Detecting Fraud and Errors Using Benfordʼs Law Mark Nigrini

This chapter reviews Benford's law as it relates to detecting fraud and errors. It starts with an introduction and a review of selected parts of Benford's original 1938 paper, which shows the results of his analysis of 20,229 records from a total of 20 sets of data. Thereafter, four complaint data sets are reviewed, pertaining to interest received amounts from tax return data, census results from the 2000 United States census, results of an analysis of streamflow data, and results of analysis of accounts payable data. This is then followed by a discussion of several Benford analyses of fraudulent data related to accounts payable amounts, payroll data, and reported corporate numbers. The concluding discussion talks about these findings and sheds some light on when Benford's law might, or might not, detect fraud or errors.