Process & Mechanism
The mechanism behind parametric coverage.
From policy binding to payout — every step is deterministic, data-driven, and auditable.
Five deterministic steps from exposure to settlement.
We analyze your geographic exposure area, asset class, and historical weather events. Exposure mapping identifies which NOAA Co-op stations provide the most statistically relevant data for your location. This stage typically takes 3–5 business days and results in a preliminary coverage suitability assessment.
We select the appropriate weather metric for your exposure — SPI-3 for drought, maximum sustained wind speed for storm damage, cooling degree days for heat stress. Threshold calibration uses historical percentile analysis against 30+ years of station data. Backtesting against historical loss years validates that the threshold correlates strongly with actual damage events, minimizing basis risk.
Contract execution defines the coverage window (e.g., April–September growing season), coverage limit, trigger threshold, and reference station set. All terms are fixed at inception — no post-event negotiation is possible. This determinism is the structural guarantee behind the 72-hour settlement promise.
Automated data ingestion runs daily from NOAA/PRISM feeds. The index calculation engine recomputes your trigger metric each day of the coverage window. No human intervention is required. You receive a policy dashboard showing real-time SPI readings against your threshold — accessible via the Policy Portal.
When the trigger index crosses the agreed threshold, settlement confirmation is generated automatically. Wire transfer initiates within 72 hours of confirmed trigger. The payment record includes the full data audit trail — station readings, index calculations, threshold comparison — providing a complete, verifiable record of the trigger event.
Data sources that define the policy.
8,700+ cooperative observer stations across the continental US, many with 50–100 year continuous records. Daily precipitation, temperature, and wind readings archived publicly at NOAA Climate Data Online. Legally defensible, independently verifiable data.
Oregon State University's gridded climatological dataset resolving at 800-meter spatial resolution. Interpolates station observations using topographic and atmospheric modeling to produce spatial precipitation and temperature grids. Used for high-resolution trigger calibration in areas with sparse station coverage.
The Standardized Precipitation Index (SPI) measures precipitation anomaly over a rolling 3-month window relative to the historical distribution for that station and period. SPI-3 = −1.5 is the conventional "severe drought" threshold endorsed by the World Meteorological Organization. Palmer Z-Index provides complementary soil moisture context.
Understanding basis risk.
Basis risk is the gap between the index movement that triggers your policy and the actual loss you experience. It's the honest tradeoff at the center of parametric insurance: you gain speed and certainty, and you accept that the index won't perfectly mirror your individual loss outcome in every event.
We design trigger thresholds to minimize basis risk through granular station selection and historical correlation analysis. By referencing the station most proximate to your insured asset — and calibrating the threshold to the historical percentile where losses actually occur for your crop type or asset class — we reduce the mismatch between index trigger and real-world impact.
The scatter plot at right shows the typical correlation between SPI-3 readings and historical yield loss for a representative row-crop portfolio. At SPI-3 values below −1.5, yield losses exceeding 15% were observed in 87% of historical events in our Southeast portfolio data.
SPI-3 vs. Yield Loss — Schematic Correlation (Illustrative)
Process questions answered.
Ready to design your coverage?
Share your exposure details and we'll walk through trigger options for your location and asset class.