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1,542
CUs report HMDA
2024
15.2%
CU mortgage market share
2024
937,142
Number of Loans
2024
$166.3 B
Loan Volume
2024

2024 Top 10 Credit Unions by Number of Mortgage Originations

2024 Rank Lender Name Originations Lender Market Share YoY
1 Navy Federal Credit Union 82,022 8.76% 14.8%
2 State Employees' Federal Credit Union 28,065 3.00% -17.3%
3 America First Federal Credit Union 16,009 1.71% -1.3%
4 Boeing Employees Credit Union 13,093 1.40% -7.2%
5 GreenState Credit Union 12,784 1.36% 3.5%
6 SchoolsFirst 12,403 1.32% 18.6%
7 Lake Michigan Credit Union 12,245 1.31% 10.1%
8 Pentagon Federal Credit Union 10,514 1.12% -14.6%
9 Summit Credit Union 9,929 1.06% -20.9%
10 Mountain America Federal Credit Union 9,806 1.05% -14.6%

Data Source: HMDAVision, 2024 Lender Rankings, 3/31/2025

58.7%
Subordinate Lien Mix of CU
originations 2024
27.5%
Home Improvement Mix of CU
originations 2024
53.2%
CUs with Assets <$500M
2024
29.5%
CUs Sell to Agencies
2024
Methodology

ACUMA Benchmark Report

ACUMA Benchmark Report Cover

This report is a collaborative effort between ACUMA and Polygon Research, developed using advanced data analytics and visualization capabilities in HMDAVision. Our goal is to help credit unions evaluate their market presence, lending practices, and fair lending outcomes through accurate, comparative, and actionable insights. The report draws on publicly available HMDA (Home Mortgage Disclosure Act) data and U.S. Census data, offering a 360 view of mortgage lending performance across operational, pricing, demographic, and regulatory fair lending dimensions.

Data Sources and Tools

HMDA Data: We analyze the most recent annual release of HMDA loan-level data, refreshed monthly with corrections filed by lenders weekly. This includes detailed information about mortgage applications, originations, pricing, and applicant demographics. (HMDA Data last refreshed on 4/14/2025)

Census Data: Demographic benchmarks are drawn from FFIEC Census data published in July 2024, to contextualize lending outcomes against population-level race and ethnicity distributions.

HMDAVision: All data exploration and visualization are performed within HMDAVision, an interactive analytics platform developed by Polygon Research.

Geographic Modeling

The location of the loan is connected to the location of the property financed with mortgage and is disclosed at the census tract level. Polygon Research rolls up the data to county, state, MSA, national level, and also introducing ZCTA (ZIP Code Tabulation Area) as a proxy for ZIP code. ZCTA (ZIP Code Tabulation Area) is a proxy for ZIP code. ZIP codes are postal designations that change over time. ZCTAs provide a census-compatible geographic unit. Within HMDAVision, we enable side-by-side mapping of Census Tracts and ZCTAs, so users can explore spatial patterns in originations, pricing, and demographic distribution. This dual-level analysis supports both compliance and strategic decision-making.

Demographics

The Minority field in HMDAVision captures applicant demographics through ethnicity and race fields, which are consolidated and engineered to provide insights into lending patterns, particularly for minority populations. Below is an overview of key fields and the minority definition used in reporting.

Ethnicity Fields: CFPB's “derived_ethnicity” field, consolidating the 10 LAR ethnicity fields (5 for applicant, 5 for co-applicant) into a single value. "Ethnicity" is a Polygon Research-derived field that further consolidates Ethnicity_CFPB to align with Census ethnicity values for a single person.

Race Fields:
The CFPB’s “derived_race” field, consolidating the 10 LAR race fields (5 for applicant, 5 for co-applicant) into a single value. "Race" is a Polygon Research-derived field that consolidates Race_CFPB to align with Census race values for a single person.

