AI-built data at a scale and quality the market hasn't seen before

Sustainable finance has outgrown its data.

Issuance, deployment, and resilience still sit in separate places, reported on different timelines, in different formats, to different standards.

Together with Arctal, we're changing that.

ARCTAL

Three Datasets. One connected view

Labelled Bonds

33,000+ instruments. 4,000+ issuers. Use-of-proceeds, impact metrics, and a proprietary avoided emissions calculation.

Green & Transition CapEx

25,000+ companies, structured against a 15-category ICMA-aligned taxonomy. Spent, committed, planned, all source-linked.

Adaptation & Resilience

15,000+ companies across the S&P Global BMI. Four pillars: exposure, governance, investment, opportunity.
Used in combination, they trace capital from how it's raised, to how it's spent, to how it's protected.

AI-native. Source-traceable

Every dataset is built by Arctal's agent-based AI system. It turns unstructured disclosures, frameworks and filings into structured data, with every point linked back to its source and continuously refreshed.

 

AI-native. Source-traceable

Arctal's agent-based AI covers 45,000+ entities across 85 sectors, drawing on 124,000+ source documents. Every data point is traceable to its origin and continuously refreshed. What once took a year now takes a week.

 

Built for the Workflows that Move Markets

Portfolio Construction

Screen for transition credibility and high-impact investments.

Impact Reporting

Quantify portfolio impact with audit trails to source.

Risk Assessment

Link physical exposure to adaptation action.

Advisory & Origination

Benchmark issuances, identify refinancing opportunities.

S&P Global Energy

"Clients need to see the whole picture. Where capital is raised, where it's deployed, and how it stands up to physical climate risk. That's what this partnership delivers."

authors image

Leanne Todd

Head of Horizons

About Arctal

An AI-native data company turning unstructured climate disclosures into structured, high-quality datasets, continuously, at scale.

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