The Quick Read: An AirDNA projection holds up in an out-of-state short-term rental loan file when the comp set is strong, the lender discounts the number, and the investor has tested the deal against long-term rent. The report is a modeled estimate for one address, not a measured result. Reviewers treat it as a starting input, so a high number does not carry a file by itself.
- The report works best as the income path for a purchase with no hosting history.
- It shows gross revenue, and the lender applies its own reduction before calculating coverage.
- Comp quality matters more than the headline figure, especially for a remote buyer.
- Across the wholesale network, short-term rental purchases reach up to 75% LTV, with a 1.00 coverage floor on purchases.
- Rules, permits, and HOA limits sit outside the data and can overrule it. Leverage, reserves, and pricing vary by lender and program; the final terms follow the full file review.
What an AirDNA Projection Actually Is
A projection is a model output built from the performance of similar nearby listings. AirDNA’s Rentalizer page says the tool draws on more than 15 million active listings across more than 120,000 markets, spanning Airbnb, Vrbo, and Booking.com. It matches listings across platforms so one property is not counted twice, and it uses a booking model to separate real reservations from dates a host blocked.
The report returns annual revenue, average daily rate, occupancy, and a monthly breakdown with a seasonality curve. It also attaches a Comp Set Strength score of Low, Medium, or High. AirDNA says a low score means the comps vary, not that the data is wrong, and that the user should review or replace them.
That score is the most useful line on the page for a loan file. It tells a reviewer how much weight the number can bear.
Why Market Data Holds Up and One Address Wobbles
Aggregate numbers are steadier than single-property numbers. Rental Recon notes that AirDNA’s published accuracy figures, 94.9% for Airbnb data and 96.2% for revenue, apply to market-level aggregates, not individual properties. A market average smooths out a hundred quirks. Your property is one of those quirks.
The vendor’s headline accuracy claim is also a self-report. Rapid Eye Inspections points out that the 97% figure has no public independent audit and describes occupancy, ADR, and revenue as modeled estimates, with the property-level report as estimates layered on estimates.
So the honest read has two parts. The data is a reasonable guide to a market. The number for your address is a forecast built from whichever comps the tool picked.
How a Loan File Uses the Projection
Across the wholesale network, a short-term rental DSCR file usually is reviewed on one of two income paths. The first is historical hosting income. The second is a third-party revenue projection such as AirDNA. Lendmire’s complete DSCR loans guide describes both paths for its short-term rental program.
The practical rule is simple. A projection is the path for a new purchase or a property with no operating history. It does not replace records you already have. If an investor owns a property with a year of booking records, those records usually tell a stronger story than any model.
Most lenders in the network also expect about 12 months of landlord or host experience on short-term rental files. A projection supports the property’s income. It does not stand in for the borrower’s track record.
Here is how the pieces move through underwriting:
1. The report is pulled. The input is the property address, bedrooms, bathrooms, and guest capacity. Rental Recon notes that a ZIP code or neighborhood search gives a wider, less accurate comp set than a specific address.
2. The comp set is reviewed. This is where most of the accuracy is won or lost.
3. Gross revenue becomes qualifying income. The lender applies its own reduction and converts the annual figure to a monthly one. Reductions differ by lender, which is why one projection can produce different coverage ratios across programs.
4. Coverage is calculated. DSCR compares that qualifying monthly income to the full monthly obligation: principal, interest, taxes, insurance, and any association dues.
5. The loan is sized at the lower of two tests. One is the LTV cap on appraised value. The other is the largest loan at which the reduced income still clears the program’s coverage floor. On a cash-out, the coverage test often binds first.
6. The appraisal runs separately. The appraiser does not use the AirDNA number to set value.
Clearing 1.00 is not the same as positive cash flow. Coverage compares income to the housing payment only. Cleaning, utilities, platform fees, management, vacancy, and repairs all sit outside the ratio.
Where Projections Break for a Remote Buyer
An out-of-state buyer cannot walk the comps. That is the central exposure, and it shows up in several specific ways.
