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Updated in [July 25th, 2023]
This program provides an in-depth look into fraud risk analytics and prevention. It covers the characteristics and different types of fraud, as well as how to detect and prevent it. Participants will learn about Benford law, box plots to identify outliers, and how AI can help detect fraud, including a case study. Best practices in fraud management will also be discussed. The program will provide a walk through of applying techniques in Excel and AI, as well as a framework to assess the maturity of the organization for fraud management. Facilitated by an industry veteran with extensive experience in fraud detection and prevention, this program offers a comprehensive look into fraud risk analytics and prevention.
Course Syllabus
Introduction
Understanding characteristics of fraud
Framework to assess fraud maturity
Understanding different types of Fraud
Fraud Analytics: Core techniques to detect fraud easily
How to use Excel to detect Fraud
Fraud Analytics: Power of AI
Anomaly Detection Using Power BI
Managing Fraud - Actions to prevent fraud
Process Approach to detect and prevent fraud
Cost recovery
Detecting Fraud Programmatically
Conclusion
Bonus Lecture