Exposure data

Exposure data is the detailed inventory of what is actually at risk: for each insured property or asset, its precise location, replacement value, construction type, building age, occupancy and other characteristics that determine how much damage a given hazard would cause it. It is the input side of risk quantification, distinct from the hazard side that describes what could happen.

A catastrophe model combines exposure data with simulated hazard events and a vulnerability curve to produce loss estimates; the same hurricane simulation run against poor-quality exposure data, missing construction details, wrong coordinates, produces materially different, and less trustworthy, results than the identical simulation run against a well-documented portfolio. Exposure data quality is frequently the binding constraint on model accuracy, more so than the hazard model itself, which is why insurers invest heavily in underwriting data capture.

Exposure data underlies probable maximum loss and return period loss estimates, portfolio accumulation management, and increasingly corporate physical climate risk assessments that need an asset-level inventory of facilities, supply-chain nodes or real estate. Common pitfalls include geocoding errors that place a property at the wrong address entirely, stale valuations that understate replacement cost after construction inflation, and aggregated or estimated exposure data being fed into a model that assumes address-level precision.