Deep Dive: Climate Risk Analytics & Scenario Modeling — The Fastest-Moving Subsegments to Watch

Climate risk has transitioned from an abstract environmental concern to a material financial variable that boards, regulators, and investors demand visibility into. The climate risk analytics market, valued at $8.72 billion in 2024, is projected to reach $104.8 billion by 2035, representing a staggering 28.23% compound annual growth rate. Alternative estimates from market research firms position the market at $2.41 billion in 2024 growing to $12.83 billion by 2032 at an 18% CAGR, reflecting different methodological approaches to market definition. Regardless of which estimate proves more accurate, the trajectory is unmistakable: climate risk analytics has become essential infrastructure for modern enterprise risk management.

This explosive growth reflects the convergence of regulatory mandates across more than 60 nations, increasingly sophisticated climate modeling capabilities, and the stark reality of mounting physical climate impacts affecting asset values and business continuity. Today, more than 9,800 multinational corporations deploy advanced climate analytics platforms to assess exposures across their global operations, supply chains, and investment portfolios.

Understanding which subsegments within this rapidly expanding market are moving fastest provides crucial insight for organizations evaluating platform investments, investors seeking opportunity, and practitioners building climate risk capabilities. The landscape is bifurcating between established data providers scaling their offerings and specialized startups tackling specific risk dimensions with novel approaches.

Why Climate Risk Analytics Matter Now

The imperative driving climate risk analytics adoption is regulatory. More than 60 nations have now adopted TCFD-aligned, ISSB, or CSRD climate disclosure mandates of varying stringency. The European Union's Corporate Sustainability Reporting Directive (CSRD), with mandatory reporting beginning in 2025, requires approximately 50,000 companies to disclose climate-related risks and opportunities. The International Sustainability Standards Board's ISSB S2 standard provides a global baseline that numerous jurisdictions are adopting or aligning with. The original Task Force on Climate-related Financial Disclosures (TCFD) framework, while now subsumed into ISSB, established the foundational structure that all modern disclosure regimes build upon.

Beyond compliance, financial institutions face mounting pressure from investors and central banks. The Network for Greening the Financial System (NGFS), comprising over 130 central banks and financial supervisors, has developed standardized climate scenarios that regulators increasingly expect financial institutions to employ in stress testing. Banks, insurers, and asset managers must demonstrate they understand and can manage climate-related exposures across their portfolios.

The physical evidence reinforcing these demands is increasingly undeniable. Global insured losses from natural catastrophes exceeded $100 billion for the fourth consecutive year in 2024, with floods, wildfires, hurricanes, and extreme heat events driving the majority of claims. The intersection of climate change, asset concentration in vulnerable areas, and aging infrastructure creates compounding risks that require sophisticated analytical approaches to quantify and manage.

Key Concepts: Mapping the Risk Landscape

Climate risk analytics platforms must address two distinct but interconnected risk categories. Physical risk encompasses the direct impacts of climate change on assets and operations. Transition risk captures the financial implications of policy changes, technology shifts, and market transformations associated with decarbonization. Critically, research indicates that approximately 35% of organizations struggle to effectively merge physical and transition risk data into unified decision-making frameworks, representing a significant implementation challenge that platform vendors are racing to address.

Physical Risk Analytics

Physical risk breaks down into acute hazards and chronic shifts. Acute physical risks include discrete events like floods, wildfires, hurricanes, and extreme heat stress episodes. These risks are increasingly modeled at asset-level resolution, with leading platforms offering analysis at individual property or facility coordinates rather than regional averages.

Chronic physical risks represent gradual shifts including sea level rise, changing precipitation patterns, average temperature increases, and water stress intensification. These slower-moving changes affect long-term asset values, operational costs, and strategic viability. Properties in coastal zones face declining valuations as insurance availability diminishes. Agricultural operations must anticipate yield impacts from shifting growing conditions. Heat stress projections inform workforce safety planning and cooling infrastructure investments.

