AI for Managing ESG Risks and Analyzing Integrated Reports in Sustainable Finance
Salhi, Ayoub
AI for Managing ESG Risks and Analyzing Integrated Reports in Sustainable Finance - 2025.
13
The transition toward sustainable finance brings new challenges, especially when integrating Environmental, Social, and Governance (ESG) criteria. In this context, Artificial Intelligence (AI) is proving to be a highly promising tool to anticipate and manage these risks. By combining data from multiple sources and identifying subtle signals, AI opens new possibilities for financial decision-making. Companies such as JPMorgan Chase, Goldman Sachs, BNP Paribas, and several other major CAC 40 firms are already using AI in this way. Beyond risk management, AI increasingly plays an important role in analyzing integrated reports, helping to reveal connections between financial performance and non-financial outcomes. This presentation seeks to demonstrate that artificial inteligence can be a powerful and effective lever for anticipating ESG risks, while also emphasizing that its use must be carefully framed, as the accuracy of results depends heavily on data context and the quality of model training
AI for Managing ESG Risks and Analyzing Integrated Reports in Sustainable Finance - 2025.
13
The transition toward sustainable finance brings new challenges, especially when integrating Environmental, Social, and Governance (ESG) criteria. In this context, Artificial Intelligence (AI) is proving to be a highly promising tool to anticipate and manage these risks. By combining data from multiple sources and identifying subtle signals, AI opens new possibilities for financial decision-making. Companies such as JPMorgan Chase, Goldman Sachs, BNP Paribas, and several other major CAC 40 firms are already using AI in this way. Beyond risk management, AI increasingly plays an important role in analyzing integrated reports, helping to reveal connections between financial performance and non-financial outcomes. This presentation seeks to demonstrate that artificial inteligence can be a powerful and effective lever for anticipating ESG risks, while also emphasizing that its use must be carefully framed, as the accuracy of results depends heavily on data context and the quality of model training
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