The Intersection of ESG, Big Data, and Artificial Intelligence

Earlier this summer, NICSA hosted an outstanding panel on ESG in New York. Previously, in part 1 of this three-part series, we discussed how the panelists described learning about ESG as being akin to “Learning a New Language”, while in part 2, we learned about the ways in which institutional investors are thinking about ESG

In the third and final post in this series, we’ll look at another main topic of conversation among the panelists that evening: the role that big data and artificial intelligence (AI) are playing in the ESG investing process and the role they may play in the future. 

To begin with, the panel pointed to the fact that the rise in required disclosures has meant there is now more data available than ever to investors as they consider the landscape. But raw data alone is not useful. One must have the right tools for parsing and best understanding of just what all of this data means, and that’s where new technologies are already starting to have a significant impact when it comes to ESG-focused investing. 

“Technology and disclosures are making ESG data sources much easier to find,” said Mark Hays, Vice President – Sustainable Investing, J.P. Morgan Asset Management. “And artificial intelligence can scrape all that data better than humans ever could on their own.”

Mark McDivitt, Managing Director, Global Head of ESG with State Street agreed and pointed back to his earlier comments about how approximately 80% of current balance sheets are non-traditional intangible assets. “As disclosure and reporting has evolved, doing a deeper dive is essential, and that is where emerging technology can play a major role,” he added.

The panel also discussed the ways in which AI can allow investors to look beyond traditional data and information sources. Numerous AI approaches can mine data from sources as disparate as cargo ship emissions, power consumption, and consumer sentiment towards a company’s governance via the scraping and analysis of news headlines and social media discussions. 

“It’s important to consider nontraditional or other untrafficked data sources,” added Hays. “AI allows investors to open entirely new doors to better understanding their investments and potential investments. 

Investment research in general is going through a technology-driven sea change, and that may be all the more true in the ESG arena, as AI-driven approaches allow investors to understand not just what has been said or written about a particular company, but why, how, when, where and with far greater depth of understanding and corresponding data than has ever been available before. How all of this will continue to impact the ESG space in years to come remains to be seen, but the panel agreed that the pace of technological advancement will only accelerate.

This is part 3 of a 3-part series of posts from this latest NICSA ESG event. Previous posts include:

Part 1: Like learning a new language

Part 2: The Institutional View of ESG

Want to learn more? Don’t miss out on these events coming this fall from NICSA:

September 25, 2019: San Francisco – ESG Product Trends & Regulatory Practices

Note: Although the observations contained in this work represent the best thoughts of the individuals comprising the NICSA panel, they do not necessarily reflect the views of NICSA or any of its member organizations. Matters addressed in this work may touch upon legal or regulatory matters, however nothing herein is intended to be or should be construed as legal advice. You should contact your own counsel in order to obtain legal advice regarding these or any other matters.

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