Data analysis is a powerful tool for fraud examiners. By searching for patterns, anomalies, trends and outliers, you might discover a cleverly hidden scheme. A skillful fraudster is adept at covering his tracks. However, data analytics empowers you to uncover even the most thoroughly hidden fraud. Furthermore, data analytics can be used to continuously monitor an organization so that red flags of fraud are discovered and investigated as soon as they occur.
This course explores the basics of using data analysis to uncover fraud. You will work through several interactive examples to illustrate simple analysis techniques. With these examples, you will learn how to perform a variety of tests and interpret the results to identify common red flags of fraud.
- Advantages and challenges of using data analytics to detect fraud
- Phases of the data analysis process
- Data analysis techniques for specific fraud schemes
- Red flags for suspicious or fraudulent data
- Basic analytical procedures
ACFE Ordering and Return Policy
You Will Learn How To:
- Identify the benefits and challenges of using data analytics
- Categorize the four phases of the data analysis process
- Recognize common red flags for data that appears to be suspicious or fraudulent
- Distinguish various data analysis techniques that can be applied based on the type of fraud scheme(s) under investigation
ADVANCED PREPARATION: NONE
FIELD OF STUDY: AUDITING
LAST UPDATED: FEBRUARY 2021
DELIVERY METHOD: QAS SELF-STUDY
Table of Contents:
- Part I: Data Analytics
- Lesson 1: What is Data Analysis?
- Lesson 2: Why Do We Use Data Analytics to Detect Fraud?
- Lesson 3: Advantages of Using Data Analytics to Detect Fraud
- Lesson 4: Challenges of Using Data Analytics to Detect Fraud
- Part II: The Data Analysis Process
- Lesson 5: The Planning Phase
- Lesson 6: The Preparation Phase
- Lesson 7: The Testing and Interpretation Phase
- Lesson 8: The Post-Analysis Phase
- Part III: Data Analysis Techniques
- Lesson 9: Basic Analytical Procedures
- Lesson 10: Data Analytics and Scheme-Specific Frauds
- Lesson 11: Billing Schemes
- Lesson 12: Check Tampering Schemes
- Lesson 13: Payroll Schemes
- Lesson 14: Expense Reimbursement Schemes
- Lesson 15: Theft of Cash Receipts Schemes
- Lesson 16: Noncash Asset Schemes
- Lesson 17: Corruption Schemes
- Lesson 18: Financial Statement Fraud Schemes
- Lesson 19: Financial Statement Analysis
- Lesson 20: Benford's Law
- Lesson 21: Textual Analytics
- Lesson 22: Conclusion
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