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SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation

Author

Listed:
  • Qilong Wu
  • Xiaoneng Xiang
  • Hejia Huang
  • Xuan Wang
  • Yeo Wei Jie
  • Ranjan Satapathy
  • Ricardo Shirota Filho
  • Bharadwaj Veeravalli

Abstract

The rapid growth of the financial sector and the rising focus on Environmental, Social, and Governance (ESG) considerations highlight the need for advanced NLP tools. However, open-source LLMs proficient in both finance and ESG domains remain scarce. To address this gap, we introduce SusGen-30K, a category-balanced dataset comprising seven financial NLP tasks and ESG report generation, and propose TCFD-Bench, a benchmark for evaluating sustainability report generation. Leveraging this dataset, we developed SusGen-GPT, a suite of models achieving state-of-the-art performance across six adapted and two off-the-shelf tasks, trailing GPT-4 by only 2% despite using 7-8B parameters compared to GPT-4's 1,700B. Based on this, we propose the SusGen system, integrated with Retrieval-Augmented Generation (RAG), to assist in sustainability report generation. This work demonstrates the efficiency of our approach, advancing research in finance and ESG.

Suggested Citation

  • Qilong Wu & Xiaoneng Xiang & Hejia Huang & Xuan Wang & Yeo Wei Jie & Ranjan Satapathy & Ricardo Shirota Filho & Bharadwaj Veeravalli, 2024. "SusGen-GPT: A Data-Centric LLM for Financial NLP and Sustainability Report Generation," Papers 2412.10906, arXiv.org.
    • Handle: RePEc:arx:papers:2412.10906
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    References listed on IDEAS

    as
    1. Neng Wang & Hongyang Yang & Christina Dan Wang, 2023. "FinGPT: Instruction Tuning Benchmark for Open-Source Large Language Models in Financial Datasets," Papers 2310.04793, arXiv.org, revised Nov 2023.
    2. Zhihan Zhou & Liqian Ma & Han Liu, 2021. "Trade the Event: Corporate Events Detection for News-Based Event-Driven Trading," Papers 2105.12825, arXiv.org, revised May 2021.
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