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Amica Insurance, a leader in auto, home, and life insurance, has expanded its adoption of ZestyAI’s Risk Decision platform with ZORRO Discover^™ to gain real-time insight into rate and form filing activity across the insurance market. 

The expansion marks the third phase of a partnership that has steadily broadened since 2021. Amica first adopted Z-FIRE™ to assess wildfire risk at the individual-property level. In 2024, the partnership grew to include Z-HAIL™, Z-WIND™, and Z-PROPERTY™, extending that same property-level precision to hail, wind, and structural risk. With ZORRO Discover, Amica now extends the relationship beyond property risk assessment into the regulatory research, competitive benchmarking, and filing workflows that shape rate and product strategy.

ZORRO Discover searches and analyzes millions of P&C rate and form filings — over 200 million pages of regulatory documentation spanning a decade — and returns answers backed by direct citations to the source. Built for insurance, ZORRO’s AI agents understand filing structure and regulatory context, tie answers to carrier market share, and continuously incorporate newly approved submissions, cutting manual research time by 95%. Amica's teams use it to anticipate regulator concerns before submitting, and respond to objections with precedent regulators have already accepted.

Three recent additions extend what the platform can do. Objection Research draws on more than two million filings to show how other carriers answered similar regulator objections and which language was accepted, shortening filing cycles. Watchlist alerts teams the day a carrier they follow files a rate change above a set threshold in any state, line, or filing type they choose. A rate intelligence view consolidates approved rate changes by carrier, state, and line of business into a single screen, with the premium and policyholder impact behind each move.

Lynn Malloney, Vice President, Actuarial State and Product Management at Amica Insurance, said: “Understanding what is changing in the market—and how regulators are responding—is essential to making sound product decisions. ZORRO Discover gives our teams that context in a fraction of the time, allowing them to focus less on gathering information and more on applying it.”

Attila Toth, Founder and CEO of ZestyAI, said: "Amica has spent more than a century taking care of its policyholders, and behind that promise are thousands of decisions that have to be right. Our work together began with a single peril model. Today it informs those decisions across perils, across their entire portfolio — and, with ZORRO Discover, across how their teams read the whole market. That kind of expansion only happens when the results earn it.”

ZestyAI has earned more than 200 model approvals across state Departments of Insurance, filing its own AI models and defending them in front of regulators. That track record is why carriers trust ZestyAI with work that has to stand up to regulatory review. Amica joins a growing number of carriers using ZORRO Discover to modernize regulatory research and support product strategy.

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Two neighboring homes can go through the same hailstorm and come away with very different losses. Carriers are increasingly designing around that difference because it shows up directly in results: growth in areas once considered too high-risk (without stepping outside risk appetite or underwriting guidelines), less adverse selection, and sharper segmentation for more accurate underwriting and rating. Regulators have embraced the approach, too: property-level risk models are already being accepted in rate filings across the country. That's the shift detailed in an August 12, 2026 P&C Specialist article by Carl Winfield, with commentary from ZestyAI co-founder and chief product officer Kumar Dhuvur on why property-level risk differentiation is becoming central to how carriers price, underwrite, and grow.

We've tracked this same shift in our own filings research, most recently in The New Competitive Battleground in P&C Insurance.

Why are carriers designing products around property-level risk data?

Because accurate pricing and underwriting depend on seeing risk at the individual property, not the territory average — and that precision is what lets carriers select risks within appetite, avoid adverse selection, and grow with confidence in areas once deemed too high-risk.

Demand for more granular wind risk assessment and hail risk assessment is growing, particularly among Midwest carriers as reinsurers raise the attachment point for severe convective storm coverage and regulators in storm-prone states audit broad ZIP-code-based rate increases instead of approving them by default.

Kumar Dhuvur, ZestyAI's Co-founder and Chief Product Officer, told P&C Specialist:

"Severe convective storm losses have exceeded $50 billion annually for three consecutive years while reinsurance absorbs less of the loss. That makes it essential to demonstrate to regulators why one property represents a materially different risk from another nearby property."

Which states are pushing back hardest on ZIP-code-based rate increases?

Minnesota, Oklahoma and Iowa have actively challenged blanket ZIP-code surcharges. In those three Midwest states, where homeowners rates have surged by double digits over the last several years, regulators have pushed back on carriers relying on ZIP-code-level pricing rather than approving it outright. Illinois went further this month: Gov. JB Pritzker signed legislation ending 50 years of insurers being able to set rates without prior state approval. Across storm corridors, the pattern is consistent — regulators want evidence that a rate reflects the risk of the specific properties it applies to, not just the region.

