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Ed Tobias, CISA, CIA May 12, 2010 Expectations Background Why it works Real-world examples How do I use it? Questions How many have heard of it? ◦ All over the professional journals J. of Accountancy – 2003, 2007 J. of Forensic Accounting – 2004 Internal Auditor – 2008 ISACA Journal – 2010 Fraud Magazine - 2010 As of 2004, over 150 articles have been written about Benford’s Law 1881 – Simon Newcomb, astronomer / mathematician Noticed that front part of logarithm books was more used Inferred that scientists were multiplying more #s with lower digits 1938 – Frank Benford, Physicist at GE Research labs Front part of the log book was more worn out than the back Analyzed 20 sets of “random numbers” – 20,299 #s in all Tested random #s and random categories Areas of rivers Baseball stats #s in magazine articles Street addresses - first 342 people listed in “American Men of Science” Utility Bills in Solomon Islands Benford’s Law: ◦ Random #s are not random ◦ Lower #s (1-3) occur more frequently as a first digit than higher numbers (7-9) In a sample of random numbers: #1 occurs 33% #9 occurs 5% What are “random numbers”? ◦Non-manipulated numbers Population stats, utility bills, Areas of rivers ◦NOT human-selected #s Zip codes, SSN, Employee ID What’s the practical use? ◦ 1990s – Dr. Mark Nigrini, college professor Tested insurance costs (reim. claims), sales figures Performed studies detecting under/overstmts of financial figures Published results in J. of Accountancy (1990) and ACFE’s The White Paper (1994) ◦ Useful for CFEs and auditors What about financial txns? ◦“Random data” = nonmanipulated numbers AP txns, company purchases ◦NOT human-selected #s Expense limits (< $25) Approval limits (No sig < $500) Hourly wage rates How will it help me with nonrandom data? ◦Aid in detection of unusual patterns Circumventing controls Potential fraud You won the lottery – invest $100M in a mutual fund compounding at 10% annually ◦ First digit is “1” ◦ Takes 7.3 yr to double your $ ◦ At $200M, first digit is “2” ... At $500M … First digit is “5” ◦ Takes 1.9 yr to increase $100MM Although time is decreasing, there are more years that start with lower digits ◦ Eventually, we will reach $1B First digit is “1” Seems reasonable that the lower digits (1-3) occur more frequently ◦ These 3 digits make up approx. 60% of naturally-occurring digits Scale invariant ◦ 1961-Roger Pinkham ◦ If you multiply the numbers by the same non-zero constant (i.e., 22.04 or 0.323) New set of #s still follows Benford’s Law Works with different currencies $2M Check Fraud in AZ $4.8M Procurement fraud in NC Check fraud in AZ ◦ #s appear random to untrained eyes ◦ Suspicious under Benford’s Law ◦ Counter-intuitive to human nature Wrote 23 checks (approx. $2M) Many amts < $100K ◦ Tried to circumvent a control that required a human signature Mgr tried to conceal fraud Human choices are not random Avoided common indicators: ◦ No duplicate amounts ◦ No round #s – all included cents Mistakes: ◦ Repeated some digits / digit combinations ◦ Tended towards higher digits (7-9) Count of the leading digit showed high tendency toward larger digits (7-9) Anyone familiar with Benford’s Law would have recognized the larger digit trend as suspicious Benford’s Law can be extended to first 2 digits ◦ Allow examiner to focus on specific areas ◦ High-level test of data authenticity Procurement fraud in NC ◦ 660 invoices from a vendor ◦ Years 2002-2005 ◦ Total of $4.8M submitted for payment Run the 660 txns through Benford’s Law … See any suspicious areas? Drilling down in the “51” txns Over a 3-year period, at least $3.8M in fraudulent invoices for school bus and automobile parts were submitted. The investigation recovered $4.8M from the vendor and former school employees. Data Analytics software ◦ ACL / IDEA Excel ◦ Add-Ons ◦ Built-in Excel Functions Expectations Background Why it works Real-world examples How do I use it? Ed Tobias [email protected] ◦ LinkedIn http://www.linkedin.com/in/ed3200 Benford’s Law Overview. n.d. Retrieved March 10, 2010 from http://www.acl.com/supportcenter/ol/courses/course.aspx?cid=010&ver=9&mod=1&nodeKey=3 Browne, M. Following Benford’s Law, or Looking Out for No. 1. n.d. Retrieved March 10, 2010 from http://www.rexswain.com/benford.html Durtschi, C., Hillison, W., and Pacini, C. The Effective Use of Benford’s Law to Assist in Detecting Fraud in Accounting Data. 2004. Journal of Forensic Accounting. Vol. V. Retrieved March 10, 2010 from http://www.auditnet.org/articles/JFA-V-1-17-34.pdf Managing the Business Risk of Fraud. EZ-R Stats, LLC. 2009. Retrieved March 10, 2010 from http://www.ezrstats.com/CS/Case_Studies.htm Kyd, C. Use Benford’s Law with Excel to Improve Business Planning. 2007. Retrieved March 10, 2010 from http://www.exceluser.com/tools/benford_xl11.htm Lehman, M., Weidenmeier, M, and Jones, T. Here’s how to pump up the detective power of Benford’s Law. Journal of Accountancy. 2007. Retrieved March 10, 2010 from http://www.journalofaccountancy.com/Issues/2007/Jun/FlexingYourSuperFinancialSleuthPower.htm Lynch, A. and Xiaoyuan, Z. Putting Benford’s Law to Work. 2008. Internal Auditor. Retrieved March 10, 2010 from http://www.theiia.org/intAuditor/itaudit/archives/2008/february/putting-benfords-law-to-work/ Nigrini, M. Adding Value with Digital Analysis. Internal Auditor. 1999. Retrieved March 10, 2010 from http://findarticles.com/p/articles/mi_m4153/is_1_56/ai_54141370/ Nigrini, M. I’ve Got Your Number. Journal of Accountancy. 1999. Retrieved March 10, 2010 from http://www.journalofaccountancy.com/Issues/1999/May/nigrini.htm Rose, A. and Rose, J. Turn Excel Into a Financial Sleuth. 2003. Journal of Accountancy. Retrieved March 10, 2010 from http://www.systrust.us/pubs/jofa/aug2003/rose.htm Simkin, M. Using Spreadsheets and Benford’s Law to Test Accounting Data. ISACA Journal. 2010, Vol. 1. Pp. 47-51. Stalcup, K. Benford’s Law. Fraud Magazine. 2010, Jan/Feb. Pp 57-58.