- Artificial Intelligence (AI) helps to circumvent some challenges with traditional ESG data.
- Textual and satellite data analysis can discover key ESG risks and opportunities.
- AI contributes to ESG integration by providing an alternative source of data for monitoring ESG reporting.
ESG data provided by rating agencies is essential, but there are concerns surrounding the quality of this data.
- There is a high degree of subjectivity in the choices made by the rating agencies on ESG criteria. They rely heavily on information provided by the companies being rated.
- Companies’ ESG ratings are reviewed infrequently while the direction of revisions tends to be strongly correlated with financial performance.
- Large discrepancies among the agencies’ ratings can occur, partly due to the different methodologies used to deal with missing data. These can be large, but, interestingly, research has established that greater ESG disclosure actually leads to greater ESG rating disagreement.
You can now read the full whitepaper at the link below
