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Active & Passive Tech and Innovation Fixed Income White Paper

Unlocking Insights and Opportunities with NLP in Asset Management

May 24, 2023
2 min read

What You Need to Know 

In research contributed to the CFA Institute Research Foundation’s Handbook of Artificial Intelligence and Big Data Applications in Investments, AB’s data science experts look at the potential for big data and data science in asset management. The white paper covers wide-ranging topics—from a decision-making framework to natural language processing applications and the business and cultural aspects of harnessing data science. 

Download PDF

Introduction 

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. Geopolitical, regulatory, technological, and social trends are upending long-held norms, and the status quo is likely an untenable option for many firms. These forces are creating a host of challenges for existing players and presenting new opportunities for emerging firms. We discuss some of the key challenges affecting the active management industry in this new environment. While our list is not meant to be exhaustive, we focus on the main trends that will drive the adoption of text mining techniques in the coming years. We also provide the motivation for firms to leverage natural language processing (NLP) to capitalize on these trends.

Past performance, historical and current analyses, and expectations do not guarantee future results.

The views expressed herein do not constitute research, investment advice or trade recommendations and do not necessarily represent the views of all AB portfolio-management teams. Views are subject to revision over time.

About the Authors

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

Che Guan is currently a Vice President and Principal Data Scientist of Data Science at AB. He is actively engaged in research and development on natural language processing. Before joining AB in 2021, Guan worked in multiple different positions, including principal data scientist at Raymond James, quantitative strategist at a start-up fund and data scientist at J.P. Morgan. Throughout his career, he has gained extensive experience in applying machine learning, optimization techniques and statistics to various projects in the financial industry. Guan holds an MS in data science from University of California, Berkeley, as well as an MS in statistics and a PhD in electrical engineering from the University of Connecticut, where he focused on forecasting applications. Location: Nashville

Additional Contributor

Yuyu Fan, Senior Data Scientist, AllianceBernstein

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