1. Quick Response Fraud Detection using Data Analytics: Hitting the Ground Running using Technology in a Suspected Fraud Case July 31, 2013 Special Guest Presenter: Rich LanzaCopyright 2013 FraudResourceNet LLCAbout Peter Goldmann, MSc., CFEPresident and Founder of White Collar Crime 101Publisher of White-Collar Crime Fighter Developer of FraudAware Anti-Fraud Training Monthly Columnist, The Fraud Examiner, ACFE Newsletter Member of Editorial Advisory Board, ACFE Author of Fraud in the Markets Explains how fraud fueled the financial crisis.Copyright 2013 FraudResourceNet LLC

2. About Jim Kaplan, MSc, CIA, CFE President and Founder of AuditNet, the global resource for auditors Auditor, Web Site Guru, Internet for Auditors Pioneer Recipient of the IIAs 2007 Bradford Cadmus Memorial Award. Author of The Auditors Guide to Internet Resources 2nd Edition Copyright 2013 FraudResourceNet LLCRichard B. Lanza, CPA, CFE, CGMA Over two decades of ACL and Excel software usage Wrote the first practical ACL publication on how to use the product in 101 ways (101 ACL Applications) Has written and spoken on the use of audit data analytics for over 15 years. Received the Outstanding Achievement in Business Award by the Association of Certified Fraud Examiners for developing the publication Proactively Detecting Fraud Using Computer Audit Reports as a research project for the IIA Recently was a contributing author of: Global Technology Audit Guide (GTAG #13) Fraud in an Automated World - IIA Data Analytics A Practical Approach - research whitepaper for the Information System Accountability Control Association. Cost Recovery Turning Your Accounts Payable Department into a Profit Center Wiley & Sons. Please see full bio at www.richlanza.com Copyright 2013 FraudResourceNet LLC 3. Webinar Housekeeping This webinar and its material are the property of FraudResourceNet LLC. Unauthorized usage or recording of this webinar or any of its material is strictly forbidden. We will be recording the webinar and you will be provided access to that recording within five-seven business days. Downloading or otherwise duplicating the webinar recording is expressly prohibited.You must answer the polling questions to qualify for CPE per NASBA.Please complete the evaluation to help us continuously improve our Webinars.Submit questions via the chat box on your screen and we will answer them either during or at the conclusion.If GTW stops working you may need to close and restart. You can always dial in and listen and follow along with the handout. Copyright 2013 FraudResourceNet LLCDisclaimers The views expressed by the presenters do not necessarily represent the views, positions, or opinions of FraudResourceNet LLC (FRN) or the presenters respective organizations. These materials, and the oral presentation accompanying them, are for educational purposes only and do not constitute accounting or legal advice or create an accountant-client relationship. While FRN makes every effort to ensure information is accurate and complete, FRN makes no representations, guarantees, or warranties as to the accuracy or completeness of the information provided via this presentation. FRN specifically disclaims all liability for any claims or damages that may result from the information contained in this presentation, including any websites maintained by third parties and linked to the FRN website Any mention of commercial products is for information only; it does not imply recommendation or endorsement by FraudResourceNet LLC Copyright 2013 FraudResourceNet LLC5 4. Todays Agenda Which data files should be requested in the area of concern or what should the data request look like when there is no specific area of concern. Using a fast-track process to validating data and understanding statistical norms for benchmarking purposes. Statistical techniques to be utilized include: standard deviation, a unique method of combining Benfords Law and other digital analysis techniques, time/size stratifications, and value/volume difference scattergraphs. How the general ledger can provide a digital road map for analytics for fraud (and errors) within the organization. How to quickly gather report ideas and techniques for analysis, as well as, obtain a list of some of the top fraud tests by process area. (continued) Copyright 2013 