Leveraging Large Language Models for Few-Shot {KPI} Extraction from Financial Reports
We explore the use of Large Language Models ({LLMs}) for automating the extraction of Key Performance Indicators ({KPIs}) from diverse financial reports without any additional fine-tuning. We focus on evaluating various proprietary and open-source {LLMs} to address the joint named entity recognition and relation extraction tasks essential for accurately linking {KPIs} to their corresponding values and attributes. Our study highlights the technical challenges involved in the extraction process and presents a comprehensive evaluation of the models’ effectiveness. Our results reveal significant insights into handling these {LLMs} in such a crucial environment and showcase the transformative potential of {LLMs} in enhancing financial analysis and decision-making.
- Published in:
2024 {IEEE} International Conference on Big Data ({BigData}) - Type:
Inproceedings - Authors:
Deußer, Tobias; Zhao, Cong; Uedelhoven, Daniel; Sparrenberg, Lorenz; Hillebrand, Lars; Bauckhage, Christian; Sifa, Rafet - Year:
2024 - Source:
https://ieeexplore.ieee.org/abstract/document/10825458
Citation information
Deußer, Tobias; Zhao, Cong; Uedelhoven, Daniel; Sparrenberg, Lorenz; Hillebrand, Lars; Bauckhage, Christian; Sifa, Rafet: Leveraging Large Language Models for Few-Shot {KPI} Extraction from Financial Reports, 2024 {IEEE} International Conference on Big Data ({BigData}), 2024, 4864--4868, December, https://ieeexplore.ieee.org/abstract/document/10825458, Deusser.etal.2024c,
@Inproceedings{Deusser.etal.2024c,
author={Deußer, Tobias; Zhao, Cong; Uedelhoven, Daniel; Sparrenberg, Lorenz; Hillebrand, Lars; Bauckhage, Christian; Sifa, Rafet},
title={Leveraging Large Language Models for Few-Shot {KPI} Extraction from Financial Reports},
booktitle={2024 {IEEE} International Conference on Big Data ({BigData})},
pages={4864--4868},
month={December},
url={https://ieeexplore.ieee.org/abstract/document/10825458},
year={2024},
abstract={We explore the use of Large Language Models ({LLMs}) for automating the extraction of Key Performance Indicators ({KPIs}) from diverse financial reports without any additional fine-tuning. We focus on evaluating various proprietary and open-source {LLMs} to address the joint named entity recognition and relation extraction tasks essential for accurately linking {KPIs} to their corresponding...}}