Audit Commander Worksheet Analyzer

Auditing
Data contained in
Excel
Worksheets

Audit Commander
Audit Guide
Data analysis made easier…
EZ-R Stats, LLC
Auditing data on Excel worksheets

Audit Commander

The software described in this document makes data analysis
easier, particularly if it is contained in an Excel work book. The
software may be freely downloaded and used without restriction for
any purpose – commercial, educational or personal. Additional
information about the audit software is available at the web site.
Although a significant amount of testing has been performed, there
is no guarantee that every function works as documented. All
comments and suggestions are welcome. Comments
The software is currently being used to teach auditing concepts,
statistical sampling and data mining. EZ-R Stats, LLC is registered
with the North Carolina State Board of Certified Public Accountant
Examiners as a provider of Continuing Professional Education.



Document History

Revision History
Revision Revision Date Summary of Changes Author
Number
1.0 10-17-2009 Initial Version M. Blakley
1.1 11-12-2009 Trend Line and additional M. Blakley
error checking. New
style of input form.


Table of Contents

1 ABOUT THIS GUIDE................................................................................................1

1.1 Who Should Use It...........................................................................................................................................1

1.2 Typographical Conventions ...........................................................................................................................1

1.3 Purpose.............................................................................................................................................................2

1.4 Scope.................................................................................................................................................................2

1.5 Intended audience............................................................................................................................................3

1.6 Hardware requirements..................................................................................................................................3

1.7 Software requirements....................................................................................................................................3

2 GETTING STARTED.................................................................................................4

2.1 Working with Excel data.................................................................................................................................4

2.2 Audit objectives................................................................................................................................................5

2.3 Accomplishing audit objectives......................................................................................................................5

3 USING THE SOFTWARE.........................................................................................6

3.1 Opening form...................................................................................................................................................7

3.2 Analyzing data on Excel worksheets............................................................................................................10
3.2.1 Selecting the data for analysis..................................................................................................................10
3.2.2 Selecting the columns for analysis...........................................................................................................12
3.2.3 Select chart colors....................................................................................................................................14
3.2.4 Select the command to be processed........................................................................................................15
3.2.5 Specifying selection criteria.....................................................................................................................20

3.2.6 The logging facility..................................................................................................................................21

4 AUDIT COMMANDS.................................................................................................1

4.1 Numeric............................................................................................................................................................2
4.1.1 Population Statistics...................................................................................................................................2
4.1.2 Round Numbers..........................................................................................................................................7
4.1.3 Benford’s Law..........................................................................................................................................11
4.1.4 Stratify......................................................................................................................................................15
4.1.5 Summarization..........................................................................................................................................19
4.1.6 Top and Bottom 10...................................................................................................................................22
4.1.7 Histograms................................................................................................................................................25
4.1.8 Box Plot....................................................................................................................................................29
4.1.9 Random numbers......................................................................................................................................33

4.2 Date.................................................................................................................................................................37
4.2.1 Holiday Extract.........................................................................................................................................37
4.2.2 Week days.................................................................................................................................................41
4.2.3 Holiday summary.....................................................................................................................................44
4.2.4 Ageing......................................................................................................................................................48
4.2.5 Date Near..................................................................................................................................................52
4.2.6 Date Range...............................................................................................................................................54
4.2.7 Week days Report.....................................................................................................................................56

4.3 Other...............................................................................................................................................................59
4.3.1 Gaps in Sequences....................................................................................................................................59
4.3.2 Data Extraction.........................................................................................................................................62
4.3.3 Duplicates.................................................................................................................................................66
4.3.4 Same, Same, Different..............................................................................................................................69
4.3.5 Trend Lines...............................................................................................................................................72
4.3.6 Time Line analysis....................................................................................................................................75
4.3.7 Confidence Band......................................................................................................................................82
4.3.8 Confidence Band (Time Series)...............................................................................................................85
4.3.9 Invoice Near Miss....................................................................................................................................89
4.3.10 Split Invoices..........................................................................................................................................92
4.3.11 Check SSN..............................................................................................................................................94
4.3.12 Check PO Box........................................................................................................................................97


4.3.13 Calculated Values.................................................................................................................................100
4.3.14 Fuzzy Match (LD)................................................................................................................................103
4.3.15 Fuzzy Match (Regular Expression)......................................................................................................105
4.3.16 Sequential Invoices...............................................................................................................................108

4.4 Patterns.........................................................................................................................................................110
4.4.1 Round Numbers......................................................................................................................................110
4.4.2 Data Stratification...................................................................................................................................114
4.4.3 Day of Week...........................................................................................................................................117
4.4.4 Holidays..................................................................................................................................................120
4.4.5 Benford’s Law........................................................................................................................................123

4.5 Sampling.......................................................................................................................................................126
4.5.1 Attributes – Unrestricted: Stop and Go..................................................................................................126
4.5.2 Variable Sampling – Unrestricted Stop and Go......................................................................................133
4.5.3 Stratified Variable Sampling – Population.............................................................................................139
4.5.4 Stratified Variable Sampling – Assessment............................................................................................142
4.5.5 Stratified Attribute Sampling – Population............................................................................................144
4.5.6 Stratified Attribute Sampling – Assessment...........................................................................................147

5 ACCESS DATABASES AND EXCEL WORKBOOKS.........................................149

5.1 Overview.......................................................................................................................................................149

5.2 The “Excel/Access” menu item...................................................................................................................150

5.3 An example...................................................................................................................................................151

5.4 Working with text files................................................................................................................................155

5.5 The “File” tab...............................................................................................................................................155

5.6 An example...................................................................................................................................................156

6 TECHNIQUES FOR “DRILL DOWN”..................................................................160

6.1 Numeric........................................................................................................................................................162

6.2 Text................................................................................................................................................................162

6.3 Date / Time...................................................................................................................................................163

6.4 Logical tests..................................................................................................................................................164

6.5 Combinations...............................................................................................................................................164

6.6 Nesting functions..........................................................................................................................................164

6.7 Selection criteria..........................................................................................................................................165

7 APPENDIX – SOFTWARE INSTALLATION........................................................167

8 COMMENT FORM ...............................................................................................173

1 About this guide

This document is divided into the following chapters:

• Chapter 1 – Overview

• Chapter 2 – Getting started

• Chapter 3 – Auditing data on Excel work sheets

• Chapter 4 –The commands and how to use them

• Chapter 5 –Access databases and Excel workbooks

• Chapter 7 –“Drill down”

• Appendix – Software installation

1.1 Who Should Use It
Auditors, researchers, business analysts and academics who use data analysis to perform their
jobs.

• Auditors: can use the software to for a variety of common audit tasks. Altogether, over
40 useful analytical audit functions are included

• Researchers: use the software for:

• Data analysis, trend investigation

• Preparation of statistical reports and charts

1.2 Typographical Conventions
This document uses the following typographical conventions:

Auditing data on Excel worksheets Page 1


• Command and option names appear in bold type in definitions and examples.

• Screen output and code samples appear in mono space type.