Thin markets. A review at bnbcalc cites a commentator who says Rentalizer can run 15 to 30 percent off in either direction, with larger misses for properties that do not fit an area’s typical profile. The review also argues that small markets produce extrapolations, not measurements, because there are too few comps. The site has a commercial angle, so treat the range as a caution, not a benchmark.
Properties that don’t fit the comps. The tool matches on numbers such as bedrooms and capacity. It cannot weigh finishes, landscaping, views, or a natural amenity. A lakefront cabin and a dated duplex can pull the same comps.
Revenue definitions. Investors commonly note that the revenue figure includes cleaning fees, so gross revenue is not net rent.
Direction of error. The error can run either way. One operator’s anecdote found projected occupancy below actual results. Other analysts argue that projections skew optimistic because failed listings drop out of the comp pool and new listings without reviews take time to earn comp-level rates. Both can be true in different markets. The right conclusion is that comp quality, not the tool’s direction of bias, decides the outcome.
Regulation overrides data. Some permits do not transfer on sale. A data model cannot see any of that.
A Stress Test Before You Submit
A strong file shows three numbers side by side: the vendor projection, the lender’s reduced qualifying income, and the investor’s own conservative pro forma. The gap between the first and third is your margin for error.
Run the file at several levels of miss. This table shows the logic in coverage terms, using no dollar figures:
| Projection outcome | Coverage effect | What a reviewer sees |
|---|---|---|
| Hits the reduced figure | Near the modeled ratio | File works as written |
| Runs modestly short | Ratio slips toward 1.00 | Thin cushion, little room |
| Runs well short | Ratio falls below 1.00 | Needs a different structure |
| Beats the figure | Ratio improves | Extra margin, no change to caps |
If the deal clears only when the projection is accurate, it is a bet on the model. If it also clears on a cautious haircut, it is a deal.
Picture an investor buying a three-bedroom house in a market two states away. The report shows a medium comp strength score and a coverage ratio that clears 1.00 by a small margin after the lender’s reduction. The same file, run on long-term rent alone, falls below 1.00. That investor has a real question to answer before applying: is the premium from nightly rentals durable, or is it a market claim that a lender can discount?
Out-of-State Validation, Step by Step
A remote buyer can close much of the information gap with a short workflow:
1. Open the comps and read them. Check each comp’s bedroom count, capacity, and listing quality. Replace outliers.
2. Pull a second estimate. Investors who buy remotely often compare several tools instead of trusting one.
3. Ask a local manager. A property manager in the area can speak to seasonality, realistic occupancy, and which amenities earn premiums.
4. Check the rules. Confirm permit status, HOA language, and local restrictions before anything else.
5. Run the long-term-rent version. If the deal works only as a nightly rental, size the risk accordingly.
6. Re-pull before submission. Projections can shift, so the report in the file should be current.
Keep the comp report, the manager’s notes, and the second estimate together. A reviewer who sees the work behind the number tends to trust it more than one who sees a bare printout.
If the Projection Doesn’t Support the Loan
The fallback can cut either way. A program that relies only on the long-term rent schedule can fail coverage where nightly revenue far exceeds long-term rent. In a weak short-term market, the same fallback can rescue a file. AirDNA’s claim that nightly rentals earn two to three times long-term rent is a market claim, and a lender can still count the lower number.
When coverage falls short, investors typically have several options:
- Lower the loan amount, which can lift the ratio.
- Add equity. A larger down payment lowers the monthly obligation and can lift coverage, but it does not erase leverage caps, credit floors, reserve rules, or property eligibility.
- Pursue a structure with adjusted terms. Coverage below 1.00 is available through select lenders in the network, with leverage and terms adjusted. Extended terms and interest-only periods are also available through select lenders.
- Wait for hosting history, which opens the actuals path.
The network’s short-term rental parameters are worth knowing here. On purchases, leverage reaches up to 75% LTV on the strongest files, while refinance and cash-out run up to 70% on short-term rental collateral. Expect a credit score of 640 or higher, about 12 months of host experience, and a 1.00 coverage floor on both purchases and refinances. Loan sizes reach up to $3,000,000 on standard programs. All of this is subject to lender guidelines, and every file is reviewed individually. Manufactured homes, log homes, and barndominiums are not offered.
