01 — DATA INPUT

EO Feeds the Chain

Earth Observation data serves as the dynamic foundation for risk modelling

Hazard
How often and how hard a climate event hits a location.
Flood depth, drought indices, wildfire fuel
Exposure
What sits in the impact zone.
Asset locations, building footprints, land-use patterns
Scenarios
Plausible futures the portfolio can be tested against.
CMIP6 and EURO-CORDEX projections via C3S
02 — RISK ENGINE

Combines the Inputs

From data to risk distributions

Risk = H × E × V
Hazard × Exposure × Vulnerability
Vulnerability Curves
Translate a hazard hitting an asset into a damage ratio.
Scenario Simulation
Calculation run across thousands of scenario paths.
Risk Distributions
Probabilistic outcomes, not single point estimates.
03 — VALUE OUTPUT

Finance-Ready Evidence

Outputs that credit teams and supervisors accept

Loss Metrics
Expected Loss and Tail Risk for underwriting and capital allocation.
Climate-adjusted LTV
Re-prices the collateral behind a loan against projected exposure.
Common Evidence Base
For credit committees, supervisors and external auditors.