Leveraging AI for ESG disclosures: a deep dive into UAE’s Islamic and conventional banking sectors

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a novel AI-based framework for comparing ESG disclosure quality across bank types, with implications for greenwashing detection and standardization research.

🏢実務担当者:Banks can adopt the AI methodology to self-assess ESG reporting quality and identify areas for improvement, particularly in consistency and addressing negative aspects.

🏛政策担当者:Regulators can leverage AI tools to monitor ESG disclosures, enforce standards, and combat greenwashing, as demonstrated in the UAE dual-banking context.

The connection between financial sector development and sustainable activities leads financial institutions to focus on improving their sustainability by using Environmental, Social and Governance (ESG) principles. Whereas the inconsistencies and exaggerations created concerns about transparency and greenwashing risk. This study aims to assess the quality of ESG reporting among Islamic Banks (IBs) and Conventional Banks (CBs) in the United Arab Emirates (UAE) during the period 2021–2024. The study uses artificial intelligence (AI), machine learning (ML) and natural language processing (NLP) techniques such as topic modeling, and sentiment analysis to evaluate the degree of disclosure, examine theme shifts over time and identify potential instances of greenwashing. The overall result of the study indicates that CBs perform better than IBs in terms of the quality of their ESG reporting, especially when it comes to the variability in the disclosure of climate change risks, regulatory compliance, and green investment activities. On the other hand, IBs are more consistent, with lower scores in the quality of their ESG reporting, and place a greater emphasis on social responsibility, ethical finance and Shari’ah law compliance. Based on the sentiment analysis results, it seems that IBs are more committed to sustainability over the long run, as they have a slightly more emotional and opinion-based tone in their ESG disclosures. The findings further indicate an emphasis on positive ESG disclosures, with limited attention to underlying challenges, which may influence perceptions of greenwashing. The study offers valuable insights for regulators, educators and industry, underscoring the need for unified ESG standards to enhance disclosure consistency and comparability among banks. It also shows how AI can strengthen monitoring, reduce ESG-related fraud and support proactive regulation against greenwashing. The original contribution of this pioneering study lies in its development of an AI-based framework that applies NLP and sentiment analysis to compare ESG disclosures of IBs and CBs, introducing the Islamic ESG lens – a Shari’ah-compliant approach to ethical reporting.

• semanticscholar https://doi.org/10.1108/jfra-05-2025-0390first seen 2026-05-15 18:19:08