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.

After years of working with leading insurers, one reality has become undeniable: enterprise data quality is one of the biggest hidden risks in the industry. 

The Problem: Carriers Don’t Trust Their Own Data

Data enters the system at the quote stage. That means it often comes directly from agents and policyholders—well-intentioned, but subjective. Did the policyholder really know the exact roof age? Did the agent catch the secondary structures in the backyard?

Inspection resources are limited, and most carriers can’t validate this information at scale. The result is a house of cards: data that looks complete in the policy system, but is riddled with blind spots and inconsistencies.

And even when the data is accurate in the moment, it quickly decays. Structures are living assets, meaning:

• Roofs degrade.
• Weather events roll through.
• Families expand, renovate, and change how they use the property.
• Secondary structures, pools, trampolines, and solar panels appear overnight.

The underwriting file that was “clean” at binding can be outdated and incomplete by renewal. Over time, carriers lose confidence that they have a real view of risk. 

The Six Dimensions of Data Quality

Data quality isn’t one thing—it’s multidimensional. For carriers, the challenge is ensuring property data is:

• Accurate: Correct at the point of use, not just at intake.
• Complete (and unbiased): Captures all risk-relevant details, verified against independent sources so fields aren’t left blank, misstated, or skewed by incentives.
• Consistent: Aligned across systems, from quoting to claims.
• Valid: Structured to meet business and regulatory rules.
• Timely: Refreshed when things change, not years later.
• Unique: De-duplicated, with a single source of truth.

By this standard, most carrier data today is falling short.

From Data Quality to Data Integrity

Data quality is foundational, but it’s only part of the picture. True data integrity comes from combining accurate data with the right context and continuous observability.

That means not just having the right roof age or square footage, but knowing whether that data has changed, and whether it aligns with other signals in the environment. It means having a complete, transparent, and continuously updated picture of every property.

 The ZestyAI Solution: Verified, Transparent Property Data

At ZestyAI, we built our property intelligence platform to solve exactly this problem. By unifying multiple independent data streams—and applying AI to synthesize them—we deliver property data that carriers can trust.

Here’s how we do it:

Imagery + Computer Vision

We ingest aerial, satellite, and terrestrial imagery, then apply over 90 proprietary computer vision models. These models don’t just “see” a property; they interpret it. That means extracting hard-to-get details like:

• Roof condition and penetrations
• Yard debris and overhanging vegetation
• Secondary structures and solar panels

This creates a dynamic, objective record of what’s on the ground, property by property.

Geospatial and Hazard Data

Context matters. We overlay geospatial layers to understand how a property interacts with its environment, including wildfire exposure, flood risk, and more.

Building Permits

Using large language models (LLMs), we extract and synthesize the real changes reflected in building permits: bathrooms added, kitchens renovated, roof replacements, solar installations. Permits reveal what’s changed, not just what was once approved.

Market and Public Records

We enrich the picture with MLS transactions, tax assessments, climatology, topography, and infrastructure data. Together, these data sources confirm and contextualize what imagery and permits reveal.

Standards and Designations

We integrate authoritative designations, such as IBHS Fortified™ standards, to validate resilience features.

Each data source adds a layer of verification. Together, they create a comprehensive, continuously updated property record that carriers can rely on.

 
Why This Matters: Enterprise Data Quality Transformed

When carriers bring ZestyAI data into their systems, the impact is immediate:

• More Accurate Underwriting and Rating: Quote data is validated against independent sources. That means fewer surprises at claim time, more consistent rating, and appropriate premiums.
• Change Detection and Accurate Renewals: Our models detect what’s changed since policy inception, leading to smarter renewal decisions, more proactive outreach to policyholders, and reduced leakage.
• Better Reinsurance Negotiations: Clean, transparent data helps carriers secure the right terms, conditions, and pricing from reinsurers—because they can prove their book is based on verified risk, not guesswork.
• Operational Efficiency: By replacing guesswork and manual inspection with AI-verified data, carriers reduce expenses and focus resources where they matter most.
• More Accurate Customer Communications: Data quality isn’t just about pricing and underwriting. It’s about trust. Verified property details enable carriers to send personalized, timely, and accurate communications.
• Renewal notices, policy updates, or even hurricane prep guidance land with credibility because they reflect the customer’s real property. That strengthens engagement, reduces confusion, and builds long-term retention. 

