We provide three audit software tools in support of analysis of data in Excel:

Analytical Software

Analytical software is efficient and effective because installation is simple.

XL Audit Commander (XLAC)

Perform complex analytical procedures from within Excel. Uses an unobtrusive toolbar which provides a variety of audit commands. This is an add-in which requires an Internet connection. See examples of audit commands in action.

Audit software for Excel

Command	XLAC	Audit Objective
Tools for Fraud Investigation
Benford's Law		Audit software to compare expected distributions of Leading and Trailing Digits with actual. Results include the Kolmogorov-Smirnov measure to enable quantification of probability).
Gap Identification		Identify missing items in sequences
Outliers		Audit software to classify amounts deviating significantly from the norm
Identification of Duplicates		Excel Audit software to identify duplicate payments or other transactions
Statistical Summaries
Histogram		Graphically display a distribution being audited
Means		Obtain basic population statistics
Data Summarization		Obtain audit totals for numeric variables
Data Classification
Linear Regression		Audit software to determine if a correlation exists between variables (analytical review)
Telephone Area Codes		Summarize telephone numbers by area code, state. Identify invalid area codes and their frequency.
Univariate Statistics		Obtain quartile, top and bottom five, mode and other statistics
Stratify		Stratify the data by various tiers.
Control Totals		List the sum of all positive, negative. List missing and absolute value. List number of zero items.
Basic Statistics		List the minimum, maximum, count, average, standard deviation for the audit population.
Analytic Review using Kolmogorov-Smirnov		Compare two balance sheets, income statements etc. to identify the most material item contributing to any difference between them. Express the difference as the D-Statistic in order that it can be measured.
Statistical Sampling
Sample size		Calculate the required attribute sample size, given confidence level, precision and expected error rate
Sample precision		Calculate the precision achieved after a sample has been selected
Interval sample		Select a random sample using interval.
CMA sampling		Select a sample based upon cumulative monetary amount.