How we design triggers and price climate risk.
Riskwright's underwriting methodology combines publicly verifiable federal weather data — NOAA ASOS, GHCN, USGS stream gauges — with PRISM climate grid analysis and historical correlation testing. We publish our approach because the transparency of the trigger is the product.
Federal networks. Public archives. No proprietary data.
All trigger data is drawn from publicly accessible federal weather observation networks. Any counterparty can independently verify the index reading used for any payout determination.
NOAA ASOS / GHCN
ASOS (Automated Surface Observing System) provides real-time surface observations at ~900 US stations for wind, precipitation, and present weather. GHCN (Global Historical Climatology Network) archives daily records at ~27,000 surface stations for drought SPI and long-term calibration. Both are publicly accessible through NOAA's Climate Data Online portal.
PRISM Climate Grids
Oregon State University's Parameter-elevation Regressions on Independent Slopes Model interpolates station data onto an 800-meter spatial grid, accounting for topographic effects on precipitation and temperature. We use PRISM for geographic basis risk assessment — comparing station readings against the gridded estimate at the insured's exact location before designating a station as the policy reference.
USGS Stream Gauges
USGS National Water Information System (NWIS) provides real-time streamflow and water level data at ~8,000 active gauges. Used for infrastructure flood trigger design where the financial exposure is mediated through river response — stormwater systems, road networks near waterways, coastal protection infrastructure — rather than directly through precipitation accumulation.
What happens between inquiry and policy binding.
Exposure characterization
We gather basic information: commodity or asset type, geographic location, season of concern, and the financial consequence of weather events (revenue loss, cost spike, coverage gap). This defines what the policy needs to protect against.
Station identification and historical analysis
We identify candidate weather stations within the insured's operating geography and pull 10–20 years of historical index data. We calculate the correlation coefficient between the proposed index and historical yield or revenue records where available. If the R² is below 0.65, we either revise the index design or decline.
Threshold calibration and payout structuring
The trigger threshold is set to match the severity at which actual financial distress begins. We use percentile analysis of historical data to calibrate — a threshold at the 20th percentile means the index has triggered in approximately 1 in 5 years historically. Payout structure can be binary (fixed sum at threshold) or proportional (increasing payout as index deepens).
Premium derivation and policy schedule
Premium reflects historical trigger frequency, payout structure, and policy term. The policy schedule documents every element of the trigger: the index formula, the measurement station, the backup station protocol, the threshold level, the payout table, and the assessment calendar. The insured reviews and approves this document before binding.
An honest note on our licensing position.
Riskwright operates as a parametric MGA (Managing General Agent). We design trigger structures, conduct correlation analysis, price premiums, and administer payouts. We are not a licensed insurance carrier. Policies are placed in collaboration with admitted carrier partners and licensed intermediaries where required by jurisdiction.
Parametric insurance regulatory treatment varies by state. We are pursuing state filings as we scale and are currently in regulatory discussions regarding our policy structures in our primary markets. We will tell you clearly what our position is for a given state before any client commitment. If a jurisdiction's regulatory structure doesn't support the placement we're proposing, we'll say so.
Contact underwriting team