审计
大数据
信息技术审计
计算机科学
信息安全审计
审核计划
审计证据
构造(python库)
会计
鉴定(生物学)
数据挖掘
内部审计
业务
联合审计
计算机安全
信息安全
植物
生物
网络安全策略
程序设计语言
保安服务
作者
Wenjia Niu,Lihua Zhao,Peiyao Jia,Jiankun Chu
摘要
Professional auditors provide audit services to businesses and they are key participants in enterprise development. Effective identification of audit risks can help auditors plan their audit work rationally and issue correct audit opinions. In the era of big data and the Internet, enterprises generate a large amount of data in their daily operations. For auditors, it is a great challenge to use data mining algorithms, machine learning, artificial intelligence, and other emerging technologies to identify high-quality audit data from the vast amount of data of audited enterprises. At the same time, some companies may falsify and modify their financial statements for their own benefit, which further increases the difficulty for auditors in conducting audits. Traditional auditing methods are costly and consuming and cannot meet standard auditing requirements. Therefore, this study applies computer data mining algorithms to construct an audit risk model that provides a reference for auditors to conduct big data analysis and mines valuable data, thereby improving the efficiency and accuracy of the audit process.
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