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For property insurers, roof age is more than just a data field — it’s a critical underwriting decision point that directly impacts pricing, risk selection, and loss costs. But what happens when that data is wrong two-thirds of the time?

A large U.S. carrier with over $500 million in direct written premium recently found out. Relying on self-reported and agent-estimated roof ages, they were systematically underpricing risky properties while overpricing safer ones. The result: adverse selection, elevated loss ratios, and underwriting decisions built on shaky foundations.

The Scale of the Problem: Two-Thirds of Roof Age Data Is Wrong

ZestyAI’s research shows that 67% of self-reported roof ages are inaccurate:

• 43% underestimate roof age — meaning roofs are older and riskier than reported
• 24% overestimate roof age — leading to overpricing or turning away good business

This isn’t just a pricing issue. Analysis also found that 78% of carriers in key U.S. regions use age-based triggers for ACV roof endorsements, with some starting as early as 8 years old. When roof age is wrong, policies can be misclassified across underwriting, eligibility, and coverage terms — creating compounding risk across the insurance lifecycle.

From Estimates to Evidence: How ZestyAI Verifies Roof Age

To replace guesswork with ground truth, the carrier deployed ZestyAI Roof Age, which analyzes building permits, more than 20 years of aerial imagery, and regional climatology using advanced machine learning. Each assessment is paired with a transparent confidence score.

Unlike traditional approaches that rely on policyholder memory or limited inspections, ZestyAI Roof Age:

• Anchors assessments in the property timeline to prevent false positives
• Cross-validates imagery with permits and climatological patterns
• Provides confidence scores to distinguish high-certainty predictions from cases requiring inspection
• Delivers explainable, auditable results that underwriters and actuaries can trust

The difference was immediate.

Real-World Examples from the Carrier’s Portfolio

In one Denver property, the agent reported an 8-year-old roof. ZestyAI identified it as 10 years old, confirmed by aerial imagery showing the replacement event.

In a Baltimore case, what was reported as a 5-year-old roof was actually 21 years old — verified through imagery and permitting history.

These weren’t edge cases. They reflected a systemic pattern across the portfolio.

The Impact: A 1.71% Improvement in Combined Ratio

By integrating verified roof age into underwriting and pricing workflows, the carrier achieved a 1.71% reduction in combined ratio. The improvement came from three measurable levers:

• Loss Cost Controls (-1.08%)
  Accurate age enabled appropriate use of deductibles and ACV endorsements, lowering claims severity.
• Better Risk Selection (-0.38%)
  More precise pricing attracted lower-risk properties while deterring higher-risk ones.
• Inspection Optimization (-0.25%)
  Confidence scores guided inspections to properties that truly needed them, reducing wasted expense.

Beyond loss ratios, better roof age data improved portfolio transparency, supported expansion into previously restricted markets, and strengthened actuarial and underwriting decision-making.

What’s Next: Expanding the Foundation of Property Intelligence

After proving the value of accurate roof age, the carrier is now building on that foundation. They are incorporating additional property attributes — including roof complexity, roof quality, and parcel-level features — through ZestyAI’s Z-PROPERTY™ platform.

By standardizing and elevating property data quality at scale, the carrier expects to unlock similar gains across quoting, underwriting, renewals, and even reinsurance discussions.

The takeaway is clear: in an industry built on precision, even a single data point — when made accurate — can deliver outsized impact.

Read the full Roof Age Accuracy case study to see how verified roof age drives measurable underwriting and pricing gains → From Self-Reported to Verified: Roof Age Accuracy That Pays Off

Across personal auto, workers' compensation, commercial auto, and homeowners, P&C carriers are rewriting their products faster than at any point in the past decade — and the clearest signal isn't market commentary, it's the filings themselves. ZestyAI used ZORRO Discover™ to review more than 2 million SERFF filings, with a deep dive into 1,700+ homeowners filings across 58 carriers and $51B in premium in five severe convective storm states. The findings show carriers redesigning coverage faster than most teams can track, regulators tightening expectations alongside, and — counterintuitively — smaller carriers leading adoption of the most material changes.

