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Issue title: Special section: Artificial Intelligence driven Big Data Analytics for COVID-19
Guest editors: Xiaolong Li
Article type: Research Article
Authors: Li, Linghana; * | Feng, Yanb | Li, Leic
Affiliations: [a] Hefei College of Finance and Economics, Hefei, Anhui, China | [b] Xuancheng Vocational and Technical College, Xuancheng, Anhui, China | [c] Chaohu University, Hefei, Anhui, China
Correspondence: [*] Corresponding author. Linghan Li, Hefei College of Finance and Economics, Hefei, Anhui, China. E-mail: lilinghan@hfcfe.edu.cn.
Abstract: As the COVID-19 epidemic continues to spread, the government has managed to prevent people from gathering. The audit work can only be carried out through the network, which puts forward higher requirements for the accuracy and effectiveness of the audit work. Under the background of the continuous development of big data and other information technologies, big data audit has gained important technical support and played an increasingly important role. Units at all levels gradually attach importance to the enterprise management mode based on the financial sharing service mode. This paper analyzes the related problems of big data audit under the financial sharing service mode, involving big data flow, big data preprocessing, big data audit process and other issues, in order to provide useful reference for the implementation of big data audit by using the financial sharing service mode under the influence of COVID-19.
Keywords: Big data, COVID-19, audit, financial sharing service model
DOI: 10.3233/JIFS-189298
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 6, pp. 8997-9005, 2020
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