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Steele County, ND: Foreclosures, Tax Liens & Distressed Properties

DLRadar tracks property distress across Steele County, North Dakota using verifiable public-record signals alone. The county's ZIP scores run from 7 up to 25/100. DLRadar scores 12 ZIPs here, with a mean composite of 17/100. The county's lending-headwind score sits at 50/100 (moderate).

In its peak phase, Steele County home prices rose 4.2% across the last year, at 44/100 phase confidence. This late in the run, the average masks the outliers with opportunity concentrated by ZIP.

Near the cycle top at +4.2% YoY (44/100 confidence), opportunity is parcel-specific — target the few ZIPs carrying distress. A moderate 50/100 lender headwind implies mixed owner- and bank-driven distress.

Distress concentrates in ZIP 58064 (25/100), ZIP 58035 (19/100), ZIP 58056 (19/100), ZIP 58016 (18/100), ZIP 58274 (18/100), ZIP 58230 (17/100) — drill into any for the parcel-level read. Further scored ZIPs: 58277, 58425, 58046, 58267, 58240, 58212.

On the housing-and-income side, Steele County's scored ZIPs show a median household income near $82,162 (near the US norm), vacancy near 24.3%, poverty running near 9%, typical home values near $185,858, residents with a median age around 48.5, an owner-occupied share of 80%. Income, equity and tenure like these set up who is forced to sell and how readily the market absorbs it.

At 17/100 composite over 12 ZIPs, Steele County is a screen-by-ZIP market for a disciplined buyer. Unlock Steele County to see every parcel's owner, address and APN, its own score, the lender behind it and an exit read.

The distress read for Steele County, North Dakota is refreshed as new public records post and uses the same methodology coast to coast, so Steele County stays directly comparable to any other market you track.

The practical read on Steele County, North Dakota is a targeting one — find the ZIPs holding real financial pressure, then work the parcels underneath them. Provenance for Steele County is explicit: recorders and courts for filings, FHFA for prices, FDIC for lenders. No interpolation, no synthetic values.

At the ZIP level, the sharpest readings in Steele County are 58064 (25/100), 58035 (19/100), 58056 (19/100), 58016 (18/100), 58274 (18/100), 58230 (17/100). DLRadar also scores 58277, 58425, 58046, 58267, 58240, 58212 across the county. Each code carries its own composite built from that ZIP's foreclosure, mortgage, tax-lien and lender signals, so two neighboring ZIPs can diverge sharply even inside one county.

Under Steele County's headline composite sit distinct layers — recorded foreclosures, tax and lien delinquency, mortgage stress and bank headwind — each scored separately before they roll up, so the same total can describe very different markets.

FREEBEGIN YOUR 7 FREE DAYS60 minutes, fully open, no payment details and no auto-renewal.Look at the whole pipeline
Peak
Market phase
4.2%
HPI YoY
0%
Drawdown
44
Confidence
Live sampleSample: distressed properties in Steele County ZIPs
ZIPStateDistress score🔒 Owner🔒 Property Address🔒 Parcel ID
58064ND25
58035ND19
58056ND19
58016ND18
58274ND18
58230ND17
58277ND17
58425ND16
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Where distress concentrates in Steele County

Work Steele County, North Dakota at the parcel level

Unlock owner and contact detail, APN, distress scoring, bank-exposure reads and the funding-to-closing workflow for Steele County.

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Spot distress early. Fund it. Close it.

This page answers one question. The platform answers the rest - who owns it, who lends on it, what it costs to close.

Open every module and read it. What stays behind the plan is the identifying detail - owner, contact, parcel ID - and the exports. One trial per customer, no card, no auto-billing.

STEP 1
Open the deal feed
STEP 2
Rank what is worth time
STEP 3
Assemble the paperwork
STEP 4
Match a lender
Open methodology, published Blank where a signal is missing Public data sources only Same model in every county

The rest of the stack behind this page

No single layer decides a deal - macro pressure, lender stress, ZIP detail and parcel data each check the others.

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