The Bottom Line

Carriers can’t compete in today’s market with messy, decaying data. Enterprise data quality is no longer a “back office” concern. It’s a competitive edge.

ZestyAI’s property intelligence platform solves the problem at its core: by continuously verifying property data with imagery, geospatial science, permits, and AI-powered interpretation.

That’s how carriers build trust in their data. That’s how they write better risks, renew smarter, negotiate stronger, and communicate with customers more effectively. 

Want to see how ZestyAI can transform your enterprise data quality? Contact us for a demo.

ZestyAI today announced a new partnership with Applied Home National Underwriters to adopt ZestyAI’s full suite of regulatory-approved models and property insights in support of more accurate underwriting, pricing, and portfolio management across its U.S. property insurance operations.

This includes peril-specific models for non-weather water (Z-Water™), wildfire (Z-Fire™), hail (Z-Hail™), wind (Z-Wind™), and severe convective storm (Z-Storm™). It also includes property insights that combine aerial imagery, building permits, and parcel-level data to identify risk-relevant features such as roof condition, vegetation overhang, and secondary structures.

ZestyAI’s models use proprietary AI trained on billions of data points, including aerial imagery, parcel-level attributes, building permits, climatology, and real-world loss data, to deliver precise, property-specific risk intelligence that supports confident risk selection, loss ratio improvement, and more robust concentration management across perils.

Brian Voorhees, Chief Operating Officer, Applied Home National Underwriters, said:

“ZestyAI’s AI-powered risk models offer the kind of granular, verified intelligence that strengthens risk evaluation across a broad spectrum of perils, from climate-related threats to non-weather water.”

“This partnership deepens our commitment to innovation and precision in underwriting and portfolio management.”

“Applied Home National Underwriters is known for taking on complex risks with clarity and conviction,” said Attila Toth, Founder and CEO of ZestyAI. “We’re proud to support that with trusted, property-specific insights that help sharpen underwriting, align pricing with true risk, and strengthen portfolio performance.”

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.

ZestyAI has secured regulatory approval to use its AI-powered Severe Convective Storm models in underwriting and rating in Nebraska and Kansas. The move greenlights Z-HAIL™, Z-WIND™, and Z-STORM™, for use in property-level hail and wind scoring, giving carriers more transparency and precision in two of the nation’s most storm-prone states.

2024 Loss Trends Highlight Urgency

Kansas recorded 495 major hail events (≥1 inch) in 2024, the second-highest total of any U.S. state. Nebraska saw 100 confirmed tornadoes, the most in over 20 years. According to 2024 NAIC reporting, Nebraska posted the highest loss ratio of any state at 135.74%, while Kansas ranked 13th at 67.98%, evidence of the severe financial pressures facing insurers in the region.

Why Property-Level Intelligence Matters

ZestyAI’s Severe Convective Storm models analyze the interaction between localized climatology and property-specific characteristics, such as roof condition, design, and complexity, to predict the likelihood and severity of hail, wind, and storm damage claims. In contrast, many models still rely on broad ZIP code or territory-level risk assessments, missing critical property-level signals.

Each model is trained and validated on extensive real-world claims data and provides clear, transparent explanations of the key factors driving each score, enabling more confident underwriting and rating decisions.

Capabilities of the ZestyAI SCS Suite

• Z-HAIL: Predicts hail damage risk and claim severity using property-specific attributes such as roof complexity and accumulated damage to identify which homes are most likely to file a claim, even within the same neighborhood.
• Z-WIND: Analyzes AI-generated 3D roof condition, complexity, and potential failure points alongside local climatology to deliver pivotal insights into property-specific wind claim vulnerability and severity.
• Z-STORM: Assesses the frequency and severity of storm damage claims, including hail and wind, examining the interaction between climatology and the unique characteristics of every structure and roof.

“Securing approval in the storm epicenter of the U.S. reflects both the transparency of our models and our alignment with rigorous regulatory standards,” said Bryan Rehor, Director of Regulatory Affairs at ZestyAI.

