ISA 11 kiểm tra chọn mẫu

Chapter 11 Audit Sampling Copyright  2006 McGraw-Hill Australia Pty Ltd 11- Learning Objective 1: Definition and Features • Audit sampling: the application of an audit procedure to less than 100 per cent of the items within a population to obtain audit evidence about particular characteristics of the population • Ref.: AUS 514/ASA 530 (ISA 530) Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-2 Importance of audit sampling • 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 Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-3 Sampling risk defined • Sampling risk: the probability that the auditor has reached an incorrect conclusion because audit sampling was used rather than 100 per cent examination (i.e correctly chosen sample was not representative of the population) Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-4 Non-sampling risk defined • Non-sampling risk: arises from factors other than sample size that cause an auditor to reach an incorrect conclusion, such as the possiblility that: – – The the auditor will fail to recognise misstatements included in examined items; The auditor will therefore apply a procedure that is not effective in achieving a specific objective Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-5 Characteristics 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  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-6 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  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-7 Statistical sampling defined • Statistical Sampling: any approach to sampling that has the following characteristics: (a)Random sample selection; and (b)Use of probability theory to evaluate sample results, including measurement of sampling risk • Major advantage of statistical sampling over nonstatistical sampling methods is defensibility, thorough quantification of sampling risk • Ref.: AUS 514.10/ASA 530.13 (ISA 530.10) Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-8 Non-statistical sampling • Non-statistical sampling: all sampling approaches that not have all the characteristics of statistical sampling • Major advantage of non-statistical sampling is greater application of audit experience • The basic principles and essential procedures identified in AUS 514/ASA 530 (ISA 530) apply equally to both statistical and non-statistical sampling Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-9 Learning Objective 3: Planning and Designing the Sample • Auditor must consider: – – – – Objectives of the audit test; Population from which to sample; Possible use of stratification; and Definition of the sampling unit Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-10 Evaluating sample results • To evaluate sample results, auditor determines the level of error found in sample and directly projects this error to relevant population e.g Sample 20%, find misstatement of $10,000 Therefore projected error = $50,000 ($10,000/20%) • Projected error is then compared with tolerable error 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 errors identified Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-20 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  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-21 Planning and designing sample for tests of controls • Auditor should consider: – – – – Audit objectives Tolerable error – maximum error rate that would still support control risk assessment 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  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-22 Reliability factors for assessing required confidence level Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-23 Sample size estimation for attribute sampling Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-24 Sample size estimation for attribute samples (alternative method) • An alternative method is to determine sample size by reference to: – – Table 11.5 (p 532), for where allowable risk of overreliance (ARO) is 10% (90% confidence) This ARO is common in practice Table 11.6 (p 532), for where allowable risk of overreliance is 5% (95% confidence) Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-25 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 internal control • This approach is consistent with standards and practice but is subject to criticism as it does not account for sample size or sample risk Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-26 Learning Objective 8: Sampling for Substantive Tests • The following matters should be considered: – – – – – Relationship of sample to relevant audit objective; Preliminary judgments about materiality levels; Auditor's allowable risk of incorrect acceptance; Characteristics of the population; and Use of other substantive procedures directed at same financial report assertion Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-27 Dollar-unit sampling • Sample unit is individual dollar units, not physical units (transactions or balances) A population with $1,000,000 that contains 1,000 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, which will then be tested Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-28 Advantages of dollar-unit sampling (DUS) • Directs auditor’s attention to material items E.g 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  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-29 Determination of sample size for substantive tests n = R reliability factor = TE  BV tolerable error  book value For convenience, this is usually presented as: n = BV x R TE E.g account balance $1,000,000 Tolerable error $50,000 Expected error is zero and risk of incorrect acceptance is 5%  Reliability factor = (Table 11.4, p 531) 1,000,000 x Sample Size  60 50,000 Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-30 Illustration of DUS with systematic selection Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-31 Illustration of DUS with systematic selection (Cont.) Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-32 Evaluation of sample results for substantive testing Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-33 Learning Objective 9: Other statistical sampling approaches • Mean per unit estimation; • Difference estimation; and • Ratio estimation Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-34 ... McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett Slides prepared by Roger Simnett 11-11 Stratification • Stratification:... sample results are evaluated and extrapolated to the population Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger... sampling risk • Ref.: AUS 514.10/ASA 530.13 (ISA 530.10) Copyright  2006 McGraw-Hill Australia Pty Ltd Revised PPTs t/a Auditing and Assurance Services in Australia 3e by Grant Gay and Roger Simnett