Regulatory acceptance is also what makes property-level analytics usable inside a filing rather than only in internal analysis: Z-HAIL™, Z-WIND™ and Z-STORM™, ZestyAI's severe convective storm suite, have been accepted in 32 states, and ZestyAI's risk models have secured more than 200 regulatory approvals nationwide.

What variables go into a property-level risk score?

A property-level risk score can account for roof geometry, material and condition, accumulated hail exposure, and localized climatology — evaluated together for how they interact during a severe storm. Carriers are building mathematical formulas around these inputs to produce a score for each individual property, which they submit as supporting evidence in rate filings.

The more precise scores also look beyond a home's standalone characteristics to how a structure interacts with its immediate surroundings — tree density or structural geometry can amplify or reduce wind and hail damage during the same storm event, even between two nearby homes.

Are property-level risk scores used at quote time, or only after a policy is bound?

Increasingly at quote time, before the policy is ever written. Carriers once ordered aerial photos weeks after binding a policy to spot-check a roof; now that same aerial and property data can support new business underwriting during the initial quote, pricing roof hazards before a policy is ever written rather than catching issues after the fact. The same property intelligence can also support renewal decisions as conditions change over time.

Are percentage deductibles and ACV roof schedules rising?

Yes. Both have grown sharply over the same decade property-level data has become more available.

A ZestyAI audit of more than 2,000 filings between 2015 and 2025 found that adoption of actual-cash-value roof settlement schedules surged from 10% to 60% among the top 10 homeowners carriers, while mandatory percentage wind and hail deductibles grew from 60% to 90% over the same period. Coverage architecture is doing on the claims side what property-level data is doing on the rate side: giving carriers a more granular way to match terms to actual risk. The important shift is not simply toward more restrictions; it is toward making those decisions more closely reflect the underlying risk, so carriers do not end up penalizing good risks while retaining the properties that are actually driving losses.

How does parcel-level pricing change the relationship between carriers, agents and policyholders?

Property-level pricing moves the conversation from territory-level generalities to the risk factors of one specific address. That actuarial precision changes the dynamic industry-wide: an agent can no longer explain a quote by pointing to a rating territory alone, because two nearby policyholders can now be priced very differently based on their own property's characteristics rather than the neighborhood they share.

It also changes what a policyholder can do about their rate. ZestyAI's severe convective storm models are mitigation-aware: verified improvements such as a roof replacement, an upgrade to more impact-resistant roofing material, or corrected property data can be reflected directly in the risk score. That gives carriers a clearer way to show not only why two nearby properties are priced differently, but how specific actions can reduce that risk.

Is territory-based rating still viable alongside property-level scoring?

Yes, but risk varies more within a single territory than a territory-level rating factor can capture.

Roof shape and geometry, features like vents and skylights, material and age all affect a property's susceptibility to storm damage, Dhuvur said.

"Two neighboring homes can experience the same hail event and still have very different loss outcomes."

Modeling the interaction between the structure and localized climatology is what produces real separation between good and bad risks within the same territory — segmentation a territory factor alone cannot see. For carriers, that means competitve and internal benchmarking has to move to the same parcel-level granularity rather than staying anchored to territory averages.

How can carriers benchmark their own rate filings against competitors?

By reviewing the risk models and coverage language competitors have already gotten approved in the same states, rather than starting from a blanket rate ask. As property-level scoring becomes table stakes in catastrophe-exposed states, the carriers with the most defensible filings are the ones who can show regulators exactly how a property's risk score was derived — and how it compares to similar filings already accepted in that state.

ZORRO Discover gives filing and product teams that reference point: competitor risk models, coverage language and adoption rates cited in approved filings, so a new filing can be built on evidence regulators have already accepted.

Read the full article: Insurers Turn to Property-Level Risk Models to Justify Rate Increases → P&C Specialist, August 12, 2026, by Carl Winfield. Includes commentary from ZestyAI Co-founder and Chief Product Officer Kumar Dhuvur.

ZestyAI's Z-WATER™, its property-level model for non-weather water risk, has been accepted for use in carrier rate and rule filings in more than 20 states nationwide. Nevada, Oregon, Ohio, South Carolina, and Oklahoma are among the model’s recent state approvals.

Non-weather water has become the fourth-costliest peril in homeowners insurance, driving more than $15 billion in annual losses across more than one million claims. Claim severity has also risen 80%, compounding the financial impact for insurers as even routine water incidents become increasingly costly. Unlike weather catastrophes, these losses often begin with ordinary failures inside the home — a burst pipe, plumbing deterioration, appliance failure, or hidden leak — but can result in significant damage before they are detected.

