Investor and Stakeholder Tools for Tracking Companies’ Climate Commitments, Greenwashing and ESG Trends

Despite the rapid growth and bright prospects of sustainable finance, investors face a crucial data deficit for selecting ESG-compliant stocks for their portfolios. Existing ESG data relies on companies’ self-disclosure, which is biased and difficult to verify. Reporting companies often highlight positive but limited ESG actions and hide truly harmful activities. Such corporate behaviour is known as 'greenwashing.'

'Investor and Stakeholder Tools for Tracking Companies’ Climate Commitments, Greenwashing and ESG Trends' is an Innosuisse Innovation project (100.562 IP-SBM),  that aims to create a set of science-based methods to systematically detect potential greenwashing in corporate communication, as well as signals for green innovation and technologies.

RAM AI, the Zurich University of Applied Sciences (ZHAW) and the University of Zurich (UZH) are combining their expertise, and by capitalising on UZH's ClimateBert models, intend to apply pre-trained natural language processing methods (NLP) to company reports and news feeds in order to assess the truthfulness of companies’ commitments to climate change and environmental damage. Additionally, the consortium intends to build science-based NLP tools to systematically identify companies producing green innovation and investing in sustainable technologies.