LSEG links licensed financial data to Model ML AI workflows
The integration gives Model ML users access to LSEG pricing, reference, macro, ESG and analytics content through an MCP connector.
By Ingrid Halvorsen · Staff Writer
· 2 min read
LSEG said it is making its licensed financial data and analytics available inside Model ML, an AI workflow automation platform built for financial services. The connection, delivered through Model ML’s Model Context Protocol connector, is intended to give users secure access to LSEG content within research, analysis and workflow applications.
The integration adds a range of LSEG datasets and tools to Model ML. According to LSEG, users will be able to access pricing data, company reference information, estimates, fundamentals, ownership data, macroeconomic indicators, ESG data, news, forecasts and financial analytical models.
Model ML provides purpose-built agents and applications for financial services firms. The platform supports research, analysis and end-to-end workflow automation, according to the companies.
How the connection works
The Model Context Protocol connector provides the link between Model ML’s AI workflows and LSEG’s financial content. In practice, that means users working with Model ML agents and applications can draw on LSEG datasets and analytics within the same environment used for research and operational tasks.
For financial institutions, the operational issue is not only whether AI tools can generate outputs, but whether those outputs can be tied to licensed data that firms are permitted to use. LSEG said the arrangement is designed to provide access to AI-ready financial content while maintaining secure use inside financial services workflows.
Emily Prince, LSEG’s group head of enterprise AI, said the connection between LSEG data and Model ML is intended to help financial institutions use AI in established workflows with more confidence. She said the collaboration places LSEG’s financial content in the settings where users are already carrying out research, analysis and decision-related work.
Chaz Englander, co-founder and chief executive of Model ML, said trusted financial data is a key requirement for effective AI use in financial services. He said the collaboration will allow Model ML users to connect market intelligence to AI-powered workflows and agents in what he described as a secure, enterprise-ready environment.
The announcement adds LSEG content to a specialist AI platform focused on financial services automation. LSEG did not disclose commercial terms for the integration.
This story draws on original reporting from Finextra Research.