ZIP 58562 Property Distress & Foreclosure Data
Grant County, North Dakota's ZIP 58562 registers 15/100 composite distress, which DLRadar reads as low. The most distinctive pressure shows up in construction/permit lag (100/100), structural risk (35/100), institutional ownership (19/100). institutional ownership (19/100) and mortgage stress (13/100) stay muted. Structural risk reads 35/100 against active distress of 4/100.
Prices here sit in a expansion phase: values rose 8.2% over the trailing year, 2.0% off the recent peak, at 57/100 phase confidence. Even climbing markets leave specific parcels in distress; the scoring isolates them.
The typical home is worth about $100,000 (1.3× income, relatively affordable). At $62,188, median income runs below typical U.S. levels. 371 residents call 58562 home, typically aged 46. The demographic-stress sub-score lands at 34/100. Vacancy runs 37.5%, above the national norm and a classic distress-and-opportunity signal. Rent burden reaches 92% of tenant households. 89% of housing is owner-occupied. Around 17% of adults hold a bachelor's degree or higher. There are about 272 housing units across 58562. The poverty rate is 12.1%.
Taken together, 58562 profiles as an active-distress market where motivated-seller and below-market acquisitions concentrate. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.
Distress signal breakdown — ZIP 58562
Tax delinquency, institutional ownership, insurance pressure, NFIP/flood, construction lag, price dislocation and auction velocity — plus the 0 individual distressed properties (owner, address, APN, per-property score and exit read) are in the full DLRadar report.
Nearby ZIPs in Grant County
Unlock the full ZIP 58562 acquisition report
Get every distressed property in 58562 with owner, address, APN, per-property distress score, bank exposure, exit-velocity read and a one-click funding + closing path. Nationwide, refreshed continuously.
Deterministic. Every signal traces to a public dataset · methodology