Some lenders in the market do not accept AirDNA at all. Others accept it with a reduction. That spread is the reason a broker who sees many programs can matter more than the report itself. In practice, the same projection can produce a workable file with one lender and a thin one with another.
For more on how documentation shapes the cash-out side, see Lendmire’s piece Electronic Verification vs Paper File on a DSCR Cash-Out.
Key Terms Defined
Comp Set Strength: AirDNA’s Low, Medium, or High score showing how similar the chosen comparable listings are to the subject property.
ADR: Average daily rate, the typical nightly price a booked unit earns.
DSCR: Debt service coverage ratio, qualifying monthly income divided by the full monthly housing obligation.
PITIA: Principal, interest, taxes, insurance, and association dues, the full obligation in the coverage calculation.
Qualifying income: The monthly figure a lender actually uses, after reducing the gross projection.
Seasoning: The time an investor has held a property before a cash-out refinance, commonly about 6 months across most of the network.
Frequently Asked Questions
Is a 97% AirDNA accuracy claim true for my property?
No. The published figures describe market-level aggregates, not single addresses, and the 97% number is a company self-report with no public independent audit. Treat your address’s number as a model estimate that depends on comp quality.
Will a lender use the full AirDNA revenue number?
Usually not. Lenders apply their own reduction to gross revenue before calculating coverage, and reductions differ by program. A few lenders may not accept a projection at all, which is why the same report can work in one program and stall in another.
Can I qualify with no hosting history?
Often, yes, through the projection path on a purchase, subject to lender guidelines. Most programs still expect about 12 months of landlord or host experience from the borrower. A projection supports the property’s income, not the borrower’s track record.
Does a high coverage ratio mean the property cash flows?
No. DSCR compares rent to the monthly housing obligation only. Cleaning, utilities, management, vacancy, repairs, and capital expenses sit outside the calculation, so a file can clear 1.00 and still earn little.
What if the projection and the local manager disagree?
Trust the stronger evidence and document why. A manager’s seasonal notes plus a tightened comp set usually carry more weight than a default report. If the gap is large, stress the deal on long-term rent before applying.
If you are buying or refinancing a rental property and want to see how the numbers work, Lendmire can help you compare DSCR loan options based on the property income, credit profile, leverage, and investor goals. You can also reach the team at 828-256-2183 or request a quote. Tax treatment varies; investors should consult a qualified professional.
A projection is a forecast about a place you may never have stood in, so the investors who do best with out-of-state files are the ones who treat the report as the first draft and the local evidence as the final one.
For current guidelines and terms, see Lendmire’s DSCR loan programs page.
About Lendmire
Lendmire, NMLS# 2371349, is a mortgage brokerage focused on investor financing, arranging DSCR loans in 40 states plus Washington, D.C. — 41 markets total. Qualification is based on the property’s income rather than personal income documentation, subject to lender guidelines, making it a fit for LLC-held rentals and scaling portfolios. Scotsman Guide named Lendmire a Top Mortgage Workplace in both 2025 and 2026.
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References
1. AirDNA Rentalizer / Airbnb Calculator
2. Rental Recon
This article is part of Lendmire’s short-term rental loan program — full qualification details, guidelines, and scenarios live on the program page.
Related reading: How to Qualify for a DSCR Loan in California · How Many Months of Booking History Does an STR Loan Need? · How to Qualify for a DSCR Loan in Tennessee
Brandon Miller
Founder & CEO, Mortgage Loan Originator, Lendmire LLC
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Legal disclosures. Lendmire (NMLS# 2371349) is a state-licensed mortgage brokerage that arranges financing through wholesale lender relationships. Lendmire is not a direct lender, depository institution, or registered financial advisor. The discussion above is general informational content about real estate financing — it is not financial, legal, or tax advice, and readers should consult licensed professionals for guidance on their individual circumstances. Loan inquiries are subject to lender underwriting; this article does not represent a commitment to lend. Loan terms, rates, and qualification standards vary by borrower, property, and state, and are subject to change at any time. Equal Housing Opportunity. NMLS Consumer Access: nmlsconsumeraccess.org.