Company-released ESG data does not always reveal the complete picture. Investors can more properly gauge risks if they incorporate available alternative data in their analysis.
Here is an excerpt from an article published in Risk.net:
In January 2019, the collapse of the tailings dam at mining giant Vale’s Córrego do Feijão mine in Brazil killed 270 people. In the aftermath of the deaths, the chief executive officer resigned and the company reported the worst quarter in its financial history, recognising almost $5 billion in charges from related liabilities and risks and costs that may continue to escalate. Prior to the incident, Vale – like most mining companies in the world – provided only limited data on the tailings facilities it managed, and had stated in its most recent sustainability report that, at the end of 2017, 100% of its audited tailings structures “were certified to be in stable condition, physically and hydraulically.” This disclosure gave investors little indication that Vale faced such major risks, even though Vale had suffered a devastating and costly tailings incident in November 2015.
Company-provided data, taken at face value, may not reveal the greatest risks that companies face – and may even mask them, diminishing the value investors receive from integrating ESG considerations into their portfolios. How can investors identify both company- and issue-specific risks across the globe when company disclosure is insufficient? One answer is to integrate alternative data sources that help fill the informational gaps and use advanced analytical techniques to develop stronger indicators of risk.
In Vale’s instance, we employed geospatial analysis and satellite-derived imagery to identify repercussions and potential hotspots. Immediately, we could see not only that Córrego do Feijão and Samarco (the sites of the past two tailings dam collapses) were very close together, but that one-third of Vale’s 2017 production value was located within a 100-mile radius, and thus likely shared similar characteristics and risk factors.
Using unconventional methods and alternative data sources to understand ESG risks is not limited to tailings dams. We use alternative data sources such as regulatory emissions data to inform us of where company assets are located or how pollutant-intensive their business lines are. We can also use regional statistics such as safety rates or wildfire frequency to help us measure companies’ exposure to these risks. In fact, we estimate that only about 35% of the data inputs in our MSCI ESG Ratings model are derived from voluntary ESG disclosures.