Benford's Law

A powerful new tool for all forensic accountants, or anyone who
analyzes data that may have been altered

Benford's Law gives the expected patterns of the digits in the
numbers in tabulated data such as town and city populations or
Madoff's fictitious portfolio returns. Those digits, in unaltered
data, will not occur in equal proportions; there is a large bias
towards the lower digits, so much so that nearly one-half of all
numbers are expected to start with the digits 1 or 2. These
patterns were originally discovered by physicist Frank Benford in
the early 1930s, and have since been found to apply to all
tabulated data. Mark J. Nigrini has been a pioneer in applying
Benford's Law to auditing and forensic accounting, even before his
groundbreaking 1999 Journal of Accountancy article introducing this
useful tool to the accounting world. In Benford's Law, Nigrini
shows the widespread applicability of Benford's Law and its
practical uses to detect fraud, errors, and other anomalies.

* Explores primary, associated, and advanced tests, all described
with data sets that include corporate payments data and election
data

* Includes ten fraud detection studies, including vendor fraud,
payroll fraud, due diligence when purchasing a business, and tax
evasion

* Covers financial statement fraud, with data from Enron, AIG,
and companies that were the target of hedge fund short sales

* Looks at how to detect Ponzi schemes, including data on Madoff,
Waxenberg, and more

* Examines many other applications, from the Clinton tax returns
and the charitable gifts of Lehman Brothers to tax evasion and
number invention

Benford's Law has 250 figures and uses 50 interesting
authentic and fraudulent real-world data sets to explain both
theory and practice, and concludes with an agenda and directions
for future research. The companion website adds additional
information and resources.