Occupational fraud is a dominant form of white collar crime that exacts a significant toll on the organisations that fall prey to it, investors, financial institutions, as well as the overall economy. The Association of Certified Fraud Examiners estimates that a typical organisation loses seven percent of its annual revenues as a result of occupational fraud and abuse.
Fraud represents a significant business risk that must be mitigated. Effective fraud detection and prevention bolsters the bottom line by minimising potential revenue leakage through unseen fraudulent activities. As compliance and standards initiatives such as the United States’ Sarbanes-Oxley (SOX) Act and Statement and Auditing Standards (SAS) No. 99 create an increasingly more complex regulatory environment for organisations across the globe, demand has increased for greater scrutiny and visibility into the effectiveness of internal controls to minimise errors and reduce the opportunity for occupational fraud.
Finding fraud is an ongoing challenge that requires both skilled practitioners and specialised technology. There are several issues that make effective fraud management a particularly challenging task. These include: enormous and ever-expanding volumes of data; the growing complexity of systems; changes in business processes and activities; continuous evolution of newer fraud schemes to bypass existing detection techniques; false alarms; and regulatory issues related to employee privacy and discrimination.
This white paper focuses on the nature and scope of occupational fraud, and delves into solutions based on transactional data analysis.
