Research on the Path and Effectiveness of Large Model Empowering Tax Collection and Administration

Siyu Chen

2025

Abstract

The ongoing wave of digitalization has resulted in an unprecedented surge in both the volume and complexity of tax data, thereby presenting significant challenges to conventional tax administration models. This research explores the potential of large models as a transformative tool for tax governance. We delve into the technical capabilities of large models, examining their application in critical areas such as data processing,risk stratification,and the development of early warning systems. Furthermore, we investigate their utility in enhancing taxpayer services. The integration of large model into tax operations promises to substantially improve the efficiency of tax collection and administration. This approach can also strengthen the data-driven foundation of decision-making processes and elevate taxpayer service satisfaction. Ultimately, the adoption of large models represents a pivotal step towards the modernization and optimization of tax collection and administration. Tax administration departments should continuously upgrade their technological infrastructure, strengthen data management, and simultaneously enhance tax personnel's understanding and application capabilities of large models to broaden the application scenarios of large models, thereby achieving a qualitative leap in tax administration.

Paper Citation

in Harvard Style

Chen S. (2025). Research on the Path and Effectiveness of Large Model Empowering Tax Collection and Administration. In Proceedings of the 2nd International Conference on E-commerce and Modern Logistics - Volume 1: ICEML; ISBN 978-989-758-775-7, SciTePress, pages 249-254. DOI: 10.5220/0013842300004719

in Bibtex Style

@conference{iceml25,
author={Siyu Chen},
title={Research on the Path and Effectiveness of Large Model Empowering Tax Collection and Administration},
booktitle={Proceedings of the 2nd International Conference on E-commerce and Modern Logistics - Volume 1: ICEML},
year={2025},
pages={249-254},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013842300004719},
isbn={978-989-758-775-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 2nd International Conference on E-commerce and Modern Logistics - Volume 1: ICEML
TI - Research on the Path and Effectiveness of Large Model Empowering Tax Collection and Administration
SN - 978-989-758-775-7
AU - Chen S.
PY - 2025
SP - 249
EP - 254
DO - 10.5220/0013842300004719
PB - SciTePress