sustain.AI: a Recommender System to analyze Sustainability Reports

• URL: http://arxiv.org/abs/2305.08711v3
• Date: Fri, 26 May 2023 07:49:33 GMT
• Title: sustain.AI: a Recommender System to analyze Sustainability Reports
• Authors: Lars Hillebrand, Maren Pielka, David Leonhard, Tobias Deu{\ss}er, Tim Dilmaghani, Bernd Kliem, R\"udiger Loitz, Milad Morad, Christian Temath, Thiago Bell, Robin Stenzel, Rafet Sifa
• Abstract summary: sustainAI is an intelligent, context-aware recommender system that assists auditors and financial investors. We evaluate our model on two novel German sustainability reporting data sets and consistently achieve a significantly higher recommendation performance.
• Score: 0.2479153065703935
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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/.

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