ZIP 48362 Property Distress & Foreclosure Data
DLRadar grades ZIP 48362 (Oakland County, Michigan) at a moderate 34/100 for overall property distress. It additionally carries heavy environmental risk: climate & FEMA risk (98/100), flood (NFIP) exposure (90/100). The latent-versus-live split is 75/100 structural and 6/100 already moving. Property-level stress concentrates in structural risk (75/100), construction/permit lag (64/100), institutional ownership (51/100). By contrast, mortgage stress (19/100) register low.
The market reads expansion — home values rose 5.6% year on year, and 17% higher over three years (phase confidence 34/100). Appreciation rarely lifts every parcel — the laggards are the opportunity.
The typical home is worth about $346,900 (2.9× income, relatively affordable). The demographic-stress sub-score lands at 22/100. Around 25% of renters are cost-burdened. The vacancy rate is 7.1%. At $108,667, median income runs above typical U.S. levels. 86% of housing is owner-occupied. Around 44% of adults hold a bachelor's degree or higher. About 14,746 people live here, median age 45. The poverty rate is 6.1% — low. The ZIP holds roughly 6,399 housing units.
Net-net, 48362 is middle-of-the-pack, where the deals are specific addresses rather than the whole ZIP. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.
Distress signal breakdown — ZIP 48362
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 Oakland County
Unlock the full ZIP 48362 acquisition report
Get every distressed property in 48362 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