The data infrastructure underlying physical risk analysis has advanced substantially. Satellite imagery, IoT sensor networks, and sophisticated atmospheric modeling enable risk characterization at unprecedented granularity. Cloud-based delivery, now representing 67% of deployments, has democratized access to computational resources previously available only to the largest institutions. This cloud-first architecture enables continuous model updates as climate science advances without requiring on-premises infrastructure investments.

Transition Risk Analytics

Transition risk analysis models the financial impacts of decarbonization pathways. Carbon pricing scenarios model how expanding carbon markets and carbon taxes could affect operational costs and asset values. Policy scenarios assess regulatory trajectories including emissions standards, fossil fuel restrictions, and green building requirements. Technology transition scenarios evaluate stranded asset risk as renewable energy displaces fossil generation and electric vehicles displace internal combustion engines.

Transition risk analytics require integrating climate scenarios with financial models at sector and company levels. The challenge lies in translating physical and policy trajectories into cash flow impacts, valuation adjustments, and portfolio-level metrics. Leading platforms combine climate science with financial engineering to produce actionable risk metrics that integrate with existing enterprise risk management frameworks.

The policy landscape driving transition risk continues to evolve rapidly. Carbon border adjustment mechanisms, methane regulations, and sector-specific decarbonization mandates create differentiated exposure profiles across industries and geographies. Organizations need analytics capable of modeling multiple policy scenarios and their cascading effects through value chains.

The Fastest-Moving Subsegments

Asset-Level Physical Risk Platforms

The most dramatic growth is occurring in platforms providing granular physical risk assessment at individual asset coordinates. These solutions enable portfolio-wide screening of thousands of assets against multiple hazard types, with forward-looking projections under different warming scenarios.

Jupiter Intelligence exemplifies this segment, providing climate risk analytics for physical infrastructure with forward-looking projections extending to 2100 under multiple climate scenarios. The company's ClimateScore platform assesses flood, wind, heat, drought, and wildfire risk at the property level, translating hazard exposure into financial impact estimates. Jupiter has secured partnerships with major financial institutions including HSBC and has raised over $100 million in funding to expand its global coverage and modeling capabilities.

Climate X, a London-based startup, has attracted significant attention for its ability to analyze climate risk across millions of assets simultaneously. The platform integrates exposure data from multiple climate hazards and provides financial impact assessments suitable for portfolio-level risk management. Climate X has partnerships with major insurers and banks and has been recognized by the Financial Times as one of Europe's fastest-growing companies, reflecting the explosive demand for asset-level physical risk intelligence.

Flood and Water Risk Specialists

Flood risk has emerged as a particularly active subsegment given its immediate materiality across many geographies. Floods represent the single largest source of insured natural catastrophe losses globally, making granular flood risk assessment a priority for property investors, lenders, and insurers.

Floodbase provides satellite-based flood monitoring and risk assessment, combining synthetic aperture radar (SAR) satellite imagery with machine learning to detect flooding in near-real-time and model future flood risk. The company's technology enables risk assessment in regions lacking historical flood records, addressing a critical gap in developing markets where traditional actuarial data is sparse.

ICEYE operates a commercial synthetic aperture radar satellite constellation providing flood extent mapping within hours of events occurring. This near-real-time capability has proven valuable for insurers responding to catastrophes and for parametric insurance products that trigger based on observed rather than modeled conditions. The company has raised over $300 million and operates one of the world's largest SAR satellite constellations, demonstrating the capital intensity required to build space-based climate observation infrastructure.

Integrated ESG and Climate Platforms

The convergence of climate risk with broader ESG data represents another fast-moving segment. Major data providers are racing to integrate climate risk analytics with their established ESG and financial data offerings, creating one-stop platforms for sustainability-focused investors and corporate sustainability teams.

Moody's has emerged as a leader in this space, ranking #1 in the Chartis RiskTech Climate Risk Solutions 2025 rankings. The company's climate risk solutions integrate physical and transition risk analytics with its credit ratings and financial research capabilities. This integration enables consistent risk assessment across asset classes and alignment with regulatory requirements. Moody's approach exemplifies how incumbent financial data providers are extending their franchises into climate analytics.

