Anomaly Detection Petty

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a process I invented years ago I share with everyone

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Anomaly Detection Petty

  1. 1. Vendor Anomaly Detection Todd E. Petty 312.961.0111 Divine © 2002 Deloitte & Touche LLP. All rights reserved .
  2. 2. A/P Fraud – Easily Concealed <ul><li>Complex structure of large businesses makes fraud detection difficult. </li></ul><ul><ul><li>Median loss due to accounts payable fraud is $250,000 </li></ul></ul><ul><ul><ul><li>Source: Association of Certified Fraud Examiners </li></ul></ul></ul><ul><li>How can fraud be found in massive amounts of data? </li></ul><ul><ul><li>One company’s A/P profile </li></ul></ul><ul><ul><ul><li>30,000 vendors </li></ul></ul></ul><ul><ul><ul><li>Three million annual disbursement transactions @ $650 average per transaction </li></ul></ul></ul><ul><ul><ul><li>$2 BILLION in annual vendor disbursements </li></ul></ul></ul><ul><li>How many vendors does your company really have? </li></ul><ul><ul><li>Is “IEE, Inc.” the same vendor as “I2E, Incorporated”? </li></ul></ul><ul><ul><ul><li>Inaccurate/sloppy data makes fraud easy to conceal </li></ul></ul></ul><ul><ul><ul><li>Vendor consolidation saves money </li></ul></ul></ul>
  3. 3. Economics of Fraud ABC Company Revenue - $10 million Profit margin – 10%
  4. 4. Anomaly Detection – Benefits <ul><li>Identifies fraud </li></ul><ul><ul><li>Ghost vendors, ghost employees, employees as vendors, fraudulent invoices, etc. </li></ul></ul><ul><ul><ul><li>Divine Security has identified fraud and duplicate payments in 100% of anomaly detection engagements. </li></ul></ul></ul><ul><ul><ul><li>Uncover fraud before the costs reach damaging proportions. </li></ul></ul></ul><ul><li>Saves money </li></ul><ul><ul><li>Identify vendor relationships </li></ul></ul><ul><ul><ul><li>Larger discounts through volume purchases </li></ul></ul></ul><ul><ul><li>Duplicate payments, overpayments, chargebacks, etc. </li></ul></ul><ul><ul><ul><li>More than 90% of our clients have been able to cover our fees with just the duplicate payments we identified. </li></ul></ul></ul><ul><li>Identifies management control issues </li></ul><ul><ul><li>Inactive suppliers, low value invoices, multiple accounts for supplier, incomplete/inaccurate records </li></ul></ul>
  5. 5. Anomaly Detection – Approach <ul><li>Normalize and analyze internal company data </li></ul><ul><ul><li>Vendor; accounts payable </li></ul></ul><ul><li>Test it (using up to 100 Divine profiles) against </li></ul><ul><ul><li>Selected internal data </li></ul></ul><ul><ul><ul><li>Human resource; payroll </li></ul></ul></ul><ul><ul><li>Selected external data </li></ul></ul><ul><ul><ul><li>Social Security Number </li></ul></ul></ul><ul><ul><ul><li>Corporate Records </li></ul></ul></ul><ul><ul><ul><li>Dun & Bradstreet </li></ul></ul></ul><ul><li>Identify anomalies that may be indicative of fraud </li></ul><ul><ul><li>Vendor phone number matches employee phone number </li></ul></ul><ul><ul><li>Vendor bank/account # matches employee bank/account # </li></ul></ul><ul><ul><li>Employee name matches vendor officer / director name </li></ul></ul><ul><ul><li>Employee SSN matches SSA paid death claim </li></ul></ul><ul><ul><li>Vendor address matches prison address </li></ul></ul>
  6. 6. Process Overview - Functional Raw Internal Data Normalization Normalized Internal Data Profiles/Queries Anomalies Fraud Processed Result Create Use Profiles to Test Against External Data Internal Data Other Tests
  7. 7. Examples of A/P Anomalies <ul><li>Vendor direct deposit disbursements and payroll direct deposit to same bank and bank account </li></ul><ul><li>Invoices with multiple purchase orders </li></ul><ul><li>Multiple purchase orders issued on the same day </li></ul><ul><li>Check amounts greater than purchase order amounts </li></ul><ul><li>Invoices with multiple checks issued </li></ul><ul><li>Ghost vendors </li></ul><ul><li>Employees as vendors </li></ul><ul><li>Ghost employees </li></ul><ul><li>Invoices with no purchase orders ( see next page) </li></ul>
  8. 8. Questionable Payments? Invoices With No Supporting PO This section reflects INVOICES without any related POs POs INVOICES VENDOR
  9. 9. Anomaly Detection - Deliverables <ul><li>Prioritized list of “hits” </li></ul><ul><ul><li>Ranked by anomaly risk score </li></ul></ul><ul><li>A summary of conflicts </li></ul><ul><ul><li>Between data on different systems or from different sources </li></ul></ul><ul><li>Identification of primary fraud risks </li></ul><ul><ul><li>See next page </li></ul></ul>
  10. 10. Primary Fraud Risks
  11. 11. Benford’s Law
  12. 12. Employee Fraud
  13. 13. Employee Fraud
  14. 14. Employee Fraud
  15. 15. Employee Fraud
  16. 16. For more information, contact: <ul><li>Todd E. Petty </li></ul><ul><li>Divine Security and Business Integrity Services </li></ul><ul><li>Forensic and Investigative Services </li></ul><ul><li>312.961.0111 </li></ul><ul><li>E-mail: todd.petty@divine.com </li></ul><ul><li>  </li></ul>

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