The Relationship between Fraudulent Financial Statements, Variations from Benford’s Law, and SEC Punishments
Open Access
Author:
Mc Farland, Antoinette
Area of Honors:
Accounting
Degree:
Bachelor of Science
Document Type:
Thesis
Thesis Supervisors:
Samuel Burton Bonsall, IV, Thesis Supervisor Samuel Burton Bonsall, IV, Thesis Honors Advisor Brent Schmidt, Faculty Reader
Keywords:
Fraud Benford's Law Fraud Detection Forensic Accounting
Abstract:
This thesis researches the impact of variations from Benford’s Law on fraudulent financial statements and SEC punishments fraudulent companies received. Benford’s Law is used by forensic accountants to detect potential fraud in financial statements. Specifically, forensic accountants use the law to find outliers in a data set by looking at the leading digit in each number. Altered numbers are unlikely to follow Benford’s Law, so if a dataset does not adhere to the law, it is possible the dataset was fraudulently manipulated.
I researched Benford’s Law to see if there is any other information about financial fraud that forensic accountants can discover using Benford’s Law. I analyzed how deviations from Benford’s Law relate to the punishment fraudulent firms receive from the SEC, the reported revenue size of each fraudulent company, and the fraud size. Understanding Benford’s Law’s impact on these three variables can help a forensic accountant better analyze potentially fraudulent financial statements.
In addition, I researched the relationships between punishments from the SEC, revenue size, and fraud size. Understanding how these three variables impact each other can be useful in financial statement analysis and predicting fraud. Forensic accountants can use historical data about past fraud cases to understand how future fraud cases might occur. If forensic accountants can predict the likelihood of a company reporting fraudulent financials, they can stop a fraud early in its stages.
