Fraud Prevention Alert—Data Analytics: Part 2


Report

Overview

As presented in our November 2017 Fraud Prevention Alert—Data Analytics: Part 1, using risk-based assessments and data analytic techniques to identify trends, patterns, anomalies, and abnormal relationships in data can be an effective anti-fraud control. In fact, data monitoring and analysis techniques have been correlated with the largest reductions in global fraud loss and duration, but only 37 percent of victimized organizations implemented these controls. Data analytic techniques can be separated into three categories for practical applications: basic, statistical, and advanced. This alert, the second in a four-part series, focuses on the practical applications for basic techniques and describes how using these techniques on an organization’s data and investigating associated findings can help public officials identify fraudulent activity before it becomes significant.