WHITE-COLLAR CRIME AND BIG DATA

WHITE-COLLAR CRIME AND BIG DATA

It may be in the best interest of business professionals throughout New York to understand more about the role big data solutions have in white-collar crime investigations. The financial investigators can work more effectively now that these big data applications make searching, monitoring and tracking more of a science than an art. The recent innovations are being paired with graphical outputs and analytic models that are more user-friendly, thus making these investigators more productive.

Normally, the complexities of some of these financial crimes enable the accused to delay or avoid apprehension for years. The capabilities of big data, analytics and vast databases now makes exposing and gathering evidence of these financial crimes happen in a much shorter timeframe. White collar crimes cost U.S. taxpayers approximately $600 billion every year. However, despite the sophisticated tools available, a Syracuse University report indicates that federal prosecutors are now making the lowest number of white-collar crime convictions recorded in the past 20 years.

As of September 2015, the federal government is on track to prosecute nearly 6,900 white-collar crime cases. According to the Syracuse report, the total is 12.3 percent less than in 2014 and almost 30 percent less than in 2010. One of the primary reasons for the decline in convictions is the Justice Department’s increasing use of deferred prosecution or non-prosecution agreements for corporations and executives accused of committing these crimes.

A person who has been issued white-collar crime charges such as embezzlement may find it advisable to meet with an attorney in order to prepare a defense strategy. These cases are very complex, and in some cases federal or state prosecutors do not have sufficient resources to bring them to trial. As a result, in some instances it would be possible to enter into a plea agreement which would provide for reduced penalties in exchange for a plea of guilty to a lesser offense.