1.3 Purpose
The purpose of this monograph is to provide a practical guide to auditing data contained on
Excel work sheets using the Audit Commander. Over 40 useful audit tests and data analyzes
can be performed. Although the primary source of data will be that contained on Excel work
sheets, the technique described also applies to certain other data sources such as Excel
workbooks, Access databases, as well as text files that are in a specific format (“tab separated
values”).

The auditor does not need special computer skills in order to be able to perform these tests
because they are largely menu driven with “fill in the blanks”.

Development of the software began in August 2005 when the author searched fruitlessly for a
relatively easy to use, economical software package for analyzing data on Excel work sheets
(and other). During its development, suggestions and improvements were made by a variety of
audit practitioners.

More information about the system is available from the website, More information is also
available about the author.

1.4 Scope
This guide explains how to install the software, the general purpose of the functions provided, as
well as examples of use.


1.5 Intended audience
The software is intended for use by both internal and external auditors, researchers, program
monitors, students learning data analysis, business analysts and anyone else interested in
analyzing data contained on Excel work sheets in a more efficient and effective manner.

1.6 Hardware requirements
At least 512 MB of memory (more if possible). Minimum disk space is 27 MB.

1.7 Software requirements
Works only in Windows XP, Vista or Windows 7. Requires ActiveX Data Objects which is part of
SP1. (ActiveX Data Objects can be downloaded from the Microsoft web site at no charge)

Auditing data in Excel
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2 Getting Started

2.1 Working with Excel data
Although Excel is a powerful tool, some audit analyzes are difficult or time consuming to perform.
The worksheet analyzer is a stand-alone program which is suitable for performing more than 30
of the most commonly needed analytical tests. This program also includes very powerful “drill-
down’ capabilities to enable the auditor or researcher to quickly isolate and locate the data that is
of special interest. This system does not require that the data be pre-sorted or specially
formatted.

The worksheet analyzer is generally used to analyze all or portions of single Excel spread
sheets. However, it can also be used to analyze data contained within MS-Access databases,
as well as text files in various formats (e.g. comma separated values, tab separated values, print
format, etc.)

The worksheet analyzer derives much of its capabilities by leveraging the software provided by
Microsoft called “ActiveX Data Objects” which provides significant database capabilities. These
database capabilities are in turn incorporated into and used by the software to provide a variety
of capabilities of special interest to auditors and data analysts.

The primary advantages of the Work sheet analyzer include:

• Pre-built functions for the most common audit tasks

• Significantly reduced time required to perform more complex extracts and analyzes

• No need to “pre-sort” the data

• Built-in help functions to simplify the process

• Small footprint - doesn’t require a lot of screen “real estate”


• Logging facility – log work performed, can be shared or used as a basis for future
analysis

The primary disadvantages of the Work sheet analyzer include :

• Is not completely “bullet proof” (some mistyped commands cause it to crash)

• Much slower with Excel 2007 than Excel 2003

• Computations for attribute sampling are slow with populations > 1,000

2.2 Audit objectives
As each available command is presented, one or more examples of specific audit objectives
which might be accomplished using that command will be included and discussed. Often entire
audit steps can be accomplished using the commands built into the system

2.3 Accomplishing audit objectives
Often, data being audited is available in Excel worksheets, after it has been extracted or
downloaded from various data sources. Once this data has been loaded onto one or more Excel
work sheets, the analyst should often perform a variety of tests in order to be able to arrive at an
audit conclusion.

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3 Using the software

Although the software is a stand-alone program, by design it is intended for use with Excel, and
is small enough that the form can reside along side the Excel workbook which contains the data
to be examined. This is done by having both the Excel workbook open as well as the Audit
Commander form on the same page while both are open. This makes it easier to transfer data
back and forth between the systems while doing a review.

An example screen shot is shown below to illustrate a case where a range of data on the
worksheet is being analyzed.

By intentionally keeping the Audit Commander form small, it becomes easier to transfer the
information from the Excel work book to the form, analyze the data and then “paste” the results


back into the Excel work book. Note that the results of any analysis performed are also stored in
the audit directory specified, so it is not necessary to also store the results in Excel.

3.1 Opening form
The opening form has three main menu items as shown below. Each of these menu items are
used to provide various types of processing information in order to analyze data.

The “commands” menu item is used to select the command or type of analysis to be performed.
The remaining menu items are “forms” which are used to gather and process information. A
summary description of the purpose of each form is provided in the table below.

Tab Name Purpose
Clipboard Process data that has been copied to
the clipboard (generally from Excel
sheets but can include others)
Text files Analyze data contained in text files (e.g.
comma separated value format, tab
separated value format, etc.)

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Excel/Access Analyzing data in Excel workbooks or
Access databases
Where Specifying and using more complex
selection criteria
Report View report produced (report is also
written to a file)
Chart Chart title and color scheme for chart
prepared (if applicable)
Audit Audit and folder information

The typical sequence used for running an audit analysis of data on a worksheet is as follows:
1. If not already done, specify the location where the audit results are to be stored, along
with the audit title, audit step number, etc. (“Audit” form)
2. Select the type of analysis to be performed (menu of 40+ commands)
3. Select the data to be analyzed, the columns or rows to be tested, along with any
additional information required for the analysis (“Clipboard/MS/Text” form)
4. If specific criteria are to be used (i.e. the test is for an extract of the data), specify this
information (“Where” tab)
5. If the data to be tested is from the clipboard, then copy the data to be tested from the
worksheet. This is done by first highlighting the data, then copying it to the clipboard
using methods such as 1) keyboard combination “Control-C”, 2) menu selection “Edit|
Copy”, or 3) right mouse click and select “Copy”. (“Clipboard” form)
6. On the tab labeled “Form”, click the button labeled “Run” (“Clipboard” form)
7. Wait until the analysis is finished, as indicated with a status message on the Status Bar
of the Audit Commander form. (“Clipboard” form)
8. View the report (“Report” tab)
9. If desired, the output in the audit folder specified may also be viewed. This includes both
a text report as well as any charts prepared (if applicable).
10. Analysis report results can also be copied to the clip board (“Report” tab)
11. Change audit parameters or specify different tests and repeat the steps above

Note: If the data to be tested resides in an Excel workbook, Access database or text file,
then “MS” or “File” tabs are used instead.


Each of these steps are illustrated below using an example analysis. In this analysis, the auditor
wishes to perform a test of fixed asset costs using Benford’s Law.

Step 1 – Specify audit information (if not already done)

Clicking on the “Audit” tab displays the information used to store the results for the analysis
performed. If any of this information needs to be changed, it can be overtyped and then the
button labeled “Update” clicked to store the information. The folder shown (in this case
C:testtemp” is the location where the reports and graphics produced by the audit analysis will
be stored. The folder name can be selected by clicking on the button labeled “Folder”, or else
overtyping the name in the text box.
The step number is used to uniquely identify the output. The starting step number is shown
above, and will be increased by one every time a procedure is run.
Once the information has been entered, click on the button labeled “Update” to save the
information. An informational message will be displayed on the status bar to acknowledge that
the change has been applied. This change will be in effect until the next change is applied.

