COUNTY MORTGAGE MARKET · FIPS 55009
Brown County, Wisconsin
Who lends in Brown County, how much, and to whom — built from HMDA public mortgage disclosure data, U.S. Census ACS housing estimates and FEMA's National Risk Index.
Origination volume · 2025
$1.84B
Origination volumeSum of loan amount over HMDA records with action taken = 1.Originations · 2025
7,330
OriginationsCount of HMDA records with action taken = 1 (loan originated) in the activity year.Denial rate · 2025
10.3%
Denial rateApplications denied (action taken = 3) divided by applications acted upon (actions 1-5).Lenders active · 2025
309
Lenders activeDistinct LEIs with at least one application acted upon (HMDA action taken 1-5, 7 or 8) in the county and year.Market structure
How spread out lending is across the 309 lenders that originated in Brown County in 2025. HHI is the Herfindahl-Hirschman index over lender shares.
Concentration (HHI)
382
unconcentrated
Top-5 lender share
36.7%
of originations
Purchase
56.2%
3,055 loans
Refinance
43.8%
2,377 loans
Origination trend
Annual mortgage origination volume and loan count in Brown County, 2023–2025. Pick a window, export the graph or its data, or click a year to open every record behind it.
Lenders in Brown County
Sort, filter, add columns, export, or open a row for the lender's card. Each row links to the lender's company page and to its Brown County loan records. The panel states which source answered and exactly which lenders that source covers.
TOP TEN LENDERS IN BROWN COUNTY · 10
The ten largest lenders by origination volume — the precomputed county leaderboard, not the whole market.
Loading every lender that acted on an application in this county. The rows below are the precomputed county leaderboard — the ten largest by volume, not the whole market.
Source: the precomputed county lender leaderboard (lender_county_year) — its ten largest lenders by origination volume, not the county. As of HMDA activity year 2025. Denial rate = denials / decisioned applications (originated + approved-but-not-accepted + denied).
ZIP areas in Brown County
All 19 ZIP Code Tabulation Areas that touch Brown County, built by grouping the county's census tracts through the Census 2020 crosswalk. A ZCTA approximates a USPS ZIP code; HMDA itself reports no postal geography, so each row opens the tracts behind it, where the records are exact.
58 of Brown County’s 58 census tracts are grouped into the ZIP areas above, with none left over. The two add up to the county exactly, because each tract is counted once. A ZCTA — ZIP Code Tabulation Area — is the U.S. Census Bureau's area approximation of a USPS ZIP code, not the ZIP code itself. HMDA reports no postal geography at all, so these rows are census tracts grouped by the Census 2020 tract-to-ZCTA relationship file: each tract is counted once, in the single ZCTA covering the most of its land. Housing figures are HMDA tract attributes for activity year 2025, summed over the tracts each ZIP area owns — a ZIP area that owns no tract shows an em-dash, never a zero.
Census tracts in Brown County
All 58 tracts, with the FFIEC income character and HMDA housing attributes of each. Open a tract for its own lender ranking, or open its records directly.
Source: FFIEC census-tract file (income level, MSA, urban/rural) and HMDA tract attributes (population, minority share, housing units), latest loaded activity year. The whole county is listed — the table is filtered and paged in the browser over the complete set, never a server-side slice of it.
Housing & households
U.S. Census American Community Survey 2024 estimates — the demand side behind the lending figures above.
Population
270,892
Median household income
$79,649
Median home value
$266,000
Median gross rent
$1,031
per month
Owner-occupied
66.0%
of occupied units
Housing units
115,493
3.9% vacant
Poverty rate
9.1%
Unemployment
2.6%
Natural-hazard exposure
FEMA National Risk Index ratings for this county — expected annual loss, social vulnerability and community resilience, plus the individual perils rated Relatively High or above.
Overall risk
Relatively Moderate
score 90.0
Social vulnerability
Very Low
Community resilience
Very High
ELEVATED PERILS
Tornado Relatively High · Hail Relatively High
Federal disaster history
Months in which a FEMA disaster declaration was active in this county, from the declarations series.
Months with an active declaration
56
Declarations recorded
9
Incident types on record: Biological, Drought, Flood, Hurricane, Severe Storm.