“It gives carriers the confidence to use precise, property-level hail and wind insights where they’re needed most, supporting risk-aligned underwriting and pricing in markets facing escalating storm losses.”

ZestyAI’s Severe Convective Storm models are now approved for use in over 20 states across the Great Plains, Midwest, and U.S. South—regions most impacted by hail, wind, and tornado losses.

VYRD, a Florida-based homeowners insurance company focused on delivering stability and protection in a challenging coastal market, has partnered with ZestyAI, the leading provider of AI-powered property risk analytics, to gain deeper visibility into property condition and risk exposure across its book of business.

By leveraging the ZestyAI platform, VYRD gains access to advanced risk insights that help identify vulnerabilities contributing to hurricane-related losses, such as roof degradation, overhanging vegetation, and yard debris. These insights support more accurate underwriting, proactive portfolio management, and better visibility into changing property conditions over time.

VYRD is using two core capabilities of Z-PROPERTY: Digital Roof applies AI to high-resolution aerial imagery to assess roof complexity, materials, and condition, highlighting structural vulnerabilities before they become claims. Location Insights evaluates the broader parcel, surfacing risk factors like vegetation overhang, yard debris, and secondary structures that can amplify storm losses or drive claims severity.

“Staying ahead of risk requires strong partnerships and smarter data,” said David Howard, President and CEO of VYRD.

“ZestyAI’s ability to deliver timely, property-level insights helps us strengthen our understanding of exposure across the homes we protect and continue delivering on our promise of dependable coverage for Florida policyholders.”

Z-PROPERTY helps VYRD assess properties at scale, surface emerging risk patterns, and make more informed decisions across the policy lifecycle. This partnership extends VYRD’s tech-forward, policyholder-first strategy—using trusted data not just at point-of-quote, but throughout ongoing portfolio management.

“Florida is one of the most unforgiving insurance markets in the country,” said Attila Toth, Founder and CEO of ZestyAI. “VYRD is taking a proactive, data-driven approach—using AI to uncover hidden property-level vulnerabilities, strengthen portfolio decisions, and build resilience where it matters most.”

Property insurers are under growing pressure to do more with less. The risks are increasing, regulatory expectations are rising, and the margin for error keeps shrinking. In regions where wildfire, hail, and wind are intensifying, the question becomes even more urgent: how can carriers continue writing business in high-exposure areas while managing loss ratios and navigating compliance?

The challenge becomes even more complex when the homes involved are in remote locations. These properties are often far from city infrastructure, difficult to inspect, and lack consistent, structured data. That’s the reality one regional carrier faced.

Their book included thousands of rural properties, many of them manufactured homes on private land across states like Texas, Arizona, and New Mexico, as well as other regions they serve nationwide. Each presented its own underwriting hurdles, from ambiguous fire protection data to increased storm exposure and aging roof systems.

To remain active in these areas and grow responsibly, the team knew they needed a more precise way to evaluate risk at the individual property level. Broad rules were no longer enough, and legacy models designed for urban density offered little support.

The Manufactured Home Challenge: Rural, Exposed, and Hard to Inspect

Standard Casualty has specialized in insuring manufactured and modular homes for decades, serving policyholders across a wide range of states, including Texas, Arizona, and New Mexico. It’s a segment that brings unique challenges, particularly when it comes to visibility and data.

“Many of the properties we insure are located in rural areas with little to no street-level data,” said Rick Smith, Underwriting Manager at Standard Casualty.

“Some are difficult to geocode. Others are so remote that a physical on-site inspection can be challenging or expensive.”

In states like Arizona and New Mexico, many homes fall within or near the wildland-urban interface (WUI), where wildfire exposure is increasing. In Texas, hail and wind are persistent threats. And across all markets, aging structures and outdated roof data complicate rating and eligibility decisions.

The team recognized they couldn’t rely solely on fire zones or broad peril maps. They needed more nuanced, property-specific data to support confident decision-making at scale.

