Research on the Application of Big Data Technology in Financial Audit Data Analysis

DOI

10.2991/978-94-6463-710-6_10How to use a DOI?

Keywords

big data technology; Financial auditing; Data analysis; Risk identification; Compliance Audit

Abstract

Against the backdrop of the rapid expansion and increasing complexity of data in the field of financial auditing, big data technology has brought new methods and tools to auditing work. The study analyzed the diverse applications of big data in the field of financial auditing, including data integration, risk detection, technological improvement, and compliance review from multiple dimensions. The concept of big data was explained, and the difficulties encountered in financial auditing, such as scattered data sources, privacy and security risks, and technological bottlenecks, were discussed. Proposed response strategies such as building a unified data integration platform, using intelligent algorithms for risk warning, adopting cutting-edge technology tools to enhance technical strength, and developing audit processes that comply with regulatory standards, aiming to provide solid technical support for innovative development and industry upgrading in the audit field.

Copyright

© 2025 The Author(s)

Open Access

Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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TY  - CONF
AU  - Xi Zhu
PY  - 2025
DA  - 2025/05/14
TI  - Research on the Application of Big Data Technology in Financial Audit Data Analysis
BT  - Proceedings of the 2025 4th International Conference on Big Data Economy and Digital Management (BDEDM 2025)
PB  - Atlantis Press
SP  - 75
EP  - 82
SN  - 1951-6851
UR  - https://doi.org/10.2991/978-94-6463-710-6_10
DO  - 10.2991/978-94-6463-710-6_10
ID  - Zhu2025
ER  -