By Ross Martin, VP Risk Analytics, Zesty AI
Housing discussions heading into 2026 focus heavily on mortgage rates and inventory. But there’s another force—less visible, yet increasingly influential—that’s reshaping affordability across the United States: the rising cost and shrinking availability of property insurance across both residential and commercial markets.
These pressures are now visible in a few concrete signals. As 2026 approaches, buyers, sellers, and lenders are paying closer attention to the ratio of premiums to mortgage payments, the number of viable insurance quotes per property, and the growing gap in insurability and cost between well-mitigated and unmitigated homes. When premiums outpace home prices or wages, affordability declines. Fewer insurer quotes mean less choice and more uncertainty. As mitigation drives larger premium differences, insurance costs will more strongly influence sales and buyer behavior, especially in catastrophe-prone regions.
The trend is clear. Harvard’s Joint Center for Housing Studies reports that homeowners’ insurance costs have grown nearly twice as fast as inflation-adjusted home prices since the Great Recession. The Federal Reserve has observed a similar pattern in rental housing: multifamily insurance costs increased 75% from 2019 to 2024, placing additional pressure on rents.
And in certain states, the increases are sharper. The Wall Street Journal has documented that average homeowners insurance premiums in Florida have soared 34–40% since 2022 alone, with some policyholders experiencing premium hikes of 80% or more, well above state and national averages. The New York Times has reported sustained upward pressure on California homeowners’ insurance premiums as insurers adapt to wildfire exposure and regulatory constraints. Meanwhile, a 2024 home insurance trends report by Matic, based on 36 million quote requests, found a 27% decline in the average number of insurance quotes available to homeowners, concentrated in states experiencing higher catastrophe losses.
Individually, these trends reflect rising risk. Collectively, they are beginning to influence how investors evaluate assets, how lenders underwrite loans, and how buyers across property types assess long-term operating costs, especially in regions exposed to wildfire, hurricanes, and severe convective storms.
This is the environment in which the 2026 housing market will operate.
Understanding the Divergence: Similar Properties, Different Risks
One of the challenges in several high-risk states is the gap between how insurance companies price risk and how the housing market evaluates properties. Insurance pricing has historically incorporated a mix of property-level details and broader territorial assumptions. In some cases, these territorial factors can overshadow differences between individual homes that carry meaningfully different levels of risk.
A more accurate view emerges when we look at some of the individual risk drivers:
Roof Condition and Materials: A 5-year-old impact-resistant roof represents a different loss profile from a 25-year-old three-tab asphalt roof. Roof age, condition, and geometry are among the strongest predictors of hail and wind claims.
Wildfire Exposure and Vegetation Management: Two homes on the same street can face different wildfire risk depending on vegetation, defensible space, and ember-resistant features. These differences directly affect the likelihood of loss but are not always reflected in insurance pricing or underwriting.
Debris and Yard Conditions: Unsecured objects, accumulated debris, and deteriorated outbuildings can increase vulnerability during hurricanes and severe convective storms, where wind-borne projectiles are a major source of property damage.
Documented Improvements: Roof replacements, structural upgrades, and mitigation retrofits documented in building permits, tax assessor records, and Multiple Listing Service (MLS) data are strong indicators of reduced expected losses, but these signals are not always consistently incorporated into pricing.
When these distinctions are not adequately captured or properly weighted in underwriting or pricing, two things can happen:
- Property owners who invest in risk mitigation may not see those efforts reflected in their insurance costs.
- Higher-risk properties may not receive early, property-specific signals that encourage mitigation or capital improvements.
Over time, this can lead to misaligned premiums, where homes with very different risk levels are treated the same, causing confusion for owners and reducing incentives to invest in mitigation.
Modern property-level models help address this issue by capturing granular, verifiable characteristics more consistently and aligning insurance pricing more closely with the actual condition of each structure, improving fairness, predictability, and long-term affordability.
Implications for Insurers: Managing Volatility and Avoiding Adverse Selection
As insurers navigate rising catastrophe losses, greater differentiation at the property level is becoming increasingly important. When pricing or underwriting does not fully reflect individual risk, insurers face the possibility of adverse selection — attracting a higher concentration of underpriced, higher-risk properties while lower-risk homes look elsewhere for coverage. Left unaddressed, this dynamic accelerates volatility, erodes margins, and makes long-term participation in catastrophe-exposed states more difficult.
