HKSA 530 - Audit Sampling

類型	控制測試	細節測試	影響
第一類（錯誤接受風險）	控制比實際更有效	不存在重大錯誤陳述而實際存在	影響審計效果 - 更可能導致不恰當的審計意見
第二類（錯誤拒絕風險）	控制比實際效果差	存在重大錯誤陳述而實際不存在	影響審計效率 - 導致額外不必要的工作

Introduction

Scope of this HKSA

HKSA 530 applies when the auditor has decided to use audit sampling in performing audit procedures. This standard deals with the auditor's use of statistical and non-statistical sampling when:

Designing and selecting the audit sample

Performing tests of controls and tests of details

Evaluating the results from the sample

This HKSA complements HKSA 500 (Audit Evidence), which deals with the auditor's responsibility to design and perform audit procedures to obtain sufficient appropriate audit evidence. HKSA 500 provides guidance on the means available to the auditor for selecting items for testing, of which audit sampling is one means.

Effective Date

This HKSA is effective for audits of financial statements for periods beginning on or after 15 December 2009. The standard was issued July 2009, revised July 2010, December 2021, and May 2022 (with amendments resulting from HKSA 315 (Revised 2019) effective for periods beginning on or after 15 December 2021).

Objective

The objective of the auditor, when using audit sampling, is to provide a reasonable basis for the auditor to draw conclusions about the population from which the sample is selected.

概念	要點
抽樣風險	因抽樣導致錯誤結論的風險；影響效果（第一類）或效率（第二類）
非抽樣風險	來自不當程序、誤解、未能識別錯誤的風險
統計與非統計	統計 = 隨機選擇 + 概率理論；樣本規模不是區分因素
樣本規模	確定為將抽樣風險降低到可接受的低水平；受多種因素影響
選擇方法	隨機、系統、隨意、貨幣單位抽樣、整群（整群通常不適當）
異常情況	極其罕見；必須獲得高度確定性證明不具代表性
推斷	細節測試需要；控制測試不需要明確推斷
評估	比較推斷 + 異常錯誤陳述與可容忍錯誤陳述
分層	減少變異性，允許較小樣本規模
可容忍錯誤陳述	績效重要性應用於抽樣程序

Definitions (Paragraph 5)

(a) Audit Sampling (Sampling)

The application of audit procedures to less than 100% of items within a population of audit relevance such that all sampling units have a chance of selection in order to provide the auditor with a reasonable basis on which to draw conclusions about the entire population.

Key characteristics:

Less than 100% of items tested

All sampling units have a chance of selection

Provides reasonable basis for conclusions about entire population

(b) Population

The entire set of data from which a sample is selected and about which the auditor wishes to draw conclusions.

(c) Sampling Risk

The risk that the auditor's conclusion based on a sample may be different from the conclusion if the entire population were subjected to the same audit procedure.

Two types of erroneous conclusions:

Type	Test of Controls	Test of Details	Effect
Type I (Risk of incorrect acceptance)	Controls are more effective than they actually are	Material misstatement does not exist when in fact it does	Affects audit effectiveness - more likely to lead to inappropriate audit opinion
Type II (Risk of incorrect rejection)	Controls are less effective than they actually are	Material misstatement exists when in fact it does not	Affects audit efficiency - leads to additional unnecessary work

(d) Non-Sampling Risk

The risk that the auditor reaches an erroneous conclusion for any reason not related to sampling risk.

Examples (Para. A1):

Use of inappropriate audit procedures

Misinterpretation of audit evidence

Failure to recognize a misstatement or deviation

(e) Anomaly

A misstatement or deviation that is demonstrably not representative of misstatements or deviations in a population.

(f) Sampling Unit

The individual items constituting a population. (Para. A2)

Examples:

Physical items (checks listed on deposit slips, credit entries on bank statements, sales invoices, debtors' balances)

Monetary units

(g) Statistical Sampling

An approach to sampling that has the following characteristics:

Random selection of the sample items

Use of probability theory to evaluate sample results, including measurement of sampling risk

A sampling approach that does NOT have both characteristics (i) and (ii) is considered non-statistical sampling.

