Man Group, the world’s largest publicly listed hedge fund, is undertaking a massive multiyear technology overhaul that places artificial intelligence and machine learning at the center of its systematic investing strategy. The new platform, dubbed Condor, represents a tens-of-millions-dollar investment designed to replace outdated systems—some over a decade old—that currently underpin Man AHL, the firm’s systematic-trading division.
Barry Fitzgerald, cohead of front-office engineering and lead technologist on the project, envisions Condor as far more than a simple replacement system. The platform is being built to accommodate future growth across multiple asset classes, investing styles, and exponentially larger data sets. “The worst thing you could do with this is build something that fulfills our need for exactly today,” Fitzgerald told Business Insider, emphasizing the platform’s 10-year-plus operational timeline.
The scope of Condor is ambitious: it will integrate hundreds of futures markets, tens of thousands of equities, and millions of corporate bonds into a single unified platform. This consolidation will enable Man Group to manage risk exposure across all assets simultaneously and make portfolio allocation decisions more holistically. The platform has already demonstrated significant performance improvements, with calculations for large multiasset research graphs now taking just 30 minutes compared to the previous 12-hour processing time.
Crucially, Fitzgerald’s team is collaborating closely with Man’s machine learning division to embed generative AI capabilities featuring a ChatGPT-style interface directly into the platform. This integration represents a forward-thinking approach to quantitative finance, positioning Man Group to leverage the latest AI advancements in systematic trading.
The project, which began approximately 18 months ago, is expected to require another two to three years for full integration. The platform will primarily serve quantitative researchers—the mathematical experts who apply machine learning and statistical modeling to complex datasets for systematic investment decisions. However, software engineers, risk management teams, and support staff will also utilize Condor’s capabilities.
Fitzgerald emphasizes that Condor is being architected with flexibility in mind, designed to quickly adapt to emerging asset classes and leverage advanced computing technologies like graphics processing units (GPUs). The platform will also enable new analytics capabilities, including ESG assessments to evaluate portfolio sustainability.
Key Quotes
The worst thing you could do with this is build something that fulfills our need for exactly today. We don’t know how we will trade in two years’ time, but I would hope this platform runs for 10 years or longer.
Barry Fitzgerald, cohead of front-office engineering at Man Group, explains the forward-thinking philosophy behind Condor’s design. This quote underscores the strategic importance of building AI infrastructure that can adapt to unknown future requirements rather than solving only current problems.
There’s the training of how do researchers get the best out of the new platform, what can the new platform offer them that the old one didn’t? Can it be faster? Can it allow them to construct portfolios in different ways? All of that brings a little bit of a different way of working too.
Fitzgerald highlights the human element of AI platform adoption, acknowledging that technological capability alone isn’t sufficient. This reflects a mature understanding that successful AI implementation requires organizational change management and user training to unlock the platform’s full potential.
Our Take
Man Group’s Condor project exemplifies the institutional finance sector’s recognition that AI and machine learning are no longer experimental technologies but foundational infrastructure. The integration of generative AI with ChatGPT-style interfaces is particularly noteworthy—it suggests that even highly technical quantitative researchers benefit from more intuitive AI interaction models.
The 30-minute versus 12-hour calculation improvement demonstrates AI’s tangible impact on research velocity, potentially enabling Man Group to test hypotheses and respond to market conditions far more rapidly than competitors using legacy systems. This speed advantage could translate directly into alpha generation.
What’s most significant is Fitzgerald’s emphasis on flexibility and future-proofing. By designing for GPU computing and unknown future asset classes, Man Group is betting that AI capabilities will continue advancing rapidly. This architectural philosophy—building for adaptability rather than current requirements—may become the defining characteristic of successful AI infrastructure projects across industries.
Why This Matters
This development signals a significant shift in how institutional finance is embracing artificial intelligence and machine learning as core infrastructure rather than peripheral tools. Man Group’s substantial investment—involving nearly all Man AHL personnel plus central teams—demonstrates that leading hedge funds view AI integration as mission-critical for competitive advantage.
The generative AI integration with ChatGPT-style interfaces represents a notable trend: making sophisticated AI capabilities accessible to quantitative researchers through intuitive interfaces. This democratization of AI tools within financial institutions could accelerate innovation in systematic trading strategies.
The platform’s emphasis on GPU computing and handling exponentially larger datasets reflects broader industry recognition that AI-driven quantitative finance requires fundamentally different technological infrastructure. As machine learning models grow more complex and data volumes explode, traditional computing architectures become inadequate.
For the financial services industry, this project illustrates how AI is reshaping not just trading strategies but the entire technological foundation of systematic investing. The multiyear timeline and massive resource commitment suggest that AI transformation in finance is a marathon, not a sprint, requiring comprehensive organizational change beyond simply deploying algorithms.
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Source: https://www.businessinsider.com/hedge-fund-man-group-rebuilds-key-platform-quants-2024-9