The Measurement of White-Collar Crime Using Uniform Crime Reporting Data
| Washington, D.C. March 06, 2002 |
The Federal Bureau of Investigation today released The Measurement of White-Collar Crime Using Uniform Crime Reporting (UCR) Data, a study in the National Incident-Based Reporting System (NIBRS) Publication Series. Defined as “... a crime committed by a person of respectability and high social status in the course of his occupation,” white-collar crime extracted from NIBRS data accounts for 4 percent of crime reported. Four percent of all arrestees reported in NIBRS were individuals arrested for bad check offenses. The majority of white-collar crime offenders have had contact with their victims and are typically white males aged late-twenties to early-thirties.
Computer crime, or technocrime, can be extracted in NIBRS by the data element that notes the offender was suspected of using a computer or computer equipment to perpetrate the crime. NIBRS data demonstrate that white-collar crime comprises 42 percent of the offenses committed with a computer. Of those offenses, the crime of larceny-theft accounts for the largest proportion. (See figure above.)
White-collar crime, on average, accounts for a greater dollar loss per incident when compared to other property crime incidents. The majority of white-collar crime incidents, with the exception of wire fraud, occur within public spaces.
Unique to NIBRS is the ability to capture information on nonperson entities that are victimized by crime. This is particularly useful when considering white-collar crime, where NIBRS data show that businesses are just as likely as individuals to fall victim.
In contrast to the limited data previously available on the topic of white-collar crime, NIBRS provides information on incidents, offenses, victims, and arrestees for five separate types of fraud, bribery, counterfeiting/forgery, embezzlement, and other offenses that in combination could constitute white-collar crime. (See figure below.)