Today's fraudsters use more technology and have access to much more information than past generations. Also, misappropriation of assets, which includes embezzlement and procurement, is the most prevalent fraud in Canada.
More interesting is that the same research from KPMG outlines the typical characteristics of the Canadian swindler. For example, he or she is between 36 to 45, holds a managerial or executive job title, commits multiple illegal transactions over one to five years and usually holds on to the same job in a firm for six years or more.
KPMG analyzed 596 companies worldwide that were victimized by fraudsters between 2011 and 2013. The research shows that the overwhelming reason for committing fraud is financial with the most common motive, not surprisingly, listed as greed, followed by financial gain and financial difficulty. A third of the fraudsters, notes KPMG, indicated that a sense of superiority was their rationale for their fraud, which is linked to the fact that 29 percent of the frauds were committed by executive directors, the largest single job title.
KPMG also divided the fraudsters into three general types.
The opportunist is described as a first-time offender, trusted employee, in a position of responsibility, often a male (married with children), with a non-sharable problem that can be solved by money. The predator, a less common type, usually seeks out a company to start a scheme and almost immediately after being hired, deliberately defrauds the organization, showing little remorse. Finally, the colluder, needs a partner, and collaborates with an internal member of the company to execute the scheme.
James McAuley, Partner, KPMG Forensic, says companies need to focus on the impact of new technologies and the changing nature of fraud.
"Two decades ago, illicitly taking money from a bank was accomplished by a closely knit gang using violent methods or forged signatures. Since that time, the ways to commit fraud have been transformed by technology – the Internet, smart devices and the ability to analyze vast amounts of data.”