Analysis of Material Facts on Financial Assets: A Generative AI Approach
Gabriel Assis, Daniela Vianna, Gisele L. Pappa, Alexandre Plastino, Wagner Meira Jr, Altigran Soares da Silva, Aline Paes
Abstract
Material facts (MF) are crucial and obligatory disclosures that can significantly influence asset values. Following their release, financial analysts embark on the meticulous and highly specialized task of crafting analyses to shed light on their impact on company assets, a challenge elevated by the daily amount of MFs released. Generative AI, with its demonstrated power of crafting coherent text, emerges as a promising solution to this task. However, while these analyses must incorporate the MF, they must also transcend it, enhancing it with vital background information, valuable and grounded recommendations, prospects, potential risks, and their underlying reasoning. In this paper, we approach this task as an instance of controllable text generation, aiming to ensure adherence to the MF and other pivotal attributes as control elements. We first explore language models’ capacity to manage this task by embedding those elements into prompts and engaging popular chatbots. A bilingual proof of concept underscores both the potential and the challenges of applying generative AI techniques to this task.- Anthology ID:
- 2024.finnlp-1.11
- Volume:
- Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing
- Month:
- May
- Year:
- 2024
- Address:
- Torino, Italia
- Editors:
- Chung-Chi Chen, Xiaomo Liu, Udo Hahn, Armineh Nourbakhsh, Zhiqiang Ma, Charese Smiley, Veronique Hoste, Sanjiv Ranjan Das, Manling Li, Mohammad Ghassemi, Hen-Hsen Huang, Hiroya Takamura, Hsin-Hsi Chen
- Venue:
- FinNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 103–118
- Language:
- URL:
- https://aclanthology.org/2024.finnlp-1.11
- DOI:
- Cite (ACL):
- Gabriel Assis, Daniela Vianna, Gisele L. Pappa, Alexandre Plastino, Wagner Meira Jr, Altigran Soares da Silva, and Aline Paes. 2024. Analysis of Material Facts on Financial Assets: A Generative AI Approach. In Proceedings of the Joint Workshop of the 7th Financial Technology and Natural Language Processing, the 5th Knowledge Discovery from Unstructured Data in Financial Services, and the 4th Workshop on Economics and Natural Language Processing, pages 103–118, Torino, Italia. Association for Computational Linguistics.
- Cite (Informal):
- Analysis of Material Facts on Financial Assets: A Generative AI Approach (Assis et al., FinNLP 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.finnlp-1.11.pdf