About this analysis. Insights are drawn from Zorro Discover, an AI agent purpose-built for insurance-specific research. Zorro ingests every public P&C filing submitted over the past decade (2M+ filings, 200M+ pages), preserves table structure during processing, and grounds every response in source filings. The homeowners deep dive covered Texas, Oklahoma, Colorado, Ohio, and North Carolina from 2023 to 2025. Presented by Stephanie Kuczynski, Director of Risk Analytics at ZestyAI (formerly Progressive, American Integrity, and The Hartford).

Prefer to watch instead? Access the full on-demand session → — full state-by-state data, tier-by-tier breakdowns, and live Q&A.

What's changing in personal auto filings?

2025 personal auto filings show a clear divergence. Most filings remain mechanical, but a meaningful subset is layering telematics signals, vehicle feature factors, and combined rating structures into a single filing rather than tweaking one variable at a time. COVID is still in the data — many carriers continue to exclude 2020 entirely or reset older years to a post-pandemic baseline before trending forward. Meanwhile, regulators are raising the proof bar: model factors increasingly need direct statistical support to be approved.

The 2026 advantage will go to carriers that can move fast and defend each change clearly.

How is the loss cost multiplier reshaping workers' comp?

In workers' compensation, the loss cost multiplier (LCM) is no longer a tuning knob — it's become the primary economic and structural control surface, subject to continuous regulatory oversight. Carriers are building risk segmentation directly into LCM structure rather than layering it on through schedule credits, and competitive pressure now shows up as surgical, state-level LCM moves rather than broad national adjustments.

What does the rideshare picture look like in commercial auto?

The market is splitting. Some commercial auto programs decline rideshare exposure outright; others continue to write it but rate it through negotiated, individually set prices that diverge sharply between states. A handful of filings have also begun referencing autonomous and driver-assist use at the rule level — early intent signals, even where pricing isn't yet defined.

What did 1,700+ homeowners filings reveal about severe convective storm?

This is where the redesign is most visible. The most striking finding: smaller Tier 4 carriers — regional mutuals, farm bureaus, and specialty writers — are leading adoption of percentage deductibles, ACV roof endorsements, and cosmetic damage exclusions, while Tier 1 nationals tend to wait and follow. Tier 4 carriers can't spread severe convective storm exposure across geographies or perils, so they have to manage it surgically.

The financial stakes are real. A single cosmetic damage exclusion can remove 15–25% of hail claim dollars from a carrier's books, and ACV settlement can shift 30–60% of roof replacement cost back to the insured. State-level patterns diverge as much as the carrier strategies do — Texas is the most restrictive market across nearly every endorsement, while North Carolina has barely adopted cosmetic damage exclusions at all because its rating bureau is still standardizing the language.

Regulators in states like Colorado and Texas now require actuarial parity: proof that premium credits given for these endorsements match the loss reductions they're claimed to produce.

What it means for 2026 product strategy

Across every line, the same pattern emerges: better data is producing faster product moves, and regulators are responding with tighter expectations for how that complexity is supported and explained. The carriers that win 2026 will be the ones that can see competitor filing moves in days rather than weeks, defend each change with traceable evidence, and translate state-specific patterns into targeted product decisions. Filings have become both the strategy document and the audit trail.

Watch the full session on demand

The Hidden Redesign of P&C Insurance: What 2 Million Filings Reveal About 2026 Product Strategy →

The on-demand session goes deeper on the homeowners study with full tier and state breakdowns, plus live Q&A on anti-matching, solar panel exposure, ACV labor depreciation, lendability under Fannie/Freddie guidelines, and more.

Access the on-demand recording — or request a trial of Zorro Discover to run your own filings analysis on any line, state, or carrier set.