Sustainability Atlas
Climate Tech & Data·15 min read··...

Playbook: adopting climate risk analytics & scenario modeling in 90 days

the fastest-moving subsegments to watch. Focus on an emerging standard shaping buyer requirements.

In 2024, the global climate risk analytics market reached $9.84 billion, with projections indicating a 17.5% compound annual growth rate through 2033 (Business Research Insights, 2025). Yet despite 63% of multinational corporations integrating climate analytics into operational planning, only 4% of publicly listed companies disclosed in line with all eleven TCFD recommendations (IFRS Foundation, 2024). This implementation gap represents both a regulatory risk and a competitive opportunity. Organizations that move decisively to embed climate scenario modeling into their decision-making frameworks will gain first-mover advantages in risk pricing, capital allocation, and stakeholder credibility. This 90-day playbook provides a structured pathway from initial assessment to operational deployment, designed for investors, financial institutions, and enterprises navigating the transition from voluntary disclosure to mandatory climate risk integration.

Why It Matters

The financial materiality of climate risk has shifted from theoretical concern to quantifiable liability. According to MSCI analysis from December 2024, under a 2°C disorderly transition scenario, baseline probability of default (PD) increases could reach +161% in Europe, +165% in the Americas, and +329% in Asia-Pacific for carbon-intensive portfolios (MSCI, 2024). Climate-related losses recorded $310 billion in damages globally in 2024, underscoring the tangible costs of physical risk exposure.

Regulatory pressure has intensified dramatically. Over 60 nations have adopted or announced mandatory climate risk disclosure requirements as of 2024, with the EU's Corporate Sustainability Reporting Directive (CSRD) entering force and California's climate disclosure laws taking effect in January 2026. The International Sustainability Standards Board (ISSB) has effectively replaced the TCFD framework, with IFRS S2 now mandating scenario analysis for covered entities. Financial institutions face additional requirements under Basel III climate stress testing provisions and Network for Greening the Financial System (NGFS) scenario frameworks.

For investors and asset managers, climate risk analytics have become essential infrastructure. Forty-three of the top 50 global asset managers now utilize MSCI's climate solutions, and 61% of US banks have embedded climate analytics into ESG frameworks (Roots Analysis, 2025). The insurance sector leads in predictive analytics adoption at 45% market share, driven by catastrophe risk estimation needs that expanded 32% between 2023 and 2025.

Beyond compliance, organizations deploying climate scenario modeling gain strategic advantages: improved capital allocation through physical risk-adjusted valuations, enhanced stakeholder confidence through transparent disclosure, and competitive positioning as climate-resilient market participants. The 90-day implementation timeline reflects the urgency of regulatory deadlines and the demonstrated capability of current analytics platforms to accelerate deployment.

Key Concepts

Climate Scenario Analysis involves projecting organizational strategy resilience under different climate futures, typically structured around transition scenarios (policy-driven decarbonization pathways) and physical scenarios (temperature rise and associated hazards). The NGFS provides standardized scenarios ranging from "Orderly Transition" (1.5°C aligned) to "Hot House World" (3°C+ warming), updated in 2024 with enhanced physical risk damage functions and short-term 3-5 year horizons for extreme event modeling.

Physical Risk Assessment quantifies exposure to acute climate hazards (floods, wildfires, tropical cyclones) and chronic stressors (sea level rise, water stress, extreme heat). Leading platforms like S&P Global's Climanomics cover 10 key hazards across 7+ million asset locations, translating exposure into financial impacts on revenue, operating expenses, and capital asset values through decadal projections extending to 2100.

Transition Risk Modeling evaluates vulnerability to policy changes, technological disruption, and market shifts during decarbonization. This includes carbon pricing scenarios, stranded asset analysis, and sector-specific pathway assessments. MSCI's scenario analysis platform enables quantification across NGFS and IPCC-aligned trajectories for 700,000+ listed and unlisted companies.

Climate-Adjusted Credit Risk integrates climate factors into traditional probability of default and loss-given-default models. S&P Global's Climate RiskGauge translates physical and transition risk exposure into credit score impacts and default probability adjustments, covering 2.2 million companies across 140+ industries in partnership with Oliver Wyman.

Materiality Thresholds determine which climate risks require disclosure and management action. The ISSB framework requires qualitative scenario analysis where quantitative approaches are not feasible, providing flexibility while maintaining disclosure rigor.

