Kế toán, kiểm toán - Chapter 11: Audit sampling

CHAPTER 11AUDIT SAMPLING1Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettAUDIT SAMPLING DEFINEDAudit sampling is 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/ISA 5302Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettIMPORTANCE OF AUDIT SAMPLINGAudit sampling is important because itprovides information on:How many items to examineWhich items to selectHow sample results are evaluated and extrapolated to the population3Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettSAMPLING RISK DEFINEDSampling risk is 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).4Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettNON-SAMPLING RISK DEFINEDNon-sampling risk arises from factors otherthan sample size that cause an auditor toreach an incorrect conclusion, such as the possiblility that:The the auditor will fail to recognise misstatements included in examined itemsThe auditor will therefore apply a procedure that is not effective in achieving a specific objective5Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettCHARACTERISTIC OF INTERESTWhen sampling, the auditor identifies a particular characteristic of the population to focus on.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.6Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettVARIOUS MEANS OF GATHERING AUDIT EVIDENCE100% 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 be representative of the population.Audit sampling.7Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettSTATISTICAL SAMPLING DEFINEDAny approach to sampling that has thefollowing 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 overnon-statistical sampling methods is defensibility,through quantification of sampling risk. Ref.: AUS 514.10 / ISA 530.108Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettNON-STATISTICAL SAMPLINGDefined as all sampling approaches that do 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/ISA 530 apply equally to both statistical and non-statistical sampling.9Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettPLANNING AND DESIGNING THE SAMPLEAuditor must consider:Objectives of the audit testPopulation from which to samplePossible use of stratificationDefinition of the sampling unit10Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettDEFINING THE AUDIT OBJECTIVE AND POPULATIONOnce 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.11Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettSTRATIFICATIONOccurs when the auditor divides the population into a series of sub-populations, each of which has an identifying characteristic, such as dollar value.Stratifying the population 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.12Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettDEFINING THE SAMPLING UNITSampling unit is commonly the:Transactions or balances making up the account balance; orIndividual dollars that make up an account balance or class of transactions, commonly referred to as Probability Proportionate to Size Sampling (PPS) or Dollar Unit Sampling (DUS).13Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettDETERMINING SAMPLE SIZESample 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.14Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettSAMPLE SIZE FOR TESTS OF CONTROLSFactorEffect on sample size1. An increase in the auditor’s intended reliance on the accounting and internal control structureIncrease2. An increase in the rate of deviation from the prescribed control procedure that the auditor is willing to accept (tolerable error)Decrease3. An increase in the rate of deviation from the prescribed control procedure that the auditor expects to find in the population (expected error)Increase4. An increase in the auditor’s required confidence level (or, conversely, a decrease in the auditor’s allowable risk of over-reliance)Increase5. An increase in the number of sampling units in the populationNegligible effect(Ref.: Table 11.1, p. .504)15Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettFACTORS THAT INFLUENCE SAMPLE SIZE FOR SUBSTANTIVE TESTINGFactorEffect on sample size1 An increase in the auditor’s assessment of inherent riskIncrease2 An increase in the auditor’s assessment of control riskIncrease3 An increase in the use of other substantive procedures directed at the same financial report assertionDecrease4 An increase in the auditor’s required confidence level (or, conversely, a decrease in the risk that the auditor will conclude that a material error does not exist when in fact it does)Increase5 An increase in the total error that the auditor is willing to accept (tolerable error)Decrease6 An increase in the errors the auditor expects to find in the population (expected error)Increase7 Stratification of the population when appropriateDecrease8 The number of the sampling units in the populationNegligible Effect(Ref.: Table 11.2, p. .506)16Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettSELECTING THE SAMPLETo draw conclusions about population or strata, the sample needs to be typical of characteristics of population or strata.Sample needs to be selected without bias so that all sampling units in the population or strata have a chance of selection.Common sampling techniques are:Random selection — random number generationSystematic selectionHaphazard selection — select without conscious bias17Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettSTEPS IN SYSTEMATIC SELECTIONFor example, suppose the sample size is 20 and the numberof 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, 9717.18Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettPERFORMING THE AUDITPROCEDURESTo 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.If auditor is unable to perform test on selected item (e.g. loss of documentation), it is considered to be an error.19Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettEVALUATING SAMPLE RESULTSTo evaluate sample results, auditor determines level of error found in sample and projects this error to relevant population.Projected error 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.20Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettSAMPLING FOR TESTS OF CONTROLS, IN PARCTICULAR, ATTRIBUTE SAMPLINGAudit 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. 21Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettPLANNING AND DESIGNING SAMPLES FOR TESTS OF CONTROLSAuditor should consider:Audit objectivesTolerable error — maximum error rate that would still support control risk assessmentAllowable risk of over-reliance — allowable risk of assessing control risk too lowExpected error — known characteristics of the population22Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettRELIABILITY FACTORS FOR ASSESSING REQUIRED CONFIDENCE LEVEL23Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettSAMPLE SIZE ESTIMATION FOR ATTRIBUTE SAMPLES: AN EXAMPLE24Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettSAMPLE SIZE ESTIMATION FOR ATTRIBUTE SAMPLES (alternative method)An alternative method is to determine samplesize by reference to: Table 11.5 (p. 515), for allowable risk of over-reliance (ARO) is 10% (90% confidence). This ARO is common in practice. Table 11.6 (p. 515), for allowable risk of over-reliance is 5% (95% confidence).25Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettEVALUATION OF ATTRIBUTE SAMPLE RESULTSApproach 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 Reliability factor = 3 (Table 11.4, p. 514)30Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettILLUSTRATION OF DUS USING SYSTEMATIC SAMPLING WITH A DOLLAR-INTERVAL I(Ref.: Example 11.4, p. 522) Invoice no. Amount of item Cumulative total A1001 $ 6 000 $ 6 000 A1002 1 000 7 000 A1003 15 000 22 000 A1004 5 000 27 000 A1005 12 000 39 000 A1006 10 000 49 000 A1007 9 000 58 000 A1008 17 000 75 000 A1009 11 000 86 000 A1010 8 000 94 000 A1011 7 000 101 000 • • • • • • • • •(continues)31Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettILLUSTRATION OF DUS USING SYSTEMATIC SAMPLING WITH A DOLLAR-INTERVAL II Population size (BV) $1 000 000 Sample size (n) 60 Sampling interval (SI) ($1 000 000 / 60) $16 667 Random start (RS) $14 068 Items selected $ Invoice no. Amount $ RS $14 068 A1003 $15 000 RS + SI 30 735 A1005 12 000 RS + 2SI 47 402 A1006 10 000 RS + 3SI 64 069 A1008 17 000 RS + 4SI 80 736 A1009 11 000 RS + 5SI 97 403 A1011 7 000    • • • •    • • • •    • • • •32Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettEVALUATION OF SAMPLE RESULTS FOR SUBSTANTIVE TESTING33Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger SimnettOTHER STATISTICAL SAMPLING APPROACHESMean per unit estimationDifference estimationRatio estimation34Copyright  2003 McGraw-Hill Australia Pty Ltd PPTs t/a Auditing and Assurance Services in Australia by Gay & SimnettSlides prepared by Roger Simnett