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Fraud Exprosed Whot you Dont Could Cost your company millions - Joseph W.

Joseph W. Fraud Exprosed Whot you Dont Could Cost your company millions - Wiley Publishing, 2003. - 289 p.
ISBN: 0-471-27475-5
Download (direct link): fraudexposedwhatyoudont2003.pdf
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The 2001 National Retail Security Survey conducted by the University of Florida reported that U.S. retailers lost more than $32.3 billion in inventory shrinkage.25 Some of that loss was caused by human error, damage, and theft by outsiders. But if only 10 percent was caused by theft by employees, that amounts to $3.2 billion dollars—larger than all of major league baseball. Informed observers from the NWCCC estimate the real percentage of such losses caused by the fraudulent actions of insiders to be about 40 to 45 percent—about five times the size of all of major league baseball!26
Even figures this striking may be substantially incomplete. Computers are part of the high-tech world in which we live, and they are certainly involved in at least some portion, and perhaps a high portion, of the frauds with which we are concerned. But are these losses also covered, are they in addition to what we believe we know, or is there some element of double counting? Again, we do not know. There is no organization believed to keep accurate loss figures on high-tech and computer crime, and even the FBI, long in the crime statistics business, has difficulty capturing such data. Compounding this issue are organizational disincentives for revealing such data, to include negative publicity, decreased stockholder acceptance, and customer confidence. Given this state of affairs, organizations such as the Computer Security Institute, in conjunction with the FBI International Computer Crime Squad, conducted the 1999 Computer Crime and Security Survey. This vehicle revealed the following results:27
• 62% of organizations had a computer security breach within the last year
• 30% reported system penetration by outsiders
• 57% pointed to their Internet connection as the point of entry from outside intrusion
• 32% reported denial of service attacks
• 19% experienced sabotage of data or networks
• 14% were victims of financial fraud
• 90% had incidents of virus contamination
• 55% had incidents of unauthorized access by insiders
• 97% reported abuse of Internet privileges by their employees
• 69% lost laptops to theft
• 26% said they had experienced theft of proprietary information
• 32% of the responding organizations had reported serious incidents to law enforcement in the last year
• Losses due to computer security breaches totaled over $100,000,000 for the third consecutive year
• Of the 51% of organizations who acknowledged financial loss, only 31% were able to put a figure on their loss
While some of these statistics are of little relevance to our concerns (e.g., virus contamination, laptop theft), much of this data is directly on point to the problem of occupational fraud. Some organizations were clearly victims of computer-related financial fraud, more than half reported unauthorized access by insiders, one quarter suffered loss of proprietary information, and less than one third of those victimized had the ability to put a dollar value on their loss. These are disturbing numbers and, when coupled with incentives to underreport, appear to be indicative of problems we see in the larger arena of occupational fraud. To some degree we are being asked to solve a problem when we do not know its dimensions or, for that matter, its definitions. Some estimate that shoplifting in the United States costs retailers $13 billion per year, and that at least some, perhaps most, of this loss is caused by employees.28 Are such figures captured as part of what we define as occupational fraud? We simply do not know.
Even the most cited of all crime indexes in the United States, the FBI’s Uniform Crime Reporting Program (UCRP), or its newest incarnation, the National Incident-Based Reporting System (NIBRS), are of little use in any detailed analysis of occupational fraud. The primary reason is the method by which the data are captured. White-collar crime, and especially occupational fraud, is not a priority category for the UCRP. Second, to the degree that this data is captured at all, analysis is difficult because of the categories involved. A typical crime committed in an occupational fraud scenario may be charged in UCRP terms as larceny, larceny by trick, uttering a forged instrument (usually, writing a bad check), or some other offense category. The problem is you cannot tell from the data if the charge relates to an employee submitting phony vouchers for payment (an occupational fraud) or someone passing a hot check at a liquor store. To the police, the courts, and to the UCRP, all these offenses are the same. To us, the distinctions make a world of difference.
The White Collar Crime Study, released by the FBI National Press Office on March 6, 2002, indicates that white-collar crime, when extracted from the NIBRS, constitutes 4 percent of all crime reported and, further, that 4 percent of all arrestees in the system were there for bad check offenses. The report goes on to note that of all computer crimes, or technocrimes, 42 percent were deemed to be white-collar crimes, with the majority of these being larceny-theft. This figure is then broken out by specific offense type: fraud offenses are 9 percent, larceny-thefts are 31 percent, and 2 percent are embezzlements. The report notes that the NIBRS attempts to capture five categories of white-collar crime: fraud, bribery, counterfeiting/forgery, embezzlement, and “other offenses that in combination
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