SectorPrimary Physical Risk KPIsPrimary Transition Risk KPIsTarget Implementation Timeframe
Financial ServicesPortfolio VaR under NGFS scenarios; Asset-level flood/wildfire exposureCarbon intensity of financed emissions; Brown asset ratioDays 1-60
Real EstateProperty-level hazard scores; Coastal/fluvial flood probabilityEnergy performance ratings; Retrofit cost projectionsDays 1-45
InsuranceCatastrophe loss projections; Geographic concentration riskUnderwriting exposure to carbon-intensive sectorsDays 1-30
Energy & UtilitiesAsset downtime probability; Water stress impact on operationsStranded asset exposure; Renewable transition capexDays 30-90
ManufacturingSupply chain disruption probability; Heat stress on workforceScope 1/2 reduction trajectory; Carbon pricing exposureDays 45-90

What's Working

Integrated Platform Deployment

Organizations achieving rapid implementation have consolidated on comprehensive analytics platforms rather than attempting bespoke model development. MSCI's GeoSpatial Asset Intelligence platform, which won the 2025 Climate Risk Analytics Solution of the Year, provides AI-driven physical risk assessment across 28 hazards for 2+ million asset locations. S&P Global's Sustainable1 platform enables bottom-up financial impact analysis with CMIP6 climate models across four RCP/SSP scenarios. These platforms reduce time-to-value by eliminating data infrastructure construction and model validation burdens.

Regulatory-Aligned Scenario Selection

Successful implementations adopt NGFS scenarios as the baseline framework, ensuring regulatory acceptance while enabling comparability. The 2024 NGFS update introduced short-term scenarios (3-5 year horizons) designed for traditional financial stability analysis, bridging the gap between long-term climate projections and near-term stress testing requirements. NatWest Group exemplifies this approach, embedding Climate Risk Macro Models in IFRS 9 expected credit loss calculations aligned with internal stress tests.

Sector-Specific Prioritization

Rather than attempting portfolio-wide analysis simultaneously, leading institutions prioritize sectors identified through regulatory stress tests. NatWest's 2024 implementation focused on UK mortgages (physical flood and coastal erosion impacts) and wholesale lending to oil and gas, aviation, automotive, and power sectors (transition risk). This targeted approach enables faster deployment while addressing highest-materiality exposures.

Cloud-Native Deployment

Cloud-based climate analytics platforms now represent 68% of market deployments, enabling subscription-based access without infrastructure investment. WTW's Climate Quantified platform (launched June 2024) and XDI's Climate Risk Hub (September 2024) exemplify this trend, offering SaaS models that accelerate implementation timelines from months to weeks.

What's Not Working

Data Quality Challenges

Thirty-five percent of organizations report difficulties merging physical and transition risk metrics from disparate sources (Industry Research, 2025). Climate model outputs from different vendors often lack interoperability, requiring manual reconciliation. Asset-level location data remains incomplete for many portfolios, particularly for private companies and complex supply chains.

Talent and Expertise Gaps

Forty-six percent of organizations cite lack of internal expertise as the primary adoption barrier. Climate scenario analysis requires interdisciplinary competencies spanning climate science, financial modeling, and regulatory compliance that few organizations possess in-house. The model risk management challenge is particularly acute: vendor climate models often lack traditional MRM documentation standards, complicating validation processes.

Scenario Analysis Complexity

Climate scenario analysis remains the least commonly disclosed TCFD recommendation, with organizations citing implementation difficulty as the primary omission reason. The requirement to assess strategy resilience under different climate futures demands capabilities beyond traditional risk modeling, including qualitative assessment of business model adaptation potential.

Model Transparency Concerns

Twenty-two percent of financial institutions express concern about "black-box" AI approaches in climate analytics (Business Research Insights, 2025). While AI/ML models deliver 27% accuracy improvements, their opacity creates governance challenges for regulated institutions subject to model risk management requirements.

Standardization Gaps

Twenty-eight percent of modeling frameworks are affected by lack of unified regulatory standards across jurisdictions. Organizations operating globally must navigate divergent requirements across ISSB, EU CSRD/ESRS, SEC (pending litigation outcomes), and regional mandates in Asia-Pacific.

Key Players

Established Leaders

MSCI leads the market with comprehensive ESG and climate integration, covering 700,000+ companies with 2,250 climate metrics spanning nearly 50 years of historical data. Their GeoSpatial Asset Intelligence platform provides AI-powered physical risk assessment used by 43 of the top 50 asset managers globally.

