Analyzing a Potpourri of Fraud in Higher Education. Calvin Wendelboe, CPA, CIA, CFE

Transcription

1 Analyzing a Potpourri of Fraud in Higher Education Calvin Wendelboe, CPA, CIA, CFE

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3 Green Dot Bank

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5 Participating with Poll Everywhere Web Voting PollEv.com/ACUA Text Voting ACUA

6 Scheme #1 Asset Misappropriation

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8 Three Distribution Channels for Stolen Property Using of two different ebay accounts

9 How was the scheme detected?

10 #2 Billing Scheme

11 STUDENT $1,000 $600 University $100 $700 1 RCM (Fraudulent Intermediary) 3 Account Assignment ($600 X 167% = $1,000) COLLECTION AGENCIES 1) University turns over student receivable ($600) to collection agency for collection. 2) Student pays collection agency amount due ($600) plus 67% collection "fee" ($400). 3) Agency remits to University amount collected ($1,000) less the agency 30% commission ($300). 4) University credits student receivable for the amount due ($600) and remits to RCM their "share" of the proceeds ($100). $300

12 Phase 1 - $21,000 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7

13 STUDENT $1,000 $600 $5,000 University $100 $5,100 $700 1 RCM (Fraudulent Intermediary) 3 Account Assignment ($600 X 167% = $1,000) COLLECTION AGENCIES 1) University turns over student receivable ($600) to collection agency for collection. 2) Student pays collection agency amount due ($600) plus 67% collection "fee" ($400). 3) Agency remits to University amount collected ($1,000) less the agency 30% commission ($300). 4) BYU credits student receivable for the amount due ($600) and remits to RCM their "share" of the proceeds ($100) Plus $5,000 Extra. $300

14 Student Account properly applied ($600). However, collection agency account is debited for an unsupported amount resulting in a large payment to RCM and a receivable from the collection agency. The University had 22 collection agency accounts each with an average receivable balance of $6,000.

15 Phase 1 - $21,000 Phase 2 - $154,000 ($16K + $138K) Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7

16 Change - journal entries require additional authorizations. Subject simply prepares check requests for payments to RCM (fraudulent intermediary). Growing unreconciled balance in refund clearing account precipitates an investigation.

17 $5,000 University $5,000 RCM (Fraudulent Intermediary) 4) University remits to RCM payments $5,000.

18 Phase 1 - $21,000 Phase 2 - $154,000 ($16K + $138K) Phase 3 - $131,000 Year 1 Year 2 Year 3 Year 4 Year 5 Year 6 Year 7 Total Fraud $306,000

19 How was the Scheme Detected?

20 #3. P-Card and Inventory Conversion

21 #3. P-Card and Inventory Conversion Certain items purchased on the P-card were still in his possession. Items were sold via ebay to help offset the restitution amount. Auctioned Items generated over $5,500.

22 The Charges

23 The Sentence

24 How was this scheme detected?

25 Occupational Fraud The World

26 Number of Cases Used in Report to the Nations

27 Estimated Loss of Revenue to Fraud Year Percent Loss % % % % % % % % % Avg. 6% Over the last 20 years the average estimated loss for fraud has been 6% of revenues 2008 Recession

28 Median Loss for Each Fraud *Median loss figures taken from report of Asset Misappropriation cases all of which account for more than 85% of total cases in the study

29 Detection Methods

30 Tip Internal Audit Management Review By Accident Account Reconciliation Other Document Examination External Audit Notified by Law Enforcement Surveillance/Monitoring IT Controls Confession Detection of Fraud Schemes 0 % 0.5% 1.1% 5.5% 6.6% 4.8% 3.8% 4.2 % 3.8% 3.0% 4.1% 3.3% 2.4% 2.2% 3.0% 1. 9% 1 2.6%.9% 1.3% 1.1% 1.1% 1.3% 0.8% 1.5% 5.6% 6.8% 7.0% 5.5% 5% 10 % As in previous years, tips were the most common detection method by a wide margin, accounting for 39.1% of cases. In the 2016 data, internal audit (16.5%) edged out management review (13.4%) as the second-most common detection method. 16.5% 14.1% 14.4% 13.4% 16.0% 14.6% 15 % 35 % 40 % 42.2% 43.3% 45 % 50 %