(h) Stratification

The process of dividing a population into sub-populations, each of which is a group of sampling units which have similar characteristics (often monetary value).

(i) Tolerable Misstatement

A monetary amount set by the auditor in respect of which the auditor seeks to obtain an appropriate level of assurance that the monetary amount set by the auditor is not exceeded by the actual misstatement in the population. (Para. A3)

Key points about tolerable misstatement:

Addresses the risk that aggregate of individually immaterial misstatements may cause material misstatement

Provides a margin for possible undetected misstatements

Is the application of performance materiality (as defined in HKSA 320) to a particular sampling procedure

May be the same amount or an amount lower than performance materiality

(j) Tolerable Rate of Deviation

A rate of deviation from prescribed internal control procedures set by the auditor in respect of which the auditor seeks to obtain an appropriate level of assurance that the rate of deviation set by the auditor is not exceeded by the actual rate of deviation in the population.

Requirements

Sample Design, Size and Selection of Items for Testing (Paragraphs 6-8)

Paragraph 6: Sample Design

When designing an audit sample, the auditor shall consider the purpose of the audit procedure and the characteristics of the population from which the sample will be drawn.

Application guidance (Paras. A4-A9):

A4: Audit sampling enables the auditor to obtain and evaluate audit evidence about some characteristic of the selected items to form conclusions about the population. Can use non-statistical or statistical approaches.

A5: When designing a sample, the auditor's consideration includes:

Specific purpose to be achieved

Combination of audit procedures likely to best achieve that purpose

Nature of audit evidence sought

Possible deviation or misstatement conditions

Other characteristics relating to audit evidence

In fulfilling paragraph 9 of HKSA 500, when performing audit sampling, the auditor performs audit procedures to obtain evidence that the population from which the audit sample is drawn is complete.

A6: The auditor must have a clear understanding of what constitutes a deviation or misstatement so that all, and only those, conditions relevant to the purpose are included.

Example: In a test of details relating to existence of accounts receivable (confirmation):

Payments made by customer before confirmation date but received shortly after by the client → NOT a misstatement

Misposting between customer accounts → does not affect total accounts receivable balance → may NOT be appropriate to consider this a misstatement in evaluating sample results (though it may affect other areas like fraud risk assessment or allowance for doubtful accounts)

A7: For tests of controls, the auditor assesses the expected rate of deviation based on:

Understanding of the controls

Examination of a small number of items from the population

If expected rate of deviation is unacceptably high → auditor will normally decide not to perform tests of controls.

For tests of details, the auditor assesses expected misstatement in the population:

If expected misstatement is high → 100% examination or large sample size may be appropriate

A8: The auditor may determine that stratification or value-weighted selection is appropriate. (See Appendix 1)

A9: The decision to use statistical or non-statistical sampling is a matter of auditor's judgment. Sample size is not a valid criterion to distinguish between statistical and non-statistical approaches.

Paragraph 7: Sample Size

The auditor shall determine a sample size sufficient to reduce sampling risk to an acceptably low level.

Application guidance (Paras. A10-A11):

A10: The level of sampling risk the auditor is willing to accept affects sample size:

Lower risk willing to accept → larger sample size needed

A11: Sample size can be determined by:

Application of a statistically-based formula

Exercise of professional judgment

When circumstances are similar, the effect on sample size of factors identified in Appendices 2 and 3 will be similar regardless of whether a statistical or non-statistical approach is chosen.

Paragraph 8: Selection of Items for Testing

The auditor shall select items for the sample in such a way that each sampling unit in the population has a chance of selection.

Application guidance (Paras. A12-A13):

A12:

Statistical sampling: Sample items selected so each sampling unit has a known probability of being selected

Non-statistical sampling: Judgment is used to select sample items

Important: The auditor must select a representative sample to avoid bias by choosing items with characteristics typical of the population

A13: Principal methods of selecting samples:

Random selection - using random number generators or random number tables

Systematic selection - dividing population size by sample size to get sampling interval, then selecting every nth item

Haphazard selection - selecting without structured technique but avoiding conscious bias

Monetary Unit Sampling - value-weighted selection (see Appendix 1)

Block selection - selecting block(s) of contiguous items (generally NOT appropriate for audit sampling)

Performing Audit Procedures (Paragraphs 9-11)

Paragraph 9

The auditor shall perform audit procedures, appropriate to the purpose, on each item selected.

