Aneta Wilk-Lys, Consultant, CFRR - World Banksiteresources.worldbank.org/EXTCENFINREPREF/Resources/4152117... · 4 “When designing audit procedures, the auditor should determine

EU-REPARIS is funded by the

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WB EDIF.

Road to Europe: Program of AccountingReform and Institutional Strengthening

Audit Training of Trainers

Aneta Wilk-Lys, Consultant, CFRR

Vienna 15 March 2016

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“When designing audit procedures,

the auditor should determine

appropriate means for selecting items

for testing so as to gather sufficient

and appropriate audit evidence to

meet the objectives of the audit

procedures.”

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»The decision as to which approach to use will depend

on the circumstances:

»Selecting all items (100% examination)

»Selecting specific items

»Audit sampling

The decision as to which means, or combination of

means, to use is made on the basis of the risk of

material misstatement related to the assertion

being tested and audit efficiency.

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»Appropriate to the objective of the audit procedure

»Complete

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» The auditor may decide that it will be most appropriate to examine

the entire population of items that make up a class of transactions

or account balance (or a stratum within that population).

» 100% examination is unlikely in the case of tests of controls;

however, it is more common for tests of details.

For example,100% examination may be appropriate when:

» the population constitutes a small number of large value items,

» there is a significant risk and other means do not provide sufficient

appropriate audit evidence,

» the repetitive nature of a calculation or other process performed

automatically by an information system makes a 100% examination cost

effective, for example, through the use of computer-assisted audit

techniques (CAATs).

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» The auditor may decide to select specific items from a population based on such

factors as the auditor’s understanding of the entity, the assessed risk of material

misstatement, and the characteristics of the population being tested.

» The judgmental selection of specific items is subject to non-sampling risk.

» Specific items selected may include:

» High value or key items.

» All items over a certain amount.

» Items to obtain information.

» Items to test control activities.

The results of audit procedures applied to items selected in this way cannot be

projected to the entire population.

The auditor considers the need to obtain sufficient appropriate

audit evidence regarding the remainder of the population when

that remainder is material.

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» Applying a procedure to less than 100% of a population of items within a class of

transactions or account balance such that all sampling units have a chance of

selection.

» To estimate some characteristic of the population

» Qualitative

» Quantitative

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» Sampling risk and non-sampling risk can affect the

components of the risk of material misstatement.For example, when performing tests of controls, the auditor may find no

errors in a sample and conclude that controls are operating effectively,

when the rate of error in the population is, in fact, unacceptably high

(sampling risk). Or there may be errors in the sample which the auditor

fails to recognize (non-sampling risk).

For both tests of controls and substantive tests of details,

sampling risk can be reduced by increasing sample

size, while non-sampling risk can be reduced by proper

engagement planning, supervision and review.

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»The auditor may decide to apply audit

sampling to a class of transactions or

account balance.

»Audit sampling can be applied using:

» non-statistical audit sampling and other

means of testing

» statistical sampling methods

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» Use of a computerized random number generator

(through CAATs) or random number tables.

» Systematic selection, in which the number of

sampling units in the population is divided by the

sample size to give a sampling interval, for example

50, and having determined a starting point within the

first 50, each 50th sampling unit thereafter is

selected.

» Monetary units sampling (MUS)- probability weighted

seletion

» Block selection involves selecting a block(s) of

contiguous items from within the speified.

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» Haphazard selection, in which the auditor selects the sample without

following a structured technique

» Judgemental selection based fully on auditors judgement

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» When planning the sample consider:

» The relationship of the sample to the relevant audit objective

» Materiality or the maximum tolerable misstatement or deviation rate

» Allowable sampling risk

» Characteristics of the population

» Select sample items in such a manner that they can be expected to be representative of the population

» Sample results should be projected to the population

» Items that cannot be audited should be treated as misstatements or deviations in evaluating the sample results

» Nature and cause of misstatements or deviations should be evaluated

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» Determine the objective of the test

» Define the attributes and deviation conditions

» Define the population to be sampled

» Choose an audit sampling technique

» Specify:

» The risk of assessing control risk too low

» The tolerable deviation rate

» Estimate the population deviation rate

» Determine the sample size

» Select the sample

» Test the sample items

» Evaluate the sample results

» Document the sampling procedure

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Large Sample Size (above 250 items) and “0” deviations expected

Inherent Risk:

Significance

Inherent Risk:

Likelihood

Minimum Sample Size

High High 60

High Medium 40

Medium High 40

Medium Small 25

Small Sample Size (below 250 items) and “0” deviations expected

Frequency Minimum Sample Size

Quarterly 2

Monthly 2-4

Semi-monthly 3-8

Weekly 5-9

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» Identify deviations. Place each sample item into one of two classifications: „deviation” or „no deviation”

» Cosider nature and cause of each deviation.

» Consider sampling risk. If deviations have been found, consider if reliance on control effectivenessshould be reduced, the sample size extended oralternative procedures performed.

THERE IS NO POINT IN TESTING CONTROLS IF DEVIATIONS ARE

LIKELY TO BE FOUND

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» The results of the sample can be evaluated by comparing the maximum tolerable deviation rate to what is called the upper deviationlimit. The upper deviation limit is approximated by the followingformula:

Upper deviation limit = adjusted confidence factor/sample size.

