sustain.AI: a Recommender System to analyze Sustainability Reports
This tool assists auditors, investors, and the public in efficiently analyzing sustainability reports, but it is incremental as it applies existing methods to a new domain.
The paper tackles the problem of analyzing sustainability reports by developing a recommender system that matches text passages to GRI standards, achieving significantly higher performance than baselines on two German datasets.
We present sustainAI, an intelligent, context-aware recommender system that assists auditors and financial investors as well as the general public to efficiently analyze companies' sustainability reports. The tool leverages an end-to-end trainable architecture that couples a BERT-based encoding module with a multi-label classification head to match relevant text passages from sustainability reports to their respective law regulations from the Global Reporting Initiative (GRI) standards. We evaluate our model on two novel German sustainability reporting data sets and consistently achieve a significantly higher recommendation performance compared to multiple strong baselines. Furthermore, sustainAI is publicly available for everyone at https://sustain.ki.nrw/.