Sustainalyze: AI Powered Transperancy in ESG Reporting

This work presents ESG Analytics, an AI-powered platform for automated analysis of Environmental, Social, and Governance (ESG) reports. ESG reports are often large, complex, and unstructured, making manual analysis inefficient and time-consuming. The proposed system uses a Retrieval-Augmented Generation (RAG) approach to extract ESG metrics from both textual and tabular data. It integrates FinBERT-ESG for classification, ChromaDB for semantic retrieval, and Large Language Models (LLMs) for accurate and context-aware extraction. The platform generates dual ESG scores, including Risk Score and Impact Score, and incorporates a multi-signal greenwashing detection mechanism to identify misleading sustainability claims. This system improves accuracy, transparency, and scalability in ESG analysis and provides evidence-based insights for better decision-making.