Everything we hold on Brown County
12 data areas have rows for this county. Each one is one click away below; the 18 we checked and did not find at county grain are named at the end with the reason.
LOAN-LEVEL
The individual HMDA application and origination records behind every figure on this page, pre-filtered to Brown County.
HMDA loan-level (hmda_loan_wide, county_code)
VA
VA-guaranteed lending in Brown County by fiscal year — the veteran channel, which HMDA counts but does not separate from the rest of the government book at this grain.
VA Loan Guaranty geographic loan volume (va_geo_loan_volume, county_fips), folded to fiscal year
VA loans · FY2026
348
—
Purchase share
41.1%
143 loans
IRRRL refinances
132
Cash-out refinances
73
The most recent fiscal year is partial until VA closes it. This file carries no lender key, so VA volume cannot be attributed to a company.
BUILDING PERMITS
New residential units authorised in Brown County — the supply-side leading indicator that runs ahead of purchase originations.
Census Building Permits Survey county series (census_building_permits, geo_id at geo_level 'county')
HOUSING SUPPLY · CENSUS BUILDING PERMITS
Brown County building permits
New privately-owned housing units authorized by building permits — the supply-side leading indicator that runs ahead of housing starts and the purchase-origination pipeline. Single-family (SF, 1-unit) vs. multifamily (MF, 2+ units), by year.
Single-family · 2025
641
+18.9% vs 2024
Multifamily · 2025
569
−45.7% vs 2024
Total authorized · 2025
1,210
−23.8% vs 2024
Permit valuation · 2025
$431.5M
authorized construction value
Units authorized by year
Brown County · total permitted units · hover for the single-family split
Source: U.S. Census Bureau Building Permits Survey (BPS), imputed totals (the published “units authorized” headline). SF = 1-unit; MF = 2+ units. Public no-login Census data. Attribution.
MIGRATION & WEALTH
IRS county-to-county migration flows for Brown County, showing population movement and wealth transfer.
IRS county-to-county migration flows (irs_county_migration, self_geoid)
UAD APPRAISALS
FHFA Uniform Appraisal Dataset aggregates for Brown County.
FHFA UAD aggregate statistics (uad_aggregate_county, geoid) and appraisal-level public use file (uad_puf, county_fips)
ECONOMY & INCOME
Local economy indicators — BLS unemployment rates and BEA personal income for Brown County.
BLS Local Area Unemployment Statistics (bls_laus_county_month, geoid) and BEA personal income (bea_county_income, geo_fips)
BLS Local Area Unemployment
BEA Personal Income
NFIP FLOOD CLAIMS
FEMA National Flood Insurance Program (NFIP) realised flood loss claims in Brown County.
FEMA NFIP redacted claims (nfip_claim, county_code)
ALSO CHECKED
18 more data areas were checked for Brown County and did not earn a tab. A missing tab and an unasked question look the same on screen, so each one is named with the reason it is missing.