Warning: Existing report files and graphics can be overwritten if the starting step number is too
low.

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3.2 Analyzing data on Excel worksheets

Once the audit parameter information has been entered (or checked), the data analysis
procedures can be performed. If the data to be analyzed is contained on an Excel worksheet,
then the analysis process begins with the first tab, which is labeled “Form”.

Note: If data in Excel work books, Access databases or text files are to be analyzed, the
tables “MS” and “File” should be used instead.

3.2.1 Selecting the data for analysis

The first step is to select the data to be analyzed. This is done by highlighting the area on the
worksheet to be analyzed and then copying it to the clipboard using any of four methods:

1. Press the keyboard combination “Control – C”
2. Right mouse click and specify “Copy”



Often, the data to be reviewed will be in vertical format as shown here. However, in some cases
the data will be organized horizontally (e. g. in comparative financial statements). If the data is
organized horizontally, then the checkbox “rows” on the main form needs to be checked before
the data is “pasted” into the form.

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Use the toolbar “copy” icon

3. Use the menu “Edit|Copy”

3.2.2 Selecting the columns for analysis

Once the data to be analyzed has been copied to the clipboard, it can then be “pasted” onto the
Audit Commander form. If the first row of the header contains column names, then the
checkbox just below the “Paste” button must be checked. When the data is pasted onto the


form, the column names will be placed into the drop down list so that the column to be analyzed
can be selected. If the area copied does not contain column names, then leave the check box
unchecked, and the system will assign column names “Col001”, “Col002” and so on.

Once the data has been pasted onto the form, the name of the first column is shown, and any
other column can be selected from the drop down list. For this test, the second column, named
“Cost” will be selected. The test to be performed will be to identify the three largest values. So
the command “Largest values” is selected from the command drop down list.

If the column name is blanked out, then all the data pasted will be processed in accordance with
the information below:

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The option to process the entire area pasted is available only for those functions which normally
process only a single column of data (list is in the table below). Depending upon the function
selected, only numeric data, date data or all data will be processed. The type of data processed
is shown in the table below.

Command Description Type of data processed
Numeric functions
Benford’s law Numeric only
Population statistics Numeric only
Histogram Numeric only
BoxPlot Numeric only
TopN Numeric only
BottomN Numeric only
Stratify Numeric only
Gaps Numeric only
Date Functions
Weekday Report Date only
Weekday Extract Date only
Holiday Report Date only
Holiday extract Date only
Date Near Date only
Date Range Date Only
Other Functions
Fuzzy match – Levenshtein distance (All)
Fuzzy match – regular expression (All)

3.2.3 Select chart colors

For commands which produce a chart, the chart title and chart colors can be specified using the
“Chart” tab.

Although all commands will produce a text file report, only certain commands will also prepare a
chart. Both the title of the chart and the color scheme used can be specified. The color scheme
can be specified in three formats:
1. “pre-set” scheme selected from the drop down list, e.g. “fall”
2. A range of colors between two specified values, e.g. brown – light tan (Note that a dash
separates the color names)
3. A range of colors specified for a numbered color group, e.g. turquoise 1 – 4. This is
equivalent to the specification turquoise 1 – turquoise 4, but shorter to type. Note that
only certain color names have color groups.



A complete list of color names accepted by the system and how they appear can be seen.
Examples of color ranges and how they appear can be seen – examples show a histogram and
use a chart title which specifies the color names used in the range. Two documents showing
examples are provided, both are predominantly harmonious color schemes. The first shows
color ranges for colors in a tight range (conservative). This is a PDF document of 251 pages
and is 8.4 MB in size. The second range of colors are less conservative, but still harmonious,
and are shown on a PDF document of 226 pages which has a size of 7.6 MB.

The case for chart colors can be either upper or lower case. Spaces are ignored. Thus the
following three specifications are equivalent:

• Turquoise 2
• TURQUOISe2
• Tur quoise 2

3.2.4 Select the command to be processed

The next step is to select the command to be processed from the command menu. The
commands are organized by function type.

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Once the command has been selected, a help message is displayed on the status bar indicating
what additional information is needed. If no additional information is needed, the status bar will
read “(No additional info)” and the info text box will not be displayed. However, if additional
information is required, the help message will be displayed on the status bar and the “Info” box
will be displayed. The resulting form is as follows:

The form now displays a fourth line called “Other info” and also displays an abbreviated help
message on the status bar: “number of values, e.g. 10”. The help message indicates that the
Other info is required and consists of a single value and the default value is “10”. In order
words, for the largest value test, the largest 10 items will be selected. In this case, we want only
the largest three values, so the number 3 is then typed into the “Other info” box.



Since all the needed information has been entered, the “Run” button can be clicked in order to
perform the analysis. After clicking the “Run” button, there will be a pause while the system
processes the information. Once processing is complete, the location of the output file will be
shown on the status bar. If a chart was also produced, it will have the same name as the output
text report file, but with a suffix of “.png”. An example of the form appears as follows:

As shown on the status bar, the report has been written to the file named “c:testtempstep-2.txt”
in the directory requested. The initial portion of the report (up to a maximum of 2,000
characters), can also be viewed by clicking on the tab labeled “Report”.

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The report lists the three lowest valued cost items in the range selected. Remaining information
about these items can be viewed by scrolling the view to the right. Note that the report has also
been stored in the report file specified.

At this point there are several options:

• Return to the “Clipboard” form and select another command to be processed, e.g.
Benford’s Law test”
• Return to the “Clipboard” form and select another column to be processed, e.g. “AD”
(accumulated depreciation)
• Return to the “Clipboard” form and “paste” another worksheet area for processing
• Switch to any of the other tabs for additional processing.
Go to a blank area in the current (or other) worksheet and “paste” the report results into that
worksheet.

Note: When a command is run, the results of that command can also be pasted to the
clipboard by clicking on the “Copy” button, making it easy to do further processing or
analysis by pasting this information on a worksheet.



Results are written to both a text file and a chart. In the example shown, the report was written
to the text file “c:testtempstep-8.txt” and a chart was produced and stored with almost the
same name, i.e. “c:testtempstep-8.png”. The results were stored in the directory “c:testtemp”
because that folder was specified as the Audit folder in this instance (can be changed using the
“Audit” form).

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For the population statistics command, the counts for positive, negative and zero amounts are
shown, along with the totals.

Note: The default color for the chart is blue and can be overridden using the values under
the “Chart” tab.

3.2.5 Specifying selection criteria



Clicking on the label named “Where?” causes the selection criteria help form above to be shown.
This form is useful in reminding you of the syntax for various types of selection that can be
performed. Of the templates shown, an example can be selected from the drop down list, then
modified and then copied over to the main processing form.

