Rent data built for underwriting and real estate investment
Banks and insurers put real money behind rental data twice over, once when underwriting a loan against a property’s revenue, and again when deploying their own capital into real estate. Unreliable data won’t hold up under either bet. Get direct-from-source signal: data pulled from property management systems, documented and auditable, built for institutional-grade scrutiny.
Never scraped • No survey data
Trusted by Leading Brands
Someone else’s numbers can put your capital at risk
A bond-substitute that doesn’t pay the coupon isn’t a substitute for anything
The real estate in your portfolio exists to fund a claim you can’t predict the timing of. If the rent income backing that position was overstated at purchase, the shortfall isn’t theoretical; it’s the difference between having the cash on hand when a policyholder needs $500,000 and not having it.
A loan underwritten on someone else’s numbers isn’t underwritten on yours
A borrower’s rent roll is the number the loan gets underwritten on. Whether that number is real is a separate question — one the rent roll itself can’t answer, because it came from the party with the most to gain from a higher figure. Only independent market rent data can check it.
Independent data is the only number nobody in the deal can shade
Independent data means a source with nothing riding on the number, with no reason to shade it high or low, because it wasn’t built to win a loan or support an asking price. Dwellsy IQ is sourced directly from PMS — where rent is actually set — not filtered through a borrower, a seller, or a broker with a stake in the number.
One data foundation, built for different decisions
Market Analysis Across Geographies
Rent data across 800+ MSAs and 16,000+ ZIP codes, normalized with a consistent methodology, built for evaluating markets before capital enters them.
Multi-Year Historical Depth
Coverage since January 2020 across SFR and multifamily, combined with the Unique Rental Unit Identifier (URU) for consistent unit-level tracking across both underwriting and long-horizon investment decisions.
Track the same unit, the whole hold period
Most rental data ties a record to an address, which breaks the moment a unit is re-listed, renumbered, or the address format changes in a new system. Dwellsy IQ assigns every unit its own permanent identifier, the URU, independent of the address attached to it.
SFR and Multifamily
The same sourcing and methodology covers single-family rentals and multifamily, so a portfolio spanning both asset classes doesn’t require reconciling two different data standards.
Continuous, Not Periodic
Data flows in as property managers set and update rents — not on a survey cycle or a scrape schedule — so the number being checked against is current, not months old.
Fits Your Existing Data Stack
Data available via API for direct integration, AWS S3 for full dataset drops into your own cloud environment, or CSV, JSON, TSV or Parquet for analysts working outside a data warehouse — no rebuild of existing infrastructure required.
How banks and insurers use this data
CRE Portfolio Underwriting
Underwriting teams verify a property’s real final asking rents before closing a loan, replacing borrower projections with owner-disclosed, unit-level data.
Real Estate Investment & Capital Deployment
Investment teams evaluate acquisitions and new markets using current and historical rent data at the asset and geography level, before capital is committed.
Compliance-Ready Sourcing Review
Compliance and legal review teams clear a deal for closing with sourcing documentation built for the reviewers who sign off after the underwriter or investment analyst already said yes.
Market-Level Investment Analysis
Investment and underwriting teams evaluate a market at the ZIP-code or MSA level using real rent data tied to actual local conditions, not a national average.
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.
Get data your underwriting and investment teams can defend
Whether you’re underwriting a CRE loan or deploying capital into a new market, Dwellsy IQ gives your team rent data with documented, auditable provenance — built to satisfy the people who have to sign off before the deal closes.
FAQ
How is Dwellsy data sourced, and can that sourcing be documented for a compliance review?
Dwellsy IQ is sourced directly from property management systems through the Dwellsy marketplace — not scraped from listing sites and not collected through self-reported surveys. That direct sourcing model is documented and can be described specifically in a compliance or regulatory review.
Is this Dwellsy IQ data legally compliant to use for underwriting or investment decisions?
Yes. The dataset is public, owner-disclosed listing data at the unit level. There is no scraped data, no survey data, and no PII involved — which eliminates the legal exposure associated with other alternatives.
How far back does the historical data go?
January 2020 to present, covering real market cycles — useful for both underwriting comparisons and evaluating a market’s trajectory before committing capital.
Our internal approval process involves risk, legal, compliance, and IT security review — can you support that?
Yes. We understand that data vendor approval at institutional scale requires sign-off from multiple internal functions, and we provide the sourcing and security documentation needed to move through that process.
Can data be delivered in a way that fits our existing risk infrastructure?
Yes. Data is available via API for direct integration, AWS S3 bucket for full dataset drops into your own cloud environment, or CSV, JSON, TSV or Parquet delivery for analysts working outside a data warehouse.
What does the Unique Rental Unit Identifier (URU) mean for our risk models?
The URU is a permanent, unit-level identifier that never changes across listings or time. For longitudinal risk models and multi-year stress tests, that means unit-level tracking without the reconciliation overhead that duplicated or re-listed units create in other sources.
Is Dwellsy IQ data appropriate for evaluating a market before deploying capital into it?
Yes. Unit-level, ZIP-code and MSA-level rent data gives investment teams the geographic granularity needed to evaluate a market’s real conditions before capital is committed.
Can data purchases start with one asset class and expand later?
Yes. Enterprise engagements often begin with a single asset class or geography and expand as underwriting or investment teams validate the data more broadly.
Equal Housing Opportunity