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Accountant and Certified Government Financial Manager, Steven M. Glover is a Professor at Brigham Young University, Julia L. Higgs is an Associate Professor at Florida Atlantic University, and Jonathan Liljegren is a Manager at Freddie Mac. Search for other works by this author on: Abraham D. Akresh; Randal J. Elder is a Professor at Syracuse University, Abraham D. Akresh is a Certified Public Accountant and
Certified Government Financial Manager, Steven M. Glover is a Professor at Brigham Young University, Julia L. Higgs is an Associate Professor at Florida Atlantic University, and Jonathan Liljegren is a Manager at Freddie Mac. Search for other works by this author on: Steven M. Glover; Randal J. Elder is a Professor at Syracuse University, Abraham D. Akresh is a Certified Public Accountant and Certified Government
Financial Manager, Steven M. Glover is a Professor at Brigham Young University, Julia L. Higgs is an Associate Professor at Florida Atlantic University, and Jonathan Liljegren is a Manager at Freddie Mac. Search for other works by this author on: Julia L. Higgs; Randal J. Elder is a Professor at Syracuse University, Abraham D. Akresh is a Certified Public Accountant and Certified Government Financial Manager,
Steven M. Glover is a Professor at Brigham Young University, Julia L. Higgs is an Associate Professor at Florida Atlantic University, and Jonathan Liljegren is a Manager at Freddie Mac. Search for other works by this author on: Jonathan Liljegren Randal J. Elder is a Professor at Syracuse University, Abraham D. Akresh is a Certified Public Accountant and Certified Government Financial Manager, Steven M. Glover is a Professor at
Brigham Young University, Julia L. Higgs is an Associate Professor at Florida Atlantic University, and Jonathan Liljegren is a Manager at Freddie Mac. Search for other works by this author on: AUDITING: A Journal of Practice & Theory (2013) 32 (Supplement 1): 99–129. - Views Icon Views
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SUMMARY
While research has influenced auditing standards for audit sampling, academic research provides limited insights into the current use of audit sampling. We synthesize relevant research based on a sampling decision framework and suggest areas for additional research. Important judgments include determining if sampling applies, what type of sampling to apply (e.g., attribute or monetary sampling), whether to use statistical or nonstatistical techniques, appropriate
inputs to determine sample size, and evaluation of results, particularly when errors are observed in the sample. Several of these judgments may be influenced by environmental factors, such as regulation, litigation, competition, culture, and technology, and there are a number of research opportunities available in exploring how these environmental factors influence audit sampling decisions. Research indicates that auditors may underestimate risks and required assurance in order to reduce the
extent of testing, although some of this research predates current risk assessment standards, as well as recent regulatory changes. Research also indicates auditors sometimes fail to project sample errors, and are prone to decision biases when evaluating nonstatistical samples. More recent research finds low rates of sample errors in many sampled populations, indicating that some sampling concerns may be mitigated in the post-Sarbanes-Oxley (SOX) environment. Data
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? Password Citing articles viaGet Email Alerts Paper F8, Audit and Assurance and Paper FAU, Foundations in Audit require students to gain an understanding of audit sampling. While you won’t be expected to pick a sample, you must have an understanding of how the various sampling methods work. This article will consider the various sampling methods in the context of Paper F8 and Paper FAU. This subject is dealt with in ISA 530, Audit Sampling. The definition of audit sampling is: ‘The
application of audit procedures to less than 100% of items within a population of audit relevance such that all sampling units have a chance of selection in order to provide the auditor with a reasonable basis on which to draw conclusions about the entire population.’ (1) In other words, the standard recognises that auditors will not ordinarily test all the information available to them because this would be impractical as well as uneconomical. Instead, the auditor will use sampling
as an audit technique in order to form their conclusions. It is important at the outset to understand that some procedures that the auditor may adopt do not involve audit sampling, 100% testing of items within a population, for example. Auditors may deem 100% testing appropriate where there are a small number of high value items that make up a population, or when there is a significant risk of material misstatement and other audit procedures will not provide sufficient appropriate audit
evidence. However, candidates must appreciate that 100% examination is highly unlikely in the case of tests of controls; such sampling is more common for tests of detail (ie substantive testing). The use of sampling is widely adopted in auditing because it offers the opportunity for the auditor to obtain the minimum amount of audit evidence, which is both sufficient and appropriate, in order to form valid conclusions on the population. Audit sampling is also widely known to reduce the risk
of ‘over-auditing’ in certain areas, and enables a much more efficient review of the working papers at the review stage of the audit. In devising their samples, auditors must ensure that the sample selected is representative of the population. If the sample is not representative of the population, the auditor will be unable to form a conclusion on the entire population. For example, if the auditor tests only 20% of trade receivables for existence at the reporting date by confirming
after-date cash, this is hardly representative of the population, whereas, say, 75% would be much more representative.
Sampling risk
Sampling risk is the risk that the auditor’s conclusions based on a sample may be different from the conclusion if the entire population were the subject of the same audit procedure. ISA 530 recognises that sampling risk can lead to two types of erroneous conclusion: - The auditor concludes that controls are
operating effectively, when in fact they are not. Insofar as substantive testing is concerned (which is primarily used to test for material misstatement), the auditor may conclude that a material misstatement does not exist, when in fact it does. These erroneous conclusions will more than likely lead to an incorrect opinion being formed by the auditor.
- The auditor concludes that controls are not operating effectively, when in fact they are. In terms of substantive testing, the auditor
may conclude that a material misstatement exists when, in fact, it does not. In contrast to leading to an incorrect opinion, these errors of conclusion will lead to additional work, which would otherwise be unnecessary leading to audit inefficiency.