Despite the scale of the problem, insurers have historically had limited ways to distinguish which individual properties are most susceptible to water losses. Traditional approaches often rely on broad geographic territories, property age, and other proxies that can overlook meaningful differences between otherwise similar homes.

Z-WATER addresses that gap by evaluating risk at the individual-property level. Trained and validated using insurer loss data, the model uses computer vision to read aerial imagery and evaluates how property characteristics, permitting history, localized climatology, and infrastructure context interact to drive both the frequency and severity of non-weather water claims. Z-AWATER delivers 18x risk segmentation lift compared with traditional territory- and age-based approaches, giving insurers a far sharper read on risk across their portfolios.

"Non-weather water losses place real pressure on carriers' books, but they're also highly preventable when you understand where the risks actually lie," said Bryan Rehor, Senior Director of Regulatory and Government Affairs at ZestyAI.

"The growing regulatory acceptance of Z-WATER reflects a broader shift toward models that can identify meaningful differences in risk from one home to the next while providing the transparency regulators expect.”

The expansion of Z-WATER builds on ZestyAI’s broader regulatory momentum. Across its models for wildfire, hail, wind, severe convective storm, non-weather water, and property and roof intelligence, ZestyAI has secured more than 200 regulatory approvals nationwide.

As insurers confront rising property loss costs, carrier adoption and regulatory acceptance of property-specific risk models are advancing in parallel, giving insurers new ways to move beyond broad geographic and age-based proxies and more accurately reflect the risk of individual properties.

ZestyAI  today announced that Mutual Capital Group companies Tuscarora Wayne Insurance Company, Keystone National Insurance Company, and Lebanon Valley Insurance Company have selected ZestyAI's property analytics platform to bring real-time, property-level intelligence to their underwriting, pricing, and inspection decisions.

Mutual Capital Group is adopting two ZestyAI solutions across its personal and commercial lines underwriting operations. Z-PROPERTY™ evaluates roof complexity, materials, condition, and surrounding risk factors that directly influence loss potential and underwriting outcomes.

Roof Age delivers verified roof age by cross-validating building permit records with more than 20 years of aerial imagery, identifying roof replacement events that traditional records often miss and assigning a confidence score to every property.

"Getting accurate, property-level data on roof quality, roof age, hail exposure, and wind risk without relying solely on physical inspections is a significant operational advantage," said Bruce White, Senior Commercial Lines Underwriting Officer and Assistant Vice President at Mutual Capital Group. "ZestyAI gives our underwriters the verified intelligence they need to evaluate every risk with greater consistency and confidence. It also allows us to direct physical inspection resources more strategically, focusing on the policies that need them most."

"Mutual Capital Group recognized the value of adopting a comprehensive approach to property analytics," said Attila Toth, Founder and CEO of ZestyAI. "We're proud to support their underwriting teams with trusted insights that help sharpen risk selection, align pricing with exposure, and strengthen overall portfolio performance."

ZestyAI today announced MAP Underwriting (Managing Agency Partners), the Lloyd’s of London managing agency, as its first London-market customer. MAP has selected Z-FIRE™, ZestyAI’s wildfire risk model, to enhance how California wildfire exposure is evaluated and managed within its property (re)insurance portfolio.

The partnership marks ZestyAI’s first international expansion and highlights growing global concern from insurers about the impact of wildfires.

Operating Syndicate 2791 at Lloyd’s, MAP is widely respected for its underwriting discipline and technical approach to risk. The firm places exposure analysis at the center of its underwriting strategy, building its own view of risk by synthesizing the most relevant inputs while maintaining a deliberate balance of exposure across its portfolio.

In California, the structural and environmental conditions that drive loss can shift materially across short distances and change faster than broad-scale models can keep up with. That variability places a premium on the quality and resolution of the underlying data. Traditional models often smooth over these localized differences—introducing uncertainty into how exposure is differentiated and priced.

Z-FIRE addresses this gap by providing a more refined view of wildfire risk, predicting which properties are most likely to experience a wildfire and which are most likely to survive. Using computer vision and machine learning, the model captures how structural and environmental characteristics — defensible space, vegetation density, building materials, and topography — interact at the property level to drive loss outcomes, and is trained on the industry’s largest wildfire loss dataset.

Integrated into MAP’s underwriting framework, this intelligence strengthens its exposure analysis—helping the team more precisely distinguish wildfire risk across California and maintain a more consistent, data-driven understanding of portfolio exposure.

"At MAP, we build our own view of risk and rely on high-quality data that strengthens that perspective," said Nick Williams, Deputy Active Underwriter at MAP.

