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Application of machine learning models and artificial intelligence to analyze annual financial statements to identify companies with unfair corporate culture

机译:机器学习模型的应用和人工智能分析年度财务报表,识别不公平企业文化的公司

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The purpose of the publication was to create a model that, based on the annual financial statements, identifies the risk of significant financial irregularities occurring in the enterprise. These irregularities may relate to different types of financial fraud that do not necessarily affect the annual financial statements. A characteristic feature of irregularities is that they are large-scale and will have a drastic impact on the company’s reputation. The results of the research show that machine learning and artificial intelligence algorithms were able to learn to recognize patterns of such scams and can detect them very effectively. An element of the novelty of the presented research is that it shows the possibility of training algorithms to recognize fraud based on information that is often not related directly to the observed fraudulent activities. The practical importance of research is the possibility of using the model in the decision-making process in the enterprise. The model allows assessing the risk that a potential business partner may commit financial fraud, which requires careful examination of the integrity of such an enterprise.
机译:该出版物的目的是创建一个基于年度财务报表的模型,确定企业发生重大金融违规行为的风险。这些不规则性可能与不同类型的金融欺诈有关,这些金融欺诈不一定会影响年度财务报表。违规性的特征是它们是大规模的,对公司的声誉产生了巨大的影响。研究结果表明,机器学习和人工智能算法能够学习识别这种诈骗的模式,并且可以非常有效地检测它们。本研究的新颖性的一个元素是它表明培训算法的可能性基于通常与观察到的欺诈活动直接相关的信息来识别欺诈。研究的实际重要性是在企业决策过程中使用该模型的可能性。该模型允许评估潜在商业伙伴可能提交金融欺诈的风险,这需要仔细检查这种企业的完整性。

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