Corporate Sustainability Analysis via Retrieval-Augmented Generation

Abstract

We investigate the application of Retrieval-Augmented Generation (RAG) for enhancing the analysis of corporate sustainability disclosures. We introduce CorSus, a novel dataset for evaluating RAG models in answering corporate sustainability-focused claims, using data from the Transition Pathway Initiative for over 100 companies. Further, we develop a subset of this dataset with reference documentation and fully explained answers. Finally, in a systematic framework, we optimise and benchmark state-of-the-art RAG approaches using the CorSus dataset. With this work, we aim to empower stakeholders with a tool for informed evaluations of corporate sustainability practices, thereby encouraging a greater commitment to environmental responsibility.