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Audit Sampling Concepts
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Importance of Sampling
Auditor does not look at everything How does this affect the opinion? Auditor CANNOT look at everything Why?
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Purpose of Sampling The auditor examines only a portion of the population in order to estimate How much is a portion?
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When to Do Sampling When:
The nature and materiality of the balance or class of transactions does not demand a 100% audit A decision must be made about the balance or class of transactions. The time and cost to audit 100% of the population would be too great
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When is Sampling Used? To conduct: Walk through tests
For tests of controls Tests of details
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Representative Sampling
Having a representative sample is important What does representative mean?
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Non-sampling risk: Sampling risk:
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Statistical Sampling Uses the laws of probability for selecting and evaluating a sample from a population Selected at random Statistical calculations are used
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Statistical vs. Non-Statistical
Similarities Both require a structured process The use of stratification Differences Sampling risk cannot be quantified
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Non-Probabilistic Sample Selection Methods
Directed sample selection When used? Auditor often able to identify items likely to contain errors Items containing selected characteristics Large dollar item coverage
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Block sample selection
A selection of several items in a sequence Reasonable number of blocks must be chosen Haphazard sample selection Auditor goes through the population and haphazardly selects items
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Probabilistic Sample Selection Methods
Sampling risk requires Simple random sample selection Every member of the population has an equal chance of being selected Systematic sample selection Auditor calculates an interval and use the interval to select sample
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Major problem with systematic sampling is bias
Once the first item is chosen No problem if But some characteristics
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Probability Proportionate-to-Size Sampling Methodology
A key statistical methodology also known as the sampling unit is MUS allows the result to be stated
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Attribute Sampling Methodology Another key statistical methodology
very useful for tests of controls The main question to be answered is If the auditor can allow 5% deviations
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Advantages of Statistical Sampling
Provides: for quantitative evaluation of the sample results a more defensible expression of the test results It is more objective
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Disadvantages of Statistical Sampling
Requires random sample selection which may be more costly and time consuming. Might require additional training costs for staff members to use statistics or specialized software
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Advantages of non-statistical sampling
Allows the auditor to inject his or her subjective judgment in determining the sample size May be designed so that it is equally effective and efficient as statistical sampling while being less costly
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Disadvantages of non-statistical sampling
Cannot draw objectively valid statistical inferences from the sample results Cannot quantitatively measure and express sampling risk.
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The Main Phases of the Sampling Process
Both statistical and non-statistical methods 1. Planning the sample 2. Selecting the sample Performing the tests Evaluating the results
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Sampling Process Fourteen steps in the sampling process.
Look at tests of controls versus tests of details
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1. State the Objectives of the Test
Test of control: Are the controls working as specified? Are there monetary errors or fraud or other irregularities Test of detail: Auditor wants to determine the maximum amount of overstatement and understatement that could exist based on the sample
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2. Decide if Audit Sampling Applies
Test of control: some controls can be sampled others cannot be Test of detail: sampling test of details depends on the nature of the population high volume can be
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3. Define attributes and exception or error conditions
Planning term: Test of control Test of detail Define the item of interest Identify the characteristic or attribute of interest Individual dollars Define exceptions or errors Define the control deviation or exception Normally, any monetary difference or error
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4. Define the population Population can be defined in a way to suit the audit tests Must sample from the entire population as defined In testing controls over sales, what is the population? In testing details in accounts receivable it is the recorded dollar population Most populations can be stratified, if needed.
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5. Define the sampling unit
Tests of controls: Usually a physical unit Test of detail: If MUS If non-statistical sampling
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6. Specify tolerable exception rate (TER) or specify materiality
Test of control TER` As TER increases Test of detail Materiality is used These decisions require the use of
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7. Specify ARACR or ARIA Test of control What is ARACR?
