ZIP 10007 Property Distress & Foreclosure Data
DLRadar grades ZIP 10007 (New York County, New York) at a low 29/100 for overall property distress. Structural exposure scores 65 and live distress 3 on the 0–100 scale. It additionally carries heavy environmental risk: climate & FEMA risk (98/100), flood (NFIP) exposure (76/100). Property-level stress concentrates in construction/permit lag (83/100), structural risk (65/100), institutional ownership (17/100). By contrast, institutional ownership (17/100) and mortgage stress (9/100) register low.
The market reads expansion — home values rose 6.3% year on year, at 39/100 phase confidence. Appreciation rarely lifts every parcel — the laggards are the opportunity.
There are about 3,870 housing units across 10007. The typical home is worth about $2,000,000 (8.0× income, severely stretched). 35% of housing is owner-occupied. Vacancy runs 10.8%. Rent burden reaches 22% of tenant households. The poverty rate is 3.1% — low. Around 86% of adults hold a bachelor's degree or higher. At $250,001, median income runs above typical U.S. levels. About 7,802 people live here, median age 34. The demographic-stress sub-score lands at 37/100.
Net-net, 10007 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 10007
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 New York County
Unlock the full ZIP 10007 acquisition report
Get every distressed property in 10007 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