3.2.6 The logging facility

A complete record of the processing performed can be recorded automatically in a log file. The
log file records the processing performed in “macro” format so that it can be re-performed at a
future date or shared with others.
To perform logging, only two actions are needed:
Specify the name of the log file to be used (only required is a different logfile is used from prior
times)
For the processing performed, check the box on the form to indicate that logging is desired. This
check box can be turned on and off at will. When turned off, no logging is recorded until the
check box is turned back on.

The primary advantages of logging are:
1. Maintain a complete record of the processing performed
2. Record processing instructions so that the actions can be re-performed, now or in the
future
3. Share processing information with others
4. Document the work performed
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The primary disadvantage of logging is:
• Takes a minor amount of disk space and CPU cycle time
Logging information is specified using the “Audit” form as shown below.


Auditing data in Excel workbooks

4 Audit Commands

Types of queries
There are some 40+ queries or audit commands which can be selected for processing. These
commands are grouped into five classes based upon the type of function performed – 1)
numeric, 2) date, 3) other, 4) patterns and 5) sampling. For each command, a brief
explanation of the purpose and use of the command is provided, an explanation of the meaning
of any “other information” which must be provided. For each command, there are further
examples and example output contained on the CD which is distributed with the software.


Audit Commands

4.1 Numeric

4.1.1 Population Statistics

Population Statistics
Overview / Use in Audit Procedures
The population statistics command is the “work horse” of the system and can be used alone to
provide information for many audit steps. Just a few examples include:

• Obtaining control totals

• Preparing a population distribution for sample or audit planning

• Identifying counts and amounts of possible exceptions

• Quantifying the number and amount of records meeting various conditions

• Identifying counts and amounts of transactions within date ranges

The population statistics command produces three text reports and one graphic:

1. Basic statistics

2. Histogram data

3. Percentile report

Basic statistics include information such as counts, totals, minimum and maximum values, etc. This
information alone can be used to perform certain audit steps such as agreeing transaction supporting
details to ledger amounts, testing for procedural compliance, etc. In the example below, a histogram
chart and histogram data is to be prepared for fixed asset costs. The purpose of the procedure is to
obtain an overview of the fixed assets cost information, identify potential errors or extreme values and
provide information for audit planning.

The statistics command can be used for a variety of purposes, including:
• Obtaining counts of transactions meeting a condition or criteria


Audit Commands
• Obtaining transaction totals
• Obtaining univariate statistics for the reasonableness tests, sample planning, etc.
• Obtaining histogram information
• Obtaining percentile information

Usage Example 1
In a test of fixed assets, determine the count and amount of fixed assets which have been over
depreciated.
Approach – using the “population statistics” command, obtain totals and counts where the asset cost
less accumulated depreciation is less than salvage.
Audit Command values
Column value – Cost
Text Box – (empty)
Where – (cost – ad) < salvage
Results
Counts, totals, minimum, maximum, etc. for all assets which have been over depreciated.

Usage Example 2
For the purposes of sample planning, determine the distribution of values for fixed asset costs in order to
be able to plan strata to use for stratified sampling.
Approach – using the “population statistics” command, obtain a histogram of fixed asset costs.
Column value – Cost
Where – (empty)

The command shown below produces three reports for cost totals for location ‘ABC’. This is a very
basic example of the command. It is possible to specify considerably more complex selection criteria.
In addition, it is possible to prepare statistics for certain calculated amounts that are not contained in the
file or the worksheet. An example might be statistics for net book value measured by “cost – ad” (cost
less accumulated depreciation.

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Audit Commands

Output results
Population Statistics


Audit Commands
Output results (pasted into Excel work sheet)

The results above were “copied” from the form and then “pasted” into a worksheet. An alternative would
be to import the report as a text file into Excel.
Output results

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Audit Commands

Histograms
Output results (chart)
The chart below was specified using a custom color scheme and the title shown. These values are
provided using the “Chart” tab on the processing form.

Output results - chart


Audit Commands
4.1.2 Round Numbers

Round numbers
Overview / Use in Audit Procedures
Round numbers are often an indicator of estimates, which may be appropriate in certain cases (e.g.
journal entries), but not appropriate in others (e.g. purchase orders, invoices, expense reports, etc.).
The system can be used to identify the extent (if any) to which round numbers are being used as well as
extract data based upon types of round numbers. The system defines a round number as one which is
a whole number (i.e. no pennies), and contains one or more zeros immediately to the left of the decimal
point, without any intervening digits other than zero. The number of such zeros determines the “order”
of the round number. The chart below indicates examples of various round numbers, as well as their
“order”. If a number is not round, then it will be classified as “NR” (not round).
Example Order
15,000.00 3
10 1
123.19 NR
1,000,000.00 6
20.19 NR
Examples of tests which can be performed are provided below:
In a test of purchase orders, determine the frequency of round numbers for purchase orders. There is
an allegation relating to purchases at store number ‘123’.
Approach – using the “round numbers” command, obtain frequencies for round numbers on purchase
orders, classified as to type of round number.
Column value – Purchase order amount
Where – [store number] = 123
Results
Frequencies of round numbers used on purchase orders for store number 123.

Usage Example 2
In a test of journal entries, determine the frequency and extent of round numbers in journal entries for
transactions relating to expenses. Expense account numbers begin with the number 3 for this
company .
Approach – using the “round numbers” command, obtain a frequency count.
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Audit Commands

Column value – Amount
Where – [account number] like ‘3%’
Results
A report classifying the usage of round numbers for account numbers beginning with ‘3’
The example form below is being used to prepare a round number report for the data column named
“Cost”.


Audit Commands

Output results
Round numbers
Round Number report:
d-stat: .003704
Digits Count Pct
Not Round 3,660 90.37%
1 354 8.74%
2 34 0.84%
3 2 0.05%
Totals 4,050 100.00%

The report indicates that just a little under 10% of the numbers are round. The largest order of round
numbers is 3 (and there are two such numbers).
The “d-stat” value of “.003704 is a measure of the difference between the expected number of round
numbers and the actual number found. The d-stat value ranges from a low of zero (indicating conformity
with that expected) to a high of one (indicating a significant difference between observed and expected).
Output results

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Audit Commands

Round numbers



Audit Commands
4.1.3 Benford’s Law

Benford’s Law

The Benford’s Law command is generally used as part of a fraud or other forensic investigation. The
purpose will be to determine if numeric values on a schedule conform with that which is expected using
Benford’s Law. The test should only be applied to numeric values which would be expected to adhere to
that expected using Benford’s Law. More information is available about Benford’s law and its use.
There are six types of tests which can be performed for Benford’s Law:

Tests using Benford’s law must specify the type of test being performed:
F1 – Test of the first digit
F2 – Test of the first two digits
F3 – Test of the first three digits
D2 – Test of the second digit only
L1 – Test of the last digit
L2 – test of the last two digits

Usage Example 1
In a test of physical inventory counts, determine if some of the counts may have been made up. It is
expected that actual inventory counts would follow Benford’s law, i.e. a frequency distribution of
inventory counts would align with that expected using Benford’s law. There is an allegation relating to
counts at warehouse 5713.
Approach – using the “benford” command, obtain frequencies for physical inventory counts and compare
those with that expected using benford’s law
Column value – Inventory count
Text Box – F1
Where – [warehouse] = 5713
Results
Frequencies of first digits of inventory counts, along with a chart and analysis comparing the
results with that expected using benford’s law.

