A Teaching Case: Applying Benford’s Law to Detect Credit Card Fraud Using Microsoft Excel

Abstract

ABSTRACT Benford’s Law has been frequently used for fraud detection and is introduced in various accounting, auditing, and analytics courses. Instead of using specialized computer-aided auditing tools, this teaching case purports to apply Microsoft Excel to demonstrate the process, applicability, and benefits of Benford’s Law by analyzing publicly available datasets on confirmed COVID-19 and credit card fraud cases. This hands-on exercise also enhances students’ Excel skills to extract, transform, and load (ETL) data and use various data visualizations (e.g., pie/100 percent stacked/combo charts) to display proportional information. This case provides an engaging learning experience that matches student skill levels, stimulates critical thinking, and fosters interest in forensic accounting. Data Availability: Data are available from the authors upon request. JEL Classifications: M42; M41; I20.