Insurance & Risk Weather data built for actuarial precision.

Weather risk models need
data you can prove.

Parametric triggers, claims validation, and climate risk underwriting all depend on reliable, verifiable weather data. WeatherLens delivers accuracy-scored forecasts and historical actuals with a full audit trail — not just a number from a black-box model.

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365-dayhistorical archive

Scoredaccuracy per endpoint

Globalany lat/lon coordinate

Risk Intelligence Use Cases

From parametric products to claims automation, reliable weather data is the foundation of accurate risk modeling.

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Parametric Trigger Validation

Parametric products need verifiable observed actuals, not estimated values. WeatherLens historical data gives you documented observed conditions at exact coordinates for any date in the past 365 days.

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Catastrophe Loss Modeling

Feed historical precipitation, temperature extremes, and wind data into your cat models. Accuracy scores tell you the data quality tier so models can weight inputs appropriately.

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Property & Construction Risk

Climate normals surface the baseline freeze/flood/heat risk for any address. Surface the delta between normal and forecast conditions to flag elevated near-term exposure.

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Crop & Agricultural Insurance

Forecast confidence scores tell underwriters how much uncertainty to price into a policy. Historical actuals validate or challenge loss claims with objective observed data.

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Auto & Mobility Risk

Correlate historical weather conditions with loss data to build location-specific risk factors. Query observed conditions on any claim date for independent validation.

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Climate Risk Disclosures

TCFD and SEC climate risk requirements need defensible data sources. WeatherLens provides citable, auditable weather data tied to observed actuals rather than model projections alone.

Data you can defend in court.

Insurance and risk applications require more than a forecast. They require provenance, accuracy, and a data layer you can explain to regulators.

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NWS-Sourced Observed Data

Historical data from the US National Weather Service — the same source used by FEMA, NOAA, and federal agencies. When a claim dispute goes to arbitration, you have a defensible, federally-recognized data source.

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Accuracy by Lead Time

Our /accuracy endpoint breaks down forecast reliability by 1-day, 3-day, and 7-day lead times for any location. Underwriters can set confidence thresholds — only trigger parametric payouts when data quality meets your bar.

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Climate Normals for Baseline Risk

Multi-year weighted climate averages surface the statistical baseline for any location and day of year. Essential for distinguishing true anomalies from expected seasonal variation in loss models.

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Historical Archive (365 Days)

Pro plan includes 365 days of observed actuals for any global coordinate. Pull exact conditions on a specific date for claims validation, loss correlation studies, or retroactive risk model calibration.

Claims Validation in One API Call

Pull observed conditions for any claim date and location in seconds.

Validate a crop loss claim — Python

import httpx, os

API_KEY = os.environ["WEATHERLENS_KEY"]
BASE = "https://weatherlens.dev/api/v1"

# Claim: freeze damage on March 15 at this farm location
claim = { "lat": 35.227, "lon": -101.831, "date": "2025-03-15" }

# Pull observed actuals for that date
historical = httpx.get(
    f"{BASE}/historical",
    params={"lat": claim["lat"], "lon": claim["lon"], "date": claim["date"]},
    headers={"X-API-Key": API_KEY},
).json()

# Pull climate normals to assess anomaly severity
climate = httpx.get(
    f"{BASE}/climate",
    params={"lat": claim["lat"], "lon": claim["lon"]},
    headers={"X-API-Key": API_KEY},
).json()

obs_low = historical["lowF"]        # → 18°F
normal_low = climate["avgLowF"]     # → 34°F
delta = normal_low - obs_low        # → 16°F below normal

print(f"Observed low: {obs_low}°F | Normal: {normal_low}°F | Delta: {delta}°F")
# → Observed low: 18°F | Normal: 34°F | Delta: 16°F below normal
# Confidence: freeze event validated, 16°F anomaly confirmed

Weather risk models needdata you can prove.

Risk Intelligence Use Cases

Data you can defend in court.

Claims Validation in One API Call

Start with free historical data access

Weather risk models need
data you can prove.