Usage Example 2
In a test of accounts payable, determine if particular vendor invoices have leading digit frequencies as
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Audit Commands

would be expected using benford’s law. The vendors in question all have vendor numbers starting with
the letters “R” – “V”.
Approach – using the “benford” command, obtain a frequency count.
Column value – [Invoice Amount]
Text Box – F1
Where – [Vendor number] like ‘[R-V]%
In the example below, the auditor is testing whether the first digits of the column named cost adhere with
that expected using benford’s Law.

Output results
Benford’s Law


Audit Commands
Benford Report
High digit 3
Chisq 730.89
p-value 0
df 8
D-stat 0.2641
Digit Observed Expected
1 473 1,219
2 432 713
3 464 506
4 463 392
5 435 321
6 419 271
7 454 235
8 456 207
9 454 185
The output results include both the expected and observed vales. Both a chi squared value and a d-stat
are provided to measure the difference and assess it. Here the large chi squared value indicates that
the data values do not conform with that expected using Benford’s law. Visually, this can be confirmed
based upon the chart which is also produced and shown below.
Output results

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Audit Commands

Benford’s Law

The chart indicates that the data distribution is fairly uniform (shown in the light tan) and differs
significantly from that which would be expected using Benford’s Law (shown in darker tan). The Chi
Square value is shown on the chart. Note that different chart colors and titles may be specified under
the “Chart” tab on the form.


Audit Commands

4.1.4 Stratify

Data stratification

The data stratification procedure classifies numeric amounts into “buckets” or value ranges specified by
the auditor. The purpose is to classify numeric amounts in order to determine the most frequently
occurring values, largest and smallest values, etc. Stratification is often used for sample planning
(stratified sampling, reasonableness tests) as well as audit planning in general.

The values to be used for the strata (specified in ascending order and
separated by commas or spaces). An example strata specification is “-
1000, -500, 0 300, 2000, 4000, 6000”. Note that the strata values do not
need to be evenly spaced. If any values are found outside the end ranges
of the strata specified, those values are reported separately.

Warning: If strata values are not numeric, or not in ascending order, invalid results may be obtained. Do
not include commas within a single value – e.g. specify 1000 NOT 1,000

Usage Example 1
In a test of accounts payable, classify the invoice amounts into particular ranges for the purpose of audit
planning. Invoices less than $100 do not require a secondary authorization. Invoices over $50,000
requires three authorizations. All invoices over $2,500 require a purchase order.
Approach – using the “stratify” command, obtain frequencies and totals for invoices classified into
various numeric ranges.
Column value – Inventory amount
Text Box – -5000 -500 0 100 500 2500 30000 50000 100000
Where – (empty)
Results
The invoice amounts for each range specified are totaled and counted. Invoices for less than -
$5,000 or ore than $100,000 (the extreme values) are tallied separately.
Usage Example 2
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Audit Commands

In a test of accounts payable, stratify the amounts of invoices for sample planning. One objective of the
analysis is to classify the amounts such that 80% of the value can be tested with one procedure and the
remaining 20% with another audit procedure. Only invoices at location ABC are to be classified.
Approach – using the “stratify” command, obtain a data stratification.
Column value – [Invoice Amount]
Text Box – 0 500 20000 50000 100000
Where – location = ‘ABC’
Results
A report classifying the invoice amounts at location ‘ABC’ into the ranges specified. The results
also include a chart.

Data stratification


Audit Commands
Summary for Strata -100 0 100 200 500 1000 5000 7000 9000 12000
Start End Count Amount Pct Cumulative
Below Below 0 0 0 0
-100 0 0 0 0 0
0 100 31 1,440.00 0.0001 0.0001
100 200 47 7,345.99 0.0004 0.0004
200 500 108 39,520.48 0.0019 0.0024
500 1000 190 143,419.53 0.007 0.0094
1000 5000 1,665 5,017,302.18 0.2465 0.2559
5000 7000 772 4,624,456.00 0.2272 0.4831
7000 9000 826 6,616,229.14 0.3251 0.8082
9000 12000 411 3,903,915.96 0.1918 1
Above Above 0 0 0 1
Totals totals 4,050 20,353,629.28
Output results

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Audit Commands

Data stratification



Audit Commands

4.1.5 Summarization

Data summarization

The summarization function obtains not only totals by each control break (sort key) specified, but also
other information such as minimum and maximum values, averages and standard deviation. There is no
limit as to the number of columns which make up the control break. A control break (sort key) may
consist of a single column, e.g. sub-totals by vendor would be specified as just a single column name –
“vendor”. If subtotals were needed by region by vendor, then the control break specification would be
“region, vendor”.

Note: The information being summarized does not need to be “pre-sorted”.

Usage Example 1
The auditor wishes to summarize sales by region and store in order to identify both the totals, as well as
the ranges of values at these stores, i.e. largest single amount and smallest single amount.
Approach – using the “summary” command, obtain totals, counts, minima, maxima, standard deviation,
average.
Column value – Sales amount
Text Box – region, store
Where – (empty)
Results
The summarized amount by store by region is produced, showing also the averages, minima,
maxima, standard deviation, etc.

Usage Example 2
Expense report information is available and includes employee number, region, expense type and
expense date. The auditor wishes to summarize expense report costs , by region and employee number
for the month of June, for travel expenses only (i.e. expense type = “travel”).
Approach – using the “summary” command, obtain a data summarization.

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Audit Commands

Column value – [Expense Amount]
Text Box – Region, [employee number]
Where – [expense type] = ‘travel’ and month([expense date]) = 6
Results
A report summarizing all travel amounts for the month of June, by region and employee. In
addition to summaries, counts, minima, maxima, averages and standard deviations are shown.

A simpler example is shown in the example below – summarize cost by location and life. All rows are to
be summarized.

Output results
Data summarization


Audit Commands
Output results (pasted into Excel work sheet – not all is shown)

Stand-
Minim- ard De-
location life Total Average um Maximum Count viation
AB 1 1 1 1 1 1 1
AB 2 2 2 2 2 1 1
AB 13 13 13 13 13 1 1
ABC 3 648 3 3 3 216 0
ABC 4 992 4 4 4 248 0
1,285.0
ABC 5 0 5 5 5 257 0
1,572.0
ABC 6 0 6 6 6 262 0
1,722.0
ABC 7 0 7 7 7 246 0
2,088.0
ABC 8 0 8 8 8 261 0
2,115.0
ABC 9 0 9 9 9 235 0
2,160.0
ABC 10 0 10 10 10 216 0
2,497.0
ABC 11 0 11 11 11 227 0
3,132.0
ABC 12 0 12 12 12 261 0
CDS 3 45 3 3 3 15 0
CDS 4 60 4 4 4 15 0
CDS 5 80 5 5 5 16 0
CDS 6 108 6 6 6 18 0
CDS 7 105 7 7 7 15 0
CDS 8 96 8 8 8 12 0
CDS 9 162 9 9 9 18 0
CDS 10 170 10 10 10 17 0
Output results

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Audit Commands

4.1.6 Top and Bottom 10

Top and Bottom 10 (Extreme values)

The Top and Bottom 10 commands are used to identify the largest (or smallest) numeric, date or text
values from a population (and criteria can be applied). The number of items to be identified can be
specified as any value. Generally the command is used to identify extremes among the following types
of data:

• For numeric values, identify unusually large (or small) items, possible outliers or to focus on just
the most significant dollar items.
• For date values, identify the latest (or earliest) dates in order to identify date ranges, transactions
outside the cutoff date, etc.
• For text values, identify high (or low) values of text as would be shown had the data been sorted.