Acceptable Risk of Assessing Control Risk Too Low Test of detail What is ARIA? Acceptable Risk of Incorrect Acceptance
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If ARIA changes from 10% to 5%
Test of control Assume TER 6% ARACR 10% But unknown to the auditor the true error rate is 8% Test of detail If ARIA changes from 10% to 5% Since assurance required increases When controls are good
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8. Estimate population exception rate or misstatements
Test of control Estimated population error rate (EPER) The lower the EPER, the smaller the sample size Test of detail Provide an advance estimate of the total dollar error, i.e. misstatements, in the population
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9. Determine the initial sample size
For non-statistical or judgmental sampling, professional judgment is used to calculate the sample size For statistical sampling, mathematical formulae are used, either in specially prepared tables or using software designed for audit sampling For stratified sampling, the sample is allocated among the strata
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10. Select the sample Using the number of items determined in Step #9, choose the items from the population using the sampling unit defined in Step #5 Use probabilistic or non-probabilistic methods To enable quantification of sampling risk, probabilistic, i.e. statistical, methods must be used
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11. Perform the audit procedures
For test of controls, examine each item for the attribute defined in Step #3, recording all exceptions found For test of details, apply the audit procedures designed in the audit program
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12. Generalize from the sample to the population
Test of controls sample error rate (SER) But that is not necessarily equal to the actual population rate In practice, auditors tend to test controls when they expect no exceptions But ultimately, the method of generalization depends on the sampling methodology used
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When generalizing tests of details, auditors deal with
Misstatements found are projected from the sample results to the population Auditor must calculate a point estimate
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To calculate the point estimate:
(Client Misstatement / Recorded Value of Sample) x Recorded Book Value of the Population Thus for a misstatement of $500 in A/R with a sample value of $10,000 and a total book value of $25,000 Note that if the population is divided into strata The total point estimate may not be an adequate result for the population The auditor must consider this fact
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Example of Point Estimate Calculation x =
Calculating Point Estimate for a population Example of Errors Found Dollars Audited Stratum Sample Size Book Value of Stratum Recorded Value Audited Value Client Misstatement 1 3 $88,955 $91,695 $(2,740) 2 6 71,235 43,995 43,024 971 47,105 13,105 10,947 2,158 Total 15 $207,295 $146,055 $145,666 $389 Example of Point Estimate Calculation Stratum Client Misstatement / Recorded Value from Sample x Recorded Book Value for Stratum = Point Estimate of Misstatement 1 $(2,740)/$88,955 $88,955 $(2,470) 2 971/43,995 71,235 1,572 3 2,158/13,105 47,105 7,757 Total $6,589
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13. Analyze exceptions or misstatements
Test of control What breakdown in internal controls caused the exceptions? Should additional substantive testing be conducted because of these results? Test of detail Were the misstatements caused by control exceptions? Is additional substantive testing required?
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14. Decide the acceptability of the population
Test of control If TER is sufficiently larger than SER If TER – SER is too small Test of detail Compare the difference between the projection to the population If projection is greater than materiality level
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What if the auditor decides the population is NOT acceptable
What if the auditor decides the population is NOT acceptable? What to do? 1. Revise TER (tolerable error rate), ARACR, or ARIA (the risks of accepting incorrect populations) 2. Expand the sample size. 3. Revise assessed control risk. 4. Report weaknesses in management letter.
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Problem 11-22, p. 357 For the examination of the financial statements of Scotia Inc., Rosa Schellenberg, a public accountant, has decided to apply non-statistical audit sampling in the tests of sales transactions. Based on her knowledge of Scotia’s operations in the area of sales, she decides that the estimated population deviation rate is likely to be 3 percent and that she is willing to accept a 5 percent risk the true population rate is not greater than 6 percent. Given this information, Rosa selects a random sample of 150 sales invoices from the 5,000 prepared during the year and examines them for exceptions. She notes the following exceptions in her working papers. There is no other documentation. REQUIRED Which of the invoices in the table should be defined as an exception? Explain why it is inappropriate to set a single acceptable TER and EPER for the combined exceptions. State the appropriate analysis of exceptions for each of the exceptions in the sample. Invoice No: Comment 5028 Sales invoice had incorrect price, but a subsequent credit not was sent out as a correction. 6791 Voided sales invoice examined by auditor. 6810 Shipping document for a sale of merchandise could not be located. 7364 Sales invoice for $2,875 has not been collected and is six months past due. 7625 Client unable to locate the printed duplicate copy of the sales invoice. 8431 Invoice was dated three days later than the date of the shipping document. 8528 Customer purchase order is not attached to the duplicate sales invoice. 8566 Billing is for $100 less than it should be due to a pricing error. 8780 9169 Credit is not authorized, but the sale was only for $7.65.
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Problem 11-25, page 358 You have just completed the accounts receivable confirmation process in the audit of Danforth paper Company Ltd., a paper supplier to retail shops and commercial users. Following are the data related to the process: Accounts receivable recorded balance $2,760,000 Number of accounts ,320 A non-statistical sample was taken as follows: All accounts over $10,000 (23 accounts) $465,000 77 accounts under $10, $81,500 Materiality $100,000 Inherent and control risk are both high No relevant analytical procedures were performed. The table below gives the results of the confirmation procedures REQUIRED Evaluate the results of the non-statistical sample. Consider both the direct implications of the misstatements found and the effect of using a sample.
