Unified PropTechUSA.ai Net Offer Sheet
How our indices come together into a single, seller-facing offer with transparent line-items and guardrails.
Most sellers worry about list price, staging, and days on market. In 2026, another gatekeeper often decides whether a “good” home actually closes: insurance underwriting. If a buyer can’t insure your property at a price that fits their debt-to-income ratio, the deal dies—no matter how many showings you had.
At Local Home Buyers USA, powered by PropTechUSA.ai, we track an internal signal we call the Uninsurable Index—and a property-level Safety Score. Where an AVM like a Zestimate sees three bedrooms and 1,700 sq. ft, our Safety Score sees fire zones, hail corridors, legal risk, and carrier exits that can quietly blow up a retail sale at the eleventh hour.
Talk to listing agents across the country and you’ll hear the same story: clean inspection, excited buyers, clear-to-close from the lender… until the insurance quote hits the file.
In disaster-exposed ZIP codes—fire, hail, wind, flood, or litigation-heavy areas—premiums have jumped 20–40% in just a few renewal cycles. That extra $150–$350 a month isn’t just a nuisance; it can push a buyer’s debt-to-income (DTI) ratio above lender limits and trigger a last-minute denial.
That’s why at PropTechUSA.ai, we treat insurability as a first-class signal, not an afterthought. The same way we mapped investor capital in America’s “As-Is” Divide, we now track the Uninsurable Index: how likely it is that a retail buyer’s loan will die because of insurance, not interest rates or price alone.
When our team looks at a property, we don’t start with the Zestimate. We start with a composite signal we call Safety Score—a 0–100 scale where higher numbers reflect greater insurability risk.
What feeds into that number?
An algorithm like a Zestimate sees “3 bed, 2 bath, 1,700 sq. ft.” Our Safety Score: 42 sees “20%+ insurance premium shock that can break a retail buyer’s loan at the last possible moment.”
This is why some homes that look perfectly “retail-ready” on paper are quietly becoming functionally uninsurable for traditional buyers. The relationships between climate, carriers, and closing are changing faster than most listing presentations reflect.
The Uninsurable Index is our ZIP-plus-property-level way of answering a question almost no one is asking explicitly: “What is the probability a retail deal on this house dies because of insurance?”
The output is a simple scale: from “Green” (low insurance-driven failure risk) to “Red” (high probability that insurance quotes will blow up deals). A Safety Score: 42 in a tightening carrier market often maps into a “yellow–red” Uninsurable Index band.
Why does this matter to you as a seller? Because:
That’s why, in markets already strained by aging owners and rising costs (see our Silver Tsunami & Debt Wall report), insurability risk is becoming the hidden line item that decides who actually gets to exit.
This simple seller-side simulator isn’t underwriting advice—it’s a way to feel how premium shock and Safety Scores show up as DTI snaps and blown-up closings. Adjust the numbers to mirror what you’re hearing from your agent or lender.
Start with ballpark numbers. You’re not trying to be exact—you’re stress-testing how fragile a typical financed buyer might be.
Combined before-tax income for the buyers most likely to look at your home.
Principal, interest, taxes, and HOA—without homeowners insurance.
Try raising this to see how quickly DTI can jump and kill a deal.
Higher scores mean more insurability risk (fires, hail, carrier exits, prior claims).
Most programs cap total DTI between roughly 43%–50%. Slide to match what your lender is using.
When Safety Scores climb and the Uninsurable Index flashes yellow or red, deals rarely fail at random. They tend to collapse in a few predictable patterns you can actually plan around.
On paper, the deal looks perfect: contract price works, inspection is clean, and the buyer’s lender issues a conditional approval. Everyone relaxes—until the real insurance quotes show up.
Instead of the $120/month the buyer assumed from an online estimate, the carrier comes back at $280–$350/month with a big wind or hail deductible. That extra line item:
From your side of the table, it feels like a bait-and-switch. From the carrier’s side, they simply priced the hazard data and loss history your listing never mentioned.
The lender originally qualified the buyers off a ballpark premium. Once the final quote lands, their total monthly payment jumps by a few hundred dollars and the file goes back through underwriting.
On the second pass, the math breaks:
You’ll often hear phrases like “The numbers just stopped working” or “They no longer qualify for this program.” What actually happened is a DTI snap driven by insurance, not by your list price or the buyers’ base income.
In some ZIP codes, the problem isn’t just how much insurance costs—it's whether a willing carrier exists at all. If major insurers are exiting your state or tightening their underwriting box, buyers get caught in the crossfire.