Note that the data being analyzed does not need to be presorted. Analysis of subsets of the data can be
readily performed. For example, the auditor may wish to know the smallest fixed asset costs for those
assets with a useful life of seven years or more and located within one or more regions or states. Other
types of criteria can also be applied, depending upon what the analyst wishes to accomplish.

Usage Example 1

For purposes of audit testing, the 10 fixed assets with the largest cost need to be identified, but only for
assets located in either Florida, Alabama or Georgia.
Approach – using the “topn” command, list the details pertaining to the ten asset records having the
largest cost. Note that the input data does not need to be pre-sorted.
Column value – asset cost
Text Box – 10
Where – location in(‘FL’,’GA’,’AL’)
Results
A list of the fixed asset records for the ten assets having the greatest cost in any of the three
states specified.


Audit Commands
Usage Example 2
Identify the first five assets which have a net negative book value
Approach – using the “bottomn” command, list the details pertaining to the ten asset records having the
least net book value. This will include any which have a negative net book value. Note that the input
data does not need to be pre-sorted.
Column value – [asset cost] – [accumulated depreciation]
Text Box – 5
Where – (empty)
Results
A list of the fixed asset records for the 5 assets having the smallest net book value (which will
include negative values if there are any).

In the example below, the auditor wishes to identify the ten asset records which have the largest cost
amounts.

Output results

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Audit Commands

Top and Bottom 10 (Extreme values)
Output results (pasted into Excel work sheet) – first ten rows in descending order (not all
columns shown)
Cost TagNo AD Replace Bookval Salvage Depr Life Location
9997 2665 4019.164 2999 5977.84 1999 803.8328 4 DFS
9995 9747 4065.581 2998 5929.42 1999 813.1162 12 ABC
9994.99 2204 4070.435 2998 5924.56 1999 814.0869 10 ABC
9994 9091 4033.723 2998 5960.28 1999 806.7445 12 ABC
9994 3619 4052.277 2998 5941.72 1999 810.4555 9 DFS
9991 5778 4055.282 2997 5935.72 1998 811.0564 7 GSE
9990 5461 4019.03 2997 5970.97 1998 803.806 7 ABC
9988 879 4046.362 2996 5941.64 1998 809.2724 6 XZS
9977 2054 4014.101 2993 5962.9 1995 802.8203 4 ABC
9975 6887 4015.735 2992 5959.27 1995 803.147 12 ABC

The records with the largest ten asset costs are shown, listed in descending order. Note that if the data
pasted did not have column headers, then the largest values would shown in the leftmost column. For
example, if an area of six columns (with no column headers) were pasted and column three (“Col003”)
were selected, then the results would be shown with Column3 as the first column, followed by Column 1,
2, 4, 5 and 6.
Output results


Audit Commands

4.1.7 Histograms

Histograms

Histograms provide a visual representation for the values or transactions being analyzed. The results
are identical to that of the population statistics, and boxplot commands, except that a different chart is
produced.

Three reports are produced:

1. Basic statistics

2. Histogram data

3. Percentile report
Basic statistics include information such as counts, totals, minimum and maximum values, etc. This
information alone can be used to perform certain audit steps such as agreeing transaction supporting
details to ledger amounts, testing for procedural compliance, etc. Examples of basic statistics reports
can be found in the work papers referenced below:
Usage Example 1
For purposes of audit testing, prepare a histogram of employee expense report amounts.
Approach – using the “histo” command, prepare a chart and detail report as to expense report amounts
at region XYZ.
Column value – [expense report amount]
Where – region = ‘XYZ’
Results
A histogram chart of expense report amounts at region XYZ, along with a text report containing
the numeric values.

Usage Example 2

For purposes of testing inventory values, prepare a histogram of inventory unit cost amounts.

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Audit Commands

Approach – using the “histo” command, prepare a chart and detail report as to inventory unit cost
amounts.
Column value – [inventory cost]
Where – (empty)
Results
A histogram chart of unit inventory costs, along with a text report containing the numeric values.
Where – (empty)
Results
The invoice amounts for each range specified are totaled and counted. Invoices for less than -
$5,000 or ore than $100,000 (the extreme values) are tallied separately.
The example below shows a histogram of cost values is to be prepared.

Output results

Histograms


Audit Commands
Histogram Report
Bin Start End Count Amount
1 1 834 146 29,783.99
2 834 1,667.00 332 276,601.51
3 1,667.00 2,500.00 352 586,450.00
4 2,500.00 3,333.00 329 826,848.02
5 3,333.00 4,166.00 357 1,188,139.13
6 4,166.00 4,999.00 337 1,399,458.47
7 4,999.00 5,832.00 355 1,773,214.05
8 5,832.00 6,665.00 325 1,895,888.28
9 6,665.00 7,498.00 318 2,124,745.17
10 7,498.00 8,331.00 335 2,517,380.31
11 8,331.00 9,164.00 348 2,899,833.39
12 9,164.00 9,997.00 516 4,835,286.96
Totals: 4,050 20,353,629.28
The data for the histogram includes both counts and amounts. The counts are plotted on the chart which
is prepared.
Output results

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Histograms

This chart indicates that the most common values are those between 9,164 and 9,997. The fewest
counts are between the values of 1 and 834.


Audit Commands
4.1.8 Box Plot

Box Plot

The Box Plot command is used to separate a population of numeric values into quartiles in order to see
the values and to also envision how the population is distributed. This provides a little more information
than just the minimum, maximum and median. Except for the chart, the command is identical to the
Population statistics and the histogram command.
Usage Example 1

As part of an audit of accounts payable, the range of invoice costs needs to be determined.
Approach – using the “boxplot” command, prepare a chart and detail report as to invoice costs for
invoices dated after 6/30/2008.
Column value – [invoice amount]
Where – [invoice date] > #6/30/2008#
Results
A box plot chart of invoice amounts for invoices dated after 6/30/2008, along with a text report
containing the numeric values.

