The document provides an overview of a webinar on the top 10 Excel analytic tests to minimize fraud and process risks. It discusses stratifying data, codifying data to run round numbers, identifying duplicate payments, calculating average days payable outstanding, conducting vendor background checks and geomapping, analyzing general ledger entries that don't net to zero, analyzing enterers and approvers, identifying the other side of revenue entries, applying Benford's Law and digital analysis, and using red flag and textual analytics. The webinar demonstrates how to automate audit steps into Excel analytics using a case study and applies the analytics across the audit lifecycle.

1. Top 10 Excel Analytic Tests
to Minimize Fraud and
Process Risks
April 19, 2017

2. About Jim Kaplan, CIA, CFE
 President and Founder of AuditNet®,
the global resource for auditors (now
available on iOS, Android and
Windows 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
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Introductions
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6. Data Files & Video
Data Files
Please see GoToWebinar console
Not all files are available as part of the webinar
 All others, please contact Rich Lanza rich@richlanza.com
Video
Will be made available in the next 3 days by AuditNet®
 Email will be sent from the Go To Webinar system
CPE
Will be made available in the next 3 days by AuditNet®
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Gensend.io (you must be able to receive mail from gensend.io)
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7. Richard B. Lanza, CPA, CFE, CGMA
• Director of Data Analytics for Grant Thornton, LLP
• Assists audit teams daily in the use of analytic software
• Nearly 25 years of ACL, Excel and other software usage
• Has written and spoken on the use of audit data analytics for over two decades
• 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 – Institute Of Internal Auditors.
• 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 And Sons.
• In 2015, discovered a new textual analytic technique using letters called the
Lanza Approach to Letter Analytics (LALA)TM
For more information Email Rich at rich.lanza@us.gt.com
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8. Today’s Agenda
Based on past experience, learn why we selected our top
10 analytic tests.
Use a case study set of examples in payables and general
ledger to see how audit steps can be automated into
analytics using Excel.
Use Excel as audit software, able to mimic practically all
data analytic commands found in more advanced tools.
Apply analytics across the entire lifecycle from risk
assessment, to planning, fieldwork, and reporting.
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9. Test #1 – Stratify Data

10. Getting Started:
Pivot to New Sheet
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11. Getting Around The Pivot
 Right click on the amount fields (data part) to
see field list and edit various Pivot Table options
 Select from the Top Ribbon Menu the Options
and Design menus for Pivot Tables (Excel
creates them when a Pivot Table is created) –
best and easiest way to make changes
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12. Stratify Your Data – Ver 1
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=IF(B4>1000,“3. Over $1000",IF(B4>100,“2. Over
$100 to $1,000",IF(B4<=100,“1. Up to $100")))
This will create three strata:
1. Up to $100
2. Over $100 to $1,000
3. Over $1,000
Start from highest to lowest – Excel picks the first
matching item

13. Stratify Your Data – Ver 2
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14. Stratification Types
 By Month
 By Department
 By Business Partner (Vendor / Customer)
 By Account
 By Enterer
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15. Polling Question #1
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16. 2. Codify Data To Run Round $s…and More

17. Text Functions
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LEFT()
With a determined set of characters in a set string, the first character
is returned from, the left of the cell
LEN()
Identifies the number of characters in a set and returns that as a
number in the cell
LOWER()
UPPER()
Lower case letters substitute upper case letters (reverse for upper)
MID()
Identifies characters in a set based on a start position and number of
characters which is determined by the user
PROPER()
Capitalizes the first letter of each character and the remaining are
lowercase
RIGHT()
Pulls the last set of character from a set and the number of character
is set by the user
TEXT()
Returns the text version of a number with a specified number format
(i.e., =TEXT(C999,"0.00") will convert 12345 into a text version of
12345.00)
TRIM()
Keeps single spaces only between words and removes all other
spaces

18. Text Functions
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CONCATENATE()
Combines numerous strings to one stream (You can also
use the & character to combine/merge/join fields)
REPT()
Repeats a character as many times as the user wants i.e. :
=REPT (“J”,10) wll lead to ‘JJJJJJJJJJ
CHAR()
Identifies a character with a number which is presented in
the cell.This number then can be used to convert other
CHAR to the number translate code from other sources
(i.e., CHAR(127) is a nonprintable character and CHAR(9)
is a tab)
CLEAN() From a text string, it removes the nonprintable characters

19. Math Functions
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VALUE() A number is given to identify a string now as a number
ISNA()
Returns true if the formula leads to a NA solution – This is
normally combined with IF so =IF(ISNA(C3/D3),0,(D3/D3))
AVERAGE() Is the mean of a range of cells set in the average function
MEDIAN()
Provides the middle number between the largest set value of
numbers and the lowest value of numbers
MAX() Provides the top value in a set of values
MIN() Provides the lowest value in a set of values
STDEV() Calculates the standard deviation for a range of numbers

20. Math Functions
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ABS() Turns a negative or positive number into a positive number
MOD()
Determines whether a number is round to a divisor set by the
user (i.e. : divisor equals 1000 and all numbers where MOD() are
=0 would be round to 1000)
ROUND() Sets a number to a specified decimal place

