Procurement Fraud
Detection and Prevention
November 11, 2008
Mike Blakley
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Joint meeting of RDU IIA and ISACA
November 11, 2008, Capitol Club, Raleigh, North Carolina
SlideSlide
1 <#>
Session objectives
1. Current trends, techniques
and best practices
2. Understand statistical basis
for analysis
3. Procurement cards (pcards)
4. Understand use of Excel
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 2
Top Six Indicators
That you might have a fraud
• 6. System designed to do “three way
match”, but only does two way
• 5. Procurement software system doesn’t
do a match
• 4. When auditors ask to help them out,
they point to the door
• 3. No procurement software system
• 2. Procurement clerk drives a Porsche
• 1. Clerk’s kids drive Porsches between
mountain home and beach home
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 3
Overview
• Fraud patterns detectable
with digital analysis
• Basis for digital analysis
approach
• Usage examples
• Using Excel
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 4
Objective 1
The Why and How
•
•
•
•
•
Two brief examples
IIA Guidance Paper
Auditors “Top 10”
Process Overview
Who, What, Why, When &
Where
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 5
Example 1 Objective 1
School Bus Transportation Fraud
• Supplier Kickback –
School Bus parts
• $5 million
• Jail sentences
• Period of years
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 6
Objective 1
Regression Analysis
• Stepwise to find
relationships
– Forwards
– Backwards
• Intervals
– Confidence
– Prediction
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 7
Objective 1
Data outliers
• Sometimes an
“out and out
Liar”
• But how do you
detect it?
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 8
Objective 1
Data Outliers
• Plot transportation
costs vs. number of
buses
• “Drill down” on costs
– Preventive maintenance
– Fuel
– Inspection
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 9
Scatter plot with prediction and
confidence intervals
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 10
Objective 1
Medicare HIV Infusion Costs
• CMS Report for 2005
• South Florida - $2.2
Billion
• Rest of the country
combined - $.1 Billion
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 11
Objective 1
Pareto Chart
Medicare HIV Infusion Costs - 2005 ($Billions)
data source: HHS CMS
120.0%
Annual Medicare Costs
100.0%
80.0%
Pct
60.0%
Cum Pct
40.0%
20.0%
15
13
11
9
7
5
3
1
0.0%
County
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 12
Objective 1
Guidance Paper
• A proposed implementation
approach
• “Managing the Business Risk of
Fraud: A Practical Guide”
http://tinyurl.com/3ldfza
• Five Principles
• Fraud Detection
• Coordinated Investigation
Approach
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 13
Objective 1
Managing the Business Risk of
Fraud: A Practical Guide
• IIA, AICPA and ACFE
• Report issued 5/2008
• Section 5 – Fraud
Detection
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 14
Objective 1
Section 5 – Fraud Detection
• Detective Controls
• Process Controls
• Anonymous Reporting
• Internal Auditing
• Proactive Fraud
Detection
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 15
Objective 1
Proactive Fraud Detection
• Data Analysis to identify:
–Anomalies
–Trends
–Risk indicators
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 16
Objective 1
Specific Examples Cited
• Journal entries – suspicious
transactions
• Identification of relationships
• Benford’s Law
• Continuous monitoring
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 17
Objective 1
Data Analysis enhances ability to
detect fraud
• Identify hidden relationships
• Identify suspicious transactions
• Assess effectiveness of internal
controls
• Monitor fraud threats
• Analyze millions of transactions
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 18
Peeling the Onion
Objective 1c
Fraud Items
Possible Error Conditions
Population as Whole
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 19
Objective 1d
Fraud Pattern Detection
Round Numbers
Market Basket
Benford’s Law
Stratification
Gaps
Target Group
Trend Line
Univariate
Duplicates
Holiday
Day of Week
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 20
Objective 1e
Who Uses Analytics
• Traditionally, IT specialists
• With appropriate tools,
audit generalists (CAATs)
• Growing trend of business
analytics
• Essential component of
continuous monitoring
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 21
Objective 1e
Analytics – what is it?