S&P Global has similarly invested heavily in climate risk capabilities, combining acquired climate analytics platforms with its established data infrastructure. The company's Climanomics platform provides climate risk assessment for real assets and infrastructure with financial impact modeling, enabling portfolio managers to quantify climate-adjusted returns and risk exposures.

Verisk, traditionally a leader in insurance analytics and catastrophe modeling, has expanded aggressively into climate risk. The company's Atmospheric and Environmental Research division provides climate science expertise, while its property and casualty analytics capabilities enable translation of climate scenarios into insurance pricing and underwriting decisions. Verisk's position at the intersection of catastrophe modeling and climate analytics positions it to capture demand from insurers adapting their models for a changing climate.

Real-World Examples: Implementation Lessons

Moody's: Building the Integrated Climate Risk Platform

Moody's journey to climate risk leadership demonstrates both the complexity and opportunity in this market. The company made multiple strategic acquisitions including Four Twenty Seven (physical risk analytics) and RMS (catastrophe modeling) to assemble comprehensive capabilities. Integration of these acquisitions into a unified platform that connects with Moody's credit analytics required substantial technical and organizational effort over multiple years.

The company's approach emphasizes regulatory alignment, with solutions explicitly designed to support TCFD, ISSB, and CSRD disclosure requirements. This regulatory-first positioning has proven commercially successful, with climate solutions now embedded in many client relationships previously focused solely on credit ratings. The outcome: Moody's climate analytics revenue grew over 40% annually from 2022 to 2024. The lesson: integration with existing workflows and regulatory compliance drives adoption more effectively than standalone climate analytics.

Jupiter Intelligence: Translating Climate Science to Financial Decision-Making

Jupiter Intelligence illustrates the challenge and opportunity of making climate science actionable for financial decision-makers. The company invested heavily in building a climate modeling capability that translates atmospheric science into risk metrics meaningful to asset managers and lenders.

Jupiter's partnership with HSBC demonstrates how climate risk analytics integrate into enterprise risk management. The bank uses Jupiter's platform to assess physical climate risk across its commercial lending portfolio, identifying concentrations of exposure and informing lending decisions. The implementation enabled HSBC to screen over 100,000 commercial property exposures for flood, heat, and wind risk, identifying previously unrecognized concentration risks in Southeast Asian coastal properties. This implementation required developing risk thresholds, integrating with existing portfolio management systems, and training relationship managers on climate risk considerations.

Intensel: AI-Driven Climate Risk for Real Estate

Hong Kong-based Intensel represents the emerging generation of AI-native climate risk platforms. The company applies machine learning to predict climate-related financial impacts on real estate assets, with particular focus on Asian markets underserved by established Western platforms.

Intensel's approach emphasizes speed and scalability, enabling portfolio-wide screening in minutes rather than weeks. The platform has been adopted by major real estate investors including Link REIT, Asia's largest real estate investment trust, which used Intensel to assess climate risk across its portfolio of over 130 properties. The analysis identified several assets with elevated typhoon and flooding exposure, informing capital expenditure priorities for resilience upgrades. The lesson: specialized geographic or asset-class focus can provide differentiation against generalist platforms, particularly in markets where local climate dynamics require specialized modeling.

What's Working and What Isn't

What's Working

Cloud-native delivery: The 67% cloud deployment rate reflects that SaaS delivery models have won. On-premises analytics cannot match the computational scale and update frequency that cloud platforms provide. Organizations adopting cloud-based analytics access continuously improving models without manual upgrades, reducing the burden on internal IT teams.

Regulatory alignment: Platforms explicitly designed around disclosure requirements (TCFD, CSRD, ISSB) are winning because they solve the immediate compliance problem rather than just providing data. Integration of risk analytics with disclosure templates and audit trails addresses what organizations actually need. The most successful vendors provide not just data but workflow tools for assembling and validating regulatory submissions.

