AI on the Buy Side: Risks, Challenges and Opportunities

Nirav Shah, a founding partner at Versor Investments, speaks with GARP editorial director Robert Sales about the pros and cons of artificial intelligence and machine learning for buy-side institutions.

Though significant concerns remain about the bias, fairness an explainability of AI and ML, these innovative technologies have made great inroads in financial services. Banks, for example, now use AI and ML for everything from anti-money laundering to fraud detection to risk modeling and analysis, while asset management firms employ these tools for portfolio optimization and risk mitigation.

Nirav Shah discusses the role ML plays in risk reduction and alpha generation at buy-side institutions, and offers his thoughts on, among other topics, data governance and data management challenges, the growth of generative AI, the importance of regulation, and potential future applications of this technology.

Speaker's Bio

Nirav Shah is a founding partner at Versor Investments, where he has built innovative, scalable systems for using alternative data and AI/ML techniques. These tools are used in the firm's investment strategies, particularly within the futures and equities markets. He has also worked on various parts of the investment process at Versor, ranging from research to portfolio construction and trading.

He has nearly two decades of experience in quantitative and systematic investment management. Prior to Versor Investments, he founded a consulting firm focused on quantitative research. Earlier, he served as Vice President at Investcorp in New York, where he focused on asset allocation and quantitative research. His career also includes a role as a Quantitative Researcher at Phoenix Global Capital Management, a CTA based in Chicago.