S&P Global Sustainable1 offers Climanomics, the industry's deepest financial impact translation capability, covering 78,000+ public companies (98% of global market cap) and 864,000 private entities. Their Climate Credit Analytics partnership with Oliver Wyman enables portfolio-level credit risk analysis for 2.2 million companies.

Moody's Analytics provides integrated climate risk solutions spanning physical and transition risk assessment, with particular strength in credit risk translation and fixed income applications.

Jupiter Intelligence specializes in high-resolution physical risk analytics, particularly flood modeling, serving insurance and real estate sectors with location-specific underwriting-grade assessments.

RMS (Moody's) leads catastrophe modeling for the insurance industry, with climate-adjusted hurricane, flood, and wildfire models underpinning reinsurance pricing globally.

Emerging Startups

ClimateAI (San Francisco, $37.5M total funding) provides AI-powered climate risk analytics focused on supply chain resilience and agricultural applications, with 51 employees and backing from AIN Ventures, DYDX, and Yaletown Partners.

Mitiga Solutions (Barcelona) acquired Cervest's EarthScan technology in September 2023, consolidating AI-powered Climate Intelligence capabilities for asset-level physical risk assessment. The combined platform serves enterprise clients across real estate, infrastructure, and financial services.

Climate-X offers physical risk analytics specifically designed for banking portfolios, with case studies demonstrating asset-level risk identification across portfolios of 500,000+ properties.

Sust Global provides climate risk data APIs enabling integration into existing enterprise systems, with particular focus on real estate and infrastructure applications.

Key Investors & Funders

Breakthrough Energy Ventures (Bill Gates) has committed significant capital to climate analytics and risk assessment infrastructure companies.

Lowercarbon Capital participated in Cervest's Series A and continues investing in climate intelligence platforms across the risk analytics value chain.

Generation Investment Management (Al Gore) invests in sustainable business intelligence and analytics capabilities supporting the climate transition.

TIME Ventures (Marc Benioff) backed Cervest's development of AI-powered climate risk platforms, supporting the emergence of enterprise-grade solutions.

Draper Esprit led Cervest's $30 million Series A in 2021, demonstrating European venture capital commitment to climate analytics scale-ups.

Examples

1. NatWest Group: Integrating Climate Risk into Credit Provisioning

NatWest Group embedded a Climate Risk Macro Model into IFRS 9 expected credit loss (ECL) calculations beginning in 2023, with enhanced methodology deployed in 2024. The implementation focused on two priority portfolios: UK mortgages (assessing flood and coastal erosion impacts on probability of default and loss-given-default) and wholesale lending to carbon-intensive sectors including oil and gas, aviation, automotive, and power generation. The 2024 enhancement moved from economy-wide carbon price assumptions to expected carbon prices for specific climate transition policies, improving scenario precision. Results showed £8 million in climate-related ECL provisions against a total ECL of £3.4 billion—indicating current minimal material impact while establishing infrastructure for future risk evolution (EY Global, 2024).

2. Tier 1 European Bank: Asset-Level Portfolio Transformation

A major European bank utilized Climate-X's platform to assess physical climate risk across approximately 500,000 property assets in their mortgage and commercial real estate portfolio. The implementation delivered three key outcomes: identification of specific at-risk properties at asset level enabling granular risk management, quantification of dollar provision requirements for regulatory stress testing, and strategic portfolio adjustments including modified lending criteria by postcode and requirements for retrofitting or adaptation measures as loan conditions. The implementation satisfied board and shareholder requirements for climate risk disclosure while providing actionable intelligence for credit decisions (Climate-X, 2024).

3. S&P Global 1200 Portfolio Analysis: Sector Risk Quantification

S&P Global's 2024 analysis of climate physical risk exposure across the S&P Global 1200 companies projected $1.2 trillion in annual climate physical risk costs by the 2050s under current trajectories. The assessment identified Information Technology, Real Estate, and Communication Services as highest-risk sectors through 2050, with water stress and extreme heat as dominant near-term hazards and coastal flooding emerging as the primary risk factor by 2090. This analysis methodology—combining bottom-up asset-level assessment with sector aggregation—provides the template for investor portfolio analytics, enabling capital allocation decisions informed by climate-adjusted valuations (S&P Global Sustainable1, 2024).