FraudResourceNet LLCTodays Agenda (continued) How to combine your reports for maximum impact and understanding this concept within a specific review of accounts payable. Additional report techniques that can be applied to expected data files include user transaction analysis, data file change reviews, and external data mapping. Understand a provided Excel macro tool (free as part of the course) that will quickly map an entire hard drive in minutes. Various applications of this tool will be presented. Your Questions ConclusionCopyright 2013 FraudResourceNet LLC 5. The Overall Fraud Analytic Process Get the Most Useful Data for Analysis General Ledger / Accounts Payable Other? / Use external data sourcesDevelop Fraud Query Viewpoints The 5 Dimensions Brainstorm report ideasAnalytically Trend Benfords Law Statistical averages and simple trending by day, month, day of week Post dated changesTransactional Score Based On the AboveCopyright 2013 FraudResourceNet LLCDetection Methods By Company SizeCopyright 2013 FraudResourceNet LLC9 6. Most Popular Products Microsoft Excel ActiveData for Excel TopCaats Microsoft Access ACL IDEA WizRule, WizWhy, & WizSame (WizSoft products)Copyright 2013 FraudResourceNet LLCTool Selection Considerations Core processing features Advanced features Advanced data import Scripting Ease of use Training / Customer Support / User Groups Years in business / Company sustainability Workpaper system integrationCopyright 2013 FraudResourceNet LLC 7. Asset Misappropriation Tops The ChartsCopyright 2013 FraudResourceNet LLCVendor Billing Fraud/Corruption Is #1 or #2 No Matter Where You GoCopyright 2013 FraudResourceNet LLC13 8. Mapping Data to ScriptsCopyright 2013 FraudResourceNet LLCPage 14Clear Data Request Accounts Payable Data Request.doc Copyright 2013 FraudResourceNet LLC 9. Sample Data Validation Accounts Payable Other QuestionsCopyright 2013 FraudResourceNet LLCIs Your Organization Working With Banned Companies?EPLS is the excluded party list service of the U.S. Government as maintained by the GSA WWW.SAM.GOVCopyright 2013 FraudResourceNet LLC 10. Is Your Organization Working With Terrorists?Copyright 2013 FraudResourceNet LLCAre Your Vendors Real? IRS TIN Matching Program Validates U.S. Tax Identification Numbers Can submit up to 100,000 TIN submissions at a time Make sure all punctuation is removed See http://www.irs.gov/taxpros/ and enter TIN matching program in the search boxCopyright 2013 FraudResourceNet LLC 11. Polling Question 1 What is the new name of the EPLS.gov system A. B. C. D.GAO.GOV SAM.GOV OFAC.GOV TREASURY.US.GOVCopyright 2013 FraudResourceNet LLCQuery ViewpointsCopyright 2013 FraudResourceNet LLC 12. Specific Tests Based on the 5 Ws Who Summarize journal entries by the persons entering to determine if theyre authorized. What Summarize journal entries by account and repetitive extracts (more than 50 instances) and unique account sequences used in the journal entry (based on the first five debit and credit postings). Extract nonstandard or manual journal entries (versus a created system such as an accounts payable ledger posting) for further analysis. Stratify size of journal entries based on amount (using the debit side of the transaction). Summarize general ledger activity on the amount field (absolute value of debit or credit) to identify the top occurring amounts. Then summarize activity by account and the amount identified for the top 25 appearing amounts. Scatter-graph general ledger account (debit and credit amounts separately) and numbers of transactions. Copyright 2013 FraudResourceNet LLCPage 22Specific Tests Based on the 5 Ws (Continued) When Extract journal entries posted on weekends and holidays. Extract journal entries relating to the prior year that were made just immediately following a fiscal-year end. Summarize journal entry credits and debits processing by day, month, and year. Where Extract journal entries made to suspense accounts and summarize by the person entering and corresponding account numbers. Extract journal entries to general ledger accounts known to be problems or complex based on past issues (errors of accounting in journal subsequently corrected by accounting staff or auditors) at the company or the industry in general. Extract debits in revenue and summarize by general ledger account. Summarize journal entries by the persons entering to determine if theyre authorized. Copyright 2013 FraudResourceNet LLCPage 23 13. Specific Tests Based on the 5 Ws (Continued) Why Extract general ledger transaction amounts (debit or credit) that exceed the average amounts for that general ledger account by a specified percentage. (Five times the average is the default.) Extract journal entries that equate to round multiples of 10,000, 100,000, and 1,000,000. Extract journal entries with key texts such as plug and net to zero anywhere in the record. Extract journal entries that are made below set accounting department approval limits especially multiple entries of amounts below such limits. Extract journal entries that dont net to zero (debits less credits). Copyright 2013 FraudResourceNet LLCReport Brainstorm ToolCopyright 2013 FraudResourceNet LLC 14. Proactively Detecting Fraud Using Computer Audit ReportsIIA Research Paper / CPE The purpose of this document is to assist Course auditors, fraud examiners, and management in implementing data analysis routines for improved fraud prevention and detection.A comprehensive checklist of data analysis reports that are associated with each occupational fraud category per the Association of Certified Fraud Examiners classification system.See the IIAs website at www.theiia.org Copyright 2013 FraudResourceNet LLCPayroll Fraud Report IdeasCopyright 2013 FraudResourceNet LLC 15. Top Reports in Payroll Duplicate employee payments Payments to the same bank account and a different employee number Overtime trending by department and person (% of overtime to gross pay, average overtime by department) Match employee data from the human resource to the payroll system Look for inaccurate or incomplete employee dataCopyright 2013 FraudResourceNet LLCIts The Trends.Right? Trend categories (meals, hotel, airfare, other) Trend by person and title Trend departments Trend vendors Trend in the type of receipts Trend under limits (company policy)Copyright 2013 FraudResourceNet LLC29 16. Other T&E Reports Unmatched query of cardholders to an active employee masterfile Cards used in multiple states (more than 2) in the same day Cards processing in multiple currencies (more than 2) in the same day Identify cards that have not had activity in the last six months Cardholders that have more than one card Extract any cash back credits processed through the card Extract declined card transactions and determine if they are frequent for certain cards Summary of card usage by merchant to find newly added merchants and most activeCopyright 2013 FraudResourceNet LLCSome Data Mining Ideas Personnel Analysis Adjustments by employee Processing by employeeContextual Summarizations Transaction typesTime Trending Month, week, and day / Also by department Last month to first 11 months Transactions at the end of and start of a fiscal yearCopyright 2013 FraudResourceNet LLC 17. Polling Question 2What is not one of the query viewpoints? A. B. C. D.Who What How WhenCopyright 2013 FraudResourceNet LLCAdding the Analysis Toolpak Add-InCopyright 2013 FraudResourceNet LLC 18. Above Average / Standard DeviationCopyright 2013 FraudResourceNet LLCStratify Data in Excel or with ActiveData for ExcelTM Use Excel Vlookup = TRUE Use ActiveData for ExcelTMCopyright 2013 FraudResourceNet LLC 19. How Fraud Grows Over TimeCopyright 2013 FraudResourceNet LLC36Scatter GraphCopyright 2013 FraudResourceNet LLC 20. Scatter Graph Explanation1 high dollar change and low count (outliers) 2 charges that make sense 3 changes that dont make sense 4 inefficiency that is developingCopyright 2013 FraudResourceNet LLCPolling Question 3Where do you find the Descriptive Statistics in Excel? A. B. C. D.Excel Option Data Menu Excel Add-Ins Insert MenuCopyright 2013 FraudResourceNet LLC 21. Benfords Law Scoring Creating the First, First 2, Last 2, and Difference to Last YearCopyright 2013 FraudResourceNet LLCCalculating BenfordsCopyright 2013 FraudResourceNet LLC 22. The Scoring Calculation SheetCopyright 2013 FraudResourceNet LLCPolling Question 4What Excel function is used to copy scores from the score sheet to the score summary sheet? A. B. C. D.GRAB() HLOOKUP() HYPERLINK() VLOOKUP()Copyright 2013 FraudResourceNet LLC 23. Unique Journal Entry Test Account SequencingCopyright 2013 FraudResourceNet LLCTop Fraud Schemes By DepartmentCopyright 2013 FraudResourceNet LLC 24. Polling Question 5 What ActiveData for Excel function allows for the development of the account sequence: A. B. C. D.Summarize Stratify Merge Top / Bottom ItemsCopyright 2013 FraudResourceNet LLCCopyright 2013 FraudResourceNet LLC 25. Simple Fraud Vendor Scoring Analysis How It Started Vendors on report 1 vs. report 2 of duplicate payments. Duplicate transactions paid on different checks. Duplicate transactions with debit amounts in the vendor account. Vendors with a high proportion of round dollar payments. Invoices that are exactly 10x, 100x or 1000x larger than another invoice. Payments to any vendor that exceed the twelve month average payments to that vendor by a specified percentage (i.e., 200%) or 3x the standard deviation for that vendor. Vendors paid with a high proportion of manual checks. Copyright 2013 FraudResourceNet LLC48The Sampling Problem Bottom Line Numbers Modern tests (round numbers, duplicates, missing fields) identify thousands of suspicious transactions, usually about 1 in 5 of all transactions get a red flag Historically at least 0.02 0.03 % of all transactions have real problems, such as a recoverable over-payment So roughly 0.00025 / 0.2 = 0.00125 or 1 in 800 red flags lead to a real problem.Imagine throwing a random dart at 800 balloons hoping to hit the right one!!! Copyright 2013 FraudResourceNet LLCPage 49 26. Transactional Score Benefits The best sample items (to meet your attributes) are selected based on the severity given to each attribute. In other words, errors, as you define them, can be mathematically calculated.Instead of selecting samples from reports, transactions that meet multiple report attributes are selected (kill more birds with one stone). Therefore a 50 unit sample can efficiently audit: 38 duplicate payments 22 round invoices 18 in sequence invoices.and they are the best given they are mathematically the most severe. Copyright 2013 FraudResourceNet LLC50Pick Items Rare in Several Ways Dont choose just ANY weekend invoice Choose an UNUSUAL weekend invoice Large weekend invoices are the rarest kind (i.e., only 2 percent of large invoices) The odds of finding a recoverable error go up AND since the invoice is large, the value recovered goes up too! Copyright 2013 FraudResourceNet LLCPage 51 27. Transactional ScoringThe result is a sampling methodology that is now based on Risk as you defineCopyright 2013 FraudResourceNet LLCPage 52Summaries on Various PerspectivesSummarizeby dimensions(andsub dimension)topinpoint withinthecubethe crossoverbetweenthetop scoredlocation,time,and placeoffraudbasedon thecombinedjudgmental andstatisticalscoreCopyright 2013 FraudResourceNet LLC53 28. Key Control Reports & ScoringCopyright 2013 FraudResourceNet LLCPage 54Combining the Scores ACL CodeCopyright 2013 FraudResourceNet LLCPage 55 29. Using Vlookup to Combine Scores Create a record number Relate sheets based on VLookupCopyright 2013 FraudResourceNet LLCPage 56Severity To ValueCopyright 2013 FraudResourceNet LLC57 30. Transactional Score Benefit Patterns ExampleCopyright 2013 FraudResourceNet LLC58GeoMapping - Map PointCopyright 2013 FraudResourceNet LLCPage 59 31. Polling Question 6What graph is used to map value to score for easier selections of data subsets? A. B. C. D.Pie Line Bar ScatterCopyright 2013 FraudResourceNet LLCFree Excel Directory Tool Collects all file information by folder Provides additional information on the files Be careful Can take 30 minutes to run an entire harddrive Useful to identify files accessed recently Great for backups and cleanups of HDsCopyright 2013 FraudResourceNet LLC 32. Questions? Any Questions? Dont be Shy!Copyright 2013 FraudResourceNet LLCComing Up Next Month 1. Benfords Law on August 7, 2013 11:00 AM 2. When Law Enforcement Comes Knocking on August 14, 2013 1:00 PM 3. Best Practices in Detecting Accounts Payable Fraud Using Data Analysis on August 21, 2013 11:00 AMCopyright 2013 FraudResourceNet LLC 33. Thank You! Website: http://www.fraudresourcenet.com Jim Kaplan FraudResourceNet 800-385-1625 jkaplan@fraudresourcenet.com Peter Goldmann FraudResourceNet 800-440-2261 pgoldmann@fraudresourcenet.com Rich Lanza Cash Recovery Partners, LLC Phone: 973-729-3944 rich@richlanza.com Copyright 2013 FraudResourceNet LLC