Anthropic’s Model Context Protocol (MCP) open standard is driving a new era of data-driven innovation. Financial institutions, known for their data intensity, can now extract deeper insights and integrate them seamlessly into daily operations. By standardising AI interactions with data, MCP helps firms maximise dataset value while maintaining security and governance. Artificial intelligence is reshaping financial markets, with LSEG at the forefront of this transformation.
With its unparalleled data, infrastructure, and strategic partnerships, the organisation is leveraging AI to enhance market efficiency and decision-making.
Its LSEG Everywhere initiative highlights the group’s commitment to embedding AI across financial workflows, creating smarter and faster solutions for clients.
In a recent Q&A, LSEG Group Head of AI Emily Prince discussed the future of MCP and its practical benefits with Nicholas Lin, Head of Product, Financial Services at Anthropic. The conversation shed light on how MCP is designed to make AI more actionable and secure for financial institutions.
When asked to explain MCP, Nicholas Lin said, “MCP is an open standard we developed at Anthropic to help AI models connect to external data and systems. It makes it easier for AI applications to connect to external data sources and take actions inside of compatible applications. In financial services, it enables AI Agents to access enterprise data in a structured, governable way. This helps organisations ensure AI Agents meet enterprise security standards while having the data and action-taking capabilities to perform.”
Nicholas also highlighted how LSEG is leveraging the protocol, saying, “By adopting MCP, you’re making financial data available to AI models in a structured format. This enhances the model’s ability to make sense of the data and utilise it for tasks. And you’re expanding the reach and value of licensed data in the process. MCP will be the foundational protocol for AI Agents to transfer data and take actions. This move positions LSEG data to become a core part of AI workflows within the financial services industry.”
On the topic of real-world applications, Nicholas explained that MCP is already delivering tangible benefits in financial services. “There’s a number of areas in financial services where MCP is already having a major impact. In research, MCP makes it easier for analysts to connect multiple data sources (market data feeds, internal research databases, and proprietary models, etc.) to Claude. This has dramatically improved productivity and research quality.”
Finally, Nicholas offered practical guidance for firms considering MCP adoption: “Start with your data. MCP works best when the underlying content is structured, contextual, and rights-managed. LSEG’s AI Ready Content is a great example—it’s not just data, it’s data designed for AI. If firms can get that foundation right, MCP can help them scale AI safely and effectively.”
Read the full interview from LSEG here.
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