1. Attributes Sampling in Audits
Dr. Donald K. McConnell Jr.
4/7/2019

2. Attributes Sampling Plans
Used typically to test controls in a controls reliance audit scenario
Results are always in terms of a percentage projection
Do not test dollar amounts
More non-stat than stat sampling is done in practice
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3. Assume the following:
Auditor wants to test controls over cash disbursements for 9 month period 1/2/xx-9/30/xx
What is an attribute?
Auditor must define attributes of interest
N=100,000 checks issued in relevant 9 month period
If auditor “intuitively” wants 90% confidence level, what do you think sample size (n) would be?
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4. The Auditor Must Specify Parameters
Risk of assessing control risk too low [risk of over-reliance on internal controls (ARO or ARACR)]
Tolerable error rate (TER)
Expected population error rate (EPER)
Also first check number issued 1/2/xx and last check number issued 9/30/xx
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5. Common Parameters in Practice
90-5-0, which is interpreted thusly:
ARO=10% [Complement of confidence level is risk of overreliance on IC’s]
TER= 5%
EPER=0% for client with good controls, a common assumption
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6. Issues Concerning Tolerable Error Rates Selected
Low TER’s (e.g 2-3%) selected:
Where IC’s have highly significant effect on account balances, i.e.:
Auditor wants more precise estimate
Tight precision: bigger sample sizes
High TER’s (e.g 5-10%) selected:
Where IC’s have less significant effect on account balances
Provides less precise estimate
Looser precision: smaller sample sizes
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7. Issues Concerning Risk of Overreliance
5% if want high IC’s reliance, resulting in less year end substantive testing
10% if want moderate IC’s reliance
20% if want low IC’s reliance, resulting in more year end substantive testing
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8. Concerning These Parameters:
How does the auditor determine EPER?
Examples:
What was last year’s actual result?
First time audit: pilot sample of 50 (per AICPA industry audit guide)
Does 5% TER bother you?
Why such a high TER?
Huge sample sizes if more precise estimate is wanted!
Year end substantive testing also provides further “utils” of evidence
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9. What Attributes Would We Want to Test? Examples:
Does check number and amount agree with entry in CDJ?
Is check supported by a vendor’s invoice in that amount?
Is there an authorized P.O. signed by purchasing agent?
Is there a receiving report from the dock?
Was check coutersigned if in excess of $xx,xxx?
Was final approval for payment authorized?
Etc.
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10. Let’s do the Test Notebook computer and audit software would be used
What if you are in West Texas and your hard drive crashed!
Resort to tables
Recall test parameters were
T 14-7: Sample size calculation
n=45 checks randomly selected
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11. Evaluating Sample Results
Assume no compliance deviations for 9 of 10 tested attributes (T14-8)
5.0% is “upper bound” or CUER
What does this mean?
We are 90% certain true rate of controls deviations doesn’t exceed 5.0%
Is this acceptable?
Yes, tolerable error (TER) was 5%
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12. Evaluating Sample Results (Con.)
Assume for one check no P.O. could be found
Can we select another check number randomly as substitute?
NO!!!! It’s a compliance deviation
What is projected error rate upper bound?
8.4%
Is this acceptable?
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13. What Options do we Have? Expand sample size?
In real world, probably wouldn’t unless clearly due to sampling error
Unless sampling error, very likely to find at least one more check with no supporting P.O.
What if we expanded sample size?
What would sample size need to be?
What if we found one more “no P.O. item”
6.5% (assuming sample expanded by 35 checks): still unacceptable
Many auditors would “drop back ten and punt,” alternatively expanding substantive testing in the area
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14. Some Final Points
Note instances in Hillsburg Hardware Case (Fig. 14-5) where CUER exceeded TER
Attributes 2,4,5, and 8
Nature, timing, and extent of testing modified, as demonstrated in Fig. 14-6
However, note treatment of attribute 6 (where CUER<TER): an example of point in Au
4/7/2019