- 1. Using Data Analytics to Find and Deter Procure-to-Pay Fraud
October 30, 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 (now available on Apple
and Android devices) 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
EditionCopyright 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
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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
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by FraudResourceNet LLC Copyright 2013 FraudResourceNet LLC5 4.
Todays 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 P2PCopyright 2013
FraudResourceNet LLCAsset Misappropriation Tops The ChartsCopyright
2013 FraudResourceNet LLC 5. Vendor Billing Fraud/Corruption Is #1
or #2 No Matter Where You GoCopyright 2013 FraudResourceNet
LLC8Risk Assessment Departmental FocusCopyright 2013
FraudResourceNet LLC9 6. Top Fraud Schemes By DepartmentCopyright
2013 FraudResourceNet LLCPrimary Weaknesses Leading to the
FraudCopyright 2013 FraudResourceNet LLC11 7. Detection Methods By
Company SizeCopyright 2013 FraudResourceNet LLC12The Top Procedures
Per SAS 99 Appendix B1. 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 LLC13 8. Where Are You Using Data
Analytics?AuditNet 2012 Data Analysis Software SurveyCopyright 2013
FraudResourceNet LLCPolling Question 1What is not one of the top
occurring frauds per the ACFE study? A. B. C. D.Billing Corruption
Overstated Revenue Expense ReimbursementsCopyright 2013
FraudResourceNet LLC 9. Mapping Red Flags to AnalyticsCopyright
2013 FraudResourceNet LLCReport Brainstorm ToolCopyright 2013
FraudResourceNet LLC 10. 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
LLCVisualizing the Cost Recovery and Savings ProcessCopyright 2013
FraudResourceNet LLC 11. Profit Opportunities Outweigh Analytic
Costs Accounts Payable Audit Fee Benchmarking Advertising Agency
Document Fleet Freight Health Benefits Lease Media Order to Cash
ProactiveFraudDetection ProjectFraud RealEstateDepreciation
Sales&UseTax/VAT/R&D tax StrategicSourcing Telecom
TravelandEntertainment UtilitiesCopyright 2013 FraudResourceNet
LLCPage 20Process to Report MappingCopyright 2013 FraudResourceNet
LLC 12. Fraud Task to Report MappingCopyright 2013 FraudResourceNet
LLCFraud Task to Supplier MapCopyright 2013 FraudResourceNet LLC
13. Polling Question #2What are example cost recovery areas
associated with the P2P cycle? Freight Order to cash Healthcare
Accounts PayableCopyright 2013 FraudResourceNet LLCPage 24Using an
Analytic Process to Detect FraudCopyright 2013 FraudResourceNet LLC
14. Analytic Command Center Analytic Command CenterShared
ServicesData Mart1. Accounts Payable 2. Accounts Receivable 3.
Financial Statement 4. General Ledger 5. Inventory 6. Payroll 7.
RevenueCopyright 2013 FraudResourceNet LLCLocal Analytic
ToolkitRecovery AuditorsFeedback from all locationsThe 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 Benfords Law Statistical averages
and simple trending by day, month, day of week Post dated changes
Use Visualization TechniquesCopyright 2013 FraudResourceNet LLC2 6
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 reviewCopyright 2013 FraudResourceNet
LLCDistribution Analysis Remove subtotals for improved visibility
Focus on sole source and multi source vendors Scroll out and drill
to details as neededCopyright 2013 FraudResourceNet LLCPage 29 16.
Query ViewpointsCopyright 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 LLC31 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 originalCopyright 2013 FraudResourceNet LLCPage
32Some Data Mining Approaches 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 18.
Stratify Data - ResultsCopyright 2013 FraudResourceNet LLCPage 34Is
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 19. 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 20. Polling Question
3What is not one of the query viewpoints? A. B. C. D.Who What How
WhenCopyright 2013 FraudResourceNet LLCOther 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 LLC 21. Daily
Transactional AnalysisCopyright 2013 FraudResourceNet
LLC40GeoMapping - Map PointCopyright 2013 FraudResourceNet LLCPage
41 22. Charting the ScoreCopyright 2013 FraudResourceNet LLCScatter
GraphCopyright 2013 FraudResourceNet LLC 23. 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 LLCDashboarding
GraphingCopyright 2013 FraudResourceNet LLCPage 45 24. Polling
Question 4What graph is used to map value to score for easier
selections of data subsets? A. B. C. D.Pie Line Bar
ScatterCopyright 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
LLC50Summaries on Various PerspectivesSummarizeby dimensions(andsub
dimension)topinpoint withinthecubethe crossoverbetweenthetop
scoredlocation,time,and placeoffraudbasedon thecombinedjudgmental
andstatisticalscoreCopyright 2013 FraudResourceNet LLC51 27. Key
Control Reports & ScoringCopyright 2013 FraudResourceNet
LLCPage 52Combining the Scores ACL CodeCopyright 2013
FraudResourceNet LLCPage 53 28. Using Vlookup to Combine Scores
Create a record number Relate sheets based on VLookupCopyright 2013
FraudResourceNet LLCPage 54Polling Question #5What Excel function
is mainly used to organize the scores into a master score? SUMIF()
COUNTIF() RAND() VLOOKUP()Copyright 2013 FraudResourceNet LLCPage
55 29. Questions? Any Questions? Dont be Shy!Copyright 2013
FraudResourceNet LLCComing 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. 20Copyright 2013
FraudResourceNet LLC 30. Thank You! Website:
http://www.fraudresourcenet.com Jim Kaplan FraudResourceNet
800-385-1625 [email protected] Peter Goldmann
FraudResourceNet 800-440-2261 [email protected] Rich
Lanza Cash Recovery Partners, LLC Phone: 973-729-3944
[email protected] Copyright 2013 FraudResourceNet LLC
