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Money laundering, terrorist financing and how to contrast them: data and text mining in business intelligence solutions

机译:洗钱,恐怖主义融资以及如何对比它们:商业智能解决方案中的数据和文本挖掘

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The application of data and text mining technologies in business intelligence solutions can give a great contribution to fighting money laundering and terrorist financing. These crimes are multiform and so laws are important, but they can't be the only tool to contrast them. Money laundering is a well known offence, but it abandons classic methods in favour of new schemes, thanks to informatics: so called "cyber-laundering". Money laundering has assumed great relevance since September 11th 2001, because it shows many links to terrorist financing. Data and text mining can be useful in understanding links between people and suspicious transactions in order to track real money laundering and terrorist financing activities. There are American and European initiatives in which data/text mining and business intelligence assume a strategic rule. However, these applications have a critical aspect that involves privacy.
机译:数据和文本挖掘技术在商业情报解决方案中的应用可以为打击洗钱和恐怖主义融资提供巨大贡献。这些罪行是多元的,所以法律很重要,但他们不能成为唯一对比它们的工具。洗钱是一种众所周知的冒犯,但它放弃了经典的方法,支持新的计划,感谢信息学:所谓的“网络洗衣店”。自洗钱以来,自2001年9月11日以来,由于它显示了与恐怖主义融资的许多联系。数据和文本挖掘对于了解人与疑交易之间的联系,以跟踪真正的洗钱和恐怖主义融资活动。有美国和欧洲举措,其中数据/文本采矿和商业智能承担战略规则。但是,这些应用程序具有涉及隐私的关键方面。

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