May 3, 2023 at 2 pm ET
With over 30,000 global publicly traded companies to cover, overburdened staff, manual processes, and lack of benchmarking tools, how do organizations effectively monitor or target fund portfolio companies for shareholder engagement?
Our discussion will revolve around how to use quantitatively structured ESG consensus scores to accomplish this important function. Valid, consistent, and comprehensive ESG engagement ratings data is critical for a proper oversight process. The application of artificial intelligence and machine learning to the consumption of ESG adherence data has provided a solution to this problem: ESG consensus ratings.
By using ESG consensus ratings, asset owners can identify those companies within a fund’s portfolio or (target lists) whose key performance indicators are aligning with an organization’s ESG goals.
Participants will learn:
- To use quantitative research to evaluate public equity portfolio alignment with fund values and ESG policies;
- To develop data driven shareholder engagement strategies and dialogues with portfolio companies;
- To track ESG performance trends and benchmarking corporate dialogues with new reporting tools and analytics;
- To obtain breakouts of each ESG metric to better understand weaknesses and strengths;
- To efficiently scale shareholder advocacy campaigns;
- To apply what they've gathered to real world use cases
Recording
ESG Returns article referenced by Brian
Speakers
Eric Darrisaw, Senior Consultant, Hackett Group
Brian J. Greene, Senior Vice President, Zeno AN Solutions
Dale M. Neibert, Managing Director, OWL ESG, Inc.