• Using software to:
– Classify
– Quantify
– Compare
• Both numeric and nonnumeric data
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 22
Objective 1e
How - Assessing fraud risk
• Basis is quantification
• Software can do the “leg work”
• Statistical measures of
difference
– Chi square
– Kolmogorov-Smirnov
– D-statistic
• Specific approaches
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 23
Objective 1e
Why - Advantages
•
•
•
•
•
•
•
•
Automated process
Handle large data populations
Objective, quantifiable metrics
Can be part of continuous monitoring
Can produce useful business analytics
100% testing is possible
Quantify risk
Repeatable process
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 24
Objective 1e
Why - Disadvantages
• Costly (time and software
costs)
• Learning curve
• Requires specialized
knowledge
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 25
Objective 1e
When to Use Analytics
• Traditional – intermittent
(one off)
• Trend is to use it as often as
possible
• Continuous monitoring
• Scheduled processing
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 26
Objective 1e
Where Is It Applicable?
• Any organization with data in
digital format, and especially
if:
– Volumes are large
– Data structures are complex
– Potential for fraud exists
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 27
Objective 1 Summarized
•
•
•
•
Objective 1
Two brief examples
IIA Guidance Paper
“Top 10” Metrics
Process Overview
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 28
Objective 1 - Summarized
1. Understand why and how
2. Understand statistical basis for
quantifying differences
3. Identify ten general tools and
techniques
Next is the basis …
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 29
Objective 2
Basis for Pattern Detection
• Analytical review
• Isolate the
“significant few”
• Detection of errors
• Quantified approach
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 30
Objective
Objective
2 3
Trapping anomalies
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 31
Objective 2
Understanding the Basis
•
•
•
•
Quantified Approach
Population vs. Groups
Measuring the Difference
Stat 101 – Counts, Totals,
Chi Square and K-S
• The metrics used
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 32
Objective 2a
Quantified Approach
• Based on measureable
differences
• Population vs. Group
• “Shotgun” technique
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 33
Objective 2a
Detection of Fraud Characteristics
• Something is different than
expected
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 34
Objective 2b
Fraud patterns
• Common theme –
“something is different”
• Groups
• Group pattern is different
than overall population
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 35
Objective 2c
Measurement Basis
•Transaction
counts
•Transaction
amounts
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 36
Objective 2d
How is digital analysis done?
• Comparison of group with
population as a whole
• Can be based on either counts or
amounts
• Difference is measured
• Groups can then be ranked using
a selected measure
• High difference = possible
error/fraud
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 37
Objective 2d
Histograms
• Attributes tallied and categorized
into “bins”
• Counts or sums of amounts
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 38
Objective 2d
Two histograms obtained
• Population and group
Population
700
Group
80
70
60
50
40
30
20
10
0
600
500
400
300
200
100
0
Jan- Feb- Mar- Apr- May- Jun- Jul- Aug- Sep- Oct- Nov- Dec07 07 07 07 07 07 07 07 07 07 07 07
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Jan- Feb- Mar- Apr- May- Jun- Jul- Aug- Sep- Oct- Nov- Dec07 07 07 07 07 07 07 07 07 07 07 07
Slide 39
Objective 2d
Compute Cumulative Amount for each
Count by Month
Cum Pct
80
120.0%
70
100.0%
60
Count
50
80.0%
40
60.0%
30
20
40.0%
10
20.0%
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
ov
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7
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Ju
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7
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-
07
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ar
-
Month
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Slide 40
Objective 2d
Are the histograms different?
• Two statistical measures of
difference
• Chi Squared (counts)
• K-S (distribution)
• Both yield a difference
metric
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 41
Objective 2d
Chi Squared
• Classic test on data in a
table
• Answers the question –
are the rows/columns
different
• Some limitations on when
it can be applied
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 42
Objective 2d
Chi Squared
• Table of Counts
• Degrees of Freedom
• Chi Squared Value
• P-statistic
• Computationally intensive
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 43
Objective 2d
Kolmogorov-Smirnov
• Two Russian mathematicians
• Comparison of distributions
• Metric is the “d-statistic”
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 44
Objective 2d
How is K-S test done?
