Andrew Y. Chin
28 Years at AB|31 Years of Experience
Andrew Chin is Chief Artificial Intelligence (AI) Officer and a member of the firm’s Operating Committee. In this role, he leads the firm’s strategy to leverage AI in transforming the organization and driving better outcomes for clients and the firm. Previously, Chin was the Head of Investment Solutions and Sciences, overseeing the research, management and strategic growth of the firm’s asset-allocation, data science, index and tax-management businesses. From 2022 to 2023, he was the head of Quantitative Research and chief data scientist, developing and optimizing quantitative research and data science infrastructure, capabilities and resources across the organization. As the firm’s chief risk officer from 2009 to 2021, Chin led all aspects of risk management and built a global team to identify, manage and mitigate the various risks across the organization. He has held various leadership roles in quantitative research, risk management and portfolio management in New York and London since joining the firm in 1997. Before joining AB, Chin spent three years as a project manager and business analyst in global investment management at Bankers Trust. He holds a BA in math and computer science, and an MBA in finance from Cornell University. Location: New York
Published Work
A richer dialogue between human experts and large language models may improve outcomes.
If investors are detectives seeking clues for outperformance in the US large-cap equity market, natural language processing is a team of tireless assistants.
The data science wave is here, and bond managers must adapt traditional investment processes to harness new technologies and amplify human talent.
AI can transform our industry—from investing to operations. We explore some of the questions asset owners and managers should be considering.
AI development is racing ahead. A thoughtful framework to making decisions and leveraging tools can help investors stay on course.
In research contributed to the Journal Investment Management, AB's data science experts test the efficacy of text mining techniques and find that there are opportunities to use these signals in stock selection.
A confluence of events is affecting the asset management industry, forcing industry participants to rethink their competitive positioning and evolve to survive in the new world order
Many equity investors are enamored by the idea of timing factors to enhance returns, but our research suggests that it's not the best way to enhance active equity performance. And skill in factor timing may not be a good gauge of future success.
Data science, artificial intelligence (AI) and machine learning are hot topics in investment management, as firms look for new ways to model investing problems and generate differentiated insights. But data science is also relatively new to the industry-and that means growing pains. What does it take to get it right?
Today, investors are taking a closer look at ways to squeeze more return from their equities. Active management offers that potential, but which managers possess true skill? Prime-alpha analysis can help shed some light on the answer.
AB's Chief Risk Officer and Head of Quantitative Research shares his perspectives on the research behind the development of prime alpha.