9.4 Money Laundering


9.4 Money Laundering

Money generated in large volume by illegal activities must be "laundered," or made to look legitimate, before it can be freely spent or invested; otherwise, it may be seized by law enforcement and forfeited to the government. Transferring funds by electronic messages between banks—"wire transfer"—is one way to swiftly move illegal profits beyond the easy reach of law enforcement agents and at the same time begin to launder the funds by confusing the audit trail.

To launder money is to disguise the origin or ownership of illegally gained funds to make them appear legitimate. Hiding legitimately acquired money to avoid taxation, or moving money for the financing of terrorist attacks also qualify as money laundering activities. United States Treasury officials estimate that as much as $300 billion is laundered annually, worldwide, with from $40 billion to $80 billion of this originating from drug profits made in the United States.

MO: Law enforcement officials describe three basic steps to money laundering.

  1. Placement: introducing cash into the banking system or into legitimate commerce

  2. Layering: separating the money from its criminal origins by passing it through several financial transactions, such as transferring it into and then out of several bank accounts, or exchanging it for travelers' checks or a cashier's check

  3. Integration: aggregating the funds with legitimately obtained money or providing a plausible explanation for its ownership

Wire transfers of illicit funds are yet another key vehicle for moving and laundering money through the vast electronic funds transfer systems. More than 465,000 wire transfers, valued at more than two trillion dollars, are moved each day in the United States. Using data mining technologies and techniques for the identification of these illicit transfers could reveal previously unsuspected criminal operations or make investigations and prosecutions more effective by providing evidence of the flow of illegal profits.

There are many ways to launder money. Any system that attempts to identify money laundering will need to evaluate wire transfers against multiple profiles. In addition, money launderers are believed to change their MOs frequently. If one method is discovered and used to arrest and convict a ring of criminals, activity will switch to alternative methods. Law enforcement and intelligence community experts stress that criminal organizations engaged in money laundering are highly adaptable and flexible. For example, they may use nonbank financial institutions, such as exchange houses and check cashing services and instruments like postal money orders, cashier's checks, and certificates of deposit. In this way, money launderers resemble individuals who engage in ordinary fraud: They are adaptive and devise complex strategies to avoid detection. They often assume their transactions are being monitored and design their schemes so that each transaction fits a profile of legitimate activity.

In a study entitled Information Technologies for the Control of Money Laundering, completed in September 1995, the Office of Technology Assessment (OTA) was asked by the Permanent Subcommittee on Investigations of the Senate Committee on Governmental Affairs to assess the proposed use of techniques derived from AI research (data mining) to monitor wire transfer traffic and recognize suspicious transfers. The OTA report rejected the use of data mining due in part to a lack of useful profiles, high false positives, high cost, and privacy issues, but, most importantly, the major challenges in constructing an effective wire transfer analysis system was related to the incomplete, spotty, and poor condition of the data, not the AI technologies. "In several cases, technologies are available that would be appropriate for wire transfer analysis, but data and (government) expertise do not exist to make those technologies effective."

As with other criminal detection applications the major obstacle to using data mining techniques is the absence of data uniformity. Related issues, such as the absence of experts, high costs, and privacy concerns, are being reevaluated in light of the recent terrorist attacks. The post-9/11 environment is changing the priorities of years ago. One of the biggest obstacles to using data mining to detect the use of wire transfers for illegal money laundering was the poor quality of the data; ineffective standards did not ensure that all the data fields in the reporting forms were complete and validated. New legislation is already changing this, ensuring that the quality of data is improved to the level that data mining can be used by government analysts from the U.S. Treasury Department's Financial Crimes Enforcement Network (FinCEN) and other investigative agencies.




Investigative Data Mining for Security and Criminal Detection
Investigative Data Mining for Security and Criminal Detection
ISBN: 0750676132
EAN: 2147483647
Year: 2005
Pages: 232
Authors: Jesus Mena

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