Reports & Research

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

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.

ZestyAI today announced that Logic Underwriters has adopted ZestyAI’s Z-PROPERTY™, Z-HAIL™, and Z-WIND™ solutions to improve underwriting and rating precision across its personal and commercial property portfolio in Texas.

Texas is the most expensive severe convective storm market in the United States, with hail and damaging wind driving billions of dollars in insured losses every year.

"Texas is one of the most challenging storm markets in the U.S., and we need tools that match that reality," said Bill Motz, Director of Operations, Logic Underwriters.

"ZestyAI's detailed property insights and dedicated hail and wind models will help us continue to provide exemplary service to our clients—from more accurate risk assessments to better loss prevention guidance in increasingly volatile weather conditions."

ZestyAI’s property-specific hail and wind models predict the likelihood and severity of storm-driven claims by analyzing how local climatology interacts with detailed property characteristics—helping underwriters to distinguish meaningful differences in risk within the same rating territory. Each model is trained on validated claims data, offering transparent explanations of the key factors driving risk.

Z-PROPERTY applies AI to high-resolution aerial imagery and multi-source data to assess roof condition, structural complexity, and parcel-level features such as vegetation overhang, yard debris, and secondary structures—factors that directly influence claim frequency and severity across multiple perils.

“Logic Underwriters is exactly the kind of forward-looking partner that is redefining underwriting in high-exposure states,” said Attila Toth, Founder and CEO of ZestyAI.

"This collaboration shows how property-level intelligence can support underwriting excellence and disciplined decision-making while helping policyholders better understand and protect their properties. When insurers can identify specific risk factors like roof condition or vegetation overhang, they can provide actionable guidance that helps clients reduce their exposure and minimize losses."

ZestyAI’s severe convective storm models are approved in 30 states, spanning the nation’s highest-exposure hail and wind markets, and used by leading insurers across the country.

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.

 General Star (GenStar), a respected provider of excess and surplus specialty property and casualty insurance and a member of the Berkshire Hathaway family of companies, has selected ZestyAI to further strengthen how it underwrites hail, wind, and severe convective storm risk across its commercial property portfolio. 

The carrier will use ZestyAI’s Z-STORM™ model to gain more precise, property-level insight for multi-structure apartment and condominium risks, further supporting underwriting, pricing, and coverage decisions.

“Z-STORM gives us a more actionable view of hail risk at the individual property level,” said Matt Brown, Senior Vice President, Delegated Division at GenStar.

“In our evaluation, the model demonstrated compelling risk-splitting lift, which allows us to further differentiate risk more effectively, price with greater precision, and ultimately strengthen relationships with our customers and distribution partners.”

Z-STORM predicts the expected frequency and severity of severe convective storm losses by combining climatology with detailed property-specific characteristics. The model is designed to support more refined wind and hail peril rating, improved deductible and endorsement strategies, and earlier visibility into accumulating and emerging storm risk across a carrier’s portfolio.

By adopting Z-STORM, GenStar aims to further:

• Improve underwriting clarity by incorporating a clearer, property-level view of hail and wind risk into core underwriting decisions
• Expand policy availability by applying deductibles, endorsements, and exclusions more precisely—helping keep coverage available even in hail-prone markets
• Align pricing with risk, potentially offering more competitive premiums for favorable risks while refining pricing for higher-risk properties
• Identify emerging storm risk sooner, enabling proactive risk management and loss mitigation before exposures become potentially costlier for both GenStar and insureds

“GenStar joins a growing number of carriers using AI to modernize property underwriting,” said Attila Toth, Founder and CEO of ZestyAI.

“With Z-STORM delivering a sharper, property-level view of hail risk across complex apartment and condo portfolios, GenStar can further strengthen underwriting and pricing decisions and identify emerging exposures earlier—before they potentially turn into avoidable losses.”