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Detection Model of Legally Registered Mafia Firms in Italy

机译:意大利合法注册的黑手党公司的检测模型

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This paper develops a model that can contribute to the detection of legally registered firms defined as Mafia firms (LMFs) due to having been confiscated by judicial authorities, in relation to alleged connections of their owners with Italian organized crime. The model correctly classifies 76.41% of firms within a matched sample of 852 firm-years including LMFs and lawful firms. Furthermore, we present an analysis of financial statement characteristics of singular private firms which are socially irresponsible by nature and whose incentives, modus operandi and legal financial statement formats differ from those of listed companies. In particular, we show that specific accruals and earnings management proxies may provide more insight into accounting manipulation patterns of LMFs. More importantly, our paper can help practitioners and regulators identify accounting signals that can be used in risk assessment models or in the detection of criminal infiltrations and related illicit practices.
机译:本文开发了一种模型,该模型可用于侦查由于其所有者与意大利有组织犯罪之间的涉嫌联系而被司法当局没收的合法注册公司(称为黑手党公司)。该模型在852个公司年的匹配样本中正确地对了76.41%的公司进行了分类,包括LMF和合法公司。此外,我们对单一私营公司的财务报表特征进行了分析,这些私营公司本质上对社会不负责任,其激励机制,操作方式和合法财务报表格式与上市公司不同。特别是,我们表明,特定的权责发生制和盈余管理代理可以为LMF的会计处理模式提供更多的见解。更重要的是,我们的论文可以帮助从业者和监管者识别会计信号,这些信号可以用于风险评估模型或用于检测犯罪渗透和相关的非法行为。

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