Bloomberg Launches BQuant Assistant as Survey Shows AI Skills in Demand

Bloomberg has launched an AI coding assistant, BQuant Assistant, for the Terminal, at the same time the firm has released results of a survey highlighting how AI skills are overtaking traditional educational degrees as a skillset in demand.

Integrated within the BQuant development environment, BQuant Assistant gives Bloomberg Terminal subscribers the ability to use natural-language prompts to write code, build dynamic applications, and accelerate financial data analysis workflows, across FX, fixed income, equities, commodities and other asset classes. It also brings conversational AI directly into the same Python environment where users build investment strategies, dashboards, and quantitative financial analyses.

The new service can also respond with code suggestions and, subject to the user’s approval, insert and run code directly in their active project within the BQuant sandbox, so users can move from question to result without switching context. Users retain full control over these actions, the firm states, because BQuant Assistant identifies the action it proposes and requests approval before reading from or writing to a notebook.

“Financial professionals are working with increasingly large and complex datasets, but turning an investment idea into a repeatable analysis can still require significant time and specialized coding knowledge,” says Shawn Edwards, Bloomberg’s chief technology officer. “BQuant Assistant brings AI-driven coding that is informed by Bloomberg’s understanding of financial data and quantitative workflows directly into the workflows our clients already use to build investment strategies. By helping every BQuant user — from a portfolio manager sketching out a first query to a quant engineering a multi-asset signal — easily move from a natural-language question to working code, data retrieval, and visualization, we are making it easier for clients to test ideas, refine analyses, and build investment strategies within BQuant.”

Meanwhile, a Bloomberg survey of 500 professionals working at City of London firms with 50+ employees, finds the criteria for entry into quantitative and analyst roles are shifting from traditional credentials toward a combination of judgement and AI fluency.

Among those who make final hiring decisions, 94% said they would hire someone into a quantitative or analytical role without a traditional finance or quant background if they were strong with AI and coding tools, and 54% already have. AI fluency (48%) now ranks ahead of a degree in maths, physics, engineering or computer science (39%) as a requirement to break into quant investing, Bloomberg says.

Barriers to entry are not disappearing, however, for while 51% of respondents say AI is widening the range of backgrounds that can enter the field, only 18% say no specialist background is needed, while 32% say a strong numerical or analytical grounding is still essential. The other half of respondents say entry still requires deep technical skill and a specific academic background (36%) or has become harder because AI expertise is now needed on top of technical skill (13%).

“Technology is driving a shift in how traditional quant roles and techniques, which once demanded a highly specialised skillset, are opening up to a broader range of people with a variety of backgrounds and expertise, including those with arts degrees,” says James Jarvis, head of go-to-market, BQuant. “This democratisation expands the effective talent pool dramatically and in turn drives innovation and extends the art of what is possible. However, while AI lowers the barrier to entry, it does not lower the barrier to knowing when and how to use these tools well. Judgement, critical thinking and human expertise are more crucial skills than ever.”