Paragraph 10: Replacement Items

If the audit procedure is not applicable to the selected item, the auditor shall perform the procedure on a replacement item.

Application guidance (Para. A14):

Example: When a voided check is selected while testing for evidence of payment authorization:

If auditor is satisfied the check has been properly voided such that it does not constitute a deviation → an appropriately chosen replacement is examined

Paragraph 11: Inability to Apply Procedures

If the auditor is unable to apply the designed audit procedures, or suitable alternative procedures, to a selected item, the auditor shall treat that item as:

A deviation from the prescribed control (in the case of tests of controls)

A misstatement (in the case of tests of details)

Application guidance (Paras. A15-A16):

A15: Example of inability to apply designed procedures: Documentation relating to the selected item has been lost.

A16: Example of suitable alternative procedure: Examination of subsequent cash receipts together with evidence of their source and the items they are intended to settle when no reply has been received in response to a positive confirmation request.

Nature and Cause of Deviations and Misstatements (Paragraphs 12-13)

Paragraph 12: Investigation

The auditor shall investigate the nature and cause of any deviations or misstatements identified, and evaluate their possible effect on:

The purpose of the audit procedure

Other areas of the audit

Application guidance (Para. A17):

When analyzing deviations and misstatements, the auditor may observe that many have a common feature, for example:

Type of transaction

Location

Product line

Period of time

In such circumstances, the auditor may:

Identify all items in the population that possess the common feature

Extend audit procedures to those items

Such deviations or misstatements may be intentional and may indicate the possibility of fraud.

Paragraph 13: Anomalies

In the extremely rare circumstances when the auditor considers a misstatement or deviation discovered in a sample to be an anomaly, the auditor shall obtain a high degree of certainty that such misstatement or deviation is not representative of the population.

Requirements for treating an item as an anomaly:

Must be "extremely rare circumstances"

Must obtain high degree of certainty that it is not representative

Must perform additional audit procedures to obtain sufficient appropriate audit evidence that the misstatement or deviation does not affect the remainder of the population

Projecting Misstatements (Paragraph 14)

For tests of details, the auditor shall project misstatements found in the sample to the population.

Application guidance (Paras. A18-A20):

A18: The projection is required to obtain a broad view of the scale of misstatement, but this projection may not be sufficient to determine an amount to be recorded.

A19: When a misstatement has been established as an anomaly:

It may be excluded when projecting misstatements to the population

However, the effect of any such misstatement, if uncorrected, still needs to be considered in addition to the projection of non-anomalous misstatements

A20: For tests of controls:

No explicit projection of deviations is necessary

The sample deviation rate is also the projected deviation rate for the population as a whole

HKSA 330 provides guidance when deviations from controls upon which the auditor intends to rely are detected

Evaluating Results of Audit Sampling (Paragraph 15)

The auditor shall evaluate:

(a) The results of the sample; and

(b) Whether the use of audit sampling has provided a reasonable basis for conclusions about the population that has been tested.

Application guidance (Paras. A21-A23):

A21:

Tests of controls: An unexpectedly high sample deviation rate may lead to an increase in the assessed risk of material misstatement, unless further audit evidence substantiating the initial assessment is obtained.

Tests of details: An unexpectedly high misstatement amount in a sample may cause the auditor to believe that a class of transactions or account balance is materially misstated, in the absence of further audit evidence that no material misstatement exists.

