ZIP 48893 Property Distress & Foreclosure Data

In Isabella County, Michigan, ZIP 48893 scores 15 of 100 for composite distress, a low level on DLRadar's public-record index. Structural risk reads 32/100 against active distress of 1/100. It additionally carries heavy environmental risk: climate & FEMA risk (65/100). Its standout signals are construction/permit lag (46/100), structural risk (32/100), mortgage stress (4/100). By contrast, mortgage stress (4/100) and institutional ownership (3/100) register low.

The market reads expansion — home values rose 5.6% year on year, and 26% higher over three years, at 34/100 phase confidence. Appreciation rarely lifts every parcel — the laggards are the opportunity.

About 5,660 people live here, median age 44. At $71,081, median income runs near typical U.S. levels. The typical home is worth about $180,000 (2.4× income, relatively affordable). There are about 2,882 housing units across 48893. Rent burden reaches 66% of tenant households. Vacancy runs 22.1%, above the national norm and a classic distress-and-opportunity signal. The poverty rate is 15.5%. Around 23% of adults hold a bachelor's degree or higher. 94% of housing is owner-occupied. The demographic-stress sub-score lands at 32/100.

Net-net, 48893 is a working-distress ZIP — the kind that rewards current, parcel-level intelligence. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.

15/100
Composite stress
32/100
Structural risk
1/100
Distress activity

Distress signal breakdown — ZIP 48893

Foreclosure activity0
Mortgage stress4
Climate / FEMA risk65
+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 Isabella County

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Deterministic. Every signal traces to a public dataset · methodology