"Z-FIRE enhances MAP’s view of California wildfire risk with a higher-resolution view that integrates cleanly into our framework and supports more confident decisions across our portfolio."

"The London market is paying closer attention to wildfire than ever before, and the bar for hazard intelligence underneath that work has risen with it," said Attila Toth, Founder and CEO of ZestyAI. "MAP is one of the most respected property (re)insurance teams at Lloyd's, and partnering with them on California wildfire is a meaningful first step in bringing Z-FIRE to the broader London Market.

"This partnership highlights the growing international demand for greater risk intelligence solutions and marks an exciting new chapter for ZestyAI."

The analysis is part of ZestyAI’s broader research into how coverage architecture is reshaping competition across P&C insurance. Download the full report, The New Competitive Battleground in P&C Insurance →

• Among the top 10 US homeowners carriers, ACV roof settlement schedules grew from 10% adoption in 2015 to 60% in 2025; percentage deductibles increased from 60% to 90% of policies over the same period
• Cosmetic damage and anti-matching provisions among the top 10 carriers accelerated from 20% adoption in 2015 to 90% in 2025
• Across all ~60 carriers reviewed in catastrophe-exposed states, 93% now use percentage deductibles, 75% use ACV roof settlement schedules, and 49% include cosmetic damage exclusions
• A single roof claim today routinely faces four or more stacked coverage restrictions from one loss event

New analysis by ZestyAI of more than 2,000 homeowners insurance regulatory filings reveals a decade-long, industry-wide rewrite of the homeowners contract - one that has left the modern homeowners policy structurally different from the one sold even a few years ago.

While rising catastrophe losses, rate pressure, and tighter underwriting continue to dominate industry discussion, the analysis identified a more consequential shift: carriers are increasingly competing not on headline price, but on how policies present at claim time.

Among the top 10 US carriers, adoption of Actual Cash Value (ACV) roof settlement schedules has jumped six-fold, from 10% of policies in 2015 to 60% in 2025, while percentage-based deductibles spread from 60% to 90% of policies over the same period. Cosmetic damage and anti-matching provisions, once rare, have accelerated even faster: from 20% adoption in 2015 to 90% in 2025.

Using its regulatory intelligence platform ZORRO Discover™, ZestyAI analyzed more than 2,000 homeowners insurance filings across approximately 60 carriers operating in catastrophe-exposed states including Texas, Oklahoma, Colorado, Ohio, and North Carolina. The data shows that coverage restrictions, once isolated endorsements or niche products, have become foundational elements of the modern homeowners insurance contract.

Across all carriers reviewed, the analysis found that:

• 93% use percentage-based deductibles
• 78% apply age-based coverage triggers
• 75% use Actual Cash Value (ACV) roof settlement schedules
• 49% include cosmetic damage exclusions
• 30% require mandatory inspections as a condition of coverage
• 17% include anti-matching language

The research shows that carriers facing similar catastrophe pressures are not converging on a single product design. Instead, they are assembling similar coverage controls in different combinations depending on geographic concentration, operating model, and risk appetite.

Texas showed 100% adoption of percentage deductibles among reviewed carriers, while Oklahoma reached approximately 95%. ACV roof settlement schedules were most prevalent in Oklahoma (85%) and Texas (82%), while cosmetic damage exclusions appeared in 57% of reviewed Texas filings and 50% in Colorado.

The analysis also found that coverage restrictions are increasingly layered together rather than introduced individually. In many filings, a single roof claim is simultaneously subject to a percentage deductible, an ACV settlement schedule, an age-based payout trigger, and a cosmetic damage exclusion - creating up to four constraints on recovery from one loss event.

Despite the spread of these restrictions, the analysis found that policyholder dissatisfaction has not yet materially increased. Across the filings examined, coverage restrictions showed a negative correlation with complaint volume - potentially reflecting the fact that these controls can help moderate premium increases at the time of bind. As a result, many policyholders may focus more on their immediate rate than changes to policy language, with the financial impact of coverage restrictions often becoming visible only when a claim occurs.

Stephanie Kuczynski, Director of Risk Analytics at ZestyAI, said:

“Two policies can look nearly identical at bind and behave very differently at claim time. The difference is that one may achieve a lower premium by layering restrictions that shift more risk back to the policyholder. Consumers naturally focus on the price they pay today, while the cumulative impact of a percentage deductible, an ACV roof settlement schedule, an age-based trigger, and a cosmetic exclusion often doesn't become clear until a loss occurs. That's why a decade-long trend like ACV adoption jumping six-fold matters: the economics of a roof claim under those policies can look fundamentally different.”