Getting the Full Picture, Even Without a Site Visit

“One of the big innovations for us is the availability of aerial photography,” Smith explained. “We’re seeing a lot more of our risks located in remote areas. They’re either very difficult to find or it’s very expensive to do an on-site inspection. Aerial photography really solves that problem for us.”

Using ZestyAI’s platform, the team now accesses high-resolution aerial and oblique imagery, property-specific peril scores, and roof condition insights, without always requiring physical inspections.

ZestyAI works with all the major aerial imagery providers, giving underwriters access to a broader range of coverage and more recent images than any single source could offer. That means more properties are visible, more clearly, and more often.

“We can actually accomplish through aerial photography what we can do through an on-site inspection, at a fraction of the cost, which is really important for us."

If a structure is misidentified or not aligned, underwriters can reposition the property tag themselves.

“With the ZestyAI platform, it’s very easy."

We can simply move the identifier tag with our mouse onto the correct building, click a button, and it automatically reruns the scoring and the evaluation,” Smith said.

Aerial views also improve their ability to assess roof condition and wildfire vulnerability. “Sometimes the current photo may have been taken late in the day, and there are shadows on the roof. We can back up to a photo taken six months earlier and get a clearer picture of what’s going on.”

Risk Differentiation at the Parcel Level

ZestyAI’s approach stood out by combining hazard probability with structure-specific vulnerability.

“For every peril — wildfire, hail, or wind — we now get two things,” said Smith. “First, the probability of the event occurring at that location. Second, the expected severity if it does."

"That allows us to say: these two homes are in the same neighborhood, but only one is truly high-risk.”

This dual scoring model,  based on climate science and property characteristics, allows the team to evaluate each property on its own merits. “That kind of granularity is really a game changer for us in terms of underwriting,” Smith added.

Beyond Underwriting: A New Frontier in Rating and Renewal

ZestyAI’s insights also support dynamic pricing and renewals. Rather than relying on static or annual updates, risk scores adjust continuously based on the most recent information available — from new aerial imagery and roof condition changes to building permits and property improvements.

“We’re not just using the model once and forgetting it,” Smith said. “The scoring gets augmented, and as a result, the premium gets augmented as well. That means our pricing reflects current risk — not just what we assumed at inception.”

Because the models are approved for use in both underwriting and pricing, Standard Casualty can incorporate granular risk insights into its rating approach, streamlining the process of keeping rates aligned with actual conditions.

“It would take months of actuarial and analytical work to try to get to that level of granularity. And this is happening instantaneously as we renew our business.”

Retention Through Mitigation: A Smarter Approach to Non-Renewals

While many insurers are pulling back or issuing non-renewals in high-peril regions, Standard Casualty has taken a different approach: empowering policyholders to reduce their risk and stay insured.

“We can run the property eight months ahead of renewal,” Smith explained. “If we see wildfire vulnerability, we don’t just cancel. We notify the policyholder, show them what needs to change — defensible space, roof repairs, vegetation removal — and give them a chance to improve. That’s how we retain the risk and still operate responsibly.”

This proactive strategy improves retention, builds customer trust, and advances the company’s mission: improving lives by providing affordable coverage.

“This is the direction we need to go as an industry,” Smith emphasized. “We need to help policyholders understand the importance of mitigation and give them guidance so their costs — and everyone’s losses — are reduced.”

Built to Scale: Regulatory Readiness That Grows With You

One often overlooked barrier to adopting new risk models is regulatory complexity. For Standard Casualty, this was a key factor in choosing ZestyAI.

“We looked at a lot of vendors,” said Smith.

“But ZestyAI stood out because they were already approved in the states we care about and had a clear filing strategy for others.”

That alignment means the team can expand into new markets without rebuilding processes from scratch. The same tools and workflows that support Texas can be applied in Arizona, New Mexico, or future states, streamlining both operations and compliance.

“The Right Tools. The Right Decisions. The Right Time.”

As carriers navigate mounting loss pressure, tighter margins, and rising expectations from regulators and policyholders alike, Smith believes one thing will separate those who retreat from those who adapt:

“ZestyAI gives us the right tools to make the right decisions at the right time. That’s what allows us to write in places other carriers are leaving. That’s how we grow profitably, even in high-risk territories.”