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Finding the Needle

Using forensic analytics to understand what happened – and what might happen


Despite all the internal controls employed by companies today, when fraud is discovered, it is usually by humans – and by accident — rather than by technology.  In fact, according to the “2010 report to the Nation on Occupational Fraud,” a biennial report published by the Association of Certified Fraud Examiners, 65% of occupational fraud at public companies was detected by tips, management review or simply by accident.1

Given the wealth of analytical technologies available in the marketplace today, that is a disappointing statistic.  It must change, and it can, through the use of forensic analytics. A combination of human intuition and leading-edge analytics technologies can have a positive impact on the detection and investigation of fraudulent and other illegal or unethical activities if the proper analytics detection methods are employed.

Forensic analytics consists of a set of analytics techniques that investigators can use to uncover irregularities in financial data. Typical problems include errors, biases, duplicates and omissions. The goal of forensic analytics is more than to simply detect irregularities, however. The real goal of forensic analytics is to find out how — and why — these irregularities exist and to find out the source of the anomalies — especially when fraudulent activity is suspected.

This article discusses the four guiding principles that are key to effectively ferreting out data anomalies and establishing confidence in results. It also provides a methodology to meet these four principles – precision, repeatability, defensibility and data integration – by employing a standard repeatable process to forensic analytics.




12010 Report to the Nation on Occupational Fraud. The Association of Certified Fraud Examiners, 2010, p. 19. (retrieved 2011 02 15)

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