21. Date and Time Functions
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DATE() A date is created with a year, month, and day (i.e. : 2015,10,7)
DAY() By pointing to a specific field the function identifies the day
HOUR()
Identifies a hour in a time field which is set to military time (0:00-
23:00 hrs.)
MINUTE() Identifies the minutes in a time field which is set at 0-59
MONTH() Identifies the month in a time field which is set as 1=January
NOW() Sets to the actual current date and time
TODAY() Sets to the actual date

22. Date and Time Functions
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NETWORKS ()
Identifies the ACTUAL Network days in a whole number from start to
finish dates. (weekends and holidays are excluded unless specified)
SECOND() Identifies seconds in a time field ie:0-59
WEEKDAY()
Identifies a day during a specified week in a specific timeframe.
1=Sunday
WEEKUM() Identifies a specific week number in the calendar year
YEAR() Identifies a year with a specific number i.e: 1900-9999

23. Polling Question #2
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24. 3. Duplicates and 4. Averages

25. 3. Duplicate Payments
• Same Vendor Number; Same Amount; Same Date
• Same Vendor Number; Same Amount; Different
Invoice Number
• Same Amount; Same Date; Different Vendor
• Same Vendor; Same Amount; Different Date
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26. Reducing False Positives
http://bit.ly/1Pdz3Df
25
Blog article explains
specifically explains
how to:
Remove noise
Filter top
predictors
Duplicate hit rates
increased to 50%
vs. less than 1%

27. 4. Calculating an Average DPO
Create a calculated field for check less invoice date
(DPO) – in data or the Pivot
Add sum of Invoice Amount and Average of newly
calculated field
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28. Average Income per Zip Code –
IRS - 2013
Quick Link: http://1.usa.gov/28YzTSX
27

29. Polling Question #3
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30. 5. Vendor Background and Geomapping

31. Search Anything Corporate
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32. 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/
31

33. Wayback Machine
https://archive.org/web/
32

34. Is Your Organization
Working With Terrorists?
Page 33
 https://sanctionssearch.ofac.treas.gov/

35. Are Vendors On a Watch List
Sam.Gov
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36. CIA Chiefs of State
https://www.cia.gov/library/publications/world-leaders-1/
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37. 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/for-Tax-Pros and
enter “TIN matching program” in the search box
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38. Power Map for Excel 2013
See:
www.MrExcel.com
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39. Tests 6 to 8 on the Lifeblood of the
Organization…..the General Ledger

40. 6. Entries Not Netting to Zero
Pivot Table the journals by entry number
Create a Calculated Field in the Pivot Table to be
the difference between the debit and credit values
Filter where the entries do not net to zero
39

41. Polling Question #4
Page 40

42. 7. Enterer and Approver Analysis
PivotTable the enterers (rows) and
approvers (columns)
Calculate a % of transaction count
41

43. 8. Other Side of Revenue Entry
Code the revenue accounts
Pivot table the entries associated with revenue
 Add the journal entry field to the Pivot Table to
then identify the journals for extraction
 Filter only on revenue accounts
Use Vlookup() to extract entry details
Pivot table the extracted revenue entries
42

44. 9. Benford’s Law and Digital Analysis

45. I’ve Got Your Number – Mark J.
Nigrini, Ph.D.
Journal of Accountancy -
http://bit.ly/1skDvZe
Random numbers follow a
pattern as defined in table at
left
Focus is placed on the first
digits of amount fields
Digital analysis can be applied
to ledger data over time
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46. Number Ranking
 Summarize each amount of the journal entries
(Pivot or ACL)
 Rank each number in order of occurrence
 Look for new numbers appearing this quarter
 Score each item in a sliding scale
 May be easiest to use a stratified score
 Decide if unique is weirder than non-unique
 Select samples based on unusual numbers
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47. Polling Question #5
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48. 10. Red Flag and Textual Analytics

49. 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.
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50. 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.
49

51. 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
50

52. Page 51
A Benford’s Law For Words?

53. 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. Three
examples are provided including Shakespeare’s plays, Berkshire
Hathaway shareholder reports and my personal Emails.
 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”
52

54. Polling Question #6
Page 53

55. Questions?
Any Questions?
Don’t be Shy!
Page 54

56. Data Files & Video
Data Files
Please see GoToWebinar console
Not all files are available as part of the webinar
 All others, please contact Rich Lanza rich@richlanza.com
Video
Will be made available in the next 3 days by AuditNet®
 Email will be sent from the Go To Webinar system
Page 55

57. AuditNet® Training on the Go
See www.auditnet.org
Offering 9 Unique Training Courses / 18 CPE
Video playback of past / missed courses
 Don’t forget the data files and templates to get you started
https://www.auditnet.org/training
Page 56

58. AuditSoftwareVideos.com
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Sample files, scripts, and macros in ACL™, Excel™, etc.
available for purchase
Bite-size video format (3 to 10 minutes)
>> Professionally
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Page 57

59. 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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