2. Unemployment Insurance Integrity Conference April 19, 2010 Forensic Techniques And Automated Oversight Brett Baker, PhD, CPA, CISA

3. 2 Overview Forensic Techniques and Automated Oversight Data Mining Techniques Equipment and Software Forensic Approach Brett M. Baker, PhD, CPA, CISA

4. 3 Forensic Techniques and Automated Oversight Definition of Forensic Audit –Audit that specifically looks for financial misconduct, abusive or wasteful activity. –Close coordination with investigators –More than Computer Assisted Audit Techniques (CAATs) Forensic audit is growing in the Federal government –GAO’s Forensic Audit and Special Investigations (FSI) –Department of Defense Data Mining Federal outlays are $2 trillion annually –OMB estimates improper payments for Federal government at $98B (4%) 100% review using automated business rules versus statistical sampling –There is a place for both Automated Oversight –Continuous monitoring –Quick response Brett M. Baker, PhD, CPA, CISA

5. FY2008 Improper Payment Estimates Brett M. Baker, PhD, CPA, CISA

6. 5 What is Data Mining? Refers to the use of machine learning and statistical analysis for the purpose of finding patterns in data sets. –If You Know Exactly What You Are Looking for, Use Structured Query Language (SQL). –If You Know Only Vaguely What You Are Looking for, Turn to Data Mining. Most often used (up until recently) in marketing and customer analysis Brett M. Baker, PhD, CPA, CISA

7. 6 Different Levels of Knowledge Information Summary Reports Knowledge Descriptive Analytics Wisdom Predictive Analytics Data Facts, numbers ACL, IDEA, MS Access SAS, SPSS, ACL, IDEA Clementine Intelligent Miner Enterprise Miner Brett M. Baker, PhD, CPA, CISA

8. 7 Can perform the tests wanted, instead of being limited to what technical staff can, or will, provide Not limited to just predetermined data formats and/or relationships Can create relationships, check calculations and perform comparisons Can examine all records, not just a sample Useful for identifying misappropriation of assets and fraudulent financial reporting Allows limitless number of analytical relationships to be assessed –within large databases –comparing large databases Identifies anomalies Data Analysis Software - Fosters Creativity Brett M. Baker, PhD, CPA, CISA

9. 8 Common Data Analysis Tests and Techniques Join Summarization Corrupt data (conversion) Blank fields (noteworthy if field is mandatory) Invalid dates Bounds testing Completeness Uniqueness Invalid codes Unreliable computed fields Illogical field relationships Trend analysis Duplicates Brett M. Baker, PhD, CPA, CISA

10. 99 Use Tight Selection Criteria –E.g. Vendor = “ Smith Company ” Use Looser Selection Criteria –E.g. Vendor = “ *Smith* ” Finds Smith Company, Smith Co., The Smith Manufacturing Company, etc. You Know Exactly What You’re Looking For e.g. All Payments to a Particular Vendor Simple Queries

11. 10 Use Tight Selection Criteria –E.g. Payments With Same Contract #, Invoice # and Invoice Amount –Few False Positives Use Looser Selection Criteria –E.g. Payments With Same Contract # and Invoice # or Same Contract # and Invoice Amount –More False Positives –More Detected Duplicates You Know The Specific Condition You’re Looking For e.g. Duplicate Payments Complex Queries

12. 11 Subject Matter Experts Can Describe Indicators –Translate Indicators to Detection Logic Apply Indicators Against Population –Many False Positives Combine Indicators –Reduce False Positives You Only Know The General Condition You’re Looking For e.g. Fraud Sophisticated Solutions 1 5 7 2 8 4 12 15 3 Combine Indicators

13. Control Charts Brett M. Baker, PhD, CPA, CISA

14. Normal ActivityAnomalous Activity Anomalous Activity Frequency Distribution Brett M. Baker, PhD, CPA, CISA

15. Disbursing Transactions Vendor Table Vendors Not Paid Yet Vendors Paid and In Vendor Table Vendors Paid but not In Vendor Table Comparing Data Files (Three-Bucket Theory) Brett M. Baker, PhD, CPA, CISA

16. 15 Hardware and Software Applications Hardware –SQL servers –Mainframe (QMF) –Docking stations –Terminal server Software Applications –Data mining and predictive analytics, e.g., Clementine –Data interrogation – e.g., ACL, IDEA, MS Access, Excel –Statistical analysis – e.g., SPSS and SAS –Link analysis – I2 –Lexis-Nexis –Data conversion utilities (Monarch) –Internet, open-source research –Access to system query tools Brett M. Baker, PhD, CPA, CISA

17. 16 Forensic Approach Start with objectives Structured brainstorming –Consider SME conference –Identify indicators of potential fraud and ways to find in data –Process to identify financial risks Map out the end-to-end process –Identify systems and key processes –Identify key controls Identify and obtain transaction-level data –Record layout –Look at 1000 records before examining all records –ACL, IDEA, and Monarch can read virtually any data format Flat files, Delimited files, Dbase files, MS Access, Report files, …. No file size limits Build targeted business rules and run against data Examine anomalies Brett M. Baker, PhD, CPA, CISA

18. 17 End-to-End Payment Universe Forensic Audit Approach Accounting Systems Federal Reserve System Commercial Pay Entitlement Systems Disbursing Systems People Pay Entitlement Systems Personnel Systems Commercial Bank $$ Treasury Check Contracting Systems Data Analysis Central Contractor Registry Brett M. Baker, PhD, CPA, CISA

19. Unemployment Benefits Employment Over-payments Under-payments Unemployment Insurance

21. 20 How To Apply In Your Organization Decide What You Are Looking For Assign Personnel With Analytical Skills Gather Data Understand Data and Business Rules Select Detection Method/Tools Produce and Research Anomalies Refine the Detection Process Discover the Irregular/Illegal Transactions Improve the Business Process –Automated oversight –Continuous monitoring