Non-sampling risk is the risk that the auditor forms the wrong conclusion, which is unrelated to sampling risk. An example of such a situation would be where the auditor adopts inappropriate audit procedures, or does not recognise a
control deviation.
Methods of sampling
ISA 530 recognises that there are many methods of selecting a sample, but it considers five principal methods of audit sampling as follows: - random selection
- systematic selection
- monetary unit sampling
- haphazard selection, and
- block selection.
Random selection
This method of sampling ensures that all items within a population stand an equal
chance of selection by the use of random number tables or random number generators. The sampling units could be physical items, such as sales invoices or monetary units.
Systematic selection
The method divides the number of sampling units within a population into the sample size to generate a sampling interval. The starting point for the sample can be generated randomly, but ISA 530 recognises that it is more likely to be ‘truly’ random if the use of random number
generators or random number tables are used. Consider the following example: Example 1
You are the auditor of Jones Co and are undertaking substantive testing on the sales for the year ended 31 December 2010. You have established that the ‘source’ documentation that initiates a sales transaction is the goods dispatch note and you have obtained details of the first and last goods dispatched notes raised in the year to 31 December 2010, which are numbered 10,000 to 15,000
respectively. The random number generator has suggested a start of 42 and the sample size is 50. You will therefore start from goods dispatch note number (10,000 + 42) 10,042 and then sample every 100th goods dispatch note thereafter until your sample size reaches 50. Monetary unit sampling
The method of sampling is a value-weighted selection whereby sample size, selection and evaluation will result in a conclusion in monetary amounts. The objective of monetary
unit sampling (MUS) is to determine the accuracy of financial accounts. The steps involved in monetary unit sampling are to: - determine a sample size
- select the sample
- perform the audit procedures
- evaluate the results and arriving at a conclusion about the population.
MUS is based on attribute sampling techniques and is often used in tests of controls and appropriate when each sample can be placed into one of two classifications – ‘exception’ or
‘no exception’. It turns monetary amounts into units – for example, a receivable balance of $50 contains 50 sampling units. Monetary balances can also be subject to varying degrees of exception – for example, a payables balance of $7,000 can be understated by $7, $70, $700 or $7,000 and the auditor will clearly be interested in the larger misstatement.
Haphazard sampling
When the auditor uses this method of sampling, he does so without following a structured technique.
ISA 530 also recognises that this method of sampling is not appropriate when using statistical sampling (see further in the article). Care must be taken by the auditor when adopting haphazard sampling to avoid any conscious bias or predictability. The objective of audit sampling is to ensure that all items that make up a population stand an equal chance of selection. This objective cannot be achieved if the auditor deliberately avoids items that are difficult to locate or deliberately avoids
certain items. Block selection
This method of sampling involves selecting a block (or blocks) of contiguous items from within a population. Block selection is rarely used in modern auditing merely because valid references cannot be made beyond the period or block examined. In situations when the auditor uses block selection as a sampling technique, many blocks should be selected to help minimise sampling risk. An example of block selection is where the auditor
may examine all the remittances from customers in the month of January. Similarly, the auditor may only examine remittance advices that are numbered 300 to 340.
Statistical versus non-statistical sampling
Paper F8 students need to be able to differentiate between ‘statistical’ and ‘non-statistical’ sampling techniques. ISA 530 provides the definition of ‘statistical’ sampling as follows: ‘An approach to sampling that has the following
characteristics:
i. Random selection of the sample items, and
ii. The use of probability theory to evaluate sample results, including measurement of sampling risk.’ (2) The ISA goes on to specify that a sampling approach that does not possess the characteristics in (i) and (ii) above is considered non-statistical sampling. The above sampling methods can be summarised into statistical and non-statistical sampling as follows:
Statistical sampling allows
each sampling unit to stand an equal chance of selection. The use of non-statistical sampling in audit sampling essentially removes this probability theory and is wholly dependent on the auditor’s judgment. Keeping the objective of sampling in mind, which is to provide a reasonable basis for the auditor to draw valid conclusions and ensuring that all samples are representative of their population, will avoid bias.
Conclusion
Paper F8 and FAU students must
ensure they fully understand the various sampling methods available to auditors. In reality there are a number of ways in which sampling can be applied that ISA 530 recognises – however, the standard itself covers the principal methods. Students must ensure they can discuss the results of audit sampling and form a conclusion as to whether additional work would need to be undertaken to reduce the risk of material misstatement. Written by a member of the F8 examining
team References (1). ISA 530, paragraph 5 (a)
(2). ISA 530, paragraph 5 (g)
How does an auditor evaluate sample results?
The auditor may decide to examine a sample of these items. The auditor evaluates the results of this sample and reaches a conclusion on the 90% of value separately from the remaining 10% (on which a further sample or other means of gathering audit evidence will be used, or which may be considered immaterial).
How do you conduct an audit as an auditor?
The basic steps to conduct an internal audit are as follows:. Identify areas that need auditing. ... . Determine how often auditing needs to be done. ... . Create an audit calendar. ... . Alert departments of scheduled audits. ... . Be prepared. ... . Interview employees. ... . Document results. ... . Report findings.. Why is it necessary to evaluate the attributes of audit evidence?
Audit evidence is important because it is all the information that an auditor gathers to reach his audit opinion about an organization's financial statements and/or internal control environment.
How do you do audit sampling?
The objective of audit sampling is to ensure that all items that make up a population stand an equal chance of selection.. determine a sample size.. select the sample.. perform the audit procedures.. evaluate the results and arriving at a conclusion about the population.. | 
