Rent data built to underwrite loans
Every DSCR calculation depends on one number: what this property will actually rent for. Get final property-level asking rents so lending teams can verify income and underwrite with confidence.
Property-level, not zip-code averages • Never scraped • Built for loan origination
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The rent number in a loan file has to survive scrutiny
The number a loan file actually depends on
A DSCR calculation on a specific asset can’t be built on a neighborhood average. The rent figure in a loan file has to match the actual unit being financed, not the ZIP code it sits in.
Most rent comps don’t hold up in origination
Scraped comps carry duplication and legal exposure. Survey data is months old before it’s published. Neither gives a lending team a rent figure they can stand behind in a regulated underwriting process.
Property-level roll-up, sourced from PMS
Dwellsy IQ data rolls up to the individual property, not just the ZIP code or MSA, captured where the rent is actually set so the rent figure in a loan file matches the actual unit being financed.
What makes Dwellsy IQ’s data different for lending analysis
Data from the systems where rental inventory is managed
Dwellsy IQ is built from rental inventory flowing into Dwellsy, the largest rental marketplace in the U.S., through direct integrations with 30+ property management systems, where rents are actually set.
No business incentive to preserve noisy listings
We do not earn revenue from renter leads, unlike other data providers. Because the marketplace is free for renters and property managers, stale or duplicated inventory has no commercial value; data accuracy does.
A consistent signal across every record
Data from different property management systems is normalized into one shared structure, with 50+ attributes, including bedrooms, bathrooms, square footage, availability, photos, and 250+ amenities across units and properties.
Historical data for understanding changing market conditions
The dataset spans from January 2020 through pandemic disruption, rapid rent growth, and subsequent market normalization.
Rent roll verification
Before a loan closes, the rents on the file need to hold up against what the market is actually paying. Unit-level, final-asking-rent data gives underwriters a direct check against inflated or stale rent rolls.
Speed to origination
The lender who underwrites faster wins the borrower. Programmatic API access and cloud delivery means rent comps and income checks can be pulled in the time it takes to run the rest of the loan file, not days later.
How lending teams use Dwellsy IQ
CRE Lenders
Property-level income validation
Verify rental income on the specific commercial property being financed, not an area average that doesn’t reflect the asset.
Defensible underwriting files
Back every rent figure with data sourced directly from property management systems, not a scraped or self-reported estimate.
Cross-asset-class coverage
Underwrite across SFR and multifamily using the same underlying dataset, no switching sources by asset type.
Mortgage Tech Platforms
Direct LOS integration
Plug rent data straight into an existing Loan Origination System via structured API, no workflow rebuild required.
Programmatic, filtered pulls
Access property-level or aggregated rent data filtered by geography or asset type, built for repeatable pulls at origination volume.
Low-friction testing before scaling
Start with a scoped sample pull against a specific market or asset class to see how the data compares against your current source.
Dwellsy is one of the most accurate and reliable data comps tools we've used. As an investor, having clean, factual, and real-time comps is a game-changer. It helps us more efficiently and effectively do our work, and we love the product.
See the data before you talk to anyone
Download our data dictionary and a sample dataset to see exactly what fields, coverage, and granularity you’d be working with.
Pull a property-level comp before you commit
Test Dwellsy IQ against your current rent data source on a real loan file, no long-term commitment required to start.
FAQ
Can this data roll up to a specific property, not just a ZIP code?
Yes. Every listing is tied to a URU (Unique Rental Unit Identifier), a permanent, unit-level ID that stays fixed to a specific rental unit even as it reappears across different listings or platforms over time. That’s what lets Dwellsy IQ data start at the individual address and roll up from there, a specific property can be matched to a comp, not just an area average. That property-level granularity is a requirement for DSCR calculations, not an optional feature.
How does this help with DSCR calculations?
DSCR depends on knowing what a specific property will actually rent for. Dwellsy IQ’s final asking rent data, pulled directly from PMS, gives underwriters an auditable income figure for the exact asset being financed.
Is this scraped or survey-based rent data?
No. Dwellsy IQ is sourced directly from property management systems through the Dwellsy marketplace, never scraped from listing sites, never collected through self-reported surveys. That removes the duplication and staleness that come with both alternatives.
Can this integrate into our Loan Origination System?
Yes. Data is delivered via API, AWS, or other methods, whichever fits your existing underwriting and LOS workflows, so it plugs into a current process without a rebuild.
Can we test the data before signing a contract?
Yes. A scoped pilot or sample pull is the natural starting point, you can benchmark it against your current rent data source before committing to anything larger.
Do we need an internal data science team to use this?
This works best for teams running their own underwriting models or DSCR calculations internally. If your platform only provides loan origination workflow software without a data or risk modeling function, talk to us about the right fit.
How fast can we get rent comps for a loan file?
Because data is delivered programmatically, comps can be pulled in the same timeframe as the rest of a loan file, not days later from a manual market search.
What asset classes does this cover?
SFR and multifamily are all covered in the same dataset, which matters for lenders underwriting across asset types.
Does this data include any PII or private information?
No. It is public, owner-disclosed listing data at the unit level, with no PII, a distinction that matters for lenders operating under regulatory scrutiny.
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