At Polygon Research, we turn open housing finance and demographics data into straightforward answers at the loan-level. Our tools and transparent datasets help lenders, fintechs, consulting companies, and other stakeholders understand market trends, set smart goals, and ensure fair lending practices. We’re here as your partner, providing the tools, insights, and knowledge you need to thrive in an AI-driven world.
Every loan application, every approval, every denial is public record. We make it searchable, comparable, and actionable.
Unlike black-box analytics, we show you exactly where every number comes from.
When lenders can see exactly how their decisions impact communities, they make better and more confident decisions.
Data literacy is not optional anymore. We teach you about the data sources, the metrics, the housing finance industry, so you get better at asking the right questions.
At Polygon Research, we harness the power of open data to deliver a single source of truth for the housing finance industry. By modeling vast, transparent datasets, we provide a clear and comprehensive view of market trends, lending practices, and borrower behavior. Open data is inherently large and complex, but we make it simple—turning complexity into clarity with careful, consistent modeling.
We’ve modeled millions of detailed application-level transactions and billions of mortgage originations, offering deep insights into market intelligence, fair lending, and trend forecasting.
Our data draws from HMDA, RMBS, HUD, Census, NMLS, Federal Reserve, and market data, ensuring a holistic and reliable perspective.
We’ve bundled the power of loan-level insight from HMDA data with the power of person and households-level insight from American Community Survey (ACS) for deeper understanding of your target market and for building better lending strategy and housing policy to serve them.
We've brought the currency of monthly loan-level insight about originations, loan product mix, and the credit box of agency loans (Fannie Mae, Freddie Mac, and Ginnie Mae), with insight into FHA endorsement activity and broker-lender relationships at the zip code level, and important local economic indicators such as unemployment rate, labor participation, and wage income.
We've delved into the trends of loan performance by servicer, by geography, by product. We allow you to examine your agency loan performance in context of other agency servicers. Find the loans that are prepaying faster and design a retention strategy that works.
We allow you to generate your own report in any of our apps with a click of a button. For those who want custom reports, we offer a rich collection of personalized options.
We've brought the currency of monthly loan-level insight about originations, loan product mix, and the credit box of agency loans (Fannie Mae, Freddie Mac, and Ginnie Mae), with insight into FHA endorsement activity and broker-lender relationships at the zip code level, and important local economic indicators such as unemployment rate, labor participation, and wage income.
In 2020, we teamed up with Fannie Mae's Future Housing Leaders to develop a curriculum focused on data science in housing finance. The live Data and AI in Housing Finance course is not only now available to all stakeholders, but it also developed into Polygon Academy's on-demand offerings.
Val leads our company, positioning Polygon Research as a leading provider of SaaS mortgage market intel solutions for all stakeholders.
With a commitment to excellence and a gift for turning competitive advantages into game-changing solutions, Greg is the powerhouse leading Polygon Research's software, cloud, and data science teams to new heights.