ESG Research in the Information Age
AI, Unstructured Data and the Future of ESG Investing
As environmental, social and governance (ESG) investing has evolved rapidly in recent years, so too has the way asset managers analyze and assign value to ESG factors.
Traditional ESG ratings are increasingly viewed as inadequate, since company-reported data is subject to greenwashing, annual ratings are not timely enough for investment decision-making, and there is a scarcity of positive ESG data.
This paper explores:
- The three ages of ESG research
- Challenges of ESG analysis and a new model to solve them
- How to find and extract meaningful signals from vast volumes of constantly proliferating unstructured data floating around our digital environment
About the author
Thomas Kuh, PhD is an industry expert with decades of deep expertise in ESG indices and ESG research. As Head of Index at Truvalue Labs, he creates benchmarks for implementing ESG investment strategies and licensing indices for ETFs, mutual funds and institutional accounts.
Prior to Truvalue Labs, Thomas was Executive Director, Global Head of ESG Indexes for seven years at MSCI, where he spearheaded the development of an innovative suite of equity and fixed income ESG indices.
His professional experience also includes 16 years at KLD Research & Analytics, and service on the boards of SIRI Company (now Sustainalytics) and the US SIF. He was also a Teaching Fellow at Harvard University and a Professor of economics at Simmons College.