Over the past few years environmental, social and governance indicators have become extremely important for broader investment strategies. This sustainability data is collected from a wide variety of sources and helps fund managers to better valuate growth and risk. Indicators are comprehensive and include factors such as corporate policies, regulatory compliance, environmental impact and more. A better ESG score induces better performance.
In recent months, with the advent of a global pandemic, which has had a devastating economic impact, it has become even more critical for fund managers to invest in “future-proof” assets that at the same time impact health and global stability in a positive way.
ESG metrics used to be collected by fund managers who determined which data mattered for their investment strategy. This, of course, created many different datasets using different definitions. More recently, as companies have begun to see the value of this approach, they have started generating their own ESG data, publishing it in their annual reports and naturally creating even more data.
This allowed outside vendors to enter and aggregate all of this data, defining key metrics and publishing additional ESG scores for target companies. The vast amount of ESG data has grown enormously in recent years from a variety of sources, from machine learning data to geospatial mapping.
Relying on richer ESG data will help fund managers invest more consciously in more sustainable assets. But to continue to do so, they will need more objective and observable processes to assess the reliability of this data.