ZIP 53503 Foreclosure, Tax-Lien & Distress Report

Iowa County, Wisconsin · Distress market

Iowa County, Wisconsin's ZIP 53503 registers 11/100 composite distress, which DLRadar reads as minimal. The most distinctive pressure shows up in construction/permit lag (58/100), structural risk (24/100), mortgage stress (3/100). On the quiet end sit mortgage stress (3/100) and institutional ownership (3/100). Structural risk reads 24/100 against active distress of 1/100.

The peak-phase market in 53503 posted values that rose 4.1% over the year, and 20% higher over three years, at 29/100 phase confidence. Near a top, distress surfaces unevenly, so parcel screening beats headline strength.

Population is roughly 1,916 with a median age of 41. Vacancy runs 4.2%. There are about 897 housing units across 53503. Around 27% of adults hold a bachelor's degree or higher. The typical home is worth about $239,900 (2.7× income, relatively affordable). At $85,900, median income runs near typical U.S. levels. 85% of housing is owner-occupied. The poverty rate is 4.7% — low. Rent burden reaches 11% of tenant households. The demographic-stress sub-score lands at 20/100.

Broadly, 53503 is a steadier market — the deals are the exceptions, not the rule. Every signal above traces to a verifiable public dataset, refreshed continuously and scored the same way in every ZIP nationwide.

11/100
Composite stress
24/100
Structural risk
1/100
Distress activity

Distress signal breakdown — ZIP 53503

Foreclosure activity0
Mortgage stress3
Climate / FEMA risk31
+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.

ZIP 53503 Stress Report snapshot

Live ZIP-level distress, market-phase, housing and bank-pressure read — the same report attached to every property.

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Deterministic. Every signal traces to a public dataset · methodology