•
Four step process
1. For each cluster element
determine percentage
2. Then calculate cumulative
percentage
3. Compare the differences in
cumulative percentages
4. Identify the largest difference
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 45
Objective 2d - KS
Kolmogorov-Smirnov
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 46
Objective 2e
Classification by metrics
•
•
•
•
•
•
•
•
•
•
Stratification
Day of week
Happens on holiday
Round numbers
Variability
Benford’s Law
Trend lines
Relationships (market basket)
Gaps
Duplicates
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 47
Objective 3
Fraud Pattern Detection
Round Numbers
Market Basket
Benford’s Law
Stratification
Gaps
Target Group
Trend Line
Univariate
Duplicates
Holiday
Day of Week
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 48
Objective 2
What can be detected
• Made up numbers
– e.g. falsified
inventory counts,
tax return
schedules
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 49
Objective 2
Benford’s Law using Excel
• Basic formula is “=log(1+(1/N))”
• Workbook with formulae available
at http://tinyurl.com/4vmcfs
• Obtain leading digits using “Left”
function, e.g. left(Cell,1)
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 50
Made up numbers
•
•
•
•
•
•
Benford’s Law
Check Chi Square and d-statistic
First 1,2,3 digits
Last 1,2 digits
Second digit
Sources for more info
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 51
How is it done?
Objective 2
• Decide type of test – (first 1-3
digits, last 1-2 digit etc)
• For each group, count number of
observations for each digit pattern
• Prepare histogram
• Based on total count, compute
expected values
• For the group, compute Chi Square
and d-stat
• Sort descending by metric (chi
square/d-stat)
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 52
Objective 2
Invoice Amounts tested with
Benford’s law - Example Results
Store
Hi Digit
Chi Sq
D-stat
324
79
5,234
0.9802
563
89
4,735
0.97023
432
23
476
0.321
217
74
312
0.2189
During tests of invoices by store, two
stores, 324 and 563 have significantly
more differences than any other store
as measured by Benford’s Law.
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 53
Next Metric
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Objective 2
Outliers
Stratification
Day of Week
Round Numbers
Made Up Numbers
Market basket
Trends
Gaps
Duplicates
Dates
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 54
Objective 2
Duplicates
Why is there more
than one?
Same, Same, Same, and
Same, Same, Different
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 55
Objective 2
Two types of (related) tests
• Same items – same vendor,
same invoice number, same
invoice date, same amount
• Different items – same
employee name, same city,
different social security number
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 56
Objective 2
Duplicate Payments
• High payback area
• “Fuzzy” logic
• Overriding
software controls
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 57
Fuzzy matching withObjective 2
software
•
•
•
•
Levenshtein distance
Soundex
“Like” clause in SQL
Regular expression
testing in SQL
• Vendor/employee
situations
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Russian
physicist
Slide 58
How is it done?
Objective 2
• First, sort file in sequence
for testing
• Compare items in
consecutive rows
• Extract exceptions for
follow-up
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 59
Objective 2
Possible Duplicates - Example Results
Vendor
Invoice
Date
Invoice
Amount
Count
10245
6/15/2007
3,544.78
4
10245
8/31/2007
2,010.37
2
17546
2/12/2007
1,500.00
2
Five invoices may be duplicates.
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 60
Next Metric
1.
2.
3.
4.
5.
6.
7.
8.
9.
10.
Objective 2
Outliers
Stratification
Day of Week
Round Numbers
Made Up Numbers
Market basket
Trends
Gaps
Duplicates
Dates
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 61
Objective 2
Holiday Date Testing
• Red Flag indicator
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 62
Objective 2
Typical audit areas
• Invoices
• Receiving reports
• Purchase orders
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 63
Objective 2
Federal Holidays
• Established by Law
• Ten dates
• Specific date (unless
weekend), OR
• Floating holiday
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 64
Objective 2
Understanding the Basis
•
•
•
•
•
Quantified Approach
Population vs. Groups
Measuring the Difference
Stat 101 – Counts, Totals, Chi
Square and K-S
The metrics used
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 65
Objective 2
Objective 2 - Summarized
1. Understand why and how
2. Understand statistical basis for
quantifying differences
3. Procurement cards
4. Understand examples done
using Excel
Next up: p-cards …
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 66
Testing Procurement Card
Transactions
1.
