report focuses on California, historically the worst victim of wildfire in the US, the entire western US is of concern in 2021. In particular, the expansion of deep drought into Colorado is of major concern.

Drought is a leading factor in seasonal wildfire risk. With drought extending through every western state this spring, insurers should consider looking deeply into how they are addressing this growing peril. According to AON, last year’s wildfires in the US West cost insurers over $8 billion.

We've released a complete detailing the devastating potential for 2021's wildfire season. The full report is available here.

Research across more than 71,000 properties involved in wildfires draws significant links between fuel management and property survival.

Read Full Study 

Oakland,Calif., April 8, 2021: Zesty^AI, a leader in climate risk analytics powered by Artificial Intelligence (AI), and the Insurance Institute for Business & Home Safety (IBHS) today released new research on how fuel management impacts destruction rates from wildfires. They found property owners who clear vegetation from the perimeter of their home or building can nearly double their structure's likelihood of surviving a wildfire.

Zesty^AI, in conjunction with, IBHS studied more than 71,000 properties involved in wildfires between 2016 and 2019 to assess the relationship between vegetation, buildings, and property vulnerability. To do this, Zesty^AI leveraged a combination of computer vision and AI to analyze high resolution satellite and aerial imagery of the properties that fell within the wildfire perimeter, which allowed them to determine what effects a property's physical environment had on its likelihood of survival. They found buildings with a high amount of vegetation within 5 feet of the structure were destroyed in a wildfire 78 percent of the time -- a rate nearly twice as high as those with small amounts of perimeter vegetation. This pattern held true as Zesty^AI analyzed the other defensible zones, ranging from 30 to 100 feet around the property.

"It's common sense that increased vegetation increases wildfire risk, but this study shows just how powerful individual action can be in safeguarding structures. Mitigation actions that can cut risk nearly in half are statistically meaningful to anyone with a stake in this peril," said Attila Toth, CEO of Zesty^AI. "These findings also underscore how wildfire research at IBHS and artificial intelligence at Zesty^AI translates to real-world impact at the intersection of homeowners, community leaders, regulators, and insurance carriers. This type of collective action will help protect our communities from the devastating impact of wildfire, which unfortunately has continued to increase over the last decade."

The study also supported and confirmed takeaways from IBHS's Suburban Wildfire Adaptation Roadmaps released last year, which go beyond the home ignition zone to detail additional actions needed across eight aspects of a home to address a home's wildfire vulnerability. Zesty^AI's new research found that having other structures in close proximity to a property increases its wildfire risk, particularly for properties in areas with moderate to high vegetation coverage. Buildings in these areas that had another structure within 30 to 100 feet from the property were destroyed in a wildfire 60 percent of the time, compared to a 31 percent destruction rate for homes without another structure in close proximity.

"This research further demonstrates to homeowners, community leaders, and policy makers just how impactful taking the mitigation actions laid out in the Suburban Wildfire Adaptation Roadmaps can be in protecting homes from wildfire ignition," said Roy E. Wright, President & Chief Executive Officer at IBHS. "Quantifying the effect of mitigating fuel density risk, one of the critical actions identified in the Roadmaps, is a first piece in the larger puzzle of what groups of mitigation actions most improve the chance of home survival and by what level."

Zesty^AI is uniquely equipped to support this type of research because of the proprietary wildfire property loss database it developed for Z-FIRE™, its AI model that generates property-specific predictive risk scores. Z-FIRE™ has been trained on more than 1,200 wildfire events across several decades and accounts for the property-level factors that contribute to wildfire risk, including defensible space, building material, and roof pitch, which legacy models fail to consider.

Wright added, "While it is not possible to eliminate wildfire risk we are not powerless against it. We must take a pragmatic approach to mitigate risk at all levels and ultimately reduce property damage through data and science. Through collaborations with modelling organizations like Zesty^AI, advanced technology like computer vision and AI help us better understand the impact of these actions at a larger scale. It is encouraging to see emerging progress in just the first months of 2021."

For additional insights you can read the full research paper, ‘Wildfire Fuel Management and Risk Mitigation - Where to Start?' here. For more information on Zesty^AI please visit www.zesty.ai, and for more information on IBHS please visit www.ibhs.org.

About Zesty^AI (www.zesty.ai): Increasingly frequent natural disasters, such as wildfires, floods and hurricanes devastated communities and drove $2.2 Trillion in economic losses over the past decade. Zesty^AI uses 200Bn data points, including aerial imagery, and artificial intelligence to assess the impact of climate change one building at a time. Zesty^AI has partnered with leading insurance companies and property owners helping them protect homes, businesses and support thriving communities. Zesty^AI was named Top 100 Most Innovative AI Company in the world by CB Insights in 2020, and Gartner Cool Vendor in Insurance by Gartner Research in 2019. For more information visit: https://www.zesty.ai/

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About the Insurance Institute for Business & Home Safety (IBHS)

The IBHS mission is to conduct objective, scientific research to identify and promote effective actions that strengthen homes, businesses and communities against natural disasters and other causes of loss. Learn more about IBHS at DisasterSafety.org.

As of September 18th, between $5.9Bn and $9.8Bn in losses have occurred this year alone.

The Zest
Zesty^AI has been keeping a close eye on the wildfires burning in the Western United States. Whether by evacuation or smoke, most of our employees have felt the impact firsthand.
Utilizing our vast wildfire data and artificial intelligence resources, we have estimated that as of September 18th, between $5.9Bn and $9.8Bn in losses have occurred this year alone.

What has made 2020 unique?
Two key aspects have made the 2020 Wildfire Season exceptional: the number of acres burned and the timing of the fires.

