With the prevalence of big data technology and its wide application in business practice, the auditing work of modern enterprises has been gradually freed from the manual mode of operation, and transitioned toward the automation at the core of data-driven. This transition not only brings unprecedented opportunities for auditing, but also exposes a series of new risk factors. The authenticity, integrity and accuracy of auditing are being challenged, and these challenges center on how to ensure the quality and effectiveness of auditing in a big data environment. In addition, big data provides auditors with deeper and broader tools for analyzing data, but it also increases the demands on their professional skills. This intersection of technology and ethics provides a unique perspective for this study to explore how to effectively identify and prevent corporate audit risks in the era of big data.

Xu Jianling. The Factors and Preventive Measures of Enterprise Audit Risk in the Era of Big Data. Academic Journal of Business & Management (2023) Vol. 5, Issue 20: 138-143. https://doi.org/10.25236/AJBM.2023.052019.

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