Subject Matte

1. Compare and contrast the nature of white collar crime with other type types of illegal acts.

2. Compare and contrast the typical participants of white collar crime against the participants of other types of illegal acts

3. Discuss the role of technology in white collar crime and how its role may create differences from other forms of crime.

4. Analyze the role of “opportunity” and how it contributes to white collar crime. Provide specific examples to support your response.

When Edwin Sutherland first began his study/analysis under the Traditional Summary Reporting System, there was a limited amount of information available on White Color Crime. The white-collar offenses that are measured are fraud, forgery/counterfeiting, embezzlement, and all other offenses. Because white-collar crimes are not Index crimes, the only information available on these offenses is arrest information, which includes age, sex, and race of the arrestee. Additionally, all other offenses arrest category is very limited in its ability to measure the white-collar offenses included in its counts. This is due to the inability to differentiate the white-collar offenses from the others that also fall in this category. Based upon the most recently published data from the FBI, the arrest rates for the offenses of embezzlement, fraud, and forgery/counterfeiting are much lower than the arrest rates for property, crime, or for total crimes in general. In order to assess the utility of using NIBRS to measure white-collar crime, a substantial, but not exhaustive, list of white-collar offenses and its classification under NIBRS is provided (see Appendix A).

Based upon that analysis, the following UCR offenses could be considered white-collar crime: fraud, bribery, counterfeiting/forgery, embezzlement (all of which are Group A offenses), and bad checks (a Group B offense). Fraud is further broken down into five subcategories: false pretenses/swindle/confidence game, credit card/ATM fraud, impersonation, welfare fraud, and wire fraud. Additionally, agencies submit arrest counts for many white-collar crimes through the All Other Offenses Group B category. As is the case with the All Other Offenses category in the Summary arrest data, the count within this category will be limited because one will be unable to distinguish the white-collar offenses from other types of offenses.

