Historical Event Intelligence
Historical Event Intelligence for Insurance and Asset Risk Decisions
A multi-peril, event-level historical catastrophe dataset with enriched footprints, severity, and impact — built for underwriting, claims, and any organization managing physical risk.
Trusted by insurance, reinsurance, supply chain, real estate, and energy teams worldwide.
The Biggest Losses Aren't Caused by Single Events
They're driven by exposure to real-world events over time. DisasterAWARE provides more than historical data — it provides Event Intelligence: a structured, queryable history of real catastrophe events with spatial footprints and impact context.
Most historical datasets
- ✕Provide scores, not events
- ✕Lack footprints, paths, or severity
- ✕Provide fragmented observations
- ✕Do not connect to portfolio exposure
DisasterAWARE delivers
- ✓Fully structured, event-level data — normalized, enriched, ready for analysis
- ✓Event-based — not just time series or static variables
- ✓Multi-peril: wildfire, flood, severe storm, earthquake, and more
- ✓Enhanced with footprints, paths, and severity metrics
- ✓API-accessible and analytics-ready
Multi-Peril Historical Event Data (API + Bulk)
Every Major Catastrophe. One Dataset.
Decades of event-level historical catastrophe data, normalized and enriched for analysis.
Wildfires
Perimeters, spread, and smoke footprints
Tornadoes
Paths and damage points (US-enhanced)
Tropical Cyclones
Tracks, wind radii, and B-deck data
Floods
Extent and severity where available
Earthquakes
PGA grids and intensity fields
Severe Convective Storms
Hail swaths, wind, and storm reports
Enhanced Data Includes
Event Footprints
Polygons, paths, and grids — not just point observations.
Severity Metrics
Wind speed, PGA, hail size, and intensity fields per event.
Time Evolution
Start → peak → dissipation. See how each event evolved.
Exposure-Ready
Portfolio overlay-ready structure for accumulation analysis.
Delivery
Built for Insurance
Enriched Historical Intelligence for Every Stage of the Risk Lifecycle
From underwriting and accumulation through claims validation and post-event analysis — event-level historical catastrophe data that fits how insurance teams actually work.
Underwriting & Risk Selection
- ●Identify high-risk zones using real event history
- ●Move beyond static models and return periods
- ●Validate assumptions with observed event data
Portfolio Accumulation
- ●Detect geographic concentration risk
- ●Analyze overlapping and cascading events
- ●Monitor exposure across regions and perils
Claims & Loss Validation
- ●Validate claims against actual event footprints
- ●Prioritize high-impact claims
- ●Reduce fraud and leakage
- ●Verify event meets parametric trigger thresholds
Post-Event Analysis
- ●Analyze recent events (last 24–72 hours) in historical context
- ●Improve loss estimation and reporting
- ●Feed downstream cat modeling and reserving
The Same Intelligence — Across Industries Managing Physical Risk
The event data trusted by insurers also powers risk decisions in supply chain, real estate, energy, and infrastructure.
Supply Chain & Logistics
- ●Identify disruption-prone regions
- ●Model event-driven delays and risk
Real Estate & Financial Services
- ●Assess property-level event history
- ●Improve investment and lending decisions
Climate & Risk Platforms
- ●Train and validate forward-looking models
- ●Ground modeled risk in real-world event data
Energy & Utilities
- ●Understand infrastructure exposure to historical events
- ●Analyze outage and damage patterns
Engineering & Infrastructure
- ●Design for real-world extremes
- ●Validate planning assumptions with observed events
There Is No Direct Equivalent in the Market
See how Historical Event Intelligence compares to the risk data most teams rely on today.
Most Risk Solutions
- ✕Provide risk scores, not events
- ✕Focus on a single peril
- ✕Lack event-level detail
- ✕Built for visualization, not analytics
DisasterAWARE
- ✓Multi-peril event catalog
- ✓Enhanced footprints (paths, polygons, grids)
- ✓Time evolution of each event
- ✓API-first + bulk delivery, built for analytics
Example Use Case
“What events impacted my portfolio in Texas over the past 2 years?”
Query
- ●Perils: tornado, hail, wildfire
- ●Geography: Texas
- ●Time range: 2023–2025
Output
- ✓Event list with footprints (polygons + tracks)
- ✓Severity metrics per event
- ✓Exposure-overlay-ready geometry
- ✓Time-evolved progression for each event
Sample output: events + footprints + severity overlay
Map illustration coming soon
Bring Real Event History Into Every Risk Decision
Start with a sample dataset, review pricing, or talk to our team about your underwriting, claims, or analytics use case.