Man Group — the $250 billion-plus asset manager whose roots date to a sugar brokerage founded in 1783— knows change can be hard.
There are both real, bottom-line costs and less tangible cultural ones associated with any tweak, no matter how minor, especially at a big institution.
But the firm’s decision to merge its two long-standing quant brands, AHL and Numeric in June, into a single, $156 billion computer-run unit was unanimous among their management committees, said Russell Korgaonkar, chief investment officer of the newly formed Man Systematic, in an interview with Business Insider.
Two things that made this an easy decision: AI and the talent war.
Advances in artificial intelligence have changed how quantitative research is done and which skills are most in demand for systematic investors. A broader platform that allows for more career advancement and provides bigger opportunities gives the manager an edge in an ultra-competitive recruiting environment.
“How research is done has changed in profound ways,” said Korgaonkar, who was previously the head of AHL.
“We want the best R&D platform we can possibly have.”
AI’s quant impact
The original large language models released by consumer-facing AI companies didn’t move the needle at large-scale quant firms that had been using machine-learning techniques for years. The advent of tools like Anthropic’s Claude code and its ilk did.
For one, it changed — “on the margins” — the type of talent able to work as a quant in a place like Man Group, said Daniel Taylor, the deputy CIO of Man Systematic and former head of Numeric, in an interview with Business Insider.
The firm has traditionally prioritized candidates with a math or coding background for these roles, Taylor said, calling that skill set a “necessity.” Now, humanities majors interested in markets can do these jobs thanks to AI.
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“The ability to think creatively will be a more relevant skill,” Taylor said.
Daniel Taylor is now the deputy head of Man Systematic.
Man Group
It’s also freed researchers from doing time-intensive coding projects, allowing them to focus on different theses and correlations machines can’t think of, Korgaonkar said.
“The depth of research you can do now is just tremendous,” he said
“The quality of research and types of research projects are just way broader, way bigger.”
Where the firm believes the most benefits will come from the merger and AI’s improvements is the firm’s internal library, shared across quant teams, where researchers are expected to update as they’re exploring an idea, even if it ultimately is a dead end.
“All research done well is good research,” Korgaonkar said.
“The idea is to build on top of the collective knowledge.”
The talent question
The manager’s quant leaders believe their offering to potential recruits is hard to beat from a curiosity perspective.
Numeric had traditionally taken a bottom-up approach to equities, while AHL had been more macro, with a top-down view of the world and a trend-following focus. The two units have separate code bases, executives said, and researchers didn’t often collaborate across the firm.
The combined platform — with a significant presence in two academic hubs, with Numeric in Boston and AHL in London — will hopefully entice people who want to follow a hunch wherever it may lead.
“The world is a big place, there are a lot of opportunities here, and the type of work they can do has broadened,” Taylor said about the average researcher, noting that people who were once under the Numeric banner have already started incorporating more macro signals into their work thanks to “across the pond collaboration.”
The firm’s asset base is a selling point as well. At $156 billion, the combined quant unit is comparable to managers such as Cliff Asness’s AQR, and the firm has deep relationships with the world’s largest pools of institutional capital.
The asset growth of the two quant businesses prior to the merger shows how in demand their strategies are. After Man bought Numeric in 2014, the firm’s total quant assets stood at roughly $26 billion. At $156 billion now, capital has grown, on average, 16% each year in the firm’s systematic strategies.
The blended division now stands at more than 250 people, including around 100 technologists, and is growing. A dozen new hires are slated to join the unit in the coming weeks, a spokesperson for the firm said, and no roles were eliminated due to the merger.
“We’re actively scaling the platform,” the spokesperson said in an email.
The next 18 months
Korgaonkar and Taylor both agree that the rapid AI advances meant their once-separate units would have had a change-filled stretch regardless of any internal moves. Even for tech-savvy quants, the transformative nature of AI is jarring. Workflows change, and once-valued skills and cutting-edge datasets become obsolete.
The realization that the organization was undergoing a wholesale change gave Korgaonkar and Taylor confidence that the melding of internal resources and research would be well received.
“We’d both be doing this journey independently,” said Taylor on the broader quant investing changes.
“We’re stronger together.”
Korgaonkar said the combined unit helps break through potential groupthink among operating teams that have worked together for years and approach problems in similar ways. Employees, he said, “don’t mind change as long as they see the point of the change.”
The merger provides a “catalyst” for the organization as a whole to dive into changing how quant strategies are run over the next year and a half, Korgaonkar said, and ultimately improve the bottom line.
“Our job is to take these algorithms and make them work a little bit better each day,” he said.