Why artificial intelligence can save the day for ESG investors?

Advances in artificial intelligence (AI) technology have the potential to help investors collect, analyze and aggregate ESG data successfully, when accounting for environmental, social, and governance risks and opportunities.

As investors are increasingly taking into consideration non-financial factors as part of their analysis process to identify material risks and growth opportunities, i.e. Environmental, Social and Governance factors, it seems that artificial intelligence (AI) technology can provide solutions to make their work easier and less time consuming.

Now tons of information are accessible and easier to analyze through computer, a task difficult for human employees to carry out at a reasonable speed.

Investors continue to struggle with questions about ESG data collection and interpretation. The absence of standardized ESG datasets and reporting methodologies makes it difficult for issuers to disclose meaningful information on sustainability. ESG research companies and data providers use their own, often inconsistent methodologies to generate ESG scores. However, better data tools could resolve this issue. The good news is that artificial intelligence (AI) promises to integrate ESG data into more stable, comprehensive databases. Many rating agencies are now integrating alternative datasets and using methods such as machine learning to provide more flexible and up-to-date information.

Speed and precision

The Dow Jones Sustainability Index will be incorporating artificial intelligence technology to speed up analyses and augment traditional research.

AI can become the key factor in helping investors and risk managers analyze ESG data that can be collected in both structured and unstructured formats. Not only can AI help extract relevant information from existing data sources, but it also offers exciting opportunities to create new ones. The power of artificial intelligence can provide asset managers improved speed and precision of data gathering, analysis, and validation.

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