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CONCLUSION

This chapter familiarized you with the primary, advanced, and associated tests of Benford's Law. It provided you with an understanding of how it works and some suggested applications. Benford's Law is a good general test that can be applied to most data sets to test for excessive duplications that may be indicators of fraud. IDEA's built-in Benford's Law tests make it simple to use and the results are graphically displayed to give you an excellent visual overview of whether the data conforms to Benford's Law. The graphical view allows you to see how well the data conforms or how much nonconformity exists. It is a good first test to apply to data sets.

With the exception of the same-same-same test that is built into IDEA and known as Duplicate Key Detection, the other tests have to be performed manually. Step-by-step instructions are provided so the reader can apply these procedures. During the step-by-step instructions, the reader is exposed to little-known items, such as using the @FieldStatistics function to calculate Z-score, even amounts extractions using MOD to provide the results, using @Precno to fix a physical record number to each record, how the Duplicate Key Exclusion feature only provides one unique exclusion, and how the same-same-different test can overcome that limitation.

All the tests described in this chapter are powerful and useful to detect and highlight anomalies in data sets. Additional tests are presented in Chapter 6.

- NOTES

1. Mark J. Nigrini, Forensic Analytics: Methods and Techniques for Forensic Accounting Investigations (Hoboken, NJ: John Wiley & Sons, 2011).

2. Scott D. J. Graham, John Hasseldine, and David Paton, "Taylor & Francis Online: Statistical Fraud Detection in a Commercial Lobster Fishery," New Zealand Journal of Marine and Freshwater Research 43, no. 1 (2009).

3. Andreas Diekmann, "Not the First Digit! Using Benford's Law to Detect Fraudulent Scientific Data," Ideas, July 9, 2005, accessed January 28, 2014, ideas.repec.org/p/ wpa/wuwpot/0507001.html.

4. Susumu Shikano and Verena Mack, "When Does the Second-Digit Benford's Law-Test Signal an Election Fraud? Facts or Misleading Test Results," Ideas, accessed January 28, 2014, ideas.repec.org/a/jns/jbstat/v231y2011i5-6p719-732.html.

5. Mark J. Nigrini, Benford's Law: Applications for Forensic Accounting, Auditing, and Fraud Detection (Hoboken, NJ: John Wiley & Sons, 2012).

6. Nigrini, Forensic Analytics .

7. Joseph T. Wells, Principles of Fraud Examination, 3rd ed. (Hoboken, NJ: John Wiley & Sons, 2011).

8. Nigrini, Forensic Analytics.

9. Ibid.

 
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