2018, which previously held the California record for acres burned at 1,975,086 has been eclipsed with months left in the seasons. More than 3.3 million acres have already been charred by wildfire this year in California alone, and more than 5 million in the Western US.

Fire season tends to start in September and peak in November. In August, a large scale lightning event occurred, triggering many of the California wildfires. Oregon, which typically has a shorter wildfire season has also seen early and widespread wildfires.

Analysis Methodology
Using Zesty^AI’s comprehensive historical wildfire loss data, up-to-date wildfire perimeter locations for the 2020 season, residential and commercial property information, and fueled by Zesty^AI’s AI-driven wildfire damage risk scores, the expected destruction and cost of the 2020 wildfire season so far was calculated for California, Oregon, and Washington.

To estimate the destruction and damages, Zesty^AI identified every structure involved in the 2020 wildfire perimeters and their associated wildfire vulnerabilities. Using the historical relationship between the risk profile of the structure, asset value, and economic loss, Zesty^AI was able to estimate the full economic loss of those events (including non-insured assets such as uninsured property, and non-insured economic cost). Actual information from CalFire on CZU and LNU incident was used to validate the methodology.

From our extensive historical loss data, a relationship between structural damage expected and the cost of wildfire events was developed based on local property and loss information and expanded to include additional considerations such as smoke damage, displacement costs, and construction.

The 5 Most Destructive Fires So Far
Our estimates place the Claremont-Bear (North Complex) at the top of the list of most destructive in terms of number of properties lost. Four of these five wildfires occurred in California with the Alameda Drive fire occurring in Oregon.

The 5 Most Expensive Fires So Far
While the Claremont-Bear (North Complex) fire is estimated to have destroyed the most properties, the CZU Lightning Complex fire is currently estimated to be the most costly at up to $2.6B. That makes it responsible for ~27% of all total economic losses from fires in the 2020 season so far. 

Putting Numbers on Destruction
By Zesty^AI estimates, between $5.9Bn and $9.8Bn of economic losses have occurred in California, Oregon, and Washington so far this year. California, which also leads in acres burned (5M+) makes up the lion’s share at up to $7.9B.

It’s important to state that the fire season is not yet over. In much of the Western US, it could be just beginning. With a number of fires still active and the potential for more to start, these numbers are almost certain to rise between now and the end of the year.

Looking Forward
Multiple estimates place the 2018 wildfire season at around $15Bn in total losses. While exceptional in terms of total acres burned, the 2020 wildfire season has not yet reached that level of economic loss. Without any doubt, this will be one of the costliest years on record, and with months left in the season, the potential exists for this year to surpass 2018 if it continues at its current pace.

Zesty^AI will continue to monitor this fire season. As in years past, new data continues to refine our models and analyses. Insurance professionals and media who would like more information about this analysis or about how artificial intelligence can help insurers protect themselves and their customers from wildfire should contact us.

For years, insurers asked:

“How old is this roof?”

Now, the real question is:

“How will this roof perform?"

The way insurers assess roof risk has evolved significantly over the past two decades. What began as a simple Roof Age-based surcharge has transformed into a sophisticated approach that considers real-time condition, storm resilience, and structural complexity.

A closer look at SERFF regulatory filings traces the first recorded use of Roof Age back to 2004 when The Hartford introduced Roof Age-based pricing in Iowa.

At the time, the insurer applied a flat 10% surcharge to roofs 26 years and older—a figure that now seems outdated, as many carriers won’t insure roofs older than 15 years. 

Roof Age quickly became a key rating factor—by the 2010s, Roof Age adoption in rate filings surged, growing at an annual rate of 29%.

If you fast forward just 10 years after The Hartford’s initial filing, you’ll find a stark contrast in how roof risk was assessed. By 2014, The Hartford’s rate filing in Iowa contained 51 pages of actuarial tables, detailing various roof materials and rate adjustment factors for age.

This shift reflected a broader trend—Roof Age moved from a simple surcharge to a more nuanced risk model that accounted for material durability, wear patterns, and structural longevity.

By 2018, insurers began looking beyond Roof Age, and that’s when Roof Condition first appeared in regulatory filings.

Over the past five years, its adoption has surged 32% annually, outpacing Roof Age at its peak. Insurers also began incorporating roof complexity variables, such as pitch and facets, to further refine their risk assessment models.

These advancements provided a more nuanced view of risk, moving beyond the assumption that all old roofs posed the same level of hazard.

Now, for the first time in two decades, Roof Age is plateauing. Over the past two consecutive years, we've seen a decline in the number of filings incorporating Roof Age, bringing its usage close to 2019 levels.

This decline suggests that carriers are moving toward more sophisticated approaches, leveraging real-time condition assessments rather than relying solely on the number of years since installation. After all, a 10-year-old roof in poor condition can present a greater risk than a 20-year-old roof that has been well-maintained—and insurers are recognizing the importance of capturing these distinctions.

With severe convective storm-related insured losses reaching $58 billion in 2024, traditional risk assessment methods can no longer keep up.

A new paradigm is emerging, where advanced AI-driven risk models provide the precision and resilience needed to navigate an increasingly volatile climate. 

At ZestyAI, we’re helping insurers make this shift with models like Z-STORM, Z-HAIL, and Z-WIND, which are already filed and approved in 14 states, including Texas, Colorado, Illinois, Oklahoma, and Louisiana.

Those who embrace these innovations will gain a competitive edge—reducing loss costs, improving operational efficiency, and ultimately shaping the future of risk assessment in property insurance.

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.