The "Minority" and "Minority Detail" field are engineered fields combining the derived Race and Ethnicity fields to include all intersections of race and ethnicity, such as Non-Hispanic Black, Hispanic Black, Non-Hispanic White, etc. These fields are designed to analyze lending patterns by distinguishing minority applicants from Non-Hispanic White applicants. For metrics like pull-through rate, records with “Not Applicable” or “Information Not Provided” are excluded.

HMDAVision page with data sources description
Crosswalk between census tract and zip codes in Pittsburgh, select census tracts.
A minority borrower breakdown for a city in Pennsylvania in HMDAVision
Definitions
Metric Definition Purpose Source Interpretation Note
Interest Rate The reported interest rate on fixed-rate mortgage loans; analyzed as an average. Reflects the base cost of borrowing and the pricing strategy. HMDA/LAR Influenced by lender credits, discount points, and borrower risk. Use with the rate spread for assessing high-cost loans and competitive pricing.
Discount Points Borrower-paid points expressed in dollars and/or as a percent of the loan amount. Indicates borrower trade-off between upfront costs and monthly payments. HMDA/LAR (Closing Disclosure - Box A) Higher points may signal rate buydowns. Should be evaluated alongside interest rate and lender credits.
Lender Credits Credits paid by the lender to offset borrower closing costs; reported in dollars and/or percent of loan amount. Used to attract rate-sensitive borrowers or offset third-party fees. HMDA/LAR Typically associated with higher interest rates. Helps decode 'zero cost' or lender-paid closing offers.
Pull-through Rate Share of applications that result in originations. Measures pipeline efficiency and borrower/lender commitment. Engineered by Polygon Research High pull-through rates may reflect stronger borrower profiles or effective pre-qualification and processing.
Rate Spread Difference between the loan's APR and the APOR (Average Prime Offer Rate) at time of lock. Central indicator for high-cost loans under regulatory rules. HMDA/LAR A threshold-based metric used to determine Higher-Priced Mortgage Loans (HPMLs). Sensitive to pricing add-ons and borrower risk adjustments.
Net Charges and Credits Origination charges minus lender credits plus any non-borrower-paid discount points. Captures the true net cost of the loan to the borrower. Derived from HMDA/LAR data Offers a fuller picture than either origination charges or credits alone. Supports cost comparisons across lenders and channels.
DTI (Debt-to-Income) Ratio of borrower monthly debt payments to income. Reflects borrower capacity to repay. A key risk-based pricing input. HMDA/LAR Higher DTI often corresponds with pricing adjustments and overlays. May be capped or excluded in certain loan programs.
CLTV (Combined Loan-to-Value) Ratio of total secured debt on the property to its appraised value. Measures borrower equity and default risk. Influences eligibility and pricing. HMDA/LAR or engineered if not reported directly CLTV above 80% usually triggers MI (Mortgage Insurance) or LLPAs. Used in the LLPA matrix created by PolyGen.
Loan Amount (Average) Average loan amount among originated loans. Indicates market segment (e.g., conforming vs. jumbo) and cost structure. HMDA/LAR Often used to normalize borrower-paid costs (e.g., points, fees) as percent of loan. Affects qualification and investor appetite.
Estimated Credit Score Approximate borrower credit tier derived using pricing behavior and available disclosures. Fills the gap where credit score is not disclosed in HMDA. Engineered by Polygon Research Enables LLPA-style pricing analysis and segmentation when official credit scores are missing. Validated using agency disclosures and market patterns.
Services (Shopped/Not) Closing costs related to third-party services that were or were not shopped for by the borrower. Highlights consumer choice and lender steering behavior. HMDA/LAR Helps evaluate lender transparency, borrower engagement, and the role of broker vs. retail channels.
TIP (Total Interest Percentage) Total interest over the life of the loan as a percent of the loan amount; used for fixed-rate loans only. Offers long-term cost perspective on loan pricing. HMDA/LAR TIP captures the cumulative impact of interest payments. High TIP can flag costly loans even with modest upfront fees or monthly payments.

Data and Strategy Resources

Member-focused mortgage lending begins with market intelligence.

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