How We Use LLM Technology to Supercharge Junior Banker Workflows

A boost in productivity and efficiency is among the benefits AI can deliver. We developed and launched the beta release of a Large Language Model-based knowledge agent—FactSet Mercury—to support junior banker workflows and enhance fact-based decision making. 

In the video below, Senior Director of Product Management Collins Dunn shows how the system operates in real time. You will see how users streamline their company research workflows by typing a prompt in natural language, similar to talking with a colleague, to generate provable, source-linked company research from FactSet data. Junior banker users can access FactSet’s comprehensive financial fundamentals and pricing data, along with extensive bank and branch regulatory data. In addition, they can prompt the chatbot to perform tasks such as generating a pitch-ready chart for clients or a SWOT analysis from a company’s 10-K.

The chatbot's release to buy-side clients is planned for Spring 2024, accompanied by an expansion of FactSet's dataset coverage.

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