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Written by: Alexandra Russo | New York Life Investments
Maybe you have heard some of the confusion with ESG ratings lately and some scores that don’t seem to make a whole lot of sense. For example, recently a prominent EV manufacturer received a lower Environmental, Social and Governance (ESG) score than a large international tobacco company, according to one of the leading ESG scoring providers.
It seems counter-intuitive, doesn’t it? On one hand, we have a tobacco company profiting from a product that is responsible for the deaths of millions of people a year. On the other hand, we have an innovative EV company, offering products key to the transition to a lower carbon economy. Yet the ratings show that the tobacco name is a superior “ESG” company.
How is this possible? When you shine light on the measurement framework and different scoring methodologies, it can make a lot more sense. Different rating providers seek to measure different risks and opportunities in their ESG scores. Just as many different types of investment funds are labeled as “ESG”, i.e. thematic, exclusionary, inclusionary, integration, best in class… and the list goes on… many different types of scores are called “ESG scores.” Fund managers of these investment strategies are using the ESG input (or data) to achieve a different outcome. Similarly, rating providers have their own frameworks seeking to measure different ESG-related risks and opportunities at the company level. Just as none of these investment approaches are wrong, none of these ratings frameworks are wrong. They are just different. The confusion comes from the lack of industry accepted definitions, not enough transparency, and the catch-all nature of the three letters. It also emphasizes the definitional challenge and the need to move away from classifying something as an “ESG company.” ESG is simply data, it’s the framework in which it is used that matters and that brings about different outcomes, be it a company rating or an investment strategy.
Now let’s shed some light on what could be driving the counterintuitive ESG scores of the EV manufacturer and the tobacco company. In this case, the score is driven by an industry relative framework and the two companies are not being held to the same bar. The framework appears to provide a score which represents how well a company manages its operational ESG risks relative only to its industry peers. So compared to other tobacco names, this tobacco company may do well. It is in complete isolation of how the EV manufacturer may be operating, as the EV manufacturer would be compared to other companies within its industry peer group, namely other automobile manufacturers (makers of both traditional combustion vehicles and EVs).
Additionally, many frameworks are only measuring operational ESG risks, meaning that what the company delivers as a product or service is not considered. So in this case, the fact the tobacco company produces a product which leads to many deaths is not factored in, just as the fact that an EV company is producing a product which helps to mitigate climate change. This focus on operational risks also impacts how scores look within industry peer groups, for example in the case of the EV company, the fact that it produces EVs when some of its peers focus on combustion vehicles would not be seen as a positive or a negative in the scoring approach. This doesn’t make the ESG approach incorrect, it just means we are using the data to understand different risk and opportunity profiles.
Other “ESG” frameworks do look at absolute risks, and account for the impact of a company’s products and services on the environment and society. This is the approach we have chosen in our proprietary ESG scoring framework. So, in this case, the EV provider would receive points for its contribution to climate change.
So the devil is in the details – remember ESG is simply data, which is meaningless without an evaluation framework. And when it comes to ESG ratings, labels and investment approaches, we must shine light on the evaluation frameworks and objectives to capitalize on the benefits that data can provide. The opaqueness stems from the lack of transparency, understanding, and the labeling of many different approaches with the same three letter acronym.