The key points about these data vendors is that they provide global data and are publicly available. Having more data sources like this would thus be advantageous to Contemporaries, as they help tackle the issue of geographic informational inequality and enforce the reliability of data due given the freedom of public scrutiny. However, there needs to be more of these types of data sources, and data vendors of this sort for the other two aspects of ESG, Social and Corporate Governance.
Additionally, corporate disclosures are also an important source of information that has not been given much attention by Contemporaries, although to avoid greenwashing or providing a false image of a company, mandates should be put in place to enforce responsible auditing on ESG issues and more transparency in company disclosure.
Perhaps a better approach for Contemporaries would be to look at the discrepancies between the corporate disclosures and the internet data they collect. Discrepancies could be used as a confidence weighting on ratings for each component of ESG to ultimately determine a company’s rating. Whatever approach is taken, it is clear more data and richer sources are therefore required to help tackle the issues of volatility and increasing equality in access to data.
What are the issues we should be worried about?
A major concern regarding Contemporaries is that they are run by profit-driven businesses. Their work is not publicly available or free to use, whereas Traditionalists like Sustainalytics have their ESG ratings available online. There is a lot of talk on how powerful their AI tools are, but not much of it can be publicly scrutinised unless you request for a demo, raising justifiable concerns about how reliable the technology actually is. Moreover, Contemporaries tend to be closely associated with international financial centres (IFCs)—TVL, for example, is owned by FactSet, an American financial services company in the second largest hedge fund state of Connecticut.
Since their methodology is not easily examined, due to limited disclosure, it is unclear as to the sort of parameters used or the assumptions made in developing its ESG rating model. Moreover, algorithms are not entirely subjective in their creation. They are subject to the scrutiny of their makers, and may have certain biases or other hints of subjectiveness built into the foundation of their AI system. Without a true value to compare ESG ratings with, we would not be entirely sure how well the algorithm really works.
With the uncertainty in the actual formulation of the Contemporary AI analyst, and the profit-driven nature of Contemporaries themselves, Hughes, Urban, and Wójcik (2021) note that Contemporaries may “complement rather than substitute” the Traditionalists in the near future (Hughes, Urban, and Wójcik, 2021). Although Contemporaries seem more democratic and provide more transparent ratings, Contemporaries also have areas of opaqueness that can affect the way ESG ratings are done. Perhaps if Contemporaries were not profit driven and rather more altruistic could AI truly replace traditional approaches to ESG.
Check out my first two posts on AIs and ESG benchmarking: ESG Benchmarking: Part #1 - ESG, AI, and the Investment Industry and ESG Benchmarking: Part #2 - AI, the New Hope of ESG
By MUHAMMED Hazim, Segi Enam intern, 30 Aug 2021 | LinkedIn
Edited by Nadirah SHARIF