Financial integration: Climate risk platforms that translate physical and transition risks into financial metrics compatible with existing risk frameworks achieve adoption. Abstract climate data requires additional work; platforms providing portfolio VaR adjustments, credit rating impacts, and insurance pricing effects are actionable. Translation from climate science to finance is the core value proposition.

What Isn't Working

Generic climate data without financial translation: Data platforms providing only hazard exposure without financial impact modeling struggle with commercial traction. Users need risk, not data. The market has moved beyond simple exposure mapping to demand financially quantified impacts.

Excessive complexity: Platforms requiring extensive customization, specialized climate expertise, or lengthy implementation cycles face adoption barriers. The market rewards usability. Organizations lack internal climate science expertise and need turnkey solutions that non-specialists can operate.

Physical-only or transition-only approaches: Siloed analysis of either physical or transition risk without integration provides incomplete risk pictures. The 35% of organizations struggling to merge these risk dimensions creates opportunity for integrated platforms. Leading vendors address both dimensions in unified frameworks.

Action Checklist

• Inventory current climate risk data sources and analytics capabilities against regulatory requirements (CSRD, ISSB, California SB 253 as applicable)
• Evaluate asset-level physical risk exposure for real estate and infrastructure portfolios using modern granular analytics platforms
• Assess transition risk exposure across sectors most vulnerable to decarbonization policy and technology shifts
• Integrate climate risk metrics into existing enterprise risk management frameworks and board-level reporting
• Develop scenario analysis capabilities aligned with NGFS scenarios for stress testing and strategic planning

FAQ

Q: How granular can climate risk analytics get? A: Leading platforms now provide risk assessment at individual property coordinates, modeling specific hazard exposures for buildings, infrastructure assets, and facilities. This granularity enables portfolio-wide screening and asset-level decision-making. Some platforms model risk at 10-meter resolution for certain hazards.

Q: What's the difference between climate risk analytics and catastrophe modeling? A: Traditional catastrophe modeling focuses on near-term event probabilities for insurance pricing. Climate risk analytics extend analysis decades forward under warming scenarios and integrate transition risk from decarbonization. The markets are converging as cat modelers add climate projections and climate platforms add event modeling. Verisk and Moody's (via RMS) exemplify this convergence.

Q: How do organizations prioritize physical vs. transition risk? A: Prioritization depends on portfolio composition and time horizon. Physical risk is immediately material for real assets in hazard-exposed locations. Transition risk dominates for carbon-intensive sectors facing decarbonization pressure. Most organizations need both but may phase implementation. The 35% of organizations struggling to integrate both dimensions highlights the importance of unified analytics platforms.

Q: What regulatory deadlines drive climate risk analytics adoption? A: EU CSRD Wave 1 reporting began in 2025 for the largest companies. ISSB S2 adoption is accelerating globally, with jurisdictions from Singapore to Canada mandating alignment. California SB 253 requires climate disclosure for large companies operating in the state starting 2027. These overlapping deadlines are driving urgent platform procurement and implementation.

Sources

• Chartis Research. (2025). RiskTech Climate Risk Solutions 2025 Rankings. https://www.chartis-research.com/technology/risktech-climate-risk-solutions
• Network for Greening the Financial System. (2024). NGFS Climate Scenarios for Central Banks and Supervisors. https://www.ngfs.net/ngfs-scenarios-portal/
• Jupiter Intelligence. (2024). Climate Risk Solutions for Financial Institutions. https://www.jupiterintel.com/
• Climate X. (2024). Physical Climate Risk Analytics Platform. https://www.climate-x.com/
• ICEYE. (2024). SAR Satellite Constellation and Flood Monitoring Services. https://www.iceye.com/
• Swiss Re Institute. (2024). Natural Catastrophe Resilience: Closing the Protection Gap. https://www.swissre.com/institute/
• Moody's Corporation. (2024). Climate Risk Solutions and ESG Data Products. https://www.moodys.com/
• Verisk Analytics. (2024). Climate Risk Analytics and Catastrophe Modeling Solutions. https://www.verisk.com/