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02 Sep 2022
4 minute read

What’s driving investment and wealth managers’ ESG strategies?

Data connects E, S and G

Margaret Doyle

 

To the point

 

Takeaways to consider:
  • Set clear processes and controls across the ESG data lifecycle, from collecting and ingesting, to managing and modeling, mapping to the appropriate frameworks, and publishing to end-users or your clients.
  • Collect and confirm ESG data from material public companies before use; address data gaps in private markets by engaging directly with investee companies or using smarter technologies (e.g., artificial intelligence).
  • Seek diverse, alternative data sources to improve the baseline understanding of the risks faced by both individual assets and the whole portfolio.
  • Establish a cohesive data-gathering plan, collate separate requirements, and identify overlaps to minimize and streamline information requests.
  • Nominate clear data owners and assign data stewardship to provide ongoing oversight.
  • Establish ESG data frameworks to provide standardized results across diverse asset classes at both the asset and portfolio levels.
  • Create clear connection points and leverage synergies between data and corporate strategies. 

 

Data is central to investment and wealth managers’ (“managers”) environmental, social and governance (ESG) strategy. However, collecting and managing the right data can be a “wicked problem”: broad, complex, and with constantly evolving business and regulatory requirements. The effort to address one challenge may uncover or even create another.

But what does this mean for you? The implications vary across the three ESG pillars.

Environmental challenges are market wide, affecting assets both publicly and privately owned. They have created a systemic need for data.

By contrast, the consideration of an investment’s social impact, the need for managers to address it and the data required remain immature at the business and regulatory levels.

Finally, governance is overseen at the corporate level. Managers are now shifting their focus to linking corporate and enterprise data governance, and how this can help establish a more streamlined and robust framework for managers to execute their investment strategies.

This article addresses the E, S and G data challenges by exploring the data lifecycle journey and outlines a series of