- WRONG GRAINFHA
FHA Neighborhood Watch DOES publish county rows, but keys them on a free-text county NAME (“CHITTENDEN|VT”), not a FIPS code, and the single-family endorsement snapshot's property_county is likewise free text. Joining either to a county FIPS by name would attribute one county's delinquency to another wherever a name repeats, so FHA is a state-grain tab only until a curated name→FIPS crosswalk exists
- WRONG GRAINFannie / Freddie
the FHFA public-use database publishes single-family acquisitions at STATE and CENSUS-TRACT grain; no county rollup is published or loaded, and rolling tracts up to counties would double-count the tracts that straddle a county line
- WRONG GRAINGSE credit-risk transfer
CAS and STACR loan-level disclosures publish PROPERTY STATE and a 3-digit zip; neither carries a county code, so credit-risk-transfer collateral cannot be attributed to a county
- WRONG GRAINGinnie Mae
Ginnie Mae's loan-level disclosure publishes PROPERTY STATE and nothing finer — there is no county, ZIP or tract field in the file, so agency-pool collateral has no county grain at all. The same is true of the UMBS pool file (fhfa_mbs_pool), which carries only CA/NY/FL/TX/PR concentration percentages
- WRONG GRAINHousing finance agency
a housing finance agency is a STATE-chartered body — county is not a grain it has. Its programmes reach counties, but the agency itself is one row per state: hfa_agency is keyed on state_code and carries no county column, and there is no county-level agency underneath it to aggregate from
- WRONG GRAINCUSO network
the NCUA CUSO Registry publishes a CUSO's city and STATE and no county at all (cuso_registry, migration 0195). A county FIPS does exist on the member-credit-union side (cuso_credit_union_link.cu_county_fips), but it is the CREDIT UNION'S CHARTER ADDRESS — where the institution is registered, not where the mortgage service it buys is delivered — so a county tab built on it would pin a statewide, often multi-state, service relationship onto the one county a charter document happens to name
- WRONG GRAINSubservicing map
the same absence, one grain finer: subservicing_relationships holds no property or collateral column at all, so there is nothing to aggregate to a county. Where a client is a state HFA, the state housing finance agency area on this hub carries that agency and its named master servicer at its own state grain
- WRONG GRAINCo-issue MSR
the same absence, and worse at county grain: Ginnie's loan-level disclosure publishes property STATE and nothing finer — no county, ZIP or tract field exists in the file — so even the collateral split that is rejected above at state grain is not available here at all
- WRONG GRAINMSR transfer graph
the same absence at a finer grain, with no additional route to one: ginnie_servicing_transfers has no county column and the Ginnie loan-level disclosure it would have to be joined to publishes property state and nothing finer — no county, ZIP or tract field exists in either file
- WRONG GRAINBuilder & realtor JV
the same absence, one grain finer: the affiliation corpus has no geographic column at all, so nothing can be aggregated to a county. The affiliate lender's actual county-level originations are on the HMDA area of the county hub, keyed on the lender rather than on its parent
- WRONG GRAINNon-QM deal calendar
the same structural gap, one grain finer: a 144A non-QM deal publishes no asset-level file at all, so there is no loan, no property and therefore no county to attribute anything to. This is the one absence on this hub that no future load can close
- WRONG GRAINAgency-MBS demand
the same absence, and Ginnie's disclosure has no county field at any grain, so even the collateral allocation that is rejected above at state grain cannot be computed here
- WRONG GRAINComplaints-rate stack
the same broken denominator, plus a numerator that does not reach county either: the CFPB publishes a complaint's state and a partially redacted ZIP and no county, so neither half of this ratio exists at county grain
- WRONG GRAINNMLS licensing
NMLS licences are issued by a STATE regulator and the industry report is published by state agency and quarter; there is no county in the licensing system to aggregate to
- WRONG GRAINCFPB complaints
the CFPB publishes a complaint's STATE and a partially redacted ZIP; it publishes no county, and deriving one from a redacted ZIP would put complaints in the wrong county wherever a ZIP straddles a county line
- WRONG GRAINState enforcement
enforcement orders are issued by a STATE regulator against a licensee; they carry no property or county
- WRONG GRAINWARN notices
a WARN notice names an employer, a CITY and a region — no county code — and matching city to county by name is ambiguous in most states
- WRONG GRAINMortgage employment
the QCEW extract loaded here holds STATE and METRO area types only — the county-level QCEW file is a separate, far larger download that is not loaded, so county mortgage employment cannot be shown honestly
Several of the areas above are published only at state grain. They are all on the WI state hub, which carries the same registry at the grain those sources actually have.
Go deeper
See the Wisconsin state market profile for the statewide picture, the Wisconsin state hub for every dataset we hold on the state in one place, or the national lender leaderboard for who is largest across every market.
Sources: HMDA public loan-level disclosure (CFPB/FFIEC) aggregated to county-year; U.S. Census Bureau American Community Survey; FEMA National Risk Index and disaster declarations. Figures are as loaded — see data attribution.
Fair-lending context: denial rates and demographic figures shown here are descriptive statistics derived from public HMDA and U.S. Census data. HMDA does not contain the credit, income, or underwriting variables that explain most lending outcomes, so a difference between lenders or areas is a statistical observation about published data — not evidence of, and not a determination of, discrimination or redlining by any institution.