A redlining analysis compares where your loans were made against the demographics of the tracts in your market, and against what lenders of similar size achieved in those same places. HMDAVision builds that from loan-level HMDA data and keeps a record of the filters behind it, so the work stays yours and someone else can follow it later.
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Redlining is the practice of lenders discouraging loan applications, denying equal access to home loans, or avoiding providing them to neighborhoods because of the race, color, or national origin of the residents.
U.S. Department of Justice, Civil Rights Division
The name is literal. Lenders drew red lines on maps around the areas where they would not lend. A century later the analysis is still a map, and it is built from data you already report.
Tracts inside your lending area where you took no applications at all, while others did.
A lower share of lending in majority-minority tracts than lenders of comparable size achieved in the same market.
A footprint that stops at a line matching racial composition rather than county, licensing, or branch geography.
Higher denial rates in particular tracts, especially denials citing insufficient collateral.
Rate-spread loans landing disproportionately in minority tracts, which is where reverse redlining appears.
A distance from peers that grows across HMDA releases rather than holding steady or closing.
One metro, every census tract shaded by minority population share, each circle sized by the number of applications taken there.
Applications cluster in the pale tracts and thin as the shading darkens. In the darkest tracts around Allentown there are almost none, though other lenders originated there the same year. That shape is the first thing an examiner looks at, and the figures below put a number on it.
Illustrative figures shown to make the output legible. Your version is built from your own loan application register against tract demographics for the markets you actually lend in, with every filter recorded.
Comparison sets are built by volume. The convention is every lender originating between 50% and 200% of your HMDA volume in the same market. A peer group you assembled yourself, however reasonable, has drawn criticism in preliminary findings letters.
Two rules catch people out. Purchased loans, reported under action taken code 6, are excluded both from majority-minority tract counts and from the volume formula that builds the set. And strong numbers across majority-minority tracts do not settle the question if few of those tracts are also majority-Black or majority-Hispanic, which recent analyses have looked at separately.
This is the whole scan. Each step is a set of filters in HMDAVision, and each produces something you can put in front of a board, a regulator, or a production meeting.
Your assessment area, field of membership, or the geography your lending and marketing reach. This is the step that decides everything downstream.
Output: a defined market with a documented rationale.
Filter to lenders at 50% to 200% of your originations in that market, excluding purchased loans. That peer group in HMDAVision is fully transparent so you can see the individual members of that group.
Output: a defensible comparison group you did not curate.
Both maps, side by side, at tract level. Look for edges, holes, and boundaries that track demographics rather than geography or licensing.
Output: the visual that starts every conversation.
Your share of lending in majority-minority, majority-Black and majority-Hispanic tracts against peers and against the market aggregate.
Output: a number a board understands without translation.
Denial rates, denials citing insufficient collateral, and higher-priced originations by area. Lending there is not sufficient if the terms differ once you do.
Output: whether the issue is access, outcome, or price.
Year, geography, loan type, metric, comparison group. Keep the selections so the analysis can be reproduced and reviewed by someone who was not in the room.
Output: a trend line, and an audit trail.
Fair lending analysis has traditionally arrived as a deliverable. Someone runs it, a report lands, and the findings are true as of a date that has already passed. That model made sense when the data was hard to reach. It is not any more.
Runs once or twice a year
Findings arrive after the quarter closes
Methodology sits with the vendor
Answering a follow-up question means another engagement
Compliance receives it. Production rarely sees it.
Run it whenever you want to know
Check a market before you enter it
Filters and selections are yours and recorded
Follow-up questions take minutes
The same view serves compliance and production
None of this replaces counsel or a formal program. It means arriving at those conversations already knowing what your data says.
Reaching peer parity in those tracts is 144 originations. A compliance officer sees exposure in that number. A production leader sees volume no competitor is contesting. Same arithmetic, same tracts, same afternoon of work. What changes is who is looking, and what they do next.
The tracts with the widest peer gap tell you where an originator, a partnership, or an office would find demand that is already being served by someone else.
Marketing that reaches the whole market is both a fair lending expectation and the cheapest source of applications you are currently not receiving.
Re-run the same filters. A closing gap is evidence of a working program, and it is evidence you produced yourself rather than purchased.
HMDAVision is so much more than a fair lending tool. It will deeply impact your marketing team and its efforts as well. No serious lender should be without it.
Debra Leone, Deputy General Counsel, Hudson Valley Credit Union
Includes Vision Pro
The full HMDAVision interface to run the six steps yourself: peer sets by volume, tract demographics, mapping, and comparison across every market you lend in.
See ProfessionalIncludes Vision Premium
Deeper history and data export, for teams that need the full time series and want the analysis to live inside their own reporting and board materials.
See ExecutivePolygon Research is a research and analytics firm, not a law firm. Nothing here is legal advice, and a fair lending program should be built with counsel.