Machine Learning to Make ESG Reporting Work for Green Finance
DescriptionThe listed companies on the Hong Kong Stock Exchange (HKEX) have been required to publish their ESG (environmental, social and governance). However, the format and content of published ESG reports vary significantly and lack of verification by auditors. Nevertheless, sustainable investment strategies are usually built upon the corporate self-reported ESG information. When the world has embraced green finance for materializing sustainable development, ESG reporting, which sets the precondition for green finance to work, has attracted unprecedented attention from regulators. To make ESG information useful for green finance, this project aims to address the following three challenges with machine learning models. First, the format and/or language of the self-reported ESG data are not standardized. Second, there is a lack of assurance on credibility of the self-reported ESG data. Third, the metrics for evaluating ESG performance are not standardized. We hope to develop algorithms and tools to handle the challenges.
|Effective start/end date||1/05/22 → …|