Secondary solution · Insurance

Turn physical-risk mitigation into quantified avoided loss.

Support risk teams with asset-level mitigation evaluation, portfolio triage, adaptation ROI, and resilience-adjusted reporting without implying a finished underwriting product.

Resilient World Model

Cocoa supply resilience scan

Baseline climate conditions are simulated against resilient future interventions to quantify financial, environmental, and social delta.

Terrain/Wireframe active
Hazard stack/Drought · heat · flood
Scenario/Baseline → resilient future

Baseline yield-at-risk

24%

Exposure before adaptation

Avoided-loss model

$11.8M

Illustrative seasonal delta

Supplier resilience

81 / 100

Future-state score

Sector problem

Risk transfer cannot price resilience clearly without comparable mitigation metrics.

Physical risk mitigation is often visible locally but hard to translate into portfolio-level avoided loss. Insurers need defensible ways to compare baseline risk, intervention impact, residual exposure, and resilience reporting across heterogeneous assets and geographies.

The operating system for climate resilience must connect geospatial risk, implementation evidence, avoided-loss models, quantified ROI, and standardised reporting in one workflow.

Resilient workflow

Plan, implement, measure, evaluate, report.

A shared operating model for moving from climate-risk signal to resilience investment case.

01

Plan

Prioritise projects, assets, suppliers, and geographies against baseline climate conditions.

02

Implement

Translate interventions into trackable resilience programmes with cost, timing, and operational assumptions.

03

Measure

Use geospatial AI, Earth Observation, hyperlocal models, and digital twins to monitor performance.

04

Evaluate

Compare baseline exposure with resilient future states and quantify avoided-loss and ROI.

05

Report

Package decision-grade resilience metrics for finance, operations, risk, and external stakeholders.

Example scenario

Baseline versus resilient future state.

Each scenario is illustrative demo data designed to show the product logic, not customer data or financial advice.

Illustrative demo scenario · Asset risk mitigation

Flood mitigation translated into avoided-loss reporting.

A mixed asset portfolio faces recurring flood exposure. Resilient compares baseline physical-risk layers with a resilient future state after drainage, site hardening, and nature-based buffer interventions.

Baseline conditions

  • High flood exposure across priority assets
  • Limited comparability between mitigation projects
  • Residual risk reported qualitatively

Resilient future state

  • Mitigation package tied to avoided-loss estimates
  • Portfolio triage by risk reduction and payback
  • Resilience-adjusted reporting support

Avoided loss

$8.4M

Illustrative annualised delta

Asset exposure

−31%

Demo exposure reduction

Risk tiers

5 → 3

Portfolio triage bands

Illustrative demo data for product storytelling; not customer, investment, or underwriting advice.

Sector metrics

Decision-grade resilience metrics.

Metrics are designed to help teams compare interventions, report outcomes, and justify adaptation investment.

Avoided loss

$8.4M

Estimated financial loss reduction after mitigation.

Residual exposure

−31%

Exposure remaining after intervention assumptions.

Mitigation ROI

2.6×

Risk reduction versus intervention cost.

Asset priority

Tier 1–5

Portfolio triage for mitigation sequencing.

Reporting status

Audit-ready

Structured resilience metrics for stakeholder reporting.

Use cases

Insurance use cases.

Focused entry points for teams that need practical resilience intelligence without overclaiming product maturity.

Asset-level risk mitigation

Portfolio triage

Adaptation ROI

Resilience-adjusted underwriting support

Risk-reduction reporting

Early access

Build the case for insurance resilience.

Use Resilient to compare baseline conditions, resilient future states, and quantified ROI before adaptation capital scales.