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Recorded Value Audited Value Items over $10,000 $465,000 $432,000 Items under $10,000 81,500 77,150 Individual misstatements for items under $10,000 Item 12 5,120 4,820 Item 19 485 385 Item 33 1,250 250 Item 35 3,975 3,875 Item 51 1,850 1,825 Item 59 4,200 3,780 Item 74 2,405 19,285 14,935
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Problem (p.357) You have been asked to do planning for statistical testing of the audit of cash receipts. Following is a partial audit program for the audit of cash receipts. Review the cash receipts journal for large and unusual transactions. Trace entries from the prelisting of cash receipts to the cash receipts journal to determine whether each is recorded. Compare customer name, date, and amount on the prelisting with the cash receipts journal. Examine the related remittance advice for entries selected from the prelisting to determine whether cash discounts were approved. Trace entries from the prelisting to the deposit slip to determine whether each has been deposited. REQUIRED Identify which audit procedures can be tested using attribute sampling. Justify your response. State the appropriate sampling unit for each of the tests in part (a). Define the attributes that you would test for each of the tests in part (a). State the audit object associated with each of the attributes. Define exception conditions for each of the attributes that you have described in part (c). Which of the exceptions would be indicative of potential fraud? Justify your response.
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Problem 12-24, page 404 Lenter Supply Corp. is a medium sized distributor of wholesale hardware supplies in southern Manitoba. It has been a client of yours for several years and has instituted excellent internal control for the control of sales, at your recommendation. In providing control over shipments, the client has prenumbered “warehouse removal slips” that are used for every sale. It is company policy never to remove goods from the warehouse without an authorized warehouse removal slip. After shipment, two copies of the warehouse removal slip are sent to billing for the computerized preparation of a sales invoice. One copy is stapled to the duplicate copy of the prenumbered sales invoice, and the other copy is filed numerically. In some cases more than one warehouse removal slip is used for billing one sales invoice. The smallest warehouse removal slip number for the year is and the largest is The smallest invoice number is and the largest is In the audit of sales, one of the major concerns is the effectiveness of the control in making sure all shipments are billed. The auditor has decided to use attribute sampling in testing internal control.
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State an effective audit procedure for testing whether shipments have been billed. What is the sampling unit for the audit procedure? Assuming the auditor expects no deviations in the sample but is willing to accept a TDR of 3%, at a 10% ARACR, what is the appropriate sample size?
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TOLERABLE DEVIATION RATE (IN PERCENTAGE) 2 3 4 5 6 7 8 9 10 15 20
EXPECTED POPULATION DEVIATION RATE (IN PERCENTAGE) TOLERABLE DEVIATION RATE (IN PERCENTAGE) 2 3 4 5 6 7 8 9 10 15 20 5 PERCENT RISK OF OVER RELIANCE (ARACR) 0.00 149 99 74 59 49 42 36 32 29 19 14 0.25 236 157 117 93 78 66 58 51 46 30 22 0.50 . 0.75 208 1.00 156 1.25 124 1.50 192 103 1.75 227 153 88 77 2.00 181 127 68 2.25 61 2.50 150 109 2.75 173 95 3.00 195 129 84 3.25 148 112 3.50 167 76 40 3.75 185 100 4.00 146 89 5.00 158 116 6.00 179 50 7.00 37
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10 PERCENT RISK OF OVER RELIANCE (ARACR)
2 3 4 5 6 7 8 9 10 15 20 10 PERCENT RISK OF OVER RELIANCE (ARACR) 0.00 114 76 57 45 38 32 28 25 22 11 0.25 194 129 96 77 64 55 48 42 18 0.50 0.75 265 1.00 . 176 1.25 221 132 1.50 105 1.75 166 88 2.00 198 75 2.25 65 2.50 158 110 58 2.75 209 94 52 3.00 3.25 153 113 82 3.50 73 3.75 131 98 4.00 149 4.50 218 130 87 34 5.00 160 115 78 5.50 142 103 6.00 182 116 7.00 199 7.50 8.00 60 8.50 68 EPDR
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Effect of population size -Initial sample size only
-Possible to make adjustment to initial sample size based on overall population size -Finite correction factor n = revised sample size n’ = initial sample size N = population size n = n’ 1 + n’/N
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From the problem 12-24 Population is n’ = Thus revised sample size is
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Use of a random number table
A one-to-one correspondence between warehouse removal slip How is this correspondence achieved?
