Chapter 9Chapter 9
Audit Sampling:An Application toSubstantive Testsof AccountBalancesAudit Sampling:An Application toSubstantive Testsof AccountBalances
McGraw-Hill/Irwin
Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.
Substantive Tests of Details ofAccount BalancesSubstantive Tests of Details ofAccount Balances
The statistical concepts we discussed in the lastchapter apply to this chapter as well. Three importantdeterminants of sample size are The statistical concepts we discussed in the lastchapter apply to this chapter as well. Three importantdeterminants of sample size are
1.Desired confidence level.1.Desired confidence level.
2.Tolerable misstatement.2.Tolerable misstatement.
3.Estimated misstatement.3.Estimated misstatement.
Population plays a bigger role in some of the samplingtechniques used for substantive testing.Population plays a bigger role in some of the samplingtechniques used for substantive testing.
Misstatements discovered in the audit sample must beprojected to the population, and there must be anallowance for sampling risk. Misstatements discovered in the audit sample must beprojected to the population, and there must be anallowance for sampling risk.
The statistical concepts we discussed in the lastchapter apply to this chapter as well. Three importantdeterminants of sample size are The statistical concepts we discussed in the lastchapter apply to this chapter as well. Three importantdeterminants of sample size are
1.Desired confidence level.1.Desired confidence level.
2.Tolerable misstatement.2.Tolerable misstatement.
3.Estimated misstatement.3.Estimated misstatement.
Population plays a bigger role in some of the samplingtechniques used for substantive testing.Population plays a bigger role in some of the samplingtechniques used for substantive testing.
Misstatements discovered in the audit sample must beprojected to the population, and there must be anallowance for sampling risk. Misstatements discovered in the audit sample must beprojected to the population, and there must be anallowance for sampling risk.
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Substantive Tests of Details ofAccount BalancesSubstantive Tests of Details ofAccount Balances
Consider the following information about the inventoryaccount balance of an audit client:
The ratio of misstatement in the sample is 2%($2,000 ÷ $100,000)The ratio of misstatement in the sample is 2%($2,000 ÷ $100,000)
The ratio of misstatement in the sample is 2%($2,000 ÷ $100,000)The ratio of misstatement in the sample is 2%($2,000 ÷ $100,000)
Applying the ratio to the entire population produces a bestestimate of misstatement of inventory of $60,000.($3,000,000 × 2%)
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Substantive Tests of Details ofAccount BalancesSubstantive Tests of Details ofAccount Balances
The results of our audit test depend uponthe tolerable misstatement associatedwith the inventory account. If the tolerablemisstatement is $50,000, we cannotconclude that the account is fairly statedbecause our best estimate of theprojected misstatement is greater thanthe tolerable misstatement. The results of our audit test depend uponthe tolerable misstatement associatedwith the inventory account. If the tolerablemisstatement is $50,000, we cannotconclude that the account is fairly statedbecause our best estimate of theprojected misstatement is greater thanthe tolerable misstatement.
The results of our audit test depend uponthe tolerable misstatement associatedwith the inventory account. If the tolerablemisstatement is $50,000, we cannotconclude that the account is fairly statedbecause our best estimate of theprojected misstatement is greater thanthe tolerable misstatement. The results of our audit test depend uponthe tolerable misstatement associatedwith the inventory account. If the tolerablemisstatement is $50,000, we cannotconclude that the account is fairly statedbecause our best estimate of theprojected misstatement is greater thanthe tolerable misstatement.
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Monetary-Unit Sampling (MUS)Monetary-Unit Sampling (MUS)
MUS uses attribute-sampling theory toexpress a conclusion in dollar amounts ratherthan as a rate of occurrence. It is commonlyused by auditors to test accounts such asaccounts receivable, loans receivable,investment securities, and inventory.MUS uses attribute-sampling theory toexpress a conclusion in dollar amounts ratherthan as a rate of occurrence. It is commonlyused by auditors to test accounts such asaccounts receivable, loans receivable,investment securities, and inventory.
MUS uses attribute-sampling theory toexpress a conclusion in dollar amounts ratherthan as a rate of occurrence. It is commonlyused by auditors to test accounts such asaccounts receivable, loans receivable,investment securities, and inventory.MUS uses attribute-sampling theory toexpress a conclusion in dollar amounts ratherthan as a rate of occurrence. It is commonlyused by auditors to test accounts such asaccounts receivable, loans receivable,investment securities, and inventory.
![MCBD04969_0000[1]](data/images/img8.png)
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Steps in MUSSteps in MUS
![MPj01783750000[1]](data/images/img10.png)
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Steps in MUSSteps in MUS
Sampling may be used for substantive testing to:
1.Test the reasonableness of assertions about afinancial statement amount (i.e., accuracy,existence). This is the most common use of samplingfor substantive testing.
2.Develop an estimate of some amount.
Sampling may be used for substantive testing to:
1.Test the reasonableness of assertions about afinancial statement amount (i.e., accuracy,existence). This is the most common use of samplingfor substantive testing.