In 1997 through 1999, white-collar crime accounted for approximately 3.8 percent of the incidents reported to the FBI. The majority of those offenses are frauds and counterfeiting/forgery. Additionally, the Group B offense of bad checks accounted for approximately 4 percent of the arrests during 1997-1999.
Other types of illegal acts are, Fraud Offenses, False Pretenses/Swindle/Confidence game, Credit Card/ATM Fraud Impersonation, Welfare Fraud, Wire Fraud Bribery, Counterfeiting/Forgery, Embezzlement, Arson + Fraud. Economic crime—Group A offenses Arrestees: Total 3,634,233, Bad Checks 135,060
Economic crime—Group B offenses, In addition to the different NIBRS offenses, using additional data elements can further define and describe white-collar crime. Even though there is a total of 53 data elements divided into six segments in NIBRS, not all of them will apply to white-collar crimes. Many data elements are applicable only to crimes against persons, while white-collar offenses are primarily crimes against property. The four Group A offenses could potentially have all six segments represented in their data elements, but there is only a limited amount of information available on the Group B offenses. Only arrestee information is collected on Group B offenses, which will include many of the corporate offenses like tax law violations, health and safety violations, environmental law violations, etc. Four data elements of particular interest for measuring white-collar crime are offender(s) suspected of using . . . , location type, property description, and type of victim. High tech crime is well represented by the data element offender is suspected of using . . . with computer as one of the possible choices. Offenses like fraud can be further delineated by the type of victim (e.g., government agency, financial institution, individual), property description, or location type. Computer Crime: Within NIBRS, the investigating agency can indicate whether the offender was suspected of using a computer during the commission of the offense. By capturing the computer-aided element of the offense in this manner, there is the ability to measure the extent of computer-related crime without losing the substantive nature of the offense. Of the offenses committed using computer equipment, 42 percent are white-collar offenses. The largest proportion of those offenses are larceny-thefts.
According to the research on this paper it is an attempt to integrate etiological research on white-collar crime under the hypothesis that criminal behavior results from the confluence of appropriate motivation and opportunity. The starting point is the interactionist theory of motivation basic to most of the social psychological research on white-collar crime. Interactionist theory helps us understand white-collar crime in terms of the offenders' symbolic construction of their social worlds but ultimately fails to explain its causes. It is argued that the origins of symbolic motivational patterns are to be found in the social structure of industrial capitalism and the "culture of competition" to which it gives rise. But no theory of motivation, however sophisticated, is sufficient to explain the causes of white-collar crime, and the paper therefore concludes with an analysis of the patterns of opportunities presented to social actors in different structural positions in advanced capitalist nations.
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Criminology theories focus on a specific element in an attempt to explain criminal behavior. However, there are many factors that contribute to an individual's decision to participate in criminal behavior. Some theories might focus on biological conditions, but they ignore the social conditions. Differential opportunity combines strain theory and social learning theory. This theory was developed by Richard Cloward and Lloyd Ohlin, and it provides an ample framework for analyzing corporate violence. By employing differential opportunity, criminologists apply both the influences of strain theory and the learned behavior of social learning to explain white collar crimes.
The definition of white collar crime and corporate violence is highly debated. The Department of Justice's defines white collar crime as "illegal acts which are characterized by deceit, concealment, or violation of trust and which are not dependent upon the application of threat of physical force or violence. Individuals and organizations commit these acts to obtain money, property, or services; to avoid the payment or loss of money or services; or to secure personal or business advantage" (Barnett, p.1). These crimes are typically performed by professionals, who hold a position of trust and power. White collar crimes are committed by "businesses, governments, and professionals kill and injure, but they get much less public attention than more flamboyant incidents of death-dealing" (Brown, Esbensen, and Geis, 2010, p.412). Businesses can overlook safety regulations, which cause devastation to employees and communities, but they also have the ability to cause financial destitution for families, such as the cases of Ponzi schemes. One discussion of the Enron ponzi scheme described one of the executives, Jeff Skilling, as a "wealthy executive who went too far and the pursuit of profit and caused financial pain and devastation to thousands of investors, employees, and contractors" (Georgiou, 2010). People and entities committing these crimes are motivated by greed and acceptance.
When employing the differential opportunity theory to white collar crimes, criminologists are able to analyze the element of social learning and the sub-culture influences of the environment. Strain theory discusses the idea of a criminal sub-culture. Strain theory suggests, "a person deviates because of some external stress" (Brown, et al,2010, p.358). Criminal sub-cultures create a lot of stress. Many businesses strongly urge financial success; they often threaten lack of success with dismissal. Frequently, the insistence to succeed is so substantial; it will tempt employees to participate in illegal activity. Enron constructed an environment of risk-taking and greed, and it was acceptable to break the law to achieve power and financial success. Enron created an environment of "unrelenting stress on growth and its absence of controls helped push execs into unethical behavior" (Byrne, 2002). The sub-culture develops norms of illegal behavior, and in this situation, people become comfortable participating in illegal behavior. They also feel it is necessary because of the stresses placed upon them to succeed.
Cloward and Ohlin expanded upon the strain theory by incorporating social learning, which helped explain why people succumb to criminal sub-culture. In relation differential opportunity, "the social learning component maintains that behavior, as well as definitions and rationalizations for the behavior, are learned in interactions with similarly situated individuals" (Brown, et al, 2010, p.358). White collar criminals often learn their crimes at their place of employment by others engaging in similar acts. In the case of Enron, the work environment suggests the "emphasis on the individual instead of the enterprise may have pushed many to cross the line into unethical behavior" (Byren, 2002). While working in an environment where crimes are accepted, it is easier for people to rationalize their behavior.
By combining social learning and strain theories into the differential opportunity, criminologists are able to explain more of the factors contributing to white collar crime. This theory explains why people initially engage in the crime and why they continue participating in the behavior. There are always numerous elements that contribute to a behavior; therefore, it is more beneficial to apply more than one theory in an attempt to more accurately explain the behavior.