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Fraud Analytics: Strategies and Methods for Detection and Prevention by Delena D. Spann

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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, ...

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