Fraud Prevention Alert—Data Analytics: Part 1


Report

Overview

Using data analysis techniques with risk-based assessments to identify trends, patterns, anomalies, and abnormal relationships in data can be an effective anti-fraud control. Regularly using these techniques on your organization’s data and investigating findings can help your organization identify fraudulent activity before it becomes significant. This Fraud Prevention Alert, the first in a four-part series, describes the different data analysis techniques and outlines how public officials can help protect public monies by establishing proactive data monitoring and analysis programs to prevent and detect fraud. The three Fraud Prevention Alerts following this one will provide practical applications for using techniques from each of the three data analysis categories: basic, statistical, and advanced.