Use Case
Underwriting-Grade Risk Intelligence from Orbit
The Challenge
What Insurance Teams Are Up Against
Your catastrophe models were built on decades of loss history. That history no longer predicts the next storm season well. Flash floods now hit regions with no flood record. Subsidence shows up where ground movement was never modelled. Wildfire spread breaks the old containment assumptions. If you underwrite or reprice a book today, you are pricing against a past that has stopped repeating itself.
After a loss event, claims triage still waits on physical inspections and aerial surveys booked after the fact. That gap between event and evidence often runs days, sometimes weeks. Every day of latency adds loss adjustment expense, delays the call to your claimant, and jams the queue the moment a storm window pushes volume up.
Stress-testing a portfolio means understanding correlated risk across regions, and that is hard when your risk data comes from five vendors with five methodologies and no shared lineage. Regulators want an audit trail. Your team needs one intelligence layer, confidence-scored at the address level and rolled up to the book.
The Solution
How EOSYN Space Solves It
- EOSYN Orbit
Sources multi-constellation data including Sentinel-1 SAR, which sees through cloud cover for flood assessment, and Sentinel-2 optical for vegetation and land-use analysis. The capital-light model gets you the right sensor for the peril and the region, not whatever one satellite happens to be overhead.
- EOSYN Fabric
Calibrates and harmonises satellite data into model-ready cubes with full provenance. Atmospheric correction holds the accuracy. Geometric alignment holds the spatial precision. Provenance records hold up under regulatory review.
- EOSYN Core
Generates per-location risk scores with confidence intervals, trained on flood proximity, vegetation density, ground stability, and topography, then validated against historical loss data. Every score ships with its contributing factors and a model version reference, so your actuaries can trace the number back to its inputs.
- EOSYN Atlas
Delivers risk scores by API straight into your underwriting systems. Post-event damage assessment for claims triage. Batch risk assessment across the whole book for stress testing. Webhook alerts when a threshold breaches.
The Stack
Outcomes
What Changes
- Post-event damage assessment in hours, not days
- 23–31% improved loss prediction accuracy vs. legacy geospatial models (2025 benchmarks)
- Faster catastrophe response with real-time impact assessment and priority routing
- Portfolio-level stress testing on confidence-scored, auditable risk data
Market
Market Opportunity
Geospatial analytics in insurance is projected to grow from USD 7.2 billion in 2025 to USD 17.4 billion by 2034 at a 14.3% CAGR. Climate risk analytics is projected to grow from USD 2.11 billion in 2026 to USD 7.71 billion by 2034.
Social Proof
What Chief Underwriting Officer Look For
“[Testimonial pending client permission — EOSYN Space is in active deployment with select institutions.]”
The recommended engagement model for insurance deployments.