Common symptoms of a carrier retreat include:
When that happens, your otherwise “normal” sale suddenly behaves like a distressed asset—even if your photos, staging, and neighborhood comps all say you should be in a traditional retail lane.
Most sellers still picture the transaction like this: list → showings → offer → inspection → close. In 2026, the actual risk map looks more like:
From the seller’s vantage point, this feels like a “sudden collapse.” From our vantage point, it was visible in the Safety Score and Uninsurable Index from day one.
You didn’t “lose the right buyer.” You lost to an insurance quote that your pricing strategy never modeled. That’s a solvable problem—if you treat insurability risk like a first-class input instead of fine print.
It’s the same logic behind our work on timing risk in Sunday Night vs. Monday Negotiation Risk . Deals don’t fall apart randomly; they fall apart where the system is most fragile. In 2026, that fragility lives at the intersection of insurance, DTI, and climate-adjusted underwriting.
If you live in a fire, hail, wind, or coastal market, assume insurance is not a background detail—it’s a front-row decision factor. Here’s how to navigate it.
Forget “Zestimate vs. list price” for a moment. Instead, ask:
Tools like AVMs and price ranges are helpful, but they have blind spots (see our analysis of Zestimate blind spots ). Our job is to connect that valuation layer to the real underwriting math that actually determines who can close.
Some sellers choose to become experts in roof quotes, mitigation measures, and policy shopping. Most don’t. If you’d rather not spend months learning the carrier landscape, there’s another option:
Our research arm, PropTechUSA.ai, doesn’t just look at photos and comps. We look at claims, climate, carrier behavior, and DTI sensitivity—then convert that into a real, net-to-you number.
No obligation, no pressure. Use our offer as a baseline—even if you ultimately decide to list.
We built our entire platform around treating “hard” homes and complex risk as normal, not exotic. Whether it’s probate (see our probate guide), as-is deserts, or insurability issues, the pattern is the same: the right match between property, capital, and timeline can preserve more of your equity than drift and denial.
If you want a deeper dive into how we route national capital into overlooked ZIP codes, read Beyond “We Buy Houses”: Building a National Seller Safety Net and From iBuyer Winter to PropTech 2.0 .
The Uninsurable Index is our way of quantifying how likely it is that a retail buyer’s loan will fail because of insurance. It combines hazard data, carrier behavior, claims history, and DTI sensitivity into a single signal so we can proactively price risk—rather than discovering it only after a deal collapses.
A Safety Score: 42 sits in our “elevated risk” band. It doesn’t mean your home can’t be sold, but it does mean: higher odds of painful insurance quotes, more fragile buyer DTIs, and a greater likelihood that traditional deals will fall apart late in the process unless someone is explicitly modeling the risk.
Because insurance is changing faster than marketing. Premiums, deductibles, and coverage exclusions are rising in many ZIP codes faster than wages or list prices can keep up. That gap shows up as DTI failures and carrier declines, not as easy-to-spot “bad houses.” From the outside, the home looks fine. On the inside, the insurance math doesn’t work.
Yes. This is where as-is liquidity matters. Local Home Buyers USA buys homes that are hard or expensive to insure— older roofs, prior claims, high-risk ZIP codes, and more. We price that complexity into a clear, written offer and let you exit without becoming an involuntary insurance expert.
We do. Local Home Buyers USA operates nationwide, with PropTechUSA.ai providing the research backbone that tracks insurability risk in each state. Whether you’re in a wildfire corridor, hail belt, coastal flood zone, or litigation-heavy market, we can walk you through options tailored to your property and your timeline.
Explore the indices and pricing rails powering Local Home Buyers USA. We don’t guess. We model — then expose the math for sellers, partners, and regulators.
How our indices come together into a single, seller-facing offer with transparent line-items and guardrails.
Measures local absorption and buyer intensity to inform timelines and pricing power.
Quantifies the value unlocked by a Novation partnership relative to an as-is cash sale.
Estimates real-world hurdles to closing (ID, title, occupancy) and shows how tasks lower risk.
Composite execution-risk score that drives the transparent Certainty Adjustment in every offer.
Signals clarity of comps, HOA disclosures, and public data—improving expectations and timelines.
Macro-local health: employment, permits, inflation, delinquencies—expressed as a stability score.
Implementation notes and lead-gen calculator patterns for deploying FOS in production.
Models expected value from targeted repairs vs timeline risk under Novation or cash.
How time-to-close and execution risk translate into a fair, transparent adjustment.
Captures block-level sentiment and uncertainty that drive list-to-close variance.
Datasets, sources, and licensing (CC BY 4.0) for transparency and reproducibility.