White-collar crime Flashcards
White-Collar Crime (Edwin H. Sutherland)
Crime in the upper, white-collar class, which is composed of respectable, or at least respected, business, and professional men.” These crimes were confined to acts performed by white-collar persons in occupational roles, thereby excluding
“most of their cases of murder, adultery, and intoxication, since these are not customarily a part of their occupational procedures
White-Collar Crime ( Dictionary of Criminal Justice Data Terminology)
nonviolent crime for financial gain
committed by means of deception by persons whose occupational status is entrepreneurial, professional or semi-professional and utilising their special occupational skills and opportunities; also nonviolent crime for financial gain utilising deception and committed by anyone having special technical and professional knowledge of business and government, irrespective of the person’s occupation
White-Collar Crime (Albert J. Reiss, Jr. and Albert Biderman)
White-collar crime violations are those violations of law to which penalties are attached that involve the use of a violator’s position of economic power, influence, or trust in the legitimate economic or political institutional order for the purpose of illegal gain, or to commit an illegal act for personal or organisational gain
High Status Anti-trust
These offenders committed the crimes with the largest dollar impact, and the
widest geographic scope. They are overwhelmingly white (99%-plus) and
male (99.1% for anti-trust,). The are likely to hold a college degree (40.9% ), and their frauds were usually occupational in nature.
1) Almost 97% of anti-trust offenders had been steadily employed in the years preceding their crime.
2) The anti-trusters had a median ratio of assets to liabilities of $200,000 (assets) to $40,000 (liabilities).
3) Anti-trust violators were own their own homes (73.5% ) and to be married (95.7%)
High Status securities
These offenders committed the crimes with the largest dollar impact, and the widest geographic scope. They are overwhelmingly white (99%-plus) and male (97.8% ). The are likely to hold a college degree (40.9% ), and their frauds were usually occupational in nature.
1) only about 60% of the securities
offenders had continually held a job.
2) The securities offenders medianly held
$57,500 in assets with $54,000 in liabilities.
3) violators were own their own homes (
58.2%) and to be married (80.7%) than
Middle •Tax fraud •Bribery
These offenders are mainly white males, around 45 years old. Their crimes are
not usually occupational—just 15% for tax fraud, less than 18% for bribery.
Roughly 57% of offenders owned their own homes, and about 28% held a college degree. Their median assets ranged from $45,000–$49,500; median liabilities were between $19,000 and $23,500. The authors remark that although tax fraud is a typical white-collar crime, “two-thirds of the tax
offenders work in the manufacturing or nonprofessional service sectors.
Low
•Credit fraud
•Mail fraud
•False claims
This group was not as likely to be white—71.5% for credit fraud, 76.8% for
mail fraud, 61.8% for false claims; or male—84.8% for credit fraud, 82.1%
for mail fraud, 84.7% for false claims. They were generally younger than the
other category offenders (less than 40 years old); less likely to be married
(about 50%); and less likely to own their own home (roughly 34–45% across
the three crime types). Their net worth, as the ratio of assets to liabilities, was
remarkably low: $7,000/$7,000 for credit fraud; $2,000/$3,500 for mail fraud;
$4,000/$5,000 for false claims
Outside Hierarchy
•Bank embezzlement
These offenders were placed outside the rankings because they were
dramatically younger (a mean age of 31) and more likely to be female (44.8%
female/55.2% male) than the other groups. While nearly 25% of the Low-
status group was unemployed at the time of their crime, only 3% of
embezzlers were without a job (just slightly above the 2.8% rate for High-
status offenders). They are the group least likely to have a college degree
(12.9%), or to own their own home (28.4%). Their median net worth was
$2,000 in assets with $3,000 in liabilities. Male embezzlers were usually
managers of a local banking operation, while females were most often tellers
or clerical workers.
Contributing Factors
• The world economy increasingly running on credit, which often means rising personal debt. The offenders in the sample often showed serious discrepancies “between their resources and their commitments
• New information technologies mean that the opportunity for wrongdoing is growing,
and many of the techniques are not widely comprehended by businesses or individuals.
• Government programs distributing large amounts of money make an enticing target
for defalcations.
• The importance of credentials in a professionalised society may influence individuals “to inflate the credentials, or to make them up when they do not exist.” This tendency involves everything from cheating on school entrance exams to falsifying credit applications.
• Most broadly, the authors observe a culture based on affluence and ever-higher levels of success. Television, and advertising in general, promise that no one has to settle for second best, prompting those who find themselves running behind to fudge the difference, crossing ethical and sometimes legal lines.
