Who should use the Climate Risk Assessment & Adaptation Planning workflow?
Teams or solo builders working on risk management tasks who want a repeatable process instead of one-off tool experiments.
AI Workflow · Risk Management
Leverage RiskThinking.AI's Climate Digital Twin to measure, manage, and adapt to physical climate risks. This workflow enables scenario modeling, asset-level risk profiling, and proactive adaptation planning for financial institutions and corporations.
Deliverable outcome
A living risk management process with ongoing monitoring, reporting, and periodic reassessment.
30-90 minutes
Includes setup plus initial result generation
Free to start
You can swap tools by pricing and policy requirements
A living risk management process with ongoing monitoring, reporting, and periodic reassessment.
Use each step output as the input for the next stage
Step map
Instead of relying on a single generic AI model, this pipeline connects specialized tools to maximize quality. First, you'll use RiskThinking.AI to a clean, geocoded asset portfolio and a clear risk assessment scope aligned with business objectives. Then, you pass the output to RiskThinking.AI to a multi-scenario, asset-level hazard exposure map with projected intensities for each location and time period. Then, you pass the output to RiskThinking.AI to a ranked list of assets with quantified financial risk metrics, enabling prioritization for adaptation. Then, you pass the output to RiskThinking.AI to a shortlist of cost-effective adaptation strategies per asset or portfolio segment, with clear financial justification. Then, you pass the output to RiskThinking.AI to a documented, actionable adaptation roadmap with clear priorities, timelines, and accountability. Finally, RiskThinking.AI is used to a living risk management process with ongoing monitoring, reporting, and periodic reassessment.
Define Asset Portfolio & Risk Context
A clean, geocoded asset portfolio and a clear risk assessment scope aligned with business objectives.
Run Climate Scenario Modeling with Digital Twin
A multi-scenario, asset-level hazard exposure map with projected intensities for each location and time period.
Perform Asset-Level Risk Profiling
A ranked list of assets with quantified financial risk metrics, enabling prioritization for adaptation.
Identify Adaptation Options & Cost-Benefit Analysis
A shortlist of cost-effective adaptation strategies per asset or portfolio segment, with clear financial justification.
Develop & Prioritize Adaptation Roadmap
A documented, actionable adaptation roadmap with clear priorities, timelines, and accountability.
Monitor, Report & Iterate (Optional)
A living risk management process with ongoing monitoring, reporting, and periodic reassessment.
Gather and standardize the inventory of physical assets (e.g., properties, supply chain nodes, infrastructure) along with their geolocations, construction details, and financial values. Define the risk tolerance thresholds and regulatory reporting requirements (e.g., TCFD, NGFS) that will guide the analysis.
Why RiskThinking.AI: RiskThinking.AI is explicitly mentioned in the step's needs as a portfolio uploader and provides climate risk measurement and scenario analysis, directly aligning with defining asset portfolio and risk context.
Load the asset portfolio into RiskThinking.AI's Climate Digital Twin and execute scenario simulations for each hazard-scenario-year combination. The Digital Twin uses high-resolution climate models and downscaling to project hazard intensities at each asset location.
Why RiskThinking.AI: RiskThinking.AI is explicitly listed as having a 'Climate Digital Twin' and provides scenario and stress testing analysis, directly matching the step's needs.
Combine hazard exposure outputs with asset vulnerability functions (e.g., depth-damage curves, fragility curves) to compute expected annual loss (EAL) and probable maximum loss (PML) for each asset. Rank assets by risk score and identify hotspots.
Why RiskThinking.AI: RiskThinking.AI provides a risk engine and physical asset risk assessment and valuation, directly fulfilling the step's requirement for asset-level risk profiling.
For high-risk assets, generate a menu of adaptation measures (e.g., flood barriers, elevation, green roofs, relocation) with estimated implementation costs and residual risk reduction. Run cost-benefit analysis to compare net present value (NPV) of each option over the asset's lifetime.
Why RiskThinking.AI: RiskThinking.AI includes a CBA module and provides risk measurement and valuation, directly supporting cost-benefit analysis for adaptation options.
Aggregate the recommended actions into a phased implementation plan, prioritizing by risk urgency, cost-effectiveness, and strategic alignment. Define timelines, responsible owners, and key performance indicators (KPIs) to track progress.
Why RiskThinking.AI: RiskThinking.AI provides a reporting dashboard, directly meeting the step's need for developing and prioritizing an adaptation roadmap.
Set up automated monitoring of asset-level risk metrics and adaptation project status. Generate periodic reports for internal stakeholders and regulators (e.g., TCFD disclosures). Re-run scenario modeling as climate data updates or portfolio changes.
Why RiskThinking.AI: RiskThinking.AI includes a monitoring dashboard, directly fulfilling the step's need for monitoring, reporting, and iteration.
§ Before you start
Teams or solo builders working on risk management tasks who want a repeatable process instead of one-off tool experiments.
No. Start with the top pick for each step, then replace tools only if they do not fit your pricing, compliance, or output needs.
Open the mapped task page and compare top options side by side. Prioritize output quality, integration fit, and predictable cost before scaling.
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