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Find growth
Compare lenders, products, channels, and geographies to see where opportunity is forming—and who is reaching it.
Polygon Research · Data Intelligence
Data for Unrivalled Mortgage Market Intelligence
At Polygon Research, every insight we deliver is built upon the most comprehensive, granular, and rigorously processed open data in mortgage and housing finance.
124M+ HMDA records modeled
Loan-level Market intelligence
Open data Processed for decisions
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One connected market view
See the whole mortgage market.
Connected data for decisions across growth, fair lending, and risk.
Mortgage market data is scattered across originations, servicing, securities, demographics, property risk, licensing, and local financial context. Polygon connects it into one decision-ready view—so teams can move from a question to evidence without rebuilding the market first.
Ask on MortgageData.AI02
Strengthen fair lending
Evaluate borrower and neighborhood outcomes in the context of the market actually available to serve.
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Understand risk and change
Connect origination, performance, property, and economic signals to understand how the market is moving.
Connected. AI-ready. One analytical environment for questions that cross the housing finance value chain.
Mortgage Data Sources
Our Key Data Pillars
A high-fidelity view of housing finance starts with individual transactions, then gains meaning through geographic, demographic, economic, performance, and risk context.
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Origination & Market Activity
See who is lending, what borrowers are choosing, and where market share is moving.
Includes
- HMDA LAR
- FHA Endorsements
- FFIEC Demographics
- NMLS
- County recorder data
- Credit box
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Community & Financial Context
Understand local access, branch presence, deposits, and competitive coverage.
Includes
- CRA Geography
- FDIC Branches & Deposits
- NCUA Call Reports
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Consumer & Economic Conditions
Add the household, income, labor, and migration context behind demand.
Includes
- ACS PUMS
- CPS & ASEC PUMS
- Survey of Consumer Finances
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Performance, Property & Risk
Connect origination strategy to loan outcomes, property exposure, and risk.
Includes
- Agency RMBS Disclosures
- Agency Loan Performance
- FEMA Hazard Risk
Connected-data example
From fragmented sources to a grounded answer.
Ask: “Where are first-time buyers entering the market?” Polygon connects activity, local context, household conditions, and risk signals before producing an answer.
Every answer retains its source and vintage.
Grounded answerA connected view of first-time buyers.Ask on MortgageData.ai
Questions about the data
Sources, scale, recency, limitations, and trust.
What data sources power Polygon Research?
We build on authoritative open data across housing finance: HMDA (mortgage applications and originations), agency loan-level disclosures (Fannie Mae, Freddie Mac, and Ginnie Mae), HUD FHA loan-level data, demographics microdata (ACS PUMS, CPS PUMS, ASEC), NMLS mortgage loan officer data, and FEMA National Risk Indicator (NRI) hazard risk data.
How large is your dataset, and why does scale matter?
Scale is what makes conclusions stable. We process complete datasets (not samples), including 138+ million HMDA loan-level records, 1.87B agency loan-level transactions over 6 years, 334M+ ACS microdata records, and decades of loan performance histories—including 25 years of Fannie and Freddie loan performance transactions measured in the billions.
How much historical data do you model?
We model modern HMDA from 2018 forward, agency loan performance back to 2000, and other sources across their available reporting histories. Coverage varies by source; every analysis identifies the source and vintage so comparisons stay apples-to-apples.
What are the data’s limitations, and how are they handled?
Public datasets differ in timing, fields, geography, and coverage. Polygon documents those limits, standardizes definitions, applies transparent assumptions only where needed, and retains source and vintage so users can distinguish observed facts from modeled context.
How current are the datasets?
Freshness follows each source. Agency loan-level disclosures update monthly; HMDA and several demographic sources follow annual reporting cycles. Polygon integrates new releases as they become available and retains the source and vintage so teams can interpret recency appropriately.
How do you ensure data quality, lineage, and trust?
We prioritize data lineage and explainability: every insight is traceable to its source. Our pipeline includes systematic acquisition from official sources, cleansing/standardization (de-duplication, missing value handling, error correction), enrichment (geo, economic, borrower/lender context), analytical modeling, and multi-point QA cross-checks against benchmarks—then continuous refinement as new data arrives.
Are you selling raw data files?
No. We’re not a raw data reseller. Our value is in transforming open microdata into a harmonized, analysis-ready intelligence layer—delivered through SaaS apps designed for fast segmentation, explainable conclusions, and confident decision-making.
Data provenance matters
See how the market intelligence is built.
Review the sources, modeling choices, and methodology that turn public data into decision-ready mortgage intelligence.