ZIP 48626 Property Distress & Foreclosure Data

ZIP code 48626 in Saginaw County, Michigan carries a composite property-distress score of 23/100 — a low reading on DLRadar's deterministic public-record index. Structural risk reads 53/100 against active distress of 2/100. It additionally carries heavy environmental risk: climate & FEMA risk (86/100), flood (NFIP) exposure (69/100). What sets it apart are the readings on construction/permit lag (55/100), structural risk (53/100), institutional ownership (16/100). By contrast, institutional ownership (16/100) and mortgage stress (7/100) register low.

The market reads peak — home values rose 4.2% year on year, and 24% higher over three years, at 38/100 phase confidence. Topping markets hide individual distress behind strong averages.

The typical home is worth about $224,100 (2.5× income, relatively affordable). Vacancy runs 0.9%. 91% of housing is owner-occupied. The poverty rate is 7.8%. About 5,813 people live here, median age 49. Rent burden reaches 53% of tenant households. At $81,961, median income runs near typical U.S. levels. Around 31% of adults hold a bachelor's degree or higher. There are about 2,338 housing units across 48626. The demographic-stress sub-score lands at 26/100.

Overall 48626 looks resilient on the surface, so the edge is isolating individual stressed parcels. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.

23/100
Composite stress
53/100
Structural risk
2/100
Distress activity

Distress signal breakdown — ZIP 48626

Foreclosure activity0
Mortgage stress7
Climate / FEMA risk86
+9 more distress dimensions scored for this ZIP

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 Saginaw County

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Deterministic. Every signal traces to a public dataset · methodology