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The Role of Artificial Intelligence and Alternative Data in Enhancing ESG Reporting

Summary

Artificial intelligence (AI) is playing an increasingly significant role in the field of environmental, social, and governance (ESG) reporting. However, the term is often misused to describe anything beyond the collection and processing of traditional ESG data. As reporting standards […]

The Role of Artificial Intelligence and Alternative Data in Enhancing ESG Reporting

Artificial intelligence (AI) is playing an increasingly significant role in the field of environmental, social, and governance (ESG) reporting. However, the term is often misused to describe anything beyond the collection and processing of traditional ESG data. As reporting standards become more detailed, companies and their financial partners are looking to leverage alternative data sources and AI technologies to improve reporting on non-financial performance.

The main advantage of AI in the financial sector is efficiency. Machine learning identifies patterns from large volumes of data to make predictions. Natural language processing (NLP) empowers computers to understand and respond to textual and spoken data. By combining these two technologies, it becomes possible to automate time-consuming processes in evaluating ESG performance.

On the other hand, alternative data, such as satellite imagery, have the ability to address the issue of missing data on climate change, thereby improving the assessment of climate change risks.

Financial institutions that are proficient in working with data are utilizing these new resources to enhance their assessment of company sustainability for investment and lending decisions.

The question remains whether they fully understand the new risks associated with the use of AI and alternative data. One of the biggest responsibilities of AI-based ESG reporting is not just how users employ this technology, but rather whether they comprehend its limitations.

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