Chapter 11: Data Analytics and Audit Sampling Flashcards
What is internal audit data analytics?
Internal audit data analytics is the use of software to retrieve data from various sources and filtering
the data to look for anomalies. Internal auditors can use data analytics to review large volumes of data
and create the ability to review only those data items that are significant and potential issues.
What are some of the key areas to which internal auditors can apply the use of data analytics?
Data analytics can be used to evaluate data in any business unit. Areas that are typical include:
accounts payable, procurement, travel and entertainment expenses, inventory, payroll, accounting entries, sales, and expense transactions.
How is “audit sampling” defined in this chapter?
Audit sampling is the application of an audit procedure to less than 100 percent of the items in a population for the purpose of drawing an inference about the entire population.
What are the two general types of audit sampling?
The two general types of audit sampling are statistical sampling and nonstatistical sampling.
How is “sampling risk” defined in this chapter?
Sampling risk is the risk that the internal auditor’s conclusion based on sample testing may be different
than the conclusion reached if the audit procedure was applied to all items in the population.
What are the two aspects of sampling risk that an internal auditor considers when performing tests of controls?
In performing tests of controls, the internal auditor is concerned with two aspects of sampling risk: the risk
of assessing control risk too low (type II risk, beta risk) and the risk of assessing control risk too high
(type I risk, alpha risk).
How does nonsampling risk differ from sampling risk?
Nonsampling risk, unlike sampling risk, is not associated with testing less than 100 percent of the
items in a population. Instead, nonsampling risk occurs when an internal auditor fails to perform his
or her work correctly.
What is attribute sampling?
Attribute sampling is a statistical sampling approach based on binomial distribution theory that
enables the user to reach a conclusion about a population in terms of a rate of occurrence.
What are the three variations of attribute sampling described in this chapter?
The three variations of attribute sampling described in the chapter are stratified attribute sampling, stop-or-go sampling, and discovery sampling.
What steps are involved in evaluating the results of an attribute sampling application?
Evaluating the results of an attribute sampling application involves:
■ Formulating a statistical conclusion.
■ Making an audit decision based on the quantitative sample results.
■ Considering qualitative aspects of the sample results
How is “haphazard sampling” defined in this chapter?
Haphazard sampling is a nonrandom selection technique that is used by internal auditors to select a
sample that is expected to be representative of the population. Haphazard, in this context, does not
mean careless or reckless. It means that the internal auditor selects the sample without deliberately
deciding to include or exclude certain items.
What is the key advantage of statistical sampling over nonstatistical sampling?
The key advantage of statistical sampling over nonstatistical sampling is that it allows the internal
auditor to quantify, measure, and control sampling risk.
Why do internal auditors sometimes choose to use nonstatistical sampling instead of statistical sampling?
Nonstatistical sampling allows the internal auditor more latitude regarding sample selection and evaluation.
In which phase(s) of the internal audit engagement can data analytics be used?
I. Planning the individual engagement.
II. Testing effectiveness and efficiency of controls.
III. Assessing risk to determine which areas of the organization to audit.
a. I only.
b. II only.
c. I and III only.
d. I, II, and III.
D is the best answer. Data analytics can be used in all phases of the audit process, although many
times it is used for testing the effectiveness and efficiency of controls. Internal audit data analytics can
also be used as part of continuous auditing and can be performed throughout the year.
Which of the following is true?
a. Continuous monitoring is the CAE’s responsibility.
b. If a control breakdown is identified through continuous auditing, it should be reported to management on a timely basis.
c. Data analytic technologies cannot be used for substantive testing.
d. Continuous auditing routines developed by internal auditors should not be shared with management.
B is the best answer. The purpose for continuous auditing is to identify control breakdowns sooner so
that management can take corrective actions. Continuous monitoring is a management responsibility and internal auditors should encourage management to utilize the results of data analytics to improve
controls and processes throughout the organization.