Chapter 11 Audit sampling Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Learning objective 1: Definition and features Audit sampling: the application of an audit procedure to less than 100% of the items within a population to obtain audit evidence about particular characteristics of the population. Audit sampling is important because it provides information on: How many items to examine Which items to select How sample results are evaluated and extrapolated to the population in order to tell us something about the population (e.g. level of misstatement). Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Non-sampling and sampling risk defined Sampling risk: the probability that the auditor has reached an incorrect conclusion because audit sampling was used rather than 100% examination (ASA/ISA 530.05). Non-sampling risk: arises from factors, other than sample size, that cause an auditor to reach an incorrect conclusion, such as the possibility that: The auditor will fail to recognise misstatements included in examined items The auditor applies a procedure that is not effective in achieving a specific objective. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Characteristic of interest When sampling, the auditor identifies a particular characteristic of the population to focus upon. For tests of control, the characteristic of interest is the rate of deviation from an internal control policy or procedure. For substantive tests, the characteristic of interest is monetary misstatement in the balance. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Learning objective 2: Various means of gathering audit evidence 100% examination: this is not a sampling method. Selecting specific items: e.g. high value or high risk — this is not a sampling method. Items selected will not necessarily be representative of the population. Audit sampling. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Statistical and non-sampling sampling Statistical sampling: an approach to sampling that has the following characteristics: Random sample selection Use of probability theory to evaluate sample results Major advantage is defensibility, thorough quantification of sampling risk Refer ASA/ISA 530.5(g) Non-statistical sampling: sampling approaches that do not have all the characteristics of statistical sampling. Major advantage is greater application of audit experience The basic principles and essential procedures identified in ASA/ISA 530 apply equally to both statistical and non-statistical sampling. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Current practice in Australia and business risk assessment In Australia, there are some disparities with regard to the practice of sampling within the large audit firms. Firms will usually use an unbiased approach but the size of the sample they select will usually be determined with the help of decision aids within the firm. Sample sizes that are commonly used in practice are around 20 items where a moderate level of testing is required, or 30 items where more extensive levels of testing are undertaken. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Basic requirements of all audit samples Whenever an auditor uses audit sampling (statistical or non-statistical) the following requirements apply: Planning and design: The auditor considers the relationship of the sample to the relevant specific audit objective or control objective and considers certain other factors that should influence sample size. Selection: Sample items are selected in such a way that the sample can be expected to be representative of the population. Performing the procedure and evaluating results: The auditor performs the required audit procedures on the items selected, projects the results of the audit procedures undertaken on the sample to the population and considers sampling risk. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Learning objective 3: Planning and designing the sample Auditor must consider: Objectives of the audit test (usually related to an audit assertion of interest) Population from which to sample Possible use of stratification Definition of the sampling unit. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Defining the audit objective and population Once the audit objective is specified, such as reliance on controls or misstatement of account balance, the auditor must consider what conditions would constitute an error. The auditor must ensure that the population from which the sample is to be selected is complete and appropriate to the audit objective. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Stratification Stratification: occurs when the auditor divides the population into a series of sub-populations, each of which has an identifying characteristic, such as dollar value (ASA 530/ISA 530 Appendix 1, paragraphs 1–4). Can assist with audit efficiency as it allows the auditor to reduce the sample size by reducing variability without increasing the sampling risk. Can direct auditor’s attention to areas of audit interest, especially risky or material items. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Defining the sampling unit The sampling unit is commonly the: Transactions or balances making up the account balance, or Individual dollars that make up an account balance or class of transactions, commonly referred to as Monetary-Unit Sampling (MUS) or Dollar Unit Sampling (DUS). Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Learning objective 4: Determining sample size Sample size is affected by the degree of sampling risk the auditor is willing to accept. Auditor's major consideration in determining sample size is whether, given expected results from examining sample, sampling risk will be reduced to an acceptably low level (ASA/ISA 530.07). Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Factors that influence sample size for tests of controls Appendix 2 to ASA/ISA 530 outlines the factors that influence sample size for tests of controls as follows: The extent to which the auditor’s risk assessment takes into account relevant controls (control risk assessment) The tolerable rate of deviation The expected rate of deviation The auditor’s desired level of assurance The number of sampling units in the population. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Factors that influence sample size for substantive testing Appendix 3 to ASA/ISA 530 outlines the factors that influence sample size for substantive testing as follows: The auditor’s assessment of risk of material misstatement The use of other substantive procedures directed at the same assertion The auditor’s desired level of assurance that actual misstatement is not greater than tolerable misstatement The tolerable misstatement The amount of misstatement the auditor expects to find in the population (expected misstatement) Stratification The number of sampling units in the population. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Learning objective 5: Selecting the sample To draw conclusions about population or stratum, the sample needs to be typical of characteristics of population or stratum. Sample needs to be selected without bias so that all sampling units in the population or stratum have a chance of selection. Common sampling techniques are: Random selection — random number generation Systematic selection Haphazard selection — select without conscious bias. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Steps in systematic selection For example, suppose the sample size is 20 and the number of items in the population is 10 000: Step 1: Calculate the sample interval: Step 2: Give every item in population chance of selection by choosing a random number (random start) within range of 1 and sampling interval (in this example, 500), e.g. 217. Step 3: Continue to add sampling interval to random start, and identify items to be sampled, e.g. item nos. 217, 717, 1217. . . 