Usage Example 2

Daily sales ranges needs to be determined for a particular store.
Approach – using the “boxplot” command, prepare a chart and detail report as to daily sales ranges at
store ABC.
Column value – [sales total]
Where – [store number] = ‘ABC’
Results
A box plot chart of daily sales ranges, along with a text report containing the numeric values.
The example below will prepare a box plot of cost values for all transactions. This plot could have been
narrowed down by specifying the “Where” information.
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Output results

Box Plot


Audit Commands
Percentiles:
P 1.0% : 125
P 5.0% : 542
P 10.0% : 1,064.99
P 25.0% : 2,579.00
P 50.0% : 4,960.00
P 75.0% : 7,559.00
P 90.0% : 9,027.00
P 95.0% : 9,503.00
P 99.0% : 9,902.00
Inter quartile range: 4,980.00
The values above are a portion of the data as it appears when pasted into Excel. This report is the
same as that for the population statistics and the histogram commands.
Output results

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Audit Commands

Box Plot



Audit Commands
4.1.9 Random numbers

Random numbers are commonly required as part of the sampling process. Excel has a built in
function for the generation of random numbers, “=RAND()”. The Excel RAND function generates
pseudo random numbers evenly distributed between 0 and 1. For many purposes, the pseudo
random number generated using the RAND function may be adequate.

Microsoft documentation at http://support.microsoft.com/support/kb/articles/q86/5/23.asp
(knowledge base article Q86523 ) describes the process used. The starting number is
determined based upon the time of day.

The RAND function is just one of a number of random number generators (RNG). The quality of
a random number generator can be tested using the “DieHard” test suite developed by the
National Institute of Standards (NIST). More information is available at
http://csrc.nist.gov/groups/ST/toolkit/rng/batteries_stats_test.html.

One of the free random number generators is called the Mersenne Twister.

The following description is provided from Wikipedia on the Mersenne Twister

“The Mersenne twister is a pseudorandom number generator developed in 1997

by Makoto Matsumoto (松本眞?) and Takuji Nishimura (西村拓士?)[1] that is
based on a matrix linear recurrence over a finite binary field F2. It provides for
fast generation of very high-quality pseudorandom numbers, having been de-
signed specifically to rectify many of the flaws found in older algorithms.

Its name derives from the fact that period length is chosen to be a Mersenne
prime.

The commonly used variant of Mersenne Twister, MT19937 has the following
desirable properties:

1. It was designed to have a period of 219937 − 1 (the creators of the algorithm
proved this property). In practice, there is little reason to use a larger period, as most ap-
plications do not require 219937 unique combinations (219937 is approximately 4.3 × 106001;

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this is many orders of magnitude larger than the estimated number of particles in the ob-
servable universe, which is 1087).

2. It has a very high order of dimensional equidistribution (see linear congruential
generator). This implies that there is negligible serial correlation between successive val-
ues in the output sequence.

3. It passes numerous tests for statistical randomness, including the Diehard tests.
It passes most, but not all, of the even more stringent TestU01 Crush randomness tests.

The Mersenne Twister algorithm has received some criticism in the computer science
field, notably by George Marsaglia. These critics claim that while it is good at generating
random numbers, it is not very elegant and is overly complex to implement.”

Generation of random numbers using Audit Commander is done using the “random”
command. A seed value consisting of an integer value between 1 and 2,147,483,647 is
used to determine the starting random number. The random numbers generated will
consist of uniformly distributed numbers between zero and one.

Usage Example 1

For purposes of sampling, generate and assign random numbers to each row of data
contained on an Excel work sheet. The starting seed number to be used is 102935427.

Command – “random”
Column name – “N/A”
TextBox – “102935427”

Results – An additional column named “Random” is created with a value on the
rightmost column between zero and 1. This is a pseudo random number generated
using the Mersenne twister algorithm based upon the seed number provided.

Random numbers


Audit Commands

The example command shown on the next page adds a random number value in the rightmost column.
This random number will be between 0 and 1 (exclusive). The starting number is based upon the seed
value provided (in this case 1738974 ). The seed value should be a whole number between 1 and
approximately 2.1 billion.

Random numbers

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Output results (pasted into Excel work sheet – highlighting added for effect, not all columns shown)
Life Location Acquisition Accode DispDate Random number
7 DEF 5/17/2008 7:40 A 0 0.974683138
8 DEF 12/19/2001 A 0 0.961858645
12 DEF 1/5/2008 11:31 A 0 0.209254051
3 DEF 10/12/2009 16:33 A 0 0.451545258
8 DEF 11/20/2008 11:16 A 0 0.362094671
10 DEF 1/31/2007 6:00 A 0 0.010547096
5 DEF 8/21/2010 21:21 A 0 0.784745319
4 DEF 3/14/2000 15:07 A 0 0.269402404
3 DEF 4/4/2001 8:38 A 0 0.417646239
3 DEF 7/31/2006 6:57 A 0 0.578761123
8 DEF 11/30/2008 9:07 A 0 0.590210739
9 DEF 1/21/2004 8:09 A 0 0.690726882
7 DEF 7/29/2010 23:31 A 0 0.902005128
8 DEF 8/12/2000 19:12 A 0 0.361275228
7 DEF 7/23/2002 9:07 A 0 0.456829664
8 DEF 5/8/2001 9:07 A 0 0.503349514
8 DEF 4/13/2010 15:36 A 0 0.119554142
9 DEF 9/9/2010 15:07 I 0 0.602501919
7 DEF 12/16/2003 6:57 A 0 0.820769995
7 DEF 6/22/2006 18:28 A 0 0.944822744
Output results


Audit Commands

4.2 Date

4.2.1 Holiday Extract

Holiday Extract

Often it is desirable to check if any transaction dates fall on a federal holiday such as the Independence
Day, etc. Although it may be possible to visually check for these dates, it becomes more complicated
when the date falls on a weekend and is therefore celebrated on the preceding Friday (or the following
Monday). This function can analyze all the dates within a specified range and quantify the number that
fall on each of the holiday dates. There are two functions related to holidays. One prepares a summary
of counts of holiday dates and the other extracts transactions whose dates fall on federal holidays.
Usage Example 1
In a test of general ledger, an extract of all journal postings on a federal holiday needs to be obtained.
Approach – using the “holiday” command, extract a list of all journal entries posted on holidays. The
date format being used is month – day – year (mdy).
Column value – [journal posting date]
Text Box – mdy
Where – (empty)
Results
A list of any journal entry transactions which have been posted on a date which is a federal
holiday. In addition, a summary chart of holiday transactions is prepared.

Usage Example 2

Determine if any receiving reports exist for dates falling on a federal holiday. Date format is mdy.
Approach – using the “holiday” command, extract a list of receiving transactions falling on a federal
holiday.

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Column value – [receiving report date]
Text Box – mdy
Where – (empty)
Results
A list of any receiving report transactions which occurred on a federal holiday. In addition, a
summary chart of holiday transactions is prepared.
Date format – “mdy” for mm/dd/yyyy or “dmy” – dd/mm/yyyy
Country code – “US” or “CA”.

Note: The default values: US and mdy will be used if no values are specified.

The command example below checks for any records which have an acquisition date falling on a federal
holiday in the United States.

