NLP-DRIVEN ESG DISCLOSURE ANALYSIS IN BANKING ANNUAL REPORTS: STRENGTHENING REGULATORY AND SUPERVISORY TECHNOLOGIES

Resum

The objective of this project is to improve the state of Environmental, Social, and Governance (ESG) reporting by the application of machine learning and natural language processing, two forms of artificial intelligence (AI). Improvements to the summary and clarity of ESG reports, the use of RegTech solutions to expedite regulatory compliance, the use of SupTech solutions to facilitate the more effective and efficient delivery of regulatory requirements, and the promotion of transparency in business operations to support sustainable development are the biggest objectives.

To achieve these objectives, a methodology was followed to collect data from the relevant financial institutions (ADIB published on its website), that helps to include as many types of data as possible so that the study is comprehensive and does not exclude any type of data, followed by accurate pre-processing of this data, (with the help of artificial intelligence tools) to ensure the quality of the resulting summary content starting from the report index in the first attributes to the rest of the text.