The terrorist attacks on the World Trade Center on September 11, 2001 highlighted the importance of open source intelligence. The establishment of the US PATEIOT Act and the Homeland Security Department heralds the potential application of information technology and data mining in detecting money laundering and other forms of terrorist mobilization. Law enforcement has long been concerned with money laundering activities that are normally traded through banks and other financial services organizations.
Law enforcement now monitors international trade prices as a financing tool for terrorist activities. With international trade, money laundering can transfer money from a country without being noticed by the government. This is mainly achieved by overestimating the price of imported goods and underestimating the price of export goods. For example, domestic importers can partner with foreign exporters to overvalue imported goods, thereby transferring money from their home countries for customs fraud, tax evasion and money laundering. Among them, foreign exporters may be members of terrorist organizations.
Data mining technology mainly analyzes the import and export transaction data of the US Department of Commerce and other business-related units. The import price exceeding the upper limit and the export price data of the remaining offline will be tracked. Data mining technology mainly focuses on taxable income transfer and tax evasion and tax evasion caused by abnormal transfer prices between companies. Such price differences may be related to tax evasion, money laundering, or terrorist financing. Of course, trade database errors can also lead to price differences.
Data mining will provide the efficiency of data evaluation. This, in turn, helps to deal with terrorists. The application of information technology and data mining technology in financial transactions will produce more useful information.