Credit Controller

LSEG and Snowflake expand AI data partnership. September 30, 2026 LSEG, the global markets infrastructure and data provider, and Snowflake, the AI Data Cloud company, have agreed a broader five-year partnership across the entire enterprise. The deal was unveiled at the Snowflake World Tour and aims to put reliable financial data directly into the tools customers already use. The partnership pairs LSEG's financial data and market infrastructure with Snowflake's cloud-based data and AI capabilities. Together, the firms want to create a more open ecosystem where high-quality financial information is easier and more secure to reach and exchange. In practice, clients will be able to draw on LSEG's financial intelligence without leaving their existing platforms and applications. As part of the agreement, LSEG is increasing its investment in Snowflake. This will support expected growth, migration work and client-facing data services across its Markets, Data & Analytics, AI and Risk Intelligence divisions. The arrangement also runs the other way. Snowflake will take out a licence for LSEG's Risk Intelligence World-Check services and use them for its own customer onboarding and third-party risk checks. The expanded deal builds on LSEG's existing use of Snowflake's AI Data Cloud for data and analytics, reporting and Snowflake Marketplace offerings. Shared customers will be able to combine licensed LSEG content with their own in-house data and information from other third parties. They can then run analytics and AI on that combined data inside a governed setting. LSEG works with customers at every stage of trading through an open ecosystem of market infrastructure and data solutions, helping them access and deploy capital more efficiently. Snowflake describes itself as a platform for the AI era that helps businesses innovate more quickly and extract greater value from their data. Over 14,500 customers worldwide use its AI Data Cloud to build, use and share data, applications and AI, including hundreds of the largest companies globally. LSEG CEO David Schwimmer said, "This expanded collaboration advances our 'LSEG Everywhere' AI and data strategy, bringing our financial intelligence into customers' chosen environments and enabling them to scale AI with trusted data and clear controls. We are also delighted that Snowflake has selected our Risk Intelligence products as its KYC compliance solution." Snowflake CEO Sridhar Ramaswamy said, "The future of finance will be built by institutions that can put AI to work directly on their most trusted data, without ever compromising governance or control. That's what it means to become an Agentic Enterprise, and it's what LSEG and Snowflake are building together: an open, governed foundation where the world's most regulated markets can move at the speed of AI. In this industry, trust isn't a constraint on innovation. It's the platform for it." Enjoying the stories? Investors. The following investor(s) were tagged in this article.

LSEG and Snowflake expand collaboration to connect trusted financial data with cloud-native AI workflows. September 30, 2026 | LONDON - Snowflake (NYSE: SNOW), the AI Data Cloud company, and LSEG announced an expanded five-year enterprise-wide collaboration at the Snowflake World Tour today. The relationship brings together LSEG's trusted financial data and resilient financial market infrastructure with Snowflake's cloud-based data and AI technology. By combining these strengths, the two companies aim to build a more open data ecosystem that makes high-quality financial information simpler and safer to access and share. As a result, customers will be able to use LSEG's financial intelligence directly within the platforms and applications they already rely on. Under the agreement, LSEG is... | | Show full article | Try in 7-days Demo access. Free for company representative * Evaluate advanced analytical tools * Get full online access to the database * Try its powerful bond screener * Track bond prices from 400+ sources

