UK Home Insurance Geospatial Risk Map

What happened · The model · Sector map · Relative risk · Temperature · Methodology

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Interactive choropleth of 2,736 UK postcode districts rating eight home-insurance perils — subsidence, weather damage, flood (rivers, sea and surface water), groundwater flooding, theft, escape of water, fire and accidental damage — the four weather-driven perils joined by a C-vine copula, the attritional four priced as independent legs (burglary does not arrive on the storm track, burst pipes answer to cold snaps, dwelling fires follow deprivation and dwelling type, and accidental damage follows the household itself), banded into 10 rating groups. A companion page decomposes good years vs bad years for the whole portfolio.

Coastal erosion is modelled in the vine but deliberately kept out of the premium — see Coastal erosion: modelled, not priced.

Every hazard input is open data, fetched by the scripts here — see DATA_SOURCES.md for all 29 datasets with their endpoints, licences, access quirks and the dead ends worth avoiding. Each peril's loss level is calibrated to published ABI claims payouts, and districts are weighted by census household counts.

⚠️ These are eight-peril technical premiums, not home insurance premiums. A real policy also carries expenses, commission and profit. Expect these figures to be a fraction of what you actually pay. This is a methodology demonstration, not a rating product.

The published site lives in docs/ and is regenerated by scripts/build_site.py; the standalone artefacts it wraps are built by build_map.py and build_analysis.py (both gitignored build outputs — run the pipeline below to produce them).

This is the beginning of the README. Read the rest at the original. Read the full README ↗