AUDIT SAMPLING (Part 1)

ACCA F8 考試：AUDIT SAMPLING (Part 1)

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:

1. 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.

2. 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.