Detecting Financial Statement Frauds Using Data Analytics

According to the ACFE’s 2018 Report to the Nations, proactive data monitoring and analysis is among the most effective anti-fraud controls. Organizations that undertake proactive data analysis techniques experience frauds that are 52% less costly and 58% shorter than organizations that do not monitor and analyze data for signs of fraud.

The Detecting Fraud with Data Analytics Workshop will teach you how to plan, design, and apply numerous data analytics tests in order to detect various fraud schemes. You will also discover how to examine and interpret the results of those tests to identify the red flags of fraud.

The first day of the course will provide a solid foundation on which to build your data analytics initiatives, from understanding the types of tests that can be used to tying your tests to the fraud risk assessment, properly preparing and normalizing your data for testing, and effectively communicating the results of your analysis.

On day two, you will link your new knowledge of analytical tests, data sources, and fraud schemes while applying data analysis techniques to real data sets and scenarios.

You will work through cases covering a variety of fraud schemes, including purchasing fraud, payroll manipulation, and financial statement fraud. 

Course Objectives:

• Recognize the most common financial statement fraud schemes
• Identify the red flags of financial statement fraud
• Detect fraud using audit procedures
• Address issues that might affect discussion and analysis of the financial statements
• Understand the fraud implications of emerging issues in financial reporting