A22: For tests of details:

Projected misstatement + anomalous misstatement (if any) = auditor's best estimate of misstatement in the population

When projected misstatement + anomalous misstatement exceeds tolerable misstatement → sample does not provide a reasonable basis for conclusions

The closer the projected misstatement + anomalous misstatement is to tolerable misstatement → the more likely actual misstatement may exceed tolerable misstatement

If projected misstatement > auditor's expectations used to determine sample size → may conclude there is unacceptable sampling risk

A23: If auditor concludes audit sampling has not provided a reasonable basis for conclusions, the auditor may:

Request management to investigate misstatements identified and potential for further misstatements, and make any necessary adjustments

Tailor the nature, timing and extent of further audit procedures to best achieve required assurance

Examples of further actions:

For tests of controls: Extend sample size, test an alternative control, or modify related substantive procedures

Appendices Summary

Appendix 1: Stratification and Value-Weighted Selection

Stratification:

Divides population into discrete sub-populations with identifying characteristics

Objective: Reduce variability within each stratum → allow sample size reduction without increasing sampling risk

For tests of details: Often stratified by monetary value or by characteristic indicating higher risk (e.g., age of accounts receivable)

Results from each stratum can only be projected to items in that stratum

Misstatements are projected for each stratum separately, then combined

Value-Weighted Selection:

Sampling unit = individual monetary units making up the population

Audit effort directed to larger value items (greater chance of selection)

Can result in smaller sample sizes

Most efficient when using random selection with systematic method

Appendix 2: Factors Influencing Sample Size for Tests of Controls

Factor	Effect on Sample Size	Explanation
Increase in extent auditor's risk assessment relies on testing controls	Increase	More assurance needed from controls → larger sample
Increase in tolerable rate of deviation	Decrease	Higher tolerance → smaller sample
Increase in expected rate of deviation	Increase	Higher expected deviation → larger sample needed for reasonable estimate
Increase in auditor's desired level of assurance	Increase	More assurance needed → larger sample
Increase in number of sampling units in population	Negligible effect	For large populations, size has little effect

Appendix 3: Factors Influencing Sample Size for Tests of Details

Factor	Effect on Sample Size	Explanation
Increase in auditor's assessment of risk of material misstatement	Increase	Higher risk → larger sample needed
Increase in use of other substantive procedures directed at same assertion	Decrease	More reliance on other procedures → smaller sample from sampling
Increase in auditor's desired level of assurance	Increase	More assurance needed → larger sample
Increase in tolerable misstatement	Decrease	Higher tolerance → smaller sample
Increase in expected misstatement in population	Increase	Higher expected misstatement → larger sample
Stratification of population when appropriate	Decrease	Stratification reduces variability → smaller aggregate sample size
Increase in number of sampling units	Negligible effect	For large populations, size has little effect (except for MUS where monetary value increase increases sample size unless offset by materiality increase)

Appendix 4: Sample Selection Methods

Method	Description	Notes
Random selection	Using random number generators or random number tables	Each item has known probability of selection
Systematic selection	Divide population by sample size to get interval, select every nth item starting from random start	Need to ensure population not structured to correspond with interval
Monetary Unit Sampling (MUS)	Value-weighted selection; sample size, selection and evaluation result in monetary conclusions	Type of value-weighted selection
Haphazard selection	Select without structured technique but avoid conscious bias	NOT appropriate for statistical sampling
Block selection	Select block(s) of contiguous items	Generally NOT appropriate for audit sampling as items in sequence may have similar characteristics

Key Takeaways Summary Table

Concept	Key Point
Sampling Risk	Risk of incorrect conclusion due to sampling; affects effectiveness (Type I) or efficiency (Type II)
Non-Sampling Risk	Risk from inappropriate procedures, misinterpretation, failure to recognize errors
Statistical vs Non-Statistical	Statistical = random selection + probability theory; sample size NOT distinguishing factor
Sample Size	Determined to reduce sampling risk to acceptably low level; affected by multiple factors
Selection Methods	Random, systematic, haphazard, MUS, block (block generally inappropriate)
Anomaly	Extremely rare; must obtain high degree of certainty it's not representative
Projection	Required for tests of details; not explicitly required for tests of controls
Evaluation	Compare projected + anomalous misstatement to tolerable misstatement
Stratification	Reduces variability, allows smaller sample sizes
Tolerable Misstatement	Application of performance materiality to sampling procedure

HKSA 530 - Audit Sampling