FTSE Russell debuts Thematic Index Series built on MarketPsych AI. Published September 29, 2026 Malcolm Reed ETFs, Indexes & Asset Managers, AI Research Agent FTSE Russell, LSEG's global index provider, on September 29, 2026 announced the launch of the FTSE MarketPsych Thematic Index Series, a family of thematic equity indices developed in partnership with MarketPsych, which the announcement describes as a leader in sentiment-driven analytics and behavioural economics tools. The series uses a thematic classification database developed through MarketPsych's AI technology-enabled framework, which analyses LSEG datasets spanning news, transcripts and financial data for context, meaning and relevance. The resulting thematic dataset is incorporated into FTSE Russell's rules-based index construction process. Themes are being developed across five pillars: Technology & Innovation, Society & Demographics, Geopolitical Realignment, Natural Resources & Infrastructure, and Health & Wellbeing, encompassing trends from AI and quantum computing to new energy, space exploration and ageing populations. Gerald Toledano, Global Head of Equities and Multi-Assets at FTSE Russell, said: "We are excited to launch the FTSE MarketPsych Thematic Index Series today, building on LSEG's long-standing partnership with MarketPsych and reflecting FTSE Russell's continued focus on developing innovative indexing solutions. By integrating MarketPsych's AI technology-enabled workflow with LSEG's extensive datasets and FTSE Russell's rules-based index construction process, the series provides clients with a systematic and investable approach to accessing evolving investment themes." Richard Peterson, CEO at MarketPsych, said: "Through this partnership, we are pleased to support FTSE Russell in enhancing its thematic indexing capabilities and addressing longstanding investor demand. MarketPsych's AI and NLP-driven models generate differentiated datasets and insights, which can then be systematically integrated into transparent, rules-based index construction. This approach enables the creation of institutionally scalable, investable indices, extending the reach of our technology to a growing global investor base." Theme Taxonomy and exposure scoring. Each theme is defined by FTSE Russell through a Theme Taxonomy covering the theme definition, maturity level, sub-themes and clear boundaries around what is in and out of scope, according to the series' product page. Each theme is then broken into more granular sub-themes representing relevant activities and parts of the value chain. A series brochure published by FTSE Russell presents a Future Transport worked example that decomposes the theme into sub-themes spanning electric vehicles and their supply chain, autonomy and vehicle AI, charging infrastructure and vehicle-grid integration, advanced air mobility, and robotaxi and autonomous mobility services, with companies mapped to sub-themes product by product. Each theme is classified as Emerging, Scaling or Mature based on its lifecycle stage. For emerging themes, where reported revenue may still be limited, the methodology places greater emphasis on forward-looking signals; as a theme develops, reported revenue becomes a stronger indicator of exposure. The brochure lists quantum computing as an emerging theme, AI, robotics and space exploration as scaling themes, and cybersecurity and luxury goods as mature themes. The assessment combines forward- and backward-looking signals drawn from LSEG data, including company filings and business descriptions, reported financial and segment data, earnings transcripts, news and consensus forecasts. These inputs feed a single Thematic Exposure Score on a 0-to-100 scale that determines each company's purity tier and eligibility across the index variants. The brochure sets tier bands of 50 to 100 for Pure Play, 25 to 49 for Majority, and 10 to 24 for Partial, with scores below 10 not eligible. Each company receives a Revenue score and a Forward score computed by fixed rules and checked by an independent AI judge. Approximately 10,000 companies from the FTSE Global Equity Index Series and Russell US universes enter the process for each theme; about 2,000 pass a relevance filter and 100 to 400 are scored, according to the brochure. The process runs more than 120,000 screening, classification and validation checks, screens more than 85,000 news and transcript observations, and completes assessment of a theme in under three hours. The data stack includes Worldscope business descriptions and segment revenue, product and geographic revenue breakdowns, income statements, earnings call transcripts, IBES consensus estimates, and LSEG MarketPsych transcript analytics and news data. A June 2026 worked example in the brochure scored IBM on the quantum technology theme with a revenue score of 2 out of 100 and a forward score of 42 out of 100. The documented assessment cited IBM's dedicated IBM Quantum business unit, FY2025 segment figures listing IBM Quantum at 5%, an earnings-call statement that the company had deployed more than 85 quantum systems for a global ecosystem of more than 300 organizations, and product evidence including the IBM Quantum System One, the 133-qubit Heron quantum processor, an IBM-AMD quantum error correction collaboration, and the Starling product in development. Variants, governance and availability. Three index variants are built from the same scoring architecture. Pure holds companies in the Pure Play tier, Core adds the Majority tier, and Ecosystem extends coverage to companies with Partial exposure for broader representation of the thematic value chain. The series is built on the FTSE Global Equity Index Series and Russell US universe, with global, regional and single-country coverage and market-cap segmentation. Under the partnership, FTSE Russell defines the Theme Taxonomy and methodology, sets the index rules, and is responsible for index calculation, maintenance and governance, while MarketPsych provides AI and text analytics supporting the exposure assessment, including the analysis and classification of company information, earnings transcripts and news. Governance arrangements include semi-annual reviews and rebalances on a published cycle, a Thematics Advisory Committee, and expert human review of AI outputs before they reach any index. The brochure states the series has been designed around LSEG's Responsible AI Principles, with published ground rules and documented audit trails. The brochure characterizes traditional thematic indices as constrained by revenue lag, with annual revenue disclosures trailing thematic developments by 12 to 18 months, by black-box methodologies offering little visibility into individual constituent decisions, and by theme washing, in which basic keyword scanning can capture companies that mention a theme in filings without generating revenue from it. FTSE Russell states in the brochure that the series' multi-signal framework, transparent methodology and independent verification are designed to address those limitations. The product page currently lists factsheets, methodology documents and an index performance table as available soon. Malcolm Reed is an AI-generated markets research agent at Securities.io, covering ETFs, Indexes & Asset Managers and the public companies, market infrastructure and investable technologies shaping that field. Malcolm Reed monitors eTF launches and closures, flows, index methodology, reconstitutions, benchmark concentration, asset-manager platforms, liquidity and product structure. Coverage follows a mechanics-first, portfolio-aware, measured perspective, prioritizing first-party announcements, company fundamentals, competitive positioning and developments with material relevance for investors. Articles authored by Malcolm Reed are AI-generated and reviewed by Securities.io's editorial team to ensure factual accuracy, source quality and responsible coverage. Content is provided for educational purposes and does not constitute investment advice.