Audit Risk Model Inherent, Control, & Detection Risks

in the audit risk model audit sampling applies to

The first audit assignment is also inherently risky as the firm has relatively less understanding of the entity and its environment at this stage. Auditors proceed by examining the inherent and control risks pertaining to an audit engagement while gaining an understanding of the entity and its environment. Random selectionThis 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.

  • Sample items should be selected in such a way that the sample can be expected to be representative of the population.
  • This approach is the most theoretically correct, but can require more time to make selections.
  • The table also illustrates the fact that the risk level for substantive tests for particular assertions is not an isolated decision.
  • Sampling risk represents the possibility that an auditor’s conclusion based on a sample is different from that reached if the entire population were subject to audit procedure.

Inherent Risk

The Audit and Assurance (AA) and Foundations in Audit (FAU) 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 AA and FAU. Audit risk may be considered as the product of the various risks which may be encountered in the performance of the audit. In order to keep the overall audit risk of engagements below acceptable limit, the auditor must assess the level of risk pertaining to each component of audit risk.

Communities by professional specialism

Detection risk forms the residual risk after taking into consideration the inherent and control risks pertaining to the audit engagement and the overall audit risk that the auditor is willing to accept. File reviewers often challenge firms on how samples are picked, as well as on whether sample sizes are big enough. The FRC thematic highlights the benefits of random sampling over haphazard sampling – but a perhaps more fundamental question concerns whether audit files make clear how each item has had an equal chance of being selected. The review highlights that care should be taken when picking ‘key items’ in a stratified sample. Reasons for selecting key items need to be clearly documented and explained, but the FRC finds that they are rarely recorded. When they are, the FRC observes that this usually states simply “selecting everything over 50% of performance materiality”, with little or no justification as to why 50% is a meaningful percentage.

Financial Services

This is a recurring theme for many firms, especially in respect of substantive analytical review (SAR), which must be ‘predictive’ for reliance to be placed on it. Block selectionThis 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. They can however balance these risks by determining a suitable detection risk to keep the overall audit risk in check.

in the audit risk model audit sampling applies to

Sampling risk

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.

Under haphazard sampling, there is no structured approach to how items are selected. However, the person doing the selections will probably skew the selections (even if inadvertently), so the selections are not truly random. AA and FAU students must ensure they fully understand the various sampling methods available to auditors.

Block Sampling

in the audit risk model audit sampling applies to

Some levels of these risks are implicit in evaluating audit evidence and reaching conclusions. Auditors using the relationship prefer to evaluate these judgment risks explicitly. An auditor assesses inherent and control risk, and plans and performs substantive tests (analytical procedures and substantive tests of details) in whatever combination to reduce audit risk to an appropriate level. Sampling risk represents the possibility that an auditor’s conclusion based on a sample is different from that reached if the entire population were subject to audit procedure. The auditor may conclude that material misstatements exist, when in fact they do not; or material misstatements do not exist but in fact they do exist.

Alternatively, low inherent risk, effective controls, or effective analytical procedures and other relevant substantive tests may lead the auditor to conclude that the sample, if any, needed for an additional test of details can be small. 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 audit risk model 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.

in the audit risk model audit sampling applies to

Conversely, where the auditor believes the inherent and control risks of an engagement to be low, detection risk is allowed to be set at a relatively higher level. 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. The auditor planning a statistical sample can use the relationship in paragraph 4 of this Appendix to assist in planning his allowable risk of incorrect acceptance for a specific substantive test of details. To do so, he selects an acceptable audit risk (AR), and substantively quantifies his judgment of risks IR, CR and AP.

Audit Risk Model: Inherent Risk, Control Risk & Detection Risk

1For purposes of this Appendix, the nonsampling risk aspect of audit risk is assumed to be negligible, based on the level of quality controls in effect. 9The auditor who prefers to think of risk levels in quantitative terms might consider, for example, a 5 percent to 10 percent risk of assessing control risk too low. Detection Risk is the risk that the auditors fail to detect a material misstatement in the financial statements. 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.

Leave a Reply

Your email address will not be published. Required fields are marked *