9217, 9717. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Biases from haphazard sampling Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Unacceptable sample selection methods Block selection: the auditor selects all items of a specified type processed on a particular day, week or month. Judgmental selection (based on sample item characteristics): the auditor selects large or unusual items from the population or uses some other judgmental criterion for selection. This method has a conscious bias and cannot be considered representative. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Learning objective 6: Performing the audit procedures To ensure conclusions arising from tests on audit samples are appropriate, auditor must perform testing on each item selected. If selected item is not appropriate for application of testing procedure, a replacement item can be selected (ASA/ISA 530.9–10). If auditor is unable to perform test on a selected item (e.g. loss of documentation), it is considered to be an error. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Evaluating sample results To evaluate sample results, auditor determines the level of misstatement found in sample and directly projects this misstatement to relevant population. For example: sample 20%, find misstatement of $10 000. Therefore projected misstatement = $50 000 ($10 000/20%). Projected misstatement is then compared with tolerable misstatement for the audit procedure to determine if characteristic of interest can be accepted or rejected. Auditor should consider both the nature and cause of any misstatement or deviations identified. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Learning objective 7: Sampling for tests of controls, attribute sampling Audit sampling is useful for tests of controls, especially involving inspection of source documentation for specific attributes such as evidence of authorisation (attribute sampling). Involves examination of documents for particular attributes related to controls (e.g. authorisation). Results of attribute sampling can be used to support or refute an initial assessment of control risk. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Planning and designing sample for tests of controls Auditor should consider: Audit objectives (assertions of audit interest) Control risk assessment and tolerable deviation rate Allowable risk of over-reliance — allowable risk of assessing control risk too low Expected error — amount of error the auditor expects to find in the population. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Audit objectives A sampling technique that is suitable for tests of controls is attribute sampling. The following steps are necessary in considering the relationship between the sample and the objective of the test: Identify relevant control objectives, policies and procedures that are relevant to restricting substantive tests of the related account balances. Identify population and sample unit. Define the characteristic of interest – so that an attribute either exists or does not exist which means that a control activity has either been complied with or not complied with. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Control risk assessment and tolerable deviation rate Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Reliability factors for assessing required confidence level Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Sample size estimation for attribute sampling Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Sample size estimation for attribute samples (alternative method) An alternative method is to determine sample size by reference to: Table 11.3 (p. 566), for where allowable risk of over- reliance (ARO) is 10% (90% confidence). This ARO is common in practice. Table 11.4 (p. 567), for where allowable risk of over- reliance is 5% (95% confidence). For example, where desired level of assurance is 90%, (Table 11.3), tolerable deviation rate is 10%, and expected deviation rate is 0, required sample size is 22. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Selection of sample items for tests of controls Having determined the appropriate sample size, it is then a matter of determining which sample items to select. The representative selection methods of random selection and systematic selection generally apply to both tests of controls and substantive tests. However, stratification is not usually applicable to tests of controls. Systematic selection is often useful for tests of controls because it helps to achieve the auditor’s internal control objective of testing continuity of controls by ensuring sampling is continuous throughout the year. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Evaluation of attribute sample results Approach in practice is to use sample deviation rate (SDR) as best estimate of population deviation rate. For example, auditor selects 25 items, finds one error => SDR rate is 4%. Auditor compares with tolerable deviation rate (TDR). If SDR ≤ TDR, sample results support auditor’s planned reliance on IC. If SDR > TDR, sample results do not support auditor’s planned reliance on IC. Auditor will need to consider reliance on IC and may consequentially increase substantive testing. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Learning objective 8: Planning for substantive tests The following matters should be considered: Relationship of sample to relevant audit objective (assertion of audit interest) Preliminary judgments about materiality levels Auditor's allowable risk of incorrect acceptance Characteristics of the population Use of other substantive procedures directed at same financial report assertion. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Dollar-unit sampling Sample unit is individual dollar units, not physical units (transactions or balances). A population with $1 000 000 that contains 1000 physical units or accounts is viewed as a population with 1 000 000 sample units. Individual dollar selected is attached to that physical unit or account in which it is contained, and the unit or account will then be tested. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Advantages of dollar-unit sampling (DUS) Directs auditor’s attention to material items. For example, under traditional sampling, debtor A (owing $10 000) and debtor B (owing $1000) have equal chance of selection. Under DUS, debtor A is ten times more likely to be selected and tested. Directs auditor’s attention towards overstatement errors. However, a disadvantage is that it directs auditor’s attention away from understatement errors. Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Determination of sample size for substantive tests For convenience, this is usually presented as: E.g. account balance $1 000 000. Tolerable error $50 000. Expected error is zero and risk of incorrect acceptance is 5%  Reliability factor = 3 (Table 11.5, p. 572) Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Illustration of DUS with systematic selection Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Illustration of DUS with systematic selection (cont.) Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Evaluation of sample results for substantive testing Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett

Learning objective 9: Other statistical sampling approaches Mean per unit estimation Difference estimation Ratio estimation Copyright  2010 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia 4e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett