Using Data Analytics to Find
and Deter Procure-to-Pay
Fraud
October 30, 2013
Special Guest Presenter:
Rich Lanza

Copyrigh...
About Jim Kaplan, MSc, CIA, CFE
President and Founder of
AuditNet®, the global resource
for auditors (now available on
Ap...
Webinar Housekeeping


This webinar and its material are the property of FraudResourceNet.
Unauthorized usage or recordin...
Today’s Agenda
 Who commits P2P fraud
 Red flags of fraud in procurement, receiving and payment
 Finding the red flags ...
Vendor Billing Fraud/Corruption
Is #1 or #2 No Matter Where You Go

Copyright © 2013 FraudResourceNet™ LLC

8

Risk Assess...
Top Fraud Schemes By
Department

Copyright © 2013 FraudResourceNet™ LLC

Primary Weaknesses Leading to
the Fraud

Copyrigh...
Detection Methods By
Company Size

Copyright © 2013 FraudResourceNet™ LLC

12

The Top Procedures
Per SAS 99 – Appendix B
...
Where Are You
Using Data Analytics?

AuditNet – 2012 Data Analysis
Software Survey

Copyright © 2013 FraudResourceNet™ LLC...
Mapping Red Flags to Analytics

Copyright © 2013 FraudResourceNet™ LLC

Report Brainstorm Tool

Copyright © 2013 FraudReso...
Proactively Detecting Fraud
Using Computer Audit Reports

IIA Research Paper / CPE
The purpose of this document is to assi...
Profit Opportunities Outweigh
Analytic Costs










Accounts Payable
Audit Fee Benchmarking
Advertising Agency...
Fraud Task to Report Mapping

Copyright © 2013 FraudResourceNet™ LLC

Fraud Task to Supplier Map

Copyright © 2013 FraudRe...
Polling Question #2

What are example cost recovery areas
associated with the P2P cycle?
 Freight
 Order to cash
 Healt...
Analytic Command Center
Analytic Command
Center

Shared Services

Data Mart

1. Accounts Payable
2. Accounts
Receivable
3....
Fraud Data Considerations for
the P2P Cycle
 A/P and G/L Review Factors
 Accounts that are sole sourced
 Accounts that ...
Query Viewpoints

Copyright © 2013 FraudResourceNet™ LLC

It’s The Trends….Right?







Trend categories (meals, ho...
Number Ranking
 Summarize each amount (Pivot or ACL)
 Rank each number in order of occurrence
 Score each item in a sli...
Stratify Data - Results

Copyright © 2013 FraudResourceNet™ LLC

Page 34

Is Your Organization Working
With Banned Compani...
Is Your Organization
Working With Terrorists?

Copyright © 2013 FraudResourceNet™ LLC

Are Your Vendors Real?
IRS TIN Matc...
Polling Question 3

What is not one of the query viewpoints?
A.
B.
C.
D.

Who
What
How
When

Copyright © 2013 FraudResourc...
Daily Transactional Analysis

Copyright © 2013 FraudResourceNet™ LLC

40

GeoMapping - Map Point

Copyright © 2013 FraudRe...
Charting the Score

Copyright © 2013 FraudResourceNet™ LLC

Scatter Graph

Copyright © 2013 FraudResourceNet™ LLC
Scatter Graph Explanation

1 – high dollar change and low count (outliers)
2 – charges that make sense
3 – changes that do...
Polling Question 4

What graph is used to map value to score
for easier selections of data subsets?
A.
B.
C.
D.

Pie
Line
...
Simple Fraud Vendor Scoring
Analysis – How It Started
 Vendors on report 1 vs. report 2 of duplicate payments.
 Duplicat...
Transactional Score Benefits


The best sample items (to meet your attributes) are selected based
on the severity given t...
Key Control Reports & Scoring

Copyright © 2013 FraudResourceNet™ LLC

Page 52

Combining the Scores
ACL Code

Copyright ©...
Using Vlookup to Combine
Scores

 Create a record number
 Relate sheets based on VLookup

Copyright © 2013 FraudResource...
Questions?
 Any Questions?
Don’t be Shy!

Copyright © 2013 FraudResourceNet™ LLC

Coming Up Next Month
 1. Detecting Fra...
Thank You!
Website: http://www.fraudresourcenet.com
Jim Kaplan
FraudResourceNet™
800-385-1625
jkaplan@fraudresourcenet.com...
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Using Data Analytics to Detect and Deter Procure to Pay Fraud

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Webinar series from FraudResourceNet LLC on Preventing and Detecting Fraud Using Data Analytics. Recordings of these Webinars are available for purchase from our Website fraudresourcenet.com
This Webinar focused on fraud detection using data analytic software (Excel, ACL, IDEA)
FraudResourceNet (FRN) is the only searchable portal of practical, expert fraud prevention, detection and audit information on the Web.
FRN combines the high quality, authoritative anti-fraud and audit content from the leading providers, AuditNet ® LLC and White-Collar Crime 101 LLC/FraudAware.
The two entities designed FRN as the “go-to”, easy-to-use source of “how-to” fraud prevention, detection, audit and investigation templates, guidelines, policies, training programs (recorded no CPE and live with CPE) and articles from leading subject matter experts.
FRN is a continuously expanding and improving resource, offering auditors, fraud examiners, controllers, investigators and accountants a content-rich source of cutting-edge anti-fraud tools and techniques they will want to refer to again and again.

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Using Data Analytics to Detect and Deter Procure to Pay Fraud

  1. 1. Using Data Analytics to Find and Deter Procure-to-Pay Fraud October 30, 2013 Special Guest Presenter: Rich Lanza Copyright © 2013 FraudResourceNet™ LLC About Peter Goldmann, MSc., CFE  President and Founder of White Collar Crime 101 Publisher 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. 2. About Jim Kaplan, MSc, CIA, CFE President and Founder of AuditNet®, the global resource for auditors (now available on Apple and Android devices) Auditor, Web Site Guru, Internet for Auditors Pioneer Recipient of the IIA’s 2007 Bradford Cadmus Memorial Award. Author of “The Auditor’s Guide to Internet Resources” 2nd Edition Copyright © 2013 FraudResourceNet™ LLC Richard 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. 3. Webinar Housekeeping  This webinar and its material are the property of FraudResourceNet. Unauthorized usage or recording of this webinar or any of its material is strictly forbidden. We are recording the webinar and you will be provided access to that recording within 5 business days after the webinar. Downloading or otherwise duplicating the webinar recording is expressly prohibited.  Please complete the evaluation questionnaire to help us continuously improve our Webinars.  You must answer the polling questions to qualify for CPE per NASBA.  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™ LLC Disclaimers  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™ LLC 5
  4. 4. Today’s Agenda  Who commits P2P fraud  Red flags of fraud in procurement, receiving and payment  Finding the red flags using data analytics tools  How to minimize risk of becoming a victim of P2P fraud  Best anti-fraud controls for P2P Copyright © 2013 FraudResourceNet™ LLC Asset Misappropriation Tops The Charts Copyright © 2013 FraudResourceNet™ LLC
  5. 5. Vendor Billing Fraud/Corruption Is #1 or #2 No Matter Where You Go Copyright © 2013 FraudResourceNet™ LLC 8 Risk Assessment Departmental Focus Copyright © 2013 FraudResourceNet™ LLC 9
  6. 6. Top Fraud Schemes By Department Copyright © 2013 FraudResourceNet™ LLC Primary Weaknesses Leading to the Fraud Copyright © 2013 FraudResourceNet™ LLC 11
  7. 7. Detection Methods By Company Size Copyright © 2013 FraudResourceNet™ LLC 12 The Top Procedures Per SAS 99 – Appendix B 1. 2. 3. 4. 5. Whistleblowing hotline Signed code of conduct Train employees Background checks Look for and respond to fraud Most companies have these procedures in place but the question is….how effective are they? Copyright © 2013 FraudResourceNet™ LLC 13
  8. 8. Where Are You Using Data Analytics? AuditNet – 2012 Data Analysis Software Survey Copyright © 2013 FraudResourceNet™ LLC Polling Question 1 What is not one of the top occurring frauds per the ACFE study? A. B. C. D. Billing Corruption Overstated Revenue Expense Reimbursements Copyright © 2013 FraudResourceNet™ LLC
  9. 9. Mapping Red Flags to Analytics Copyright © 2013 FraudResourceNet™ LLC Report Brainstorm Tool Copyright © 2013 FraudResourceNet™ LLC
  10. 10. Proactively Detecting Fraud Using Computer Audit Reports IIA 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 IIA’s website at www.theiia.org Copyright © 2013 FraudResourceNet™ LLC Visualizing the Cost Recovery and Savings Process Copyright © 2013 FraudResourceNet™ LLC
  11. 11. Profit Opportunities Outweigh Analytic Costs          Accounts Payable Audit Fee Benchmarking Advertising Agency Document Fleet Freight Health Benefits Lease Media Order to Cash         Proactive Fraud Detection Project Fraud Real Estate Depreciation Sales & Use Tax / VAT / R&D  tax Strategic Sourcing Telecom Travel and Entertainment Utilities Copyright © 2013 FraudResourceNet™ LLC Page 20 Process to Report Mapping Copyright © 2013 FraudResourceNet™ LLC
  12. 12. Fraud Task to Report Mapping Copyright © 2013 FraudResourceNet™ LLC Fraud Task to Supplier Map Copyright © 2013 FraudResourceNet™ LLC
  13. 13. Polling Question #2 What are example cost recovery areas associated with the P2P cycle?  Freight  Order to cash  Healthcare  Accounts Payable Copyright © 2013 FraudResourceNet™ LLC Page 24 Using an Analytic Process to Detect Fraud Copyright © 2013 FraudResourceNet™ LLC
  14. 14. Analytic Command Center Analytic Command Center Shared Services Data Mart 1. Accounts Payable 2. Accounts Receivable 3. Financial Statement 4. General Ledger 5. Inventory 6. Payroll 7. Revenue Copyright © 2013 FraudResourceNet™ LLC Local Analytic Toolkit Recovery Auditors Feedback from all locations The Overall Fraud Analytic Process  Get the Most Useful Data for Analysis  General Ledger / Accounts Payable  Other? / Use external data sources  Develop Fraud Query Viewpoints  The 5 Dimensions  Brainstorm report ideas  Analytically Trend  Benford’s Law  Statistical averages and simple trending by day, month, day of week  Post dated changes  Use Visualization Techniques Copyright © 2013 FraudResourceNet™ LLC 2 6
  15. 15. Fraud Data Considerations for the P2P Cycle  A/P and G/L Review Factors  Accounts that are sole sourced  Accounts that have too many vendors  Categories that map to the “recovery list”  Assess to industry cost category benchmarks  Top 100 vendors  Trend analysis over time  Trend analysis by vendor (scatter graph)  Purchase Order / Price List  Match to invoice payments to assess price differences  Strategic sourcing vendor review Copyright © 2013 FraudResourceNet™ LLC Distribution Analysis  Remove subtotals for improved visibility  Focus on sole source and multi source vendors  Scroll out and drill to details as needed Copyright © 2013 FraudResourceNet™ LLC Page 29
  16. 16. Query Viewpoints Copyright © 2013 FraudResourceNet™ LLC It’s 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™ LLC 31
  17. 17. Number Ranking  Summarize each amount (Pivot or ACL)  Rank each number in order of occurrence  Score each item in a sliding scale May be easiest to use a stratified score Decide if unique is weirder than non-unique  Relate this summarized list back to the original Copyright © 2013 FraudResourceNet™ LLC Page 32 Some Data Mining Approaches Personnel Analysis   Adjustments by employee Processing by employee Contextual Summarizations  Transaction types Time Trending    Month, week, and day / Also by department Last month to first 11 months Transactions at the end of and start of a fiscal year Copyright © 2013 FraudResourceNet™ LLC
  18. 18. Stratify Data - Results Copyright © 2013 FraudResourceNet™ LLC Page 34 Is 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.GOV Copyright © 2013 FraudResourceNet™ LLC
  19. 19. Is Your Organization Working With Terrorists? Copyright © 2013 FraudResourceNet™ LLC Are 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 box Copyright © 2013 FraudResourceNet™ LLC
  20. 20. Polling Question 3 What is not one of the query viewpoints? A. B. C. D. Who What How When Copyright © 2013 FraudResourceNet™ LLC 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 active Copyright © 2013 FraudResourceNet™ LLC
  21. 21. Daily Transactional Analysis Copyright © 2013 FraudResourceNet™ LLC 40 GeoMapping - Map Point Copyright © 2013 FraudResourceNet™ LLC Page 41
  22. 22. Charting the Score Copyright © 2013 FraudResourceNet™ LLC Scatter Graph Copyright © 2013 FraudResourceNet™ LLC
  23. 23. Scatter Graph Explanation 1 – high dollar change and low count (outliers) 2 – charges that make sense 3 – changes that don’t make sense 4 – inefficiency that is developing Copyright © 2013 FraudResourceNet™ LLC Dashboarding Graphing Copyright © 2013 FraudResourceNet™ LLC Page 45
  24. 24. Polling Question 4 What graph is used to map value to score for easier selections of data subsets? A. B. C. D. Pie Line Bar Scatter Copyright © 2013 FraudResourceNet™ LLC Copyright © 2013 FraudResourceNet™ LLC
  25. 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™ LLC 48 The 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™ LLC Page 49
  26. 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™ LLC 50 Summaries on Various Perspectives Summarize by  dimensions (and sub  dimension) to pinpoint  within the cube the  crossover between the top  scored location, time, and  place of fraud based on  the combined judgmental  and statistical score  Copyright © 2013 FraudResourceNet™ LLC 51
  27. 27. Key Control Reports & Scoring Copyright © 2013 FraudResourceNet™ LLC Page 52 Combining the Scores ACL Code Copyright © 2013 FraudResourceNet™ LLC Page 53
  28. 28. Using Vlookup to Combine Scores  Create a record number  Relate sheets based on VLookup Copyright © 2013 FraudResourceNet™ LLC Page 54 Polling Question #5 What Excel function is mainly used to organize the scores into a master score?  SUMIF()  COUNTIF()  RAND()  VLOOKUP() Copyright © 2013 FraudResourceNet™ LLC Page 55
  29. 29. Questions?  Any Questions? Don’t be Shy! Copyright © 2013 FraudResourceNet™ LLC Coming Up Next Month  1. Detecting Fraud in Key Accounts Using Data Analytics: Nov.12  2. Detecting and Preventing Management Override of Anti-Fraud Controls: Nov. 14  3. Using Data Analytics to Detect PCard Fraud: Nov. 20 Copyright © 2013 FraudResourceNet™ LLC
  30. 30. 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

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