Advances in Economics, Management and Political Sciences

- The Open Access Proceedings Series for Conferences


Proceedings of the 2nd International Conference on Financial Technology and Business Analysis

Series Vol. 73 , 05 March 2024


Open Access | Article

Study on the Application of Big Data Technology in Inventory Audit - Taking Swertia Audit as an Example

Jingyi Liu * 1
1 Department of Accounting, Beijing Institute of Petrochemical Technology, Beijing 102627,China,

* Author to whom correspondence should be addressed.

Advances in Economics, Management and Political Sciences, Vol. 73, 188-193
Published 05 March 2024. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Jingyi Liu. Study on the Application of Big Data Technology in Inventory Audit - Taking Swertia Audit as an Example. AEMPS (2024) Vol. 73: 188-193. DOI: 10.54254/2754-1169/73/20231730.

Abstract

The arrival of the big data era provides new ideas for auditing to help transform traditional auditing into modern auditing. In this paper based on the existing literature, the basic data and application framework of big data auditing models are extensively reviewed, analyzed and summarized. The research and application of big data and its technology has become a domestic and foreign hot topic. In this paper, the application of big data technology in auditing is based on inventory analysis and auditing based on the analysis of the original auditing procedures and methods as well as the associated risks and difficulties. The case study of the Roe Deer Island scallop inventory audit event is used to study the possibility of applying big data auditing techniques in this area and the risk response in the case of the audit model, which provides a reference for the application of big data auditing in other inventory companies.

Keywords

inventory audit, big data, fixed assets

References

1. Liu R.Z, et al. (2005). Algorithms for Audit Analysis Modeling. Beijing: Tsinghua University Press.

2. He Y.J, Zhang J.C. (2006). Database Technology in Computer Auditing. Auditing Research (Supplement), 33-44.

3. Chen W, Smieliauskas W. (2016) Electronic Data Auditing in Big Data Environment: Opportunities, Challenges and Methods. Computer Science, 43, 8-13+34.

4. Chen D.P. (2009) Research on the Use of Data Mining Technology in Modern Auditing. Journal of Nanjing Audit Institute, 2, 61 65.

5. Yu H, Chen J.X, Wang J.C. (2023) Remote Internal Auditing Based on Big Data: Application Framework and Problem Study. Business Accounting, 2, 15-19.

6. Bao S.W. (2016) Exploration of Government Procurement Audit Ideas and Technical Methods Under Big Data Environment. Audit Research, 6, 13-18.

7. Wang Z, Wu Z. (2005) Application of Data Mining in the Analysis of Audit Information. Computer Application Research, 2.

8. Yan X.F, Zhang D.X. (2013) Big Data Research. Computer Technology and Development, 23, 168-172.

9. Yang G.Y. (2011) Analysis of Inventory Audit Risk and Improvement Measures. China Township Enterprise Accounting, 6, 145-146.

10. Wu D.Q. (2023) Research on the Application of Big Data Technology in Inventory Project Audit. Zhejiang Gongshang University.

Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the 2nd International Conference on Financial Technology and Business Analysis
ISBN (Print)
978-1-83558-319-7
ISBN (Online)
978-1-83558-320-3
Published Date
05 March 2024
Series
Advances in Economics, Management and Political Sciences
ISSN (Print)
2754-1169
ISSN (Online)
2754-1177
DOI
10.54254/2754-1169/73/20231730
Copyright
© 2023 The Author(s)
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated