Super-Data-Charging Your Corruption Reviews With Integrated Analytics - It comes as no surprise that the Association of Certified Fraud Examiners fraud surveys over the past 10 years identify corruption as the most frequently occurring fraud scheme. Corruption has come under great focus in the last decade with enhanced enforcement of the Foreign Corrupt Practices Act but has been a concept dating back to the start of business. What has changed are the tools and more precisely, analytics, which can be used to detect bribery and other corruption schemes. Specific learning objectives include: o Explore the top internal and external data sources to interrogate for corruption schemes. o Be able to identify the key red flags leading to corrupt behavior and how they present themselves in data. o Learn to bolster any compliance program with data-driven prediction and decision making analytics. o Complete a who, what, when, and where set of analytics to hone in on the specific corruption and bribery within your business processes. o Understand the benefits of integrating and managing a continuous review of data sets to identify corrupt behavior.

1. Super-Data Charging Your
Corruption Reviews with
Integrated Analytics
About Jim Kaplan, CIA, CFE
 President and Founder of AuditNet®,
the global resource for auditors
(available on iOS, Android and
Windows devices)
 Auditor, Web Site Guru,
 Internet for Auditors Pioneer
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Award Recipient
 Local Government Auditor’s Lifetime
Award
 Author of “The Auditor’s Guide to
Internet Resources” 2nd Edition
Slide 1

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Introductions
Slide 2
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Slide 4
Richard B. Lanza, CPA, CFE, CGMA
• Director of Audit Data Analytics for Grant Thornton, LLP
• Over 25 years of ACL, Excel and other software usage
• 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:
• Detecting Corruption with Analytics: A Roadmap – The
International Institute for Analytics
• Global Technology Audit Guide (GTAG #13) Fraud In An
Automated World – Institute Of Internal Auditors.
• Cost Recovery – Turning Your Accounts Payable Department
Into A Profit Center – Wiley And Sons.
• Data Analytics: A Roadmap for Expanding Capabilities
(published 2018 in partnership with the IIA's Internal Audit
Foundation)
• In 2015, discovered a new textual analytic technique using letters
called the Lanza Approach to Letter Analytics (LALA)TM
Slide 5
The views expressed by the
presenters do not necessarily
represent the views, positions, or
opinions of Grant Thornton, LLP.
These materials, and the oral
presentation accompanyingthem,
are for educational purposes only
and do not constitute accounting
or legal advice or create an
accountant-client relationship.
rich.lanza@us.gt.com

4. Today’s Agenda
Explore the top internal and external data sources to
interrogate for corruption schemes.
Be able to identify the key red flags leading to corrupt
behavior and how they present themselves in data.
Learn to bolster any compliance program with data-driven
prediction and decision making analytics.
Complete a who, what, when, and where set of analytics to
hone in on the specific corruption and bribery within your
business processes.
Understand the benefits of integrating and managing a
continuous review of data sets to identify corrupt behavior.
Page 6
Defining Corruption and Associated Red Flags

5. What Are We Looking For?
Bribery – To influence a decision
Illegal Gratuities – To reward a decision
Economic Extortion – To coerce a decision
Conflicts of Interest – To take one's interests in a decision
8
Fraud Frequency By Type
9
©2018, Association of Certified Fraud Examiners. All rights reserved. Used by permission.

6. Corruption Compared to
Misappropriations
©2018, Association of Certified Fraud Examiners. All rights reserved. Used by permission.
Forget the Charts
Corruption By the Numbers
83.5% of reporting companies had an asset misappropriation
 However, this is allocated to nine misappropriation schemes
 The top scheme's frequency was 21% vs. corruption at 38%
 Some countries report corruption frequency as high as 62%
Median fraud $ for asset misappropriation - $114,000
 Corruption average was $250,000
Transparency International – Perception Index
 Nearly two-thirds fall below the midpoint of their "clean" scale
 Peter Eigen – Chairman TED Talk at https://youtu.be/XkiXXP_hycA
Forbes (http://reut.rs/2lStjHH) reported 2016 FCPA fines of $2.6B,
2nd only to the record amount collected in 2008
11

7. Why Is Corruption So Elusive?
Misappropriation is the taking of tangible goods
Corruption rather lives within the intangible
Influencing decisions is mostly within one's mind
Most value is transferred outside of accounting records
However, there are usually notable trails left behind
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The Elusive Red Flags
Buyer's Perspective
Consistent winning bids to a vendor
Other vendors issuing bids later than the submission date
Over-priced / Over-purchased goods and services
Matching vendor to employee record
Low quality product or services
Non receipt of goods or services
Obsolete goods
13

8. How It Is Hidden - Examples
Buyer's Perspective
Solicit bids from known high-bidder entities (false competition)
Don't issue a purchase order
Split purchases among various orders to avoid PO limits
Seller allowed to update bid after review of other bidders
Purposely provide short-time frames to vendors submitting bids
Self-approve the purchase order
Approve delivery as if it occurred
14
The Elusive Red Flags
Seller's Perspective
Over-priced or unusual increases in sales
Inflated hours for service
Petty cash usage for influence payment
Gifts and entertainment to influence sales
Consulting payments made to sales facilitation organizations
Payments to customer politically exposed person (“PEP”)
Receipt of inside information
15

9. How It Is Hidden - Examples
Seller's Perspective
Communications among partners uses non-company based devices
Self-approve the sales order / Collusion among the sales ordering
and approving parties
Forge petty cash or gift payment request form for other purpose
General ledger adjustments to spread payment or hide it in an
unreconciled ledger account
 Consulting expenses are adjusted to other benign accounts to avoid concern
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Data Sources To Base Analytics

10. The Population of Data Type
18
Structured Data
 Accounting records
 Sub ledger details
 Monthly performance
measures
Unstructured Data
 Documents (Excel, PDF,
Word)
 Emails
 Network Logs
External Data
 Geomap Service
 OFAC, SAM.Gov Watch Lists
 IRS Tax ID Match
Buyer Perspective Key Sources
Contract Management System
Purchase Order
Vendor Invoice Header
Vendor Invoice Distribution
Employee and Vendor Masterfiles
General / Nominal Ledger
Conflict of Interest Form Management
Email Server
Web Traffic Log
Meeting Room Request System
Related Party List
19

11. Seller Perspective Key Sources
Contract Management System
Sales Order
Approved Contract Price List
Sales Invoice Header
Sales Invoice Distribution
General / Nominal Ledger
Petty Cash Log
Travel & Entertainment System
Procurement Card History
Email Server
Web Traffic Log
Meeting Room Request System
Related Party List
20
External Data Sources To Aid Analytics

12. Search Anything Corporate
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Specific Business Partner
Information
Yellow Pages
 http://www.yellowpages.com/
 http://www.bbb.org/
 http://www.linkedin.com
 http://glassdoor.com
IP Address Lookup
 www.iplocation.net for Email and reverse DNS lookup
State Websites
 Business Listings and Incorporation Documents
 Unclaimed Property
 http://www.statelocalgov.net/
23

13. Wayback Machine
https://archive.org/web/
24
Are Vendors On a Watch List
Sam.Gov
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14. CIA Chiefs of State
https://www.cia.gov/library/publications/world-leaders-1/
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Power Map for Excel 2013
Page 27

15. Proactively Detecting Corruption
Why Proactively Review?
Fraud losses can be reduced by 65% in relation to
a management tip
Given elusive nature disparate data sets can
correlate wrongdoing
Start to build predictive models based on the past
29

16. Common Proactive Analysis
Employee to Vendor Testing
Politically Exposed Person Search
Key Word Searches – T&E Expenses
Travel and Entertainment Analysis
Petty Cash Testing
30
Uncommon Proactive Analysis
Key Word and Word Summary Searches
 Contracts, Emails, Meeting Rooms and Web Traffic
Obsolete inventory and adjustments
Purchase and sales process mapping
Vendor and purchase ledger change log review
31

17. Employee to Vendor
The Basic Match
Obtain vendor and employee masters
Create "related field" in each table
 LEFT, RIGHT and MID functions
Relate tables using the VLOOKUP function
Filter for any matches
32
Enterer and Approver Analysis
PivotTable the enterers (rows) and approvers (columns)
 Consider both as rows for a "lined up" match
Calculate a % of transaction count
 Identify high % and low % (outliers)
Identify matched approver and enterers
33

18. Under The Radar - Approval Limits
Apply a stratification table on approval limits
Filter items within approval limit ranges
Pivot results by vendor
34
Trend Analysis
Find The Unexpected
35
Buyer Enterer Date/Time
Where – GeoCode/Zip Supplier Department
Textual Analytics Digital Analysis Value Stratification

19. Making Best Use of
Purchase Ledgers
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)
36
Distribution Analysis
Remove subtotals for improved visibility
Focus on sole source and multi source
vendors
Scroll out and drill to details as needed
37

20. Textual and Letter Analytics
Lessons from
WorldCom/ MCI
The fraud was accomplished primarily in
two ways:
1.Booking "line costs" (interconnection
expenses with other telecommunication
companies) as capital expenditures on
the balance sheet instead of expenses.
2.Inflating revenues with bogus
accounting entries from "corporate
unallocated revenue accounts".
In 2002, a small team of internal
auditors at WorldCom worked together,
often at night and secretly, to investigate
and reveal $3.8 billion worth of fraud….
Per Wikipedia – MCI Inc.
Page 39

21. Fraud Red Flag
Word Searches
 What You Need
 Word Search Table
 Table Being Searched
 How You Do It
 SPLIT the field to be searched into words
 Convert data to be the same format
 Lookup to the word lookup list using Vlookup
Page 40
***AuditNet® Key Words Survey***
http://www.auditnet.org/key-word-analytics
Word Summary Analysis
Split account or journal description field
Copy and paste each column to the end
Add a type (or few type) fields
Pivot table on the combined list of words
by types
41

22. Can You Read This?
It deosn't mttaer in waht oredr
the ltteers in a wrod are, the
olny iprmoetnt tihng is taht the
frist and lsat ltteer be at the rghit
pclae.
42
43
A Benford’s Law For Words

23. Useful Links on LALA
 http://bit.ly/1jFD87b - Blog announcing the discovery of letter analytics.
 http://bit.ly/1RZpolz - Research Paper #1 – Focused on explaining the
letter analytic concept with reference to a benchmark for the English
Language and an analysis of British song titles from 1960 to 1999.
 http://bit.ly/1QebYkL - Research Paper #2 – Provides a more in-depth
analysis of the population of text data and how letters can explain text
variations over time more quickly than word summaries
 http://bit.ly/1W0CAZO - Predictive Analytics Times article on how Word
clouds analysis could improved with letter analytic visualizations
 http://bit.ly/1TGwvPS and http://bit.ly/21mEbsU - ACFE Fraud
Magazine articles on “The Benford’s Law of Words – Parts 1 and 2”
 http://bit.ly/2di87aH - ACL Blog on using ACL to calculate LALA
 http://bit.ly/2oCtRlx - How to Win at Wheel of Fortune Using Letter
Analytics
44
Questions?
Any Questions?
Don’t be Shy!
Page 45

24. AuditNet® and cRisk Academy
If you would like forever access
to this webinar recording
If you are watching the
recording, and would like to
obtain CPE credit for this
webinar
Previous AuditNet® webinars
are also available on-demand for
CPE credit
http://criskacademy.com
http://ondemand.criskacademy.com
Use coupon code: 50OFF for a
discount on this webinar for one week
Slide 46
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25. Thank You!
Jim Kaplan
AuditNet® LLC
1-800-385-1625
Email: webinars@auditnet.org
www.auditnet.org
Richard B. Lanza, CPA, CFE, CGMA
Contact Information
D: +1 732 516 5527
M: +1 732 331 3494
Email: rich.lanza@us.gt.com
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