1. Use of Non-financial Measures to Detect Fraudulent Financial Reporting: Evidence from Recent Research Joseph F. Brazel North Carolina State University Raleigh-Durham Chapter of The Institute of Internal Auditors January 13, 2015

2. Sponsors  Institute of Internal Auditors Research Foundation  Financial Industry Regulatory Authority (FINRA) Investor Education Foundation  The Institute for Fraud Prevention  IAASB  CohnReznick, KPMG, and Ernst & Young  NCSU Poole COM 2

3. Caveats  External audit focus  10,000 foot level / Highlights Tour  All these papers are available at ssrn.com 3

4. Background  Financial Measures = Revenue, Earnings, Total Assets, etc.  What are “Nonfinancial Measures” (NFMs)?  Examples from Brazel, Jones, and Zimbelman (2009)  Number of:  Employees  Retail outlets  Patient visits  Production facilities  Patents  Distribution Centers  Square footage of production facilities 4

5. Background  NFMs are measures of business activity:  Often in 10-K (Part 1 and MD&A) – in the same 10-K filing as fraudulent financial statements  Produced internally and externally (e.g., customer satisfaction)  “Explains” financial results, current push for more disclosure  Correlated with financial statement data  Easy to verify / hard to conceal manipulation  Good benchmark for financial statements  “Fraud” = Fraudulent Financial Reporting, “cooking the books”  Enron, WorldCom, Xerox, The North Face, Rite Aid, Computer Associates 5

6. “Using Nonfinancial Measures to Assess Fraud Risk,” Joe Brazel, Keith Jones, and Mark Zimbelman. Journal of Accounting Research, December 2009, Volume 47, Issue 5, pp. 1135-1166. Research Question If NFMs serve as a good benchmark for the financial statements, do fraudulent firms exhibit NFM RED FLAGS? 6

7. Example: Fraudulent Electronic Component Manufacturer 1997 Income: Overstated $3.7 million. Revenue: 25% from Prior Year. Employees: 6% (440 to 412) Distribution Dealers: 38% (400 to 250) Non-fraud Electronic Component Manufacturer: Revenue: 27% Employees: 20% Distribution Dealers: 7% 7

8. Using Nonfinancial Measures to Assess Fraud Risk DIFF = Growth in Revenue – Average Growth in NFMs Variable NMean EMPLOYEE DIFF Fraud Firms 110 20% RED FLAG Competitors 110 4% CAPACITY DIFF Fraud Firms 50 30% RED FLAG Competitors 50 11% 8

9. “Auditors’ Reactions to Abnormal Inconsistencies between Financial and Nonfinancial Measures: The Interactive Effects of Fraud Risk Assessment,” Joe Brazel, Keith Jones, and Doug Prawitt. Behavioral Research in Accounting, Spring 2014, Volume 26, Issue 1, pp. 131-156.  Key findings:  Virtually no reaction to NFM red flag without “help” (only 5% detected)  Auditors need help detecting abnormal inconsistencies  Tool/prompt greatly improves this process (but ignored under low and medium fraud risk) 9

10. NFM Prompt Revenue Expectation Auditors’ Reactions to Abnormal Inconsistencies between Financial and Nonfinancial Measures: The Interactive Effects of Fraud Risk Assessment FR Assessment Reliance on NFMs + + - 10

11. Reports from the Field 2009 (n = 226 senior level auditors) 11

12. Reports from the Field 2013 (n = 94 senior level auditors) 12 What percent of the time do you use NFMs when performing A/Ps?

13. Reports from the Field Importance of Fraud Red Flags (n = 23 managers and partners) 12 common red flags investigated (1) MW over revenue recognition (2) NFM red flag (3) Significant EBC for Mgt (4) Difficult discussions with Mgt over audit adjustments (5) CFO resignation Important that staff bring NFM red flag to attention of engagement management, but may not always be the case. WHY?????? 13

14. “Hindsight Bias and Professional Skepticism,” Joe Brazel, Scott Jackson, Tammie Schaefer, and Bryan Stewart, working paper To detect the NFM red flag you must be SKEPTICAL: search for inconsistent evidence from a non-traditional evidence source, but also more COSTS (budget, mgt relations)! Research Question  Are the audit firms currently rewarding appropriate skeptical behavior, regardless of the outcome? (Recent PCAOB synthesis paper) 14

15. Auditor Experiment  Experiment with 75 practicing audit seniors. Role: Evaluator of a subordinate performing a substantive A/P related to a division’s revenue balance.  All Subordinates:  SKEPTICAL JUDGMENT: Decided to use NFMs in CY (employees, production space). NFMs not consistent with revenue. Revenue consistent with other sources used in PY. So PS led to IDing NFM Red Flag.  SKEPTICAL ACT: Investigated the NFM red flag, outsourcing overseas (Brazel et al. 2009)

16. Auditor Experiment  For half, subordinate investigated red flag and IDed a MM in overseas operation.  For other half, subordinate investigated red flag and DID NOT ID MM in overseas operation.  All subordinates encountered same costs of PS: over-budget and upset management.  Also, manipulated AC Support (high vs. low): fees and mgt.

17. Auditor Experiment  KEY DV: Evaluation of subordinate (-5, 0, +5) -5 = Below Expectations 0 = Met Expectations +5 = Above Expectations

18. Results - Experiment EVAL ID MISSTATE NO ID MISSTATE ABOVE MET

19. What About CONSULTATION as a SOLUTION? ID MISSTATE ABOVE EVAL MET

20. THE GOOD NEWS and the NEXT RESEARCH QUESTION

21. NFM Problems for OUTSIDERS  F/S comparative, NFM disclosures for CY only  NFM data scattered in 50-100 page 10-K  What specific NFMs should I look for? What are the benchmarks for my investment/client and industry?  So, using NFMs is too hard and too time consuming (5-6 hours to hand collect per company)  Only limited evidence, in very specific industries (pharma), of PROFESSIONAL investors using NFMs.  FINRA grants → Create a tool to solve problems based on research 21

22. 22

23. Sample from the Website DIFF = Change in Revenue - Average Change in NFMs

24. Sample from the Website DIFF = Change in Revenue - Average Change in NFMs

25. Sample from the Website DIFF = Change in Revenue - Average Change in NFMs

26. Sample from the Website DIFF = Change in Revenue - Average Change in NFMs

27. Sample from the Website DIFF = Change in Revenue - Average Change in NFMs

28. Sample from the Website DIFF = Change in Revenue - Average Change in NFMs

29. Sample from the Website DIFF = Change in Revenue - Average Change in NFMs

30. Thank you!!! Questions? Comments? ssrn.com jfbrazel@ncsu.edu 30