Modern property-level and mitigation-aware models, including those developed by organizations like ZestyAI, help reduce this imbalance by:
- Improving segmentation of high- and low-risk properties
- Supporting risk-appropriate pricing and retention of well-mitigated homes
- Enhancing portfolio stability in catastrophe-exposed markets
- Informing underwriting appetite and mitigation programs
By sharpening the distinction between low- and high-risk properties, these models support healthier risk pools and more durable participation in catastrophe-exposed regions. For homeowners, investors, and operators, this often translates into clearer expectations about where insurance costs may differ meaningfully between properties and why those differences exist.
The Role of Property-Level and Mitigation-Aware Models
Recent advances in property-specific data availability and risk modeling now enable insurers to assess risk with a level of precision that mirrors, and in many ways exceeds, the way real estate professionals evaluate properties. These models use extensive property-level data, often more than 50 attributes that are difficult for human inspectors to evaluate accurately and consistently, including roof age and materials, defensible space, vegetation conditions, building permits, occupancy type, and hazard-specific science, to generate a more accurate view of a structure’s vulnerability. Leaders across the insurance industry are already moving in this direction, incorporating more granular, property-level signals into underwriting and pricing to better reflect actual exposure.
One important development is the ability to account for mitigation measures that homeowners and business owners undertake to reduce losses. Examples include:
- Creating defensible space in wildfire-prone regions
- Replacing aging or vulnerable roofs
- Clearing yard debris that could become wind-borne
These improvements meaningfully reduce expected losses. When models can recognize and score these actions, insurers can incorporate them into pricing and underwriting decisions more transparently and consistently.
This alignment has several benefits:
- Homeowners and investors gain more control over premiums when mitigation is visible and rewarded.
- Insurers can maintain more stable portfolios, even in regions with elevated climate-driven exposure.
- Housing markets benefit from clearer signals, especially for buyers evaluating long-term affordability in high-risk areas.
Regulators in several states are also examining how mitigation, property-level data, and modern risk modeling approaches can be incorporated more consistently into rate structures—an important step toward improving clarity and fairness for consumers.
The common thread is that risk becomes more transparent, and incentives begin to align across the ecosystem.
Signals to Watch as 2026 Approaches
As insurance becomes a more visible component of total housing cost, several indicators will matter more for buyers, sellers, lenders, and housing analysts:
1. Premium-to-mortgage ratios:
In many regions, insurance and taxes make up a substantial portion of the monthly payment. When insurance premiums grow faster than home prices or wages, overall affordability goes down.
2. Number of viable insurance quotes per property
When fewer insurance companies are willing to provide quotes, as seen in the 27% drop in 2024, homeowners find it harder to secure home loans as banks become more cautious, affecting both consumer choice and lender confidence.
3. Differences in insurability between mitigated and unmitigated homes
As mitigation-aware models gain adoption, the gap in premiums between updated and non-updated homes is likely to widen. This divergence may begin influencing list prices, buyer preferences, and days on market, particularly in wildfire-, wind-, or flood-exposed regions.
A More Nuanced View of Housing Affordability
Insurance availability and affordability are becoming more prominent factors for buyers in 2026, particularly in regions exposed to wildfires, hurricanes, and severe convective storms.
That shift is already influencing how the housing market behaves.
- Buyers will evaluate long-term insurance costs earlier in the decision process.
- Sellers will see demand influenced by a property’s risk characteristics and mitigation history.
- Insurers will continue adopting property-level models that better differentiate risk and recognize mitigation more reliably and consistently.
As these trends continue, property-specific risk and mitigation data will play a larger role in helping all parties understand differences in long-term cost. Properties with lower expected losses usually experience fewer disruptions and have more predictable expenses. Models that capture these distinctions provide a clearer foundation for assessing affordability and investment performance, and they help explain why insurance considerations are becoming a more standard part of acquisition and underwriting decisions across multiple property types. This shift is already underway: leading insurers are modernizing their approaches to incorporate property-level insights and mitigation data, setting the direction for the broader market.
