98 INTERVIEW Democratising the power of AI Emily Prince from LSEG explains how financial services professionals are reducing AI agent development cycles from weeks to minutes with LSEG-licensed data in Copilot Studio Not long ago, creating an AI agent meant securing budget, coordinating with engineering teams and waiting weeks – sometimes months – to see an idea take shape. Now, financial services professionals can use Microsoft Copilot Studio to build and refine their own agents in minutes with access to 33 petabytes of LSEG-licenced financial data delivered through an LSEG managed Model Context Protocol (MCP) server. This self-service approach represents a step change in speed and efficiency. “We’re making our trusted LSEG data available as part of Copilot Studio so customers can build custom agents,” says Emily Prince, group head of analytics and AI at LSEG. “When a customer builds their own agent, they can also blend it with their own proprietary data, which is very powerful.” This flexibility means firms are no longer constrained to single-purpose tools or predetermined use cases. Instead, agents can be orchestrated to work together, each performing a specific role as part of a wider workflow. “Agents don’t have to be limited to any one field,” says Prince. “There are all sorts of different ways we can build and organise them from credit agents, to signal agents that capture market events and turn those into action, or even customer-support agents.” A major factor is the democratisation of agent building itself. Less than six months ago, developing even the simplest agent required highly technical skills or direct support from engineering teams, which slowed down experimentation and increased the cost of innovation. The availability of LSEG-licensed data within Copilot Studio changes that. “Copilot Studio is a democratised platform where people can build agents without needing engineering help, which is very liberating,” says Prince. “Teams can now selfserve and build entire applications without a single piece of help.” That shift is most visible in the time it takes to get started. What once required a formal project plan can now be done in the space of a meeting. “Agents can be very fast to build – it could be completed within a couple of minutes,” says Prince. “Of course, complexity adds development time, particularly when users focus on validation and quality assurance. But even that work is more accessible. Mechanically, it is not a complicated thing to do – it’s very controllable for the end user.” Financial services teams are already experimenting with a range of scenarios. A credit analyst, for example, might create an agent that brings together market signals, validated data sources, internal documentation and automated alerts. “You might specify the intent and the descriptor of what the agent is trying to achieve, set the knowledge sources and trigger an email to the portfolio management team based on a market event,” explains Prince. BY ALICE CHAMBERS “ It’s the first ever MCP integration within Copilot Studio – a landmark that gives customers access to great, rich historical content”
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