Action Checklist

  • Days 1-10: Governance and Mandate Establishment — Secure executive sponsorship and board mandate for climate risk analytics implementation; establish cross-functional steering committee spanning risk, finance, sustainability, and technology; define success metrics aligned with regulatory requirements (ISSB, CSRD, jurisdictional mandates)

  • Days 11-25: Data Inventory and Gap Assessment — Audit existing asset location data quality and completeness; identify data gaps requiring vendor solutions or collection initiatives; assess integration requirements with existing risk management and reporting systems; evaluate current carbon footprint and emissions data infrastructure

  • Days 26-40: Platform Selection and Procurement — Issue RFP to leading vendors (MSCI, S&P Global Sustainable1, Jupiter Intelligence, Climate-X); evaluate based on coverage (asset locations, companies, hazards), methodology transparency (NGFS alignment, CMIP6 models), and integration capabilities; negotiate cloud deployment terms and data governance provisions

  • Days 41-55: Pilot Portfolio Implementation — Deploy selected platform on priority portfolio segment identified through materiality assessment; configure NGFS scenario parameters appropriate to organizational strategy; validate outputs against internal expectations and regulatory requirements; document model risk management considerations

  • Days 56-70: Financial Integration — Translate climate risk outputs into financial metrics (climate-adjusted PD/LGD, portfolio VaR, asset valuations); integrate with IFRS 9 ECL processes where applicable; develop climate risk overlays for credit committee decision-making; establish reporting workflows for TCFD/ISSB disclosure

  • Days 71-85: Enterprise Rollout and Training — Extend platform deployment across full portfolio scope; conduct training programs for risk managers, portfolio managers, and disclosure teams; establish data refresh and model update governance; document methodology for external assurance requirements

  • Days 86-90: Disclosure Preparation and Validation — Prepare climate scenario analysis disclosures meeting ISSB S2 requirements; validate outputs with internal audit and external assurance providers; establish ongoing monitoring and enhancement roadmap; document lessons learned for continuous improvement

FAQ

Q: What is the minimum viable investment for climate risk analytics implementation? A: Cloud-based subscription models have democratized access, with SME-appropriate solutions available from $50,000-150,000 annually depending on portfolio complexity and coverage requirements. Enterprise implementations with comprehensive platform access typically range from $500,000-2 million annually, though this represents significant cost reduction compared to building in-house capabilities requiring climate scientists, data engineers, and model validation specialists. The 39% growth in cloud-based adoption among SMEs between 2023-2025 reflects subscription model effectiveness in lowering barriers to entry.

Q: How do we select between qualitative and quantitative scenario analysis approaches? A: IFRS S2 permits qualitative scenario analysis where quantitative approaches are not feasible, particularly for organizations with limited historical data or complex, non-financial climate dependencies. The recommended approach is a hybrid methodology: quantitative analysis for financially material physical and transition risks where data supports modeling, supplemented by qualitative narrative assessment of strategic resilience and adaptation capacity. Organizations should document their approach rationale clearly for assurance purposes, explaining why qualitative methods were selected where applicable.

Q: Which sectors should prioritize implementation and why? A: Financial services and insurance face the most immediate regulatory pressure, with Basel III climate stress testing requirements and EIOPA ORSA framework mandates driving urgency. Real estate and infrastructure follow closely due to physical risk concentration in fixed assets with long investment horizons. Energy and utilities face dual exposure to transition risk (stranded assets, carbon pricing) and physical risk (operational disruption). Manufacturing and agriculture sectors should prioritize supply chain climate risk given demonstrated vulnerability to extreme weather disruption—the 28% of SMEs now using flood and temperature modeling for logistics represents recognition of this exposure.

Q: How do we address the "black box" concern with AI-powered climate models? A: Model governance for AI-powered climate analytics requires adapted model risk management frameworks. Key practices include: requiring vendors to provide methodology documentation meeting internal MRM standards; establishing model validation protocols that test outputs against historical events and expert judgment; implementing explainability requirements for high-stakes credit decisions; and maintaining human oversight layers for material risk determinations. The 22% of financial institutions expressing concern about AI opacity underscores the importance of governance frameworks that balance analytical power with transparency requirements.

Q: What ongoing maintenance does climate risk analytics require post-implementation? A: Climate analytics require regular maintenance across three dimensions. First, climate model updates: NGFS scenarios are updated periodically (most recently in 2024), requiring scenario parameter refreshes. Second, asset data maintenance: as portfolios change, location data must be updated to maintain coverage accuracy. Third, methodology evolution: as climate science advances and regulatory requirements develop, analytical approaches require enhancement. Organizations should budget for annual platform updates, quarterly data refreshes, and periodic methodology reviews aligned with disclosure cycles.

Sources

Topics

resiliencetransition planMRVbiomaterialscapex

Related Articles