Issue |
E3S Web Conf.
Volume 275, 2021
2021 International Conference on Economic Innovation and Low-carbon Development (EILCD 2021)
|
|
---|---|---|
Article Number | 01022 | |
Number of page(s) | 5 | |
Section | Energy Application and Ecological Resource Sustainability | |
DOI | https://doi.org/10.1051/e3sconf/202127501022 | |
Published online | 21 June 2021 |
Research on Data Mining of Personal Income Tax in Tax Collection and Administration Audit
Chongqing College Of Architecture And Technology, 401331
In the context of the rapid development of economy and information technology, the level of tax informatization is getting higher and higher. The tax department has obtained a large amount of tax management data. Taxation departments must analyze and apply these data in order to grasp the deficiencies in the current tax management work, so as to take effective measures to improve tax quality and efficiency. This is the focus of the work of the taxation department. In the process of personal income tax collection and management, full application of data mining technology can break through the traditional personal tax collection and management model and improve the level of personal tax collection and management. At the same time, this can also ensure the effectiveness of the tax data verification work, which is positively helpful to improve the tax data application capabilities. This can also provide an effective reference for tax management decision-making. At this stage, the full application of risk-oriented audit methods based on data mining technology can improve the effectiveness of personal income tax collection and management audits. However, it is necessary to pay attention to a comprehensive study of the sources of personal income tax data. At the same time, the taxation department should also discuss the data processing of personal income tax and the review of the rationality, legality, and compliance of personal tax collection, so as to improve the data mining level of China’s personal tax collection and management.
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.