HMDA stands for Home Mortgage Disclosure Act. It is fair lending legislation implemented via Reg C. HMDA requires US mortgage lenders to report details about the applications they take to the government each year. The collective result is the HMDA Loan Application Register (LAR), a rich annual dataset offering an important lens into the US mortgage market.
HMDA data is best known for its use by federal and state regulators to enforce fair lending laws, as it is frequently used for statistical analysis of application outcomes and for benchmarking compliance activities, but we'll save this discussion for our compliance-focused posts. For now, we'll focus on other features of the HMDA data that can be leveraged by stakeholders - e.g. lenders, non-profits, think tanks, investors, consulting firms, fintechs, and consumer advocates. One of the best of these features of the HMDA LAR data is its
Geographic granularity!
HMDA transactions are geocoded at the census tract level, and roll up to County, MSA, State, and US. This allows for very granular definition of market territory:
In other words, HMDA is your go-to data for exploring mortgage lending patterns at very granular geographic levels like census tracts. And there are about 80,000 census tracts in the U.S. waiting to be explored through HMDA analysis!#nbsp;
At Polygon Research, we model loan-level HMDA data from 2018 forward (with earlier years on request) in our HMDAvision app, making the analysis robust, easy, and accurate. Schedule#nbsp;a demo#nbsp;to see how you can maximize the value of the HMDA data through the use of powerful cloud analytics, or visit#nbsp;our store#nbsp;to subscribe now.
We will continue to answer the question,
in a series of posts throughout the month of March.#nbsp;