Previous analytical experience.

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Course Description

With over 300 images, this course reviews and shows how twenty substantive and rigorous tests can be used to detect fraud, errors, estimates, or biases in your data. For each test, the original data is shown with the steps needed to get to the final result. The tests range from high-level data overviews to assess the reasonableness of data to highly focused tests that give small samples of highly suspicious transactions. These tests are relevant to your organization, whether small or large, for profit, nonprofit, or government-related.


Mark J. Nigrini, PhD

Mark J. Nigrini, PhD, is a professor at The College of New Jersey where he teaches managerial accounting, auditing, and forensic accounting. Benford’s Law has been his research passion since his days as a Ph.D student at The University of Cincinnati. Mark’s current line of research addresses advanced theoretical work on Benford’s Law, applications of forensic analytics to contemporary topics such the detection of Ponzi schemes, financial statement fraud, LIBOR manipulations, and the legal process surrounding fraud convictions.

Nigrini is the author of several Wiley publications. His work has been featured in national media including The Financial Times, New York Times, and The Wall Street Journal, and he has published papers on Benford’s Law in accounting academic journals, scientific journals, and pure mathematics journals, as well as professional publications such as Internal Auditor and Journal of Accountancy. His radio interviews have included the BBC in London and NPR in the United States. His television interviews have included an appearance on NBC's Extra and the Discovery Channel. He regularly presents professional seminars for accountants and auditors in the U.S. and Canada, Europe, and Asia with recent events in Singapore, Malaysia, and New Zealand.

Course Specifics

Sep 13, 2016
Previous analytical experience.

Compliance Information

Qualifies for CA Fraud: No

Learning Objectives

Upon successful completion of this course, participants will be able to:

Chapter 1

  • Describe how Access is used in forensic analytics and discuss the basic architecture of Access and Access tables.
  • Identify how to import data into Access and discuss the main types of Access queries.
  • Analyze how the Access Documenter can be utilized in a forensic investigation and discuss other aspects of Access.

Chapter 2

  • Cite how Excel is used in forensic investigations, including how to import data into Excel and the pitfalls that can be encountered when using Excel.
  • State how Excel can be used in Word files.

Chapter 3

  • Discuss the planning involved in the forensic presentation, including the use of PowerPoint.
  • Describe the process of copying from Word, Excel, and other sources to PowerPoint.

Chapter 4

  • Analyze the three tests (data profile, data histogram, and periodic graph) that are used to form a good foundation for a data-driven forensic investigation.
  • Describe how Access and Excel can be used in preparing the data profile, data histogram, and the periodic graph.

Chapter 5

  • Summarize the history of Benford's Law and how it can be used in forensic investigations.
  • Analyze how data sets and data size impact Benford's Law, and define the basic digit tests.

Chapter 6

  • Compute the Z-statistic, the Chi-Square test, and the Mean Absolute Deviation test and determine their applicability in forensic investigations.
  • Analyze the tests based on the logarithmic basis of Benford’s Law and the Mantissa Arc Test, and discuss how to create a perfect synthetic Benford Set.

Chapter 7

  • Discuss how the second-order and summation tests can be used in forensic analytic tests.

Chapter 8

  • Explain how the number duplication and last-two digits tests drill down into the data table to identify abnormalities.

Chapter 9

  • Define descriptive statistics and analyze how it can be used in a forensic analytic case.

Chapter 10

  • Discuss the value of the largest subsets test and the largest growth test and determine how to run the tests in Access.
  • Analyze how to run the largest subsets test and the largest growth test in Excel.

Chapter 11

  • Cite how the relative size factor (RSF) findings are used to find anomalies.
  • State how the RSF test can be run in Access or Excel.

Chapter 12

  • Analyze how the same-same-same test, the same-same-different test, and the subset number duplication aid are used in forensic analytics.
  • Discuss how the tests can be run in Excel and Access.

Chapter 13

  • Define the concepts behind correlation.
  • Explain how correlation can be used to detect fraud and irregularities.
  • Discuss how to calculate correlations in Access and Excel.

Chapter 14

  • Describe time-series methods.
  • Discuss the applications for time-series analysis.
  • Explain how to run a time-series analysis in Excel, including the calculation of the seasonal factors.

Chapter 15

  • Explain the risk-scoring method.
  • Discuss how the risk-scoring method was used in a case involving franchised restaurants.

Chapter 16

  • Discuss the audit selection method of the IRS.
  • Cite how risk scoring is used to detect various frauds.

Chapter 17

  • Assess how the various techniques such as the digits of financial statement numbers and detecting biases in accounting numbers can uncover financial statement fraud.
  • Analyze the case that used risk scoring to detect manipulations in monthly subsidiary reports.

Chapter 18

  • Discuss the use of purchasing cards and their potential for fraud.
  • Analyze how analytics can be used on purchasing card transactions.

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