2.Develop an estimate of some amount.
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Steps in MUSSteps in MUS
For MUS the population is defined as themonetary value of an account balance,such as accounts receivable, investmentsecurities, or inventory.
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Steps in MUSSteps in MUS
An individual dollar represents the sampling unit.
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Steps in MUSSteps in MUS
A misstatement is defined as the difference betweenmonetary amounts in the client’s records andamounts supported by audit evidence.
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Steps in MUSSteps in MUS
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Steps in MUSSteps in MUS
The auditor selects a sample for MUS by using asystematic selection approach called probability-proportional-to-size selection. The sampling interval canbe determined by dividing the book value of thepopulation by the sample size. Each individual dollar inthe population has an equal chance of being selectedand items or “logical units” greater than the interval willalways be selected.
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Steps in MUSSteps in MUS
Assume a client’s book value of accounts receivable is $2,500,000, and theauditor determined a sample size of 93. The sampling interval will be$26,882 ($2,500,000 ÷ 93). The random number selected is $3,977, so theauditor would select the following items for testing:
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Steps in MUSSteps in MUS
After the sample items have been selected,the auditor conducts the planned auditprocedures on the logical units containingthe selected dollar sampling units.
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Steps in MUSSteps in MUS
The misstatements detected in the samplemust be projected to the population. Let’s lookat the following example:
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Steps in MUSSteps in MUS
Misstatements DetectedMisstatements DetectedIn the sample of 93 items, the following misstatementswere found:
$3,284 ÷ $21,893 = 15%$3,284 ÷ $21,893 = 15%
$3,284 ÷ $21,893 = 15%$3,284 ÷ $21,893 = 15%
Because the Axa balance of $32,549 is greater than theinterval of $26,882, no sampling risk is added. Since allthe dollars in the large accounts are audited, there is nosampling risk associated with large accounts.
Because the Axa balance of $32,549 is greater than theinterval of $26,882, no sampling risk is added. Since allthe dollars in the large accounts are audited, there is nosampling risk associated with large accounts.
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Steps in MUSSteps in MUS
Computed Upper Misstatement LimitComputed Upper Misstatement LimitWe compute the upper misstatement limit by calculating basicprecision and ranking the detected misstatements based onthe size of the tainting factor from the largest to the smallest.
(0.15 × $26,882 × 1.4 = $5,645)(0.15 × $26,882 × 1.4 = $5,645)
(0.15 × $26,882 × 1.4 = $5,645)(0.15 × $26,882 × 1.4 = $5,645)
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Steps in MUSSteps in MUS
Basic Precision using the TableBasic Precision using the TableIf no misstatements are found in the sample,the best estimate of the populationmisstatement would be zero dollars.
$26,882 × 3.0 = $80,646 upper misstatement limit$26,882 × 3.0 = $80,646 upper misstatement limit
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Steps in MUSSteps in MUS
We compare the tolerable misstatement to the uppermisstatement limit. If the upper misstatement limit is lessthan or equal to the tolerable misstatement, we concludethat the balance is not materially misstated.We compare the tolerable misstatement to the uppermisstatement limit. If the upper misstatement limit is lessthan or equal to the tolerable misstatement, we concludethat the balance is not materially misstated.
We compare the tolerable misstatement to the uppermisstatement limit. If the upper misstatement limit is lessthan or equal to the tolerable misstatement, we concludethat the balance is not materially misstated.We compare the tolerable misstatement to the uppermisstatement limit. If the upper misstatement limit is lessthan or equal to the tolerable misstatement, we concludethat the balance is not materially misstated.
In our example, the final decision iswhether the accounts receivable balanceis materially misstated or not.
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Steps in MUSSteps in MUS
In our example, the upper misstatement limit of $150,621is greater than the tolerable misstatement of $125,000, sothe auditor concludes that the accounts receivablebalance is materially misstated.
When faced with this situation, the auditor may:
1.Increase the sample size.
2.Perform other substantive procedures.
3.Request the client adjust the accounts receivable balance.
4.If the client refuses to adjust the account balance, theauditor would consider issuing a qualified or an adverseopinion.
When faced with this situation, the auditor may:
1.Increase the sample size.
2.Perform other substantive procedures.
3.Request the client adjust the accounts receivable balance.
4.If the client refuses to adjust the account balance, theauditor would consider issuing a qualified or an adverseopinion.
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Risk When Evaluating AccountBalancesRisk When Evaluating AccountBalances
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Effect of UnderstatementMisstatementsEffect of UnderstatementMisstatements
MUS is not particularly effective at detectingunderstatements. An understated account is less likely to beselected than an overstated account.
The most likely error will be reduced by $2,688(– 0.10 × $26,882)The most likely error will be reduced by $2,688(– 0.10 × $26,882)
The most likely error will be reduced by $2,688(– 0.10 × $26,882)The most likely error will be reduced by $2,688(– 0.10 × $26,882)
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