COUNTY MORTGAGE MARKET · FIPS 46102
Oglala Lakota County, South Dakota
Who lends in Oglala Lakota 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.
This is a very small mortgage market — fewer than 50 originations in 2025. The figures below are real but thin, so this page is excluded from our sitemap and marked no-index.
Origination volume · 2025
$250K
Origination volumeSum of loan amount over HMDA records with action taken = 1.Originations · 2025
2
OriginationsCount of HMDA records with action taken = 1 (loan originated) in the activity year.Denial rate · 2025
41.7%
Denial rateApplications denied (action taken = 3) divided by applications acted upon (actions 1-5).Lenders active · 2025
4
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 4 lenders that originated in Oglala Lakota County in 2025. HHI is the Herfindahl-Hirschman index over lender shares.
Concentration (HHI)
5,288
highly concentrated
Top-5 lender share
100.0%
of originations
Purchase
50.0%
1 loans
Refinance
50.0%
1 loans
Origination trend
Annual mortgage origination volume and loan count in Oglala Lakota County, 2023–2025. Pick a window, export the graph or its data, or click a year to open every record behind it.
Lenders in Oglala Lakota 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 Oglala Lakota County loan records. The panel states which source answered and exactly which lenders that source covers.
TOP TEN LENDERS IN OGLALA LAKOTA COUNTY · 2
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 Oglala Lakota County
All 11 ZIP Code Tabulation Areas that touch Oglala Lakota 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.
3 of Oglala Lakota County’s 4 census tracts are grouped into the ZIP areas above; the other 1 lie in no ZCTA at all — water, parkland or unpopulated area the Census leaves outside every ZIP polygon — and are listed in the census-tract table below. 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 Oglala Lakota County
All 4 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
13,491
Median household income
$41,417
Median home value
$52,900
Median gross rent
$584
per month
Owner-occupied
51.5%
of occupied units
Housing units
3,470
15.8% vacant
Poverty rate
57.6%
Unemployment
16.4%
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 Low
score 49.8
Social vulnerability
Very High
Community resilience
Very Low
ELEVATED PERILS
Strong wind Relatively High
Everything we hold on Oglala Lakota County
7 data areas have rows for this county. Each one is one click away below; the 23 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 Oglala Lakota County.
HMDA loan-level (hmda_loan_wide, county_code)
MIGRATION & WEALTH
IRS county-to-county migration flows for Oglala Lakota County, showing population movement and wealth transfer.
IRS county-to-county migration flows (irs_county_migration, self_geoid)
ECONOMY & INCOME
Local economy indicators — BLS unemployment rates and BEA personal income for Oglala Lakota 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
ALSO CHECKED
23 more data areas were checked for Oglala Lakota 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
- NONE HEREVA
the VA loan-volume file publishes no row for this county FIPS
VA Loan Guaranty geographic loan volume (va_geo_loan_volume, county_fips), folded to fiscal year
- 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
- NONE HEREBuilding permits
the Census permits survey publishes no county series for this FIPS
Census Building Permits Survey county series (census_building_permits, geo_id at geo_level 'county')
- NONE HEREDisasters
no FEMA declaration designates this county
FEMA disaster declarations at their county designation grain (fema_disaster_declarations, county_fips)
- NONE HEREUAD Appraisals
neither FHFA UAD aggregate statistics nor the public use file holds data for this county FIPS
FHFA UAD aggregate statistics (uad_aggregate_county, geoid) and appraisal-level public use file (uad_puf, county_fips)
- NONE HERENFIP Flood Claims
no FEMA NFIP claims are recorded for this county FIPS
FEMA NFIP redacted claims (nfip_claim, county_code)
Several of the areas above are published only at state grain. They are all on the SD state hub, which carries the same registry at the grain those sources actually have.
Go deeper
See the South Dakota state market profile for the statewide picture, the South Dakota 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.