Cash, SC
Cash, SC's wildfire risk, in USFS's own numbers
USFS's Wildfire Risk to Communities model puts Cash at the 82nd national percentile for risk to structures, in USFS's highest wildfire-risk band nationally — a score built from 298 actual buildings. (Source: USFS's Wildfire Risk to Communities methodology.)
Fire likelihood alone (USFS's burn-probability figure) ranks Cash at the 83rd national percentile — 1 points above its risk-to-structures score, a gap driven by how much is actually built there.
Cash's building exposure, zone by zone
Direct exposure dominates in Cash: 91.3% of its 298 buildings, versus 8.7% Indirect and 0% Minimal. Clearing space around a structure changes the outcome here more than any single building-material swap.
Cash against the rest of the country
Cash's risk sits at a similar level relative to South Carolina (88th percentile statewide) as it does nationally (82nd) — this place isn't unusual for its own state either way. Among the 31,521 US communities USFS scores, Cash ranks 5,682 for wildfire risk (1 is highest) and 21,691 by building count (1 is largest). Within South Carolina alone, it ranks 56 of 474 places by risk. See the full county-by-county picture for South Carolina on its state page.
What this risk score means for insurance
At the 82nd percentile nationally, Cash carries the very high rating that has pushed some carriers to limit new business in similarly-scored places elsewhere in the country. Worth comparing quotes rather than assuming last year's renewal terms still apply.
Lowering exposure, not just insuring around it
With 91.3% of Cash in Direct exposure, defensible-space clearing and ember-resistant construction (vents, Class-A roofing) address the exposure this page's own numbers describe, not a generic checklist. See the home-hardening guide.
Where Cash's figures come from
Cash's 82nd-percentile score and its burn-probability figure both come from the same USFS workbook, documented in the methodology guide. The exposure-zones guide covers what Cash's dominant direct exposure actually means, with real examples from across the dataset.