Chapter One

The Schematics of Fraud and Fraud Analytics

Fraud analytics has become the emerging tool of the twenty-first century for detecting anomalies, red flags, and patterns within voluminous amounts of data that is sometimes quite challenging to analyze. The use of fraud analytic tools does not have to be complex to be effective. The techniques of criminals and fraudsters and their shenanigans are savvier due to technology and the means they use to hide fraudulent activities. While technology has played a role in increasing the opportunities to commit fraud, the good news is that it can also play a key role in developing new methods to detect and prevent fraud. In the past, a spreadsheet was the master of fraud analytics. However, a new revolution has taken us by force—new strategies, data mining techniques, and powerful new software are constantly evolving.

The term “fraud” is commonly used for many forms of misconduct even though the legal definition of fraud is very specific. In the broadest sense, fraud can encompass any crime for gain that uses deception as a principal modus operandi. More specifically, “fraud” is defined by Black's Law Dictionary as “a knowing representation of truth or concealment of a material fact to induce another to act to his or her detriment.”1 Consequently, fraud includes any intentional or deliberate act to deprive another of property or money by guile, deception, or other unfair means.

According to the American Association of Fraud Examiners (ACFE):

Health care fraud, identity theft, padded expense reports, mortgage fraud, theft of inventory by employees, manipulated financial statements, insider trading, Ponzi schemes—the range of possible fraud schemes is large, but at the core, all of these acts involve a violation of trust. It is this violation, perhaps even more than the resulting financial loss, that makes such crimes so harmful.2

Because fraud inherently involves efforts at concealment, many frauds go undetected and the criminals get away with them. For these cases, it is impossible to know the impact of the fraud.

How do we Define Fraud Analytics?

Fraud analytics is when analysis relies on “critical thinking” skills to integrate the output of diverse methodologies into a cohesive actionable analysis product. Analysis is used for various approaches, depending upon the type of data/information that is available and the type of analysis that is being performed. The analysis process requires the development and correlation of knowledge, skills, and abilities.

As we embark on the efforts to incorporate more fraud analytics within our organizations it is my hope that many develop a clear understanding of how imperative it is to start using the various tools that are available. There should be no excuse. A few years ago we were baffled after hearing that Bear Stearns had a liquidity problem and that perhaps it was one of the greatest financial scandals in history. The troubles deepened with Fannie Mae, Freddie Mac, AIG, Lehman Brothers, Bernie Madoff, WAMU and countless others. In my white-collar crime mind I often wonder if any fraud analytic tools were used and if so what might they have been? Up until now, the greatest financial debacle in history was perpetrated—believe it or not—in the 1700s. “The South Sea Bubble” scandal in 1720 caused the loss of over $500 billion translated to today's dollars. It took over 300 years to beat that record but is quite obvious that the 21st century has made its mark with fraud and the collapse of major companies that have for decades graced the pages of business magazines. Again, I'm curious to know what kind of fraud analytic tool those uncovered “The South Sea Bubble” scandal used. One would hope that it was a precursor to one of the tools mentioned in the chapters set forth.

Fraud analytics has aligned itself with more than one way to detect and deter, there are more definitions on fraud analytics than in the past and more organizations that are depending upon the most effective and efficient tools that can get the job done.

Report to the Nations on Occupational Fraud and Abuse

In 2012 the ACFE released its annual Report to the Nations on Occupational Fraud and Abuse. The international expansion allows the ACFE to more fully explore the truly global nature of occupational fraud and provides an enhanced view into the severity and impact of these crimes. Additionally, the ACFE compared the anti-fraud measures taken by organizations worldwide in order to give fraud fighters everywhere the most applicable and useful information to help them in their fraud prevention and detection efforts.

James D. Ratley, president of the ACFE, stated in the 2012 Report:

As in previous years, what is perhaps most striking about the data we gathered is how consistent the patterns of fraud are around the globe and over time. We believe this consistency reaffirms the value of our research efforts and the reliability of our findings as truly representative of the characteristics of occupational fraudsters and their schemes.3

Key Findings and Highlights of the 2012 Report to the Nations

Here are some key findings and statistics provided by the 2012 Report to the Nations:

Impact of Occupational Fraud

Fraud Detection

Figure 1.1 are results provided in order to “identify patterns and other interesting data regarding fraud detection methods,”6 the ACFE asked respondents to indicate how the frauds were uncovered. The results are shown in Figure 1.1.

Victims of Fraud

Perpetrators of Fraud

The 2012 Report to the Nations research:

continues to show that small businesses are particularly vulnerable to fraud. These organizations typically have fewer resources than their larger counterparts, which often translates to fewer and less effective anti-fraud controls. In addition, because they have fewer resources, the losses experienced by...