» Adjusted confidence factor can be based on the numer of deviationsfound:

Adjusted confidence factor for number of deviations found

Confidence level required 1 2 3 4 5

95% 4.7 6.3 7.8 9.2 10.5

90% 3.9 5.3 6.7 8 9.3

80% 3.0 4.3 5.5 6.7 7.9

70% 2.4 3.6 4.7 5.8 7

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» Let’s assume sampling of 30 items (using 90% confidence level and 10% maximum tolerable deviation rate) and two deviations were found. The upperdeviation limit would be calculated as follows:

Adjusted confidence factor (5.3)/sample size (30) = upper deviation limit (17%)

» The result 17% is much higher than the maximum tolerable deviation rate of 10%. This means that reliance on control effectiveness would have to be reduced.

» However, if it was decided to increase the sample size, it would have to be extended to 60 items and no further deviations found. This would reduce the upper deviation limit (as calculated below) to an acceptable level of ca. 9%

Adjusted confidence factor (5.3)/sample size (60) = Upper deviation limit (9%)

» However, if further deviations are found, it would require another extensiojn of a sample to try for desired results. This would not be effective use of audit time, as yet another deviation could well be found.

Adjusted confidence factor (6.7)/sample size (75)=Upper deviation limit (9%)

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» Conclusions?

» Decisions?

» Professional judgement

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» Determine the objective of the test

» Define the population and sampling unit

» Choose an audit sampling technique

» Define tolerable misstatement

» Determine the sample size

» Select the sample

» Test the sample items

» Evaluate the sample results

» Document the sampling procedure

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»Monetary Unit Sampling (MUS), also known as

probability proportional-to-size sampling (PPS) or

dollar unit sampling (DUS), is a statistical

sampling method used to determine the accuracy

of financial account balances.

»Each individual dollar (i.e. monetary unit) in an

account balance is considered a sampling unit,

thus accounts in the population with a higher

balance have a proportionately higher chance of

being selected.

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»The sample size can be determined by using

MUS sampling tables (e.g. AICPA or IFAC audit

guides) or statistical audit sampling software.

The inputs required are:

» Population Value (PV): the book value or monetary value

of the population.

» Tolerable Misstatement (TM): the tolerable margin of error

or precision for the sample estimate of the population value

(i.e. performance materiality).

» Expected Misstatement (EM): the expected amount of

misstatement in the population value.

» Confidence Level (CL): the level of assurance required

(i.e. complement of risk of incorrect acceptance).

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» Assuming:PV=170 203, TM= 15 000, EM=0 and CL=95%

» Specific items (subject to separate review) 38 340

» Determine the Confidence Factor from the MUS sampling tables:» Ratio of Expected-to-Tolerable Misstatement (EM/TM) = 0.00

» Match to the Confidence Level of 95% (i.e. 5% Risk of Incorrect Acceptance)

» MUS confidence factor = 3

» Calculate the sample size using the MUS formula :Sample Size = Confidence Factor × (PV/TM)

» = 3× [(170 203-38 340)/15 000)]= 28

» Calulate the sampling interval using the formula:PV/sample size

= (170 203-38 340)/28

= 5 000

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»Select the sample using calculated interval.

Each amount in the population is added to a cumulative total. The amount which

causes the cumulative total to equal or exceed the random start ($436) is selected as

the first sample. The remaining samples are selected from subsequent amounts which

cause the cumulative total to equal or exceed each increment of the sampling interval

(i.e. $5 436, 10 436 etc).

Customer Accounts receivable balance Cumulative total Sampling intervalInlude in sample?

Customer A 4750 4750 436 Yes

Customer B 3500 8250 5436 Yes

Customer C 1800 10050 10436 No

Customer D 2700 12750 15436 Yes

Customer E 950 13700 20436 No

Customer F 2580 16280 25436 Yes

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» Calculate thevalue of misstatement in each item. (eg. Balance found50, but should have been 60, the misstatement is 10, ie 17% of the total.

» Add up misstatements netting overstatements and understatements.

» Calculate the average percentage misstatement per item sampled by dividing the total misstatement percentages by the numer of all itemssampled (with and without misstatements).

» Multiply the average percentage misstatement by the totalrepresentative population monetary value (excluding high value and key items tested separately).

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» For example, sample of 50 items selected from a population of

250 000 EUR contained the following three misstatements:

Correct value (EUR) Audited value (EUR)

Misstatement (EUR)

Misstatement %

500 400 100 20.00%

350 200 150 42.86%

600 750 -150 -25.00%

Total percentage error 37.86%

Average misstatement 37.86%/50 (sample size) 0.7571%

Projected misstatement 0.7571%*250000 1,892.86

Consideranomalies

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» Conclusions?

» Decisions?

» Professional judgement

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»Use template 9 to perform a Sample calculation for Accounts

Receivable confirmations using MUS selection

»Work in Groups for 15 minutes

»The following sampling parameters are given:

Sampling Parameters

Population book value 100.000 EUR

Number of items 30

Sampling Interval

(Performance Materiality / Confidence Factor)

8.450 EUR / 3 = 2,8

Random number (between 1 and sampling interval) 2