Property-level rent data for underwriting
DSCR calculations, credit models, and loan origination decisions depend on one thing: whether the rent roll numbers hold up. Validate those numbers with final asking rent pulled from 17M+ listings across 25,000+ property managers, so underwriting is built on the asset you’re financing, not a seller’s inflated numbers.
Never scraped • No survey data
Trusted by Leading Brands
Have you confirmed the rent roll against the market?
What a loan committee actually needs to see
Lenders approve loans on the rent roll, but nobody’s confirmed those rents against the market. If the number is wrong, so is the underwriting.
A rent roll can look accurate and still be wrong
Free months and move-in credits inflate stated rent without showing up on the roll. The numbers stay technically correct while hiding a lower real income.
Final asking rent confirms whether the numbers hold up
Final asking rents, pulled from 17M+ listings across 25,000+ property managers, show whether the rent roll’s numbers hold up or are inflated, so you know the borrower can actually cover the debt.
What makes Dwellsy IQ’s data different for underwriting
First-party data
Dwellsy IQ’s data comes from Dwellsy, the largest free rental listing marketplace, connected directly to 30+ property management systems — where rents are actually set.
Built without the industry’s lead-volume problem
Other marketplaces profit from paid listings and leads — a false, stale or duplicative listing still generates a lead, so nobody has a reason to fix it. Ours is free for renters and property managers. Data accuracy is what we’re paid for.
Legally compliant, always
Every listing is owner-disclosed and captured where the rent is actually set, with no scraped or surveyed data, no legal exposure, and no fraudulent or duplicated units skewing the model.
Beyond the basics
Every listing carries 50+ core attributes plus 250+ tracked amenities and listing photos, so the comp behind your rent roll validation reflects the actual unit, not a stripped-down data point.
Built to stress-test against a full cycle
Historical depth back to January 2020 covers the COVID-era disruption and the post-pandemic normalization.
Built for LOS integration
Delivered in the format that fits your infrastructure: direct LOS integration, cloud delivery, API IQ, MCP IQ, or spreadsheet.
How underwriting and risk teams use Dwellsy IQ’s rent data
Lenders & Mortgage
DSCR calculation on the actual asset
Confirm whether the rent roll numbers hold up or are inflated, so the DSCR you calculate reflects what the borrower can actually repay, not what the rent roll claims.
Direct LOS integration
Delivered directly into your Loan Origination Systems and underwriting models: native integration, cloud delivery, API IQ, or MCP IQ. No dashboards, no manual exports.
Faster origination, without the risk
Close loans faster to win borrower business, knowing the borrower can actually cover the debt instead of funding a deal on rent numbers that don’t hold up once the loan is live.
Banks & Financial Institutions
Underwrite CRE and multifamily loans at volume
Weigh a construction, value-add, or lease-up loan’s pro forma rent against final asking rent for comparable stabilized units, so the loan is sized to what the market will actually support once the property is finished or renovated.
Enterprise-wide credit risk modeling
Feed historical, unit-level rent data back to January 2020 into underwriting models and systems that need credible inputs.
Audit- and regulator-ready data lineage
Every figure traces back to an owner-disclosed listing sourced directly from a property management system. Defensible when a regulator or auditor asks where the number came from.
Insurers
Underwrite the policy on real rent, not the declared figure
Check a landlord’s declared rental income against final asking rent for the unit, so loss-of-rents and landlord coverage is priced on what the property earns, not what the applicant reported.
Claims modeling grounded in real rent behavior
Base claims and exposure models on actual market rent activity instead of inferred or averaged inputs.
Portfolio surveillance across a book of policies
Monitor rent performance across an entire insured portfolio using one consistent, unit-level data 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.
Test it against what you’re using now
Test the data against your own model before you commit. You’ll talk directly with our team and get data pulled specifically for your market.
FAQ
How is Dwellsy IQ’s rent data different from what our underwriting team uses now?
Underwriting teams typically lean on MLS data, ACS/Census figures, survey-based providers, or scraped listings to check a rent roll, and each one falls short of the job. - MLS is built for home sales, not rentals, so fewer than 5% of rentals ever appear in it. - ACS and Census data are aggregated to the tract or county level and lag by a year or more, too coarse and too outdated to validate a single unit. - Survey-based providers collect owner-disclosed rents at the community-average level once or twice a year, which means the number you’re checking against is already months old and was never granular enough to catch a concession in the first place. - Scraped listings are fragmented, legally dubious, and stale, since nobody has an incentive to pull a listing down once it’s done its job generating a lead. Dwellsy IQ is different because the data source comes from the Dwellsy marketplace through property management systems where rent is actually set, captured at the unit level and updated continuously, so you’re validating a rent roll against what a comparable unit is renting for right now, not an average from months ago.
Can Dwellsy IQ’s data integrate into our Loan Origination System?
Yes. Data is delivered through cloud delivery, API IQ, or MCP IQ, whichever fits how your LOS and underwriting models ingest data.
Does Dwellsy IQ provide historical data for backtesting models?
Yes. Historical rent data goes back to January 2020, covering the COVID-era and post-pandemic normalization period.
Is scraped rental data reliable enough for underwriting?
No. Scraped data is collected periodically rather than continuously, carries legal exposure, and is prone to fraudulent, duplicative, or stale listings. None of that holds up when a rent projection determines whether a loan performs.
Can we test the data before committing to a contract?
Yes. Talk to our team about scoped access to test the data against your own underwriting model before signing anything.
Do you sell PII or private renter data?
No. All data is public, owner-disclosed listing information at the unit level. No PII, no private data, no survey responses.
How current is Dwellsy IQ’s rent data used for underwriting decisions?
Data is updated continuously as property managers update their systems. Update frequency for your specific delivery method (API, AWS S3) is confirmed during the sales call.
Which product should we use for underwriting?
Most underwriting teams use Total IQ delivered through AWS S3 or another cloud environment for the complete raw dataset. API IQ is the right fit for programmatic, property-level pulls straight into an LOS or underwriting model, while MCP IQ is built for AI-native workflows that need to query rental data through natural-language or agent-based interfaces. Talk to our team for a direct comparison, since we offer several delivery methods.
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