ZIP 49665 Property Distress & Foreclosure Data

Osceola County, Michigan's ZIP 49665 registers 16/100 composite distress, which DLRadar reads as low. The most distinctive pressure shows up in construction/permit lag (100/100), structural risk (37/100), mortgage stress (9/100). On the quiet end sit mortgage stress (9/100) and institutional ownership (8/100). Structural exposure scores 37 and live distress 3 on the 0–100 scale.

The expansion-phase market in 49665 posted values that rose 6.3% over the year, and 7% higher over three years, at 37/100 phase confidence. Rising prices can mask pockets of distress, where per-parcel scoring earns its keep.

Owners hold 87% of homes, renters 13%. There are about 2,198 housing units across 49665. DLRadar's demographic-stress index for the area reads 33/100. Rent burden reaches 52% of tenant households. Population is roughly 4,022 with a median age of 45. Educational attainment sits at 13% bachelor's-or-above. Vacancy runs 27.2%, above the national norm and a classic distress-and-opportunity signal. Median household income is $51,125, below the U.S. median near $78,000. Home values center near $150,800, an affordability ratio of 2.7× — accessible. 20.5% of residents fall below the poverty threshold.

On the whole, 49665 leans distressed, with opportunity clustered in specific stressed parcels. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.

16/100
Composite stress
37/100
Structural risk
3/100
Distress activity

Distress signal breakdown — ZIP 49665

Foreclosure activity0
Mortgage stress9
Climate / FEMA risk26
+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 Osceola County

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Deterministic. Every signal traces to a public dataset · methodology