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Population of Warehouse Removal Slips
37039 97547 64673 31546 99314 66854 97855 25145 84834 23009 51584 66754 77785 52357 98433 54725 18864 65866 76918 78825 58210 97965 68548 81545 82933 93545 85959 63282 78049 67830 14624 17563 25697 07734 48243 50203 25658 91478 08509 23308 48130 65047 40059 67825 18934 64998 49807 71126 77818 84350 67241 54031 34535 04093 35062 58163 30954 51637 91500 48722 60988 60029 60873 86723 36464 98305 08009 00666 29255 18514 50188 22554 86160 92250 14021 65859 16237 50014 00463 13906 35936 71761 95755 87002 66023 21428 14742 94874 58533 26507 04458 61862 63119 09541 01715 87901 91260 57510 36314 30452 09712 37714 95482 30507 43373 58939 95848 28288 60341 52174 11879 61500 12763 64433 02268 57905 72347 49498 78938 71312 99705 71546 42274 23915 38405 64257 93218 35793 43671 64055 88729 11168 56864 21554 70445 24841 04779 56774 96129 35314 29631 06937 54545 04470 75463 77112 40704 48823 65963 39359 12717 56201 22811 07318 44623 02843 33299 59872 86774 06926 94550 23299 45557 07923 75126 00808 01312 34348 81191 21027 77087 10909 03676 97723 92277 57115 50789 68111 75305 53289 39751 56093 58302 52236 65756 50273 61566 61962 16623 17849 96701 94971 94758 08845 32260 50848 93982 66451 32143 05441 10399 17775 48006 58200 58367 66577 68583 21108 41361 56640 27890 28825 96509 21363 53657 60119 Population of Warehouse Removal Slips 14,682 – 37,521 Random Stab Random Number Table
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Computed Upper Exception Rate
Sample size = TER = ARACR = Number of deviations = Using the following tables: CUER = Are the controls working?
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ACTUAL NUMBER OF DEVIATIONS FOUND 1 2 3 4 5 6 7 8 9 10
Table 14-10 SAMPLE SIZE ACTUAL NUMBER OF DEVIATIONS FOUND 1 2 3 4 5 6 7 8 9 10 5 PERCENT RISK OF OVER RELIANCE 25 11.3 17.6 . 30 9.5 14.9 19.5 35 8.2 12.9 16.9 40 7.2 18.3 45 6.4 10.1 13.3 16.3 19.2 50 5.8 9.1 12.1 14.8 17.4 19.9 55 5.3 8.3 11.0 13.5 15.9 18.1 60 4.9 7.7 12.4 14.6 16.7 18.8 65 4.5 7.1 9.4 11.5 15.5 19.3 70 4.2 6.6 8.7 10.7 12.6 14.4 16.2 18.0 19.7 75 3.9 6.2 10.0 11.8 15.2 18.4 20.0 80 3.7 11.1 12.7 14.3 15.8 17.3 90 3.3 5.2 6.8 8.4 9.9 14.1 16.8 100 3.0 4.7 7.6 8.9 10.2 14.0 16.4 125 2.4 6.1 9.3 10.3 12.2 13.2 150 2.0 3.1 4.1 5.1 6.0 6.9 8.6 200 1.5 2.3 3.8 6.5
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1 2 3 4 5 6 7 8 9 10 Sample size ACTUAL NUMBER OF DEVIATIONS FOUND .
1 2 3 4 5 6 7 8 9 10 10 PERCENT RISK OF OVER RELIANCE 20 10.9 18.1 . 25 8.8 14.7 19.9 30 7.4 12.4 16.8 35 6.4 10.7 14.5 40 5.6 9.4 12.8 15.9 19.0 45 5.0 8.4 11.4 14.2 17.0 19.6 50 4.5 7.6 10.3 12.9 15.4 17.8 55 4.1 6.9 11.7 14.0 16.2 18.4 60 3.8 6.3 8.6 10.8 14.9 16.9 18.8 70 3.2 5.4 9.3 11.1 14.6 17.9 19.5 80 2.8 4.8 6.5 8.3 9.7 11.3 14.3 15.7 17.2 18.6 90 2.5 4.3 5.8 7.3 8.7 10.1 12.7 15.3 16.6 100 2.3 5.2 6.6 7.8 9.1 11.5 13.8 15.0 120 1.9 4.4 5.5 9.6 10.6 11.6 12.5 160 1.4 2.4 3.3 4.9 5.7 7.2 8.0 9.5 200 1.1 2.6 4.0 4.6 7.0
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