ESG (Environmental, Social, and Governance) rating has become an increasingly important tool for investors and companies alike in assessing the sustainability and ethical practices of businesses. 

Messy landscape of different ESG ratings and rankings (Source: Corporate Citizenship)

As we look towards the future, I would like to share several trends and predictions that I think will shape the future of ESG rating, particularly in the world of AI.

Trends

AI can help investors analyze vast amounts of data quickly and efficiently, enabling them to identify companies that are making significant progress in ESG practices and those that are not. The use of AI in ESG rating can also help companies to track their ESG performance in real-time and make improvements where necessary.

Another trend is the growing importance of social factors. As investors and companies continue to prioritize ESG issues, social factors such as diversity, equity, and inclusion (DEI) are becoming increasingly important considerations. AI can play a significant role in assessing a company's DEI performance, enabling investors to make more informed decisions about their investments.

Also, AI-powered ESG rating platforms will continue to grow in popularity and sophistication. These platforms will enable investors to analyze ESG data from a variety of sources, including company disclosures, industry reports or even including unstructured data such as news articles and social media posts, to provide more accurate, comprehensive and reliable ESG ratings. AI can also help identify patterns and trends in ESG data that may be difficult for humans to discern.

Examples of AI-based ESG rating providers:

- RepRisk - from their methodology page, RepRisk scanned over 100,000 public sources and stakeholders in 23 languages on a daily basis. As of 2022, the RepRisk Dataset includes more than 225,000 companies that are risk-associated: ~4% are listed companies and ~93% are non-listed companies.

- Truvalue Labs – from their methodology paper, Truevalue process information from more than 100,000 sources. They provide four scores to support a full range of investment strategies: Insight, Pulse, Momentum, and Volume scores are the foundation of all Truvalue products.

- ESG Book - Incubated by Arabesque in 2018, ESG Book combines cutting-edge technology and proprietary research. Their ESG Data Solutions enable company and portfolio level analysis with ESG data for more than 25,000 companies.

Examples on how AI can help investors and companies in analyzing ESG performance:

- Dig out ESG risks which were difficult to detect: AI is expected to help investors and companies identify ESG risks and opportunities that were previously difficult to detect. For example, AI-powered analysis of satellite imagery can help identify deforestation and other environmental risks/opportunities, while analysis of social media sentiment can help identify potential human rights issues.

- Improve stakeholder engagement: AI can help investors identify companies that are lagging in their ESG performance, and engage with those companies to encourage improvements.

- Cost savings: AI helps reduce the cost and time required to conduct ESG assessments. This can make ESG rating more accessible to a wider range of investors and companies, and help drive greater adoption of ESG principles throughout the investment industry.

Challenges

Same as traditional ESG ratings, AI-powered ESG ratings also contain the risk of "black box" algorithms that are difficult to understand and interpret. 

Also, it is important that the algorithms can be trained to analyze false or fake news. There are already several ways in the AI world to analyze false or fake news or social media articles:

- Sentiment analysis: identify whether the content is biased or misleading, or whether it is intended to generate emotional responses.

- Fact-checking: comparing the claims made in the content with verified sources of information

- Network analysis: analyze the network of sources of news articles and social media posts to identify patterns of misinformation and disinformation

- Image analysis: analyze images and videos used in news articles and social media posts to identify whether they have been manipulated or altered

In short, AI-powered ESG rating platforms should incorporate diverse perspectives and ensure that their algorithms are regularly audited for bias.

In my opinion, no matter how advanced AI is, I believe that analysts still play an important role even though they could be subjective and the results could be skewed towards individual interpretation. As experienced analysts can identify companies which are becoming more sophisticated in their efforts to "greenwash" their ESG performance.

Conclusion

Overall, the use of AI in ESG rating is expected to have a significant impact on the investment industry in the years to come. By providing more accurate, reliable, and accessible ESG ratings, AI can help drive greater adoption of ESG principles and encourage companies to improve their ESG performance. However, it is equally important to address concerns around transparency, bias, and accuracy to ensure that AI-powered ESG rating platforms are trusted by investors and companies alike.

If you are interested to know more about different ESG ratings providers and how investors are using them, you can refer to the annual research “Rate the Raters” conducted by ERM: https://www.sustainability.com/globalassets/sustainability.com/thinking/pdfs/2023/rate-the-raters-report-april-2023.pdf