31 Schemes by Industry 2012

32 Industry/ Scheme Banking and Financial Services Government and Public Administration Schemes by Industry 2014 Manufacturing Health Care Education Retail Insurance Oil & Gas Services (Other) Construction Religious, Charitable or Social Services Cases Transportation and Warehousing Billing 5.7% 19.1% 22.4% 29.0% 33.8% 10.4% 17.7% 24.5% 28.9% 34.9% 32.5% 33.3% Cash Larceny 13.1% 10.6% 6.0% 12.0% 6.3% 15.6% 6.5% 2.0% 11.1% 14.0% 7.5% 2.1% Cash on Hand 18.9% 12.1% 7.8% 16.0% 16.3% 22.1% 1.6% 2.0% 11.1% 7.0% 12.5% 10.4% Check Tampering 5.7% 5.7% 7.8% 21.0% 10.0% 7.8% 4.8% 4.1% 17.8% 27.9% 35.0% 20.8% Corruption 37.3% 36.2% 54.3% 37.0% 36.3% 22.1% 33.9% 57.1% 35.6% 46.5% 30.0% 29.2% Expense Reimbursements Financial Statement Fraud 4.1% 12.8% 7.8% 23.0% 31.3% 3.9% 4.8% 14.3% 17.8% 27.9% 32.5% 14.6% 10.2% 5.0% 13.8% 8.0% 10.0% 6.5% 3.2% 12.2% 6.7% 11.6% 7.5% 10.4% Non-Cash 13.1% 17.7% 34.5% 12.0% 12.5% 33.8% 12.9% 16.3% 17.8% 20.9% 15.0% 33.3% Payroll 5.3% 15.6% 8.6% 15.0% 16.3% 5.2% 8.1% 6.1% 6.7% 18.6% 20.0% 16.7% Register Disbursements 2.5% 0.7% 2.6% 3.0% 5.0% 13.0% 0.0% 0.0% 6.7% 2.3% 2.5% 4.2% Skimming 5.7% 11.3% 4.3% 18.0% 20.0% 18.2% 22.6% 2.0% 33.3% 7.0% 12.5% 6.3% Graphic adapted from the 2014 Report to the Nations

33 Industry/ Scheme Banking and Financial Services Schemes by Industry 2016 Government and Public Administratio n Manufacturing Health Oil & Education Retail Insurance Care Gas Services (Other) Construction Religious, Charitable, Telecommu or Social nications Services Transportation Services (Professional) Technology and Warehousing Cases Billing 9.5% 25.3% 32.8% 31.3% 34.1% 15.4% 17.6% 20.3% 22.9% 27.9% 25.0% 12.9% 26.7% 29.7% 22.1% Cash Larceny 11.1% 7.9% 5.2% 9.7% 13.6% 12.5% 4.7% 4.1% 15.7% 8.1% 9.6% 1.6% 13.3% 5.4% 4.4% Cash on Hand 17.9% 10.5% 8.3% 11.1% 17.4% 11.5% 4.7% 9.5% 22.9% 7.0% 13.5% 4.8% 20.0% 8.1% 5.9% Check Tampering 9.5% 9.2% 13.5% 14.6% 7.6% 9.6% 17.6% 4.1% 18.6% 10.5% 25.0% 6.5% 31.7% 5.4% 10.3% Corruption 37.5% 38.4% 48.4% 30.6% 31.8% 32.7% 28.2% 48.6% 28.6% 36.0% 28.8% 41.9% 16.7% 44.6% 51.5% Expense Reimbursemen ts Financial Statement Fraud 5.4% 15.7% 22.9% 20.1% 15.9% 8.7% 9.4% 10.8% 12.9% 20.9% 25.0% 19.4% 16.7% 27.0% 8.8% 12.0% 7.9% 10.9% 13.2% 5.3% 5.8% 7.1% 6.8% 17.1% 17.4% 3.8% 9.7% 11.7% 12.2% 5.9% Non-Cash 10.6% 14.8% 30.2% 13.2% 17.4% 32.7% 5.9% 17.6% 22.9% 22.1% 13.5% 38.7% 10.0% 18.9% 29.4% Payroll 3.8% 13.5% 11.5% 9.7% 7.6% 3.8% 5.9% 8.1% 11.4% 16.3% 13.5% 3.2% 11.7% 2.7% 7.4% Register Disbursements 2.7% 1.7% 5.7% 2.1% 1.5% 8.7% 0.0% 0.0% 5.7% 1.2% 1.9% 3.2% 1.7% 1.4% 2.9% Skimming 6.8% 14.0% 8.3% 12.5% 25.0% 17.3% 10.6% 8.1% 21.4% 15.1% 19.2% 6.5% 18.3% 5.4% 11.8% Graphic adapted from the 2016 Report to the Nations

34 Direct Contributors to Fraud CONTROL WEAKNESSES IN ORGANIZATIONS OFTEN DIRECTLY CONTRIBUTE TO FRAUD. Top 3 control weaknesses that contributed to fraud 29% 20% 19% LACK OF INTERNAL CONTROLS OVERRIDE OF EXISTING INTERNAL CONTROLS LACK OF MANAGEMENT REVIEW Graphic adapted from the 2016 Report to the Nations

35 Perpetrators: Criminal Record THE VAST MAJORITY OF OCCUPATIONAL FRAUDSTERS ARE FIRST-TIME OFFENDERS. among perpetrators in our study, only 5 % 8% were convicted of a prior fraudrelated offense were fired for fraud-related conduct by a previous employer Graphic adapted from the 2016 Report to the Nations

36 2012: Anti-Fraud Controls

37 2014: Anti-Fraud Controls

38 2016: Anti-Fraud Controls

39 2016: Anti-Fraud Controls

40 Fraud Risk Assessment Tool A fraud risk assessment expands upon traditional risk assessment. It is scheme and scenario based rather than based on control risk or inherent risk.

41 Why Conduct a Fraud Risk Assessment?

42 COSO 2013

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44 ACFE Fraud Risk Assessment Tool

45 Fraud is Happening! Its not only in the news, but likely happening at your institution. Are you preventing it through ensuring basic internal controls are in place and functioning properly? Are you finding fraud? Can you implement data analytics to help identify fraud? Have you implemented a formal fraud risk assessment?

46 Questions?