Output results
Holiday Extract


Audit Commands
Output results (pasted into Excel work sheet – not all rows and columns are shown, highlighting added
for emphasis)
AcqDate TagNo Cost AD Replace Bookval Salvage Depr
11/24/2005 1939 6199 2539.986 1860 3659.01 1240 507.9973
1/17/2005 4982 8649 3488.15 2595 5160.85 1730 697.63
1/17/2005 4759 8649 3488.15 2595 5160.85 1730 697.63
5/28/2007 3740 4993 2040.753 1498 2952.25 999 408.1506
7/4/2005 2392 9223 3728.142 2767 5494.86 1845 745.6284
1/2/2006 3543 4267 1726.003 1280 2541 853 345.2006
10/9/2006 2344 7175 2929.244 2152 4245.76 1435 585.8487
1/2/2006 4754 9473 8400 2842 1073 1895 1680
11/24/2005 4887 9867 4009.78 2960 5857.22 1973 801.956
2/19/2007 2035 1615 654.74 484 960.26 323 130.948
11/10/2006 4215 3776 1521.438 1133 2254.56 755 304.2876
10/10/2005 3475 9503 3845.354 2851 5657.65 1901 769.0709
1/1/2007 3166 7941 3240.535 2382 4700.46 1588 648.1071
11/11/2004 3197 2179 889.3601 654 1289.64 436 177.872
2/19/2007 1224 3424 1375.961 1027 2048.04 685 275.1921
12/31/2004 1353 3912 2920 1174 992 782 584
2/19/2007 4232 4544 1835.211 1363 2708.79 909 367.0423
2/20/2006 4194 3068 1251.079 920 1816.92 614 250.2158
12/31/2004 4107 1785 714.4909 536 1070.51 357 142.8982
12/25/2006 5243 1518 614.6649 455 903.34 304 122.933
9/4/2006 5193 6506 2652.665 1952 3853.33 1301 530.5331
Output results

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Holiday Summary

This chart indicates that the most frequent holiday for asset acquisitions was President’s Day (19
instances).


Audit Commands

4.2.2 Week days

Week days

In many instances the auditor wishes to extract just certain data within Excel based upon days of the
week. In this instance one column or row will contain dates which the auditor wishes to examine.
Usage Example 1

In a test of certain expense, an extract is needed for expenses incurred on a Friday or Saturday.
Approach – using the “wd” command, extract a list of all such transactions. The date format being used
is month – day – year (mdy).
Column value – [expense date]
Text Box – Friday, saturday
Where – (empty)
Results
A list of any expense transactions which fell on a Friday or Saturday are prepared.

Usage Example 2
An audit test is to be performed to identify any travel expense transactions on Saturdays, which is not
allowed at this company.
Approach – using the “wd” command, extract a list of all such transactions. The date format being used
is month – day – year (mdy).
Column value – [expense date]
Text Box –Saturday
Where – [travel code] = ‘airline’
Results
A list of any expense transactions which fell on a Saturday is prepared.
The day of the week must include at least the first three letters of the week day name. case does not
matter. Thus, Sunday could be specified using any of the following: “sun”, “Sunday”, “sund”, etc.
The example below is used to extract all transactions which fall on either a Saturday or a Monday. Note
that additional selection criteria could have been applied, e.g. store = ‘ABC’ to isolate the extract to just
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those transactions at store ‘ABC’. Similarly a date range could have also been applied, e.g. acqdate
between #7/1/2005# and #9/30/2005#. When specifying dates as part of the extract criteria, the date
value must be enclosed in pound signs (‘#’).

Output results
Week days


Audit Commands
Output results (pasted into Excel work sheet – not all rows and columns are shown)
AcqDate TagNo Cost AD Replace Bookval Salvage Depr Life
5/26/2007 2547 8258 3346.594 2477 4911.41 1652 669.3188 9
3/4/2006 1299 -3115 1253.43 934 1861.57 623 250.6859 12
3/6/2006 2881 2244 905.4028 673 1338.6 449 181.0806 8
3/17/2007 2791 3039 2431 912 608 608 761.4 12
12/19/2005 4163 3048 1223.804 914 1824.2 610 244.7607 4
4/8/2006 5205 1165 932 350 233 233 95.43749 8
7/10/2006 4219 2500 1022.871 750 1477.13 500 204.5741 3
6/24/2006 3112 1131 460.5792 339 670.42 226 92.11584 3
2/26/2005 1921 7527 3033.435 2258 4493.57 1505 606.6869 4
9/19/2005 4857 6106 2448.247 1832 3657.75 1221 489.6493 9
5/2/2005 2391 4339 1745.635 1302 2593.37 868 349.1269 8
7/17/2006 2205 7858 3195.106 2357 4662.89 1572 639.0212 5
1/20/2007 1639 7073 2870.923 2122 4202.08 1415 574.1847 6
4/16/2007 4964 2410 975.3022 723 1434.7 482 195.0604 7
6/19/2006 4185 6705 2715.957 2012 3989.04 1341 543.1915 4
9/18/2006 4673 7966 3233.326 2390 4732.67 1593 646.6653 3
11/6/2006 3363 6586 2658.405 1976 3927.6 1317 531.6809 3
1/17/2005 4982 8649 3488.15 2595 5160.85 1730 697.63 9
1/27/2007 1501 521 208.4521 156 312.55 104 41.69043 12
3/28/2005 3965 1775 715.3794 532 1059.62 355 143.0759 10
1/17/2005 4759 8649 3488.15 2595 5160.85 1730 697.63 9
1/27/2007 3743 521 208.4521 156 312.55 104 41.69043 12
3/28/2005 5045 1775 715.3794 532 1059.62 355 143.0759 10
11/22/2004 1870 2589 1060.414 777 1528.59 518 212.0829 6
12/5/2005 3391 795 322.078 238 472.92 159 64.4156 5
12/11/2006 5140 4897 1989.455 1469 2907.55 979 397.891 6
5/7/2005 2589 5555 2229.728 1666 3325.27 1111 445.9457 10
Output results

Page 43
worksheets

Audit Commands

4.2.3 Holiday summary

Holiday Summary

In certain instances it is desirable to extract just those transactions in a file which fall on a federal
holiday. These transactions can then be reviewed separately. The holiday extract command can be
used in conjunction with date ranges, location codes or any other criteria which should be applied as
part of the extract.

Usage Example 1

In a test of general ledger, an extract of all journal postings on a federal holiday needs to be obtained.
Approach – using the “holiday” command, extract a list of all journal entries posted on holidays. The
date format being used is month – day – year (mdy).
Column value – [journal posting date]
Text Box – mdy
Where – (empty)
Results
A list of any journal entry transactions which have been posted on a date which is a federal
holiday. In addition, a summary chart of holiday transactions is prepared.

Usage Example 2

Determine if any receiving reports exist for dates falling on a federal holiday. Date format is mdy.
Approach – using the “holiday” command, extract a list of receiving transactions falling on a federal
holiday.
Column value – [receiving report date]
Text Box – mdy
Where – (empty)

Results


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