2.
3.
4.
5.
Objective 3
Understand Merchant Charge Codes (MCC)
Understand common policies
Test procurement card transactions contained on
worksheets using VBA
Ability to test procurement card transactions in a file
using VBA
Perform an audit of procurement card transactions in a
more efficient and effective manner using the concepts
and techniques presented
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 67
Audit Benefits
Objective 3
(How this test supports the audit)
• Test compliance with policy on an
account by account basis
• Test compliance with policies on
account limits
• Enable 100% testing of transactions
• Audit process which can be tailored for
policy changes
• Repeatable audit process
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 68
MCC Structure
•
•
•
•
•
Objective 3
Major Categories
Airlines 30XX – 32XX
Car Rental 33XX, 34XX
Hotels 35XX – 37XX
All Other
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 69
Policy Structure
Objective 3
• Prohibited Codes
• Codes allowed with a
monthly limit
• Codes allowed without limit
• Overall card limit
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 70
Summary and Wrap Up
Objective 3
1. Understand Merchant Charge Codes (MCC)
2. Understand common policies
3. Test procurement card transactions contained
on worksheets using VBA
4. Ability to test procurement card transactions
in a file using VBA
5. Perform an audit of procurement card
transactions in a more efficient and effective
manner using the concepts and techniques
Joint meeting
of the RDU IIA and ISACA chapters
presented
November 11, 2008, Capitol Club, Raleigh, NC
Slide 71
Objective 3 - Summarized
1. Understand why and how
2. Understand statistical basis for
quantifying differences
3. Procurement cards
4. Understand examples done
using Excel
Next up: Excel …
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 72
Objective 4
Use of Excel
•
•
•
•
Built-in functions
Add-ins
Macros
Database access
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 73
Objective 4
Excel – Univariate statistics
• Work with Ranges
• =sum, =average, =stdevp
• =largest(Range,1),
=smallest(Range,1)
• =min, =max, =count
• Tools | Data Analysis |
Descriptive Statistics
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 74
Excel Histograms
Objective 4
• Tools | Data Analysis |
Histogram
• Bin Range
• Data Range
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 75
Excel Gaps testing
Objective 4
• Sort by sequential
value
• =if(thiscell-lastcell <>
1,thiscell-lastcell,0)
• Copy/paste special
• Sort
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 76
Objective 4
Detecting duplicates with Excel
• Sort by sort values
• =if testing
• =if(=and(thiscell=l
astcell, etc.))
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 77
Objective 4
Performing audit tests with macros
• Repeatable process
• Audit standardization
• Learning curve
• Streamlining of tests
• Examples http://tinyurl.com/576tp8
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 78
Use of Excel
•
•
•
Objective 4
Built-in functions
Add-ins
Macros
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 79
Objective 4 - Summarized
1.
2.
3.
4.
Understand why and how
Understand statistical basis for
quantifying differences
Identify ten general tools and
techniques
Understand examples done using
Excel
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 80
Questions?
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 81
Links for more information
• Kolmogorov-Smirnov
• http://tinyurl.com/y49sec
• Benford’s Law
http://tinyurl.com/3qapzu
• Chi Square tests
http://tinyurl.com/43nkdh
• Continuous monitoring
http://tinyurl.com/3pltdl
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 82
Excel macros used in auditing
• Excel as an audit software
http://tinyurl.com/6h3ye7
• Selected macros http://tinyurl.com/576tp8
• Spreadsheets forever http://tinyurl.com/5ppl7t
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 83
Contact info
• E-mail:
Mike.Blakley@ezrstats.com
• Web: http://ezrstats.com
Joint meeting of the RDU IIA and ISACA chapters
November 11, 2008, Capitol Club, Raleigh, NC
Slide 84