Greenwashing Analysis: A Data Science Approach to Evaluating ESG Integrity
Project Summary
The project helps businesses improve the credibility of their environmental, social, and governance (ESG) practices by identifying and reducing greenwashing, the gap between companies’ sustainability claims and their actions.
As ESG information becomes increasingly important to investors, regulators, and the public, corporate sustainability claims must be credible, evidence-based, and reflect genuine action.
Developed through collaboration between academic researchers and industry partners, the project builds tools to assess how a company’s ESG claims align with financial and media perceptions. We are building tools to assess how a company’s ESG claims align with financial and media perceptions.
Our interactive web platform will analyse ESG reports, real-time news sentiment using machine learning (ML) models, and market data to detect potential misalignment. It will offer dynamic risk scores, benchmarking tools, and a simulation feature to show how ESG strategies could impact company’s greenwashing risk and market trust.
By making these insights accessible to investors, regulators, and financial institutions, the project supports more informed decision-making and encourages transparent, accountable ESG reporting.
We aim to reduce ESG information asymmetry, strengthen trust in sustainability disclosures, and drive meaningful, measurable progress, particularly in the financial sector where transparency and accountability are critical to long-term success.
Meet The Team

Dr Fahimeh Jafari
University of East London
Senior Lecturer in Computer Science, Postgraduate Research Lead, Associate Director of UEL FinTech Centre

