Clarity AI Launches Asset-Level Physical Climate Risk Solution for Banks

Clarity AI has announced the availability of its asset-level physical climate risk solution, enabling asset owners, investors and banks to assess climate-related physical risks across 16 climate and nature hazards, nine climate scenarios and five time horizons, with coverage of more than three million assets across over 17,000 companies including more than two million material assets identified through Clarity AI's proprietary framework as critical to core operations. The solution addresses a recognised gap in institutional physical climate risk assessment where more than 75 percent of institutional investors expect physical climate risk to affect asset prices within five years and more than half say extreme weather events are already having a greater impact on investment decisions than in previous years, yet granular asset-level data needed to accurately measure these risks has been unavailable at the required scale and specificity. Alice Borgonovo, Climate Solutions Lead at Clarity AI, said it is no longer enough to simply know a risk exists and that investors need to understand its financial implications and measure it with the same rigour as any other financial risk, describing the solution as bringing the granularity and transparency investors need for informed investment, lending and strategic decisions.

 

The Technology Architecture and Asset Coverage

 

The solution's coverage of more than three million assets across 17,000-plus companies represents a substantially broader physical risk assessment universe than most competing solutions provide, enabling institutional investors with diversified global portfolios to assess physical climate risk exposure across their full investment universe rather than only for the subset of large companies with disclosed asset location data. The proprietary framework that identifies more than two million material assets critical to company core operations addresses one of the most commercially significant methodological challenges in physical climate risk assessment, where the physical risk exposure of a minor warehouse or ancillary facility may be measured but carries little financial relevance compared with the risk to primary manufacturing facilities, distribution hubs or revenue-generating infrastructure that would materially affect earnings if disrupted. The 16 hazard coverage spanning both climate and nature hazards reflects the expanding scope of physical risk assessment beyond conventional temperature and precipitation hazards into nature-related risks including biodiversity loss, ecosystem degradation and water availability that are increasingly recognised as financially material alongside conventional climate hazards.

The nine climate scenario coverage allows institutional users to assess physical risk under different warming trajectories from optimistic near-2-degrees pathways through higher warming scenarios, providing the scenario range needed for regulatory stress testing requirements including the EBA's 2027 banking climate stress test module that requires transition and physical risk scenario analysis. The five time horizon capability enables assessment from near-term risk materialisation through to long-term chronic physical risk exposure, addressing both the immediate investment risk management needs of portfolio managers and the longer-term strategic planning requirements of capital allocation decisions with multi-decade time horizons. The ability for institutions to upload proprietary asset data or request on-demand coverage beyond the standard universe addresses a critical gap for institutional investors with material exposures to private assets, real estate portfolios or infrastructure positions that are not captured in standard company-level asset databases.

 

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Market Context and Competitive Positioning

 

The Clarity AI physical risk solution launch follows MSCI's acquisition of First Street for $120 million and Morningstar Sustainalytics' partnership with XDI and Veridion announced in the same week, illustrating the simultaneous convergence of major ESG data providers on asset-level physical climate risk as the next critical frontier in sustainable investment analytics. The coincidence of these three competitive announcements within days of each other reflects the shared recognition that institutional demand for financially quantified, property-level climate risk data is reaching a tipping point driven by regulatory requirements, extreme weather event frequency and growing investor sophistication about the financial materiality of physical climate risks. Clarity AI's differentiating emphasis on granularity, transparency and financial implication quantification positions the solution within the broader market shift from qualitative physical risk awareness toward quantitative risk measurement that can be integrated into investment decision-making with the same rigour as conventional financial metrics.

For banks subject to the EBA's Pillar 3 ESG disclosure requirements requiring country and hazard-level physical risk exposure disclosure from December 2026, and for asset managers navigating TCFD and TNFD reporting obligations, the Clarity AI solution provides the standardised, comparable asset-level data infrastructure needed to meet regulatory disclosure requirements without building bespoke data collection and analysis capabilities internally. The financial implication quantification dimension that Borgonovo highlights as differentiating Clarity AI from existing solutions addresses the most commercially significant gap between available physical risk data and actionable investment intelligence, where the conversion of hazard exposure probabilities into estimated financial impacts including asset damage, business interruption and credit loss is the critical analytical step that enables risk-adjusted pricing and portfolio construction decisions.

 

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Outlook for Asset-Level Physical Climate Risk Analytics

 

Whether Clarity AI can establish a differentiated competitive position in the rapidly crowding physical climate risk analytics market will depend on the quality and accuracy of its asset materiality identification methodology, the financial implication quantification approach and the breadth of its scenario and hazard coverage relative to the MSCI First Street combination and Morningstar Sustainalytics XDI and Veridion partnership. The simultaneous market entries of multiple well-resourced competitors will accelerate the development of institutional best practices for physical climate risk assessment and disclosure, potentially benefiting the entire market by raising awareness and demand among institutional investors who have not yet integrated physical risk into their investment frameworks. Sustained delivery of granular, accurate and financially relevant physical climate risk assessments would establish Clarity AI as a reference solution for the institutional investor and banking market and demonstrate that AI-powered sustainability analytics platforms can provide genuinely superior physical risk intelligence relative to the data aggregation and basic scoring approaches that have characterised earlier generations of ESG risk tools.