LSEG, the global financial markets infrastructure and data provider, has announced that its licensed data and analytics are now available within Model ML through the firm’s Model Context Protocol (MCP) connector.
The move is designed to give financial services firms secure access to AI-ready content directly inside the workflows where they already operate. Through the integration, users will be able to draw on a broad range of LSEG content, spanning pricing, company reference data, estimates, fundamentals, ownership information, macroeconomic indicators, ESG data, news, forecasts and financial analytical models.
Model ML operates an AI workflow automation platform aimed at the financial services industry. Its purpose-built agents and applications are designed to support research, analysis and the automation of end-to-end processes.
LSEG describes itself as a leading provider of financial markets infrastructure and data, occupying an important social and economic position within the global financial system.
The group works across data and analytics, indices, capital formation, as well as trade execution, clearing and risk management spanning multiple asset classes. Headquartered in the UK, the company operates in 65 countries across EMEA, North America, Latin America and Asia Pacific, employing more than 26,000 people worldwide, over half of whom are based in Asia Pacific. Its shares trade under the ticker LSEG.
LSEG group head of enterprise AI Emily Prince said, “By bringing LSEG’s trusted, licensed data into Model ML through MCP, we are helping financial institutions apply AI to real workflows with greater confidence. This gives users access to high-quality financial content where research, analysis and decisions are already taking place.”
Model ML co-founder and CEO Chaz Englander said, ““Access to trusted financial data is critical for effective AI in financial services. Through this collaboration with LSEG, Model ML users will be able to connect high-quality market intelligence to AI-powered workflows and agents in a secure, enterprise-ready environment.”
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