Session Descriptions

Data Analytics for Fraud Detection

Wednesday, August 28, 2024

1:30 p.m. to 2:45 p.m.

Fraud and data quality issues can be pervasive and costly problems that affects various sectors and contexts. Organizations need to leverage the power of data analytics to uncover patterns, anomalies, and trends that could indicate fraudulent activities, determine the extent of fraud, or address other risks. In this session, you will learn how to perform data analytics for fraud detection and investigation in an audit setting. You will see real-world examples of how both basic repeatable tests and creative one-time searches can highlight transactions and events that warrant immediate follow-up attention. You will also learn how to use software to monitor data sets for fraud risks on an ongoing basis.

Learner Outcomes:

1. Explore data analytics targeting fraud detection.
2. Identify high payback tests you and your team can perform on any audit project.
3. Evaluate the use of data and bots to expedite anomaly detection and enhance fraud prevention.
4. Understand challenges and lessons learned from implementing data analytics.