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ACCT 4240: Auditing

ACCT 4240: Auditing

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ACCT 4240: Auditing

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  1. ACCT 4240: Auditing Introduction to Audit Sampling

  2. Definitions • Sampling is the examination of less than 100% of the population for the purpose of evaluation some aspect of the population • Each item in the population is a population unit • Each population unit selected for examination is a sampling unit

  3. Sampling: Purpose & Definition • Obtaining information about a lot from a little • Used in everyday life • Need to understand principles • Use when they fit objectives • Identify population (universe, field) • Base opinions only on what is sampled • Nothing in sampling is precise • Confidence level • Precision

  4. Inclusions and Exclusions • A 100% audit does not involve sampling • Analytical procedures normally are not applied to samples • Procedures usually involved with sampling include • Recalculation • Physical observation of inventory • Confirmations • Document examination

  5. Projecting the Error in the Sample to the Population Book value of the population………… $1,500,000 Book value of the sample……………… $1,000,000 Dollar amount of error in the sample…… $10,000 Projected Error = $15,000

  6. Statistical Sampling • Uses the laws of probability for selecting and evaluating the sample items • Selected at random so each population unit has an equal chance of being selected • Statistical calculations are used for selecting sample units and evaluating audit results • Sample size determines the level of confidence in the results

  7. Nonstatistical Sampling • Results are evaluated judgmentally rather than statistically • Sample selection can be random or nonrandom • Block sampling • Select a group of items in sequence • Sample may not be representative of the population • Haphazard sampling - may introduce bias • Judgmental sampling - sample size and items selected depends on auditor judgment

  8. Biased samples (nonstatistical): Purposeful Deliberate exclusions Patterns in population Statistical: Random sample selection Interval sampling Cluster sampling Stratified sampling Example When to stratify Sample Selection: Random vs. Haphazard Selection

  9. Sampling Risk and Non-Sampling Risk • Sampling risk is the risk that the sample is not representative of the population • Non-sampling risk results from human error • Failure to recognize a mistake • Use of an ineffective audit procedure • Non-sampling risk is not quantifiable • Level is reduced through • Adequate supervision • Quality control standards

  10. Attribute and Variables Sampling Techniques

  11. Attribute Sampling • Primary purpose is to estimate how effectively a specific accounting control performs a specified function • Example: Comparison of a vendor’s invoice to a corresponding receiving report Invoice Receiving Report Compare Qty = 15 Qty = 15

  12. Attribute Sampling • Used to estimate the RATE of OCCURRENCE of a specific quality within a population • Generally viewed as a YES/NO or TRUE/FALSE outcome • A deviation occurs when an attribute is not present

  13. Steps in Attribute Sampling • Determine the audit objectives of sampling plan • Define population and sampling unit • Specify attributes of interest • Determine sample size • Determine sample selection method • Execute sampling plan • Evaluate sample results

  14. Factors that Affect Attribute Sample Size

  15. Steps in Performing a Statistical Test of Controls • Determine the control to be sampled • Define the population and the sampling unit • Determine the initial sample size • Specify the tolerable deviation rate (e.g. 5%) • Specify Beta risk (risk of over-reliance) (e.g. 5%) • Estimate the expected population deviation rate • Estimate the population size

  16. Determining Sample Size (Not in text) Sample Size Allowable Deviations

  17. Statistical Tests of Controls • Select the sample • Random sampling • Systematic selection - auditor picks every nth item from one or more random starting points • Audit the selected items

  18. Statistical Tests of Controls • Evaluate the sample results • Determine why errors occurred • Evaluate effect of results on related substantive audit procedures

  19. Evaluating Sample Results (Appendix FB.1)

  20. Evaluation • Determining reasons for deviations • Purpose of examination – opinion • Factors relevant to an overall opinion • Internal control • Supervisory review • Administration • Experience and training of personnel • Materiality of errors • Effect on other transactions • Risk analysis

  21. Sampling Risk - Attribute Sampling • Sampling Risk - the risk that the sample is not representative of the population Tested Control Actually Is Effective Not Effective Alpha Risk Not Correct Effective Decision Risk of assessing Tests of Controls control risk too high Indicate that Controls Are Beta Risk Correct Effective Decision Risk of assessing control risk too low

  22. Sequential (Stop-or-Go Sampling) • Select initial (smaller) sample and consider results • Decision • Rely on control; discontinue sampling • Cannot rely on control • Select additional items; make decision • Discontinue sampling • Advantage is that evidence may support reliance on control with a relatively small sample size • Disadvantage is that auditor may continually extend the sample, creating inefficiencies

  23. Discovery Sampling • Used when deviations from control are expected to be infrequent but very critical • Allows the auditor to • Determine the necessary sample size to find at least one example of a deviation if such deviations exist • Determine the probability that the rate of occurrence of a deviation is less than a specific (low) level

  24. Discovery Sampling • Used when expected error rate is low or near zero • Sample is designed to identify at least one example of an error if it occurs in the population at a specified error rate • Probabilities determined by using Appendix AC

  25. Discovery Sampling

  26. Audit Sampling for Substantive Tests • Define the objective of the test • Define the population to be sampled • Identify individually significant items • Determine the method of sampling • Determine the sample size • Select the sample and examine the items • Evaluate the sample results • Project sample results to N • Make decision about N

  27. Statistical Sampling for Substantive Testing • Hypothesis testing - measures whether an estimated book value determined by statistical sampling is substantially different than the book value recorded by the client • Materiality • Sampling risk

  28. Statistical Sampling Techniques for Substantive Tests • Dollar-Unit Sampling • Most efficient when population error rate is very low • Book value must generally be available for each item in the population • Ratio and Difference Estimation • Moderate error rate must exist in the population • Book value must generally be available for each item in the population • Ratio estimation is more efficient when the errors are proportionate to the book values • Stratified Mean-per-Unit Estimation • May be used under any circumstance

  29. Audit Evidence Indicates Sampling Risk - Substantive Procedures • Sampling Risk - the risk that the sample is not representative of the population Recorded Amount Actually Is Materially Not Materially Misstated Misstated Alpha Risk Reject as Correct Materially Risk of Incorrect Decision Misstated Rejection Accept as Beta Risk Correct Not Risk of Incorrect Decision Materially Acceptance Misstated

  30. Steps in Sampling • Determine the objective of the sampling • Define the population and sampling unit • Determine the method of sampling

  31. Methods of Sampling • Classical variables sampling • Mean-per-unit estimation • Difference estimation • Ratio estimation • Probability Proportional to Size (PPS) - Also called Dollar-Unit Sampling

  32. Steps in Sampling • Determine the initial sample size • Using random sampling techniques, identify the items to audit • Audit the selected items and identify monetary misstatements • Evaluate the sample results • Amount of known misstatement • Project known amount to population (likely misstatement)

  33. Classical Variables Sampling • For difference and ratio estimation methods, a minimum of about 30 errors are necessary to ensure a reasonable estimate of the true but unknown monetary balance • For Mean-per-Unit sampling, auditors usually stratify populations into smaller sub-populations to reduce total sample size • Book values must be available for difference and ratio estimation techniques

  34. Probability Proportional to Size • Uses attribute sampling theory to estimate the maximum amount of misstatement in an account balance • The sampling unit is an individual dollar of the account balance • PPS is more effective for identifying overstatements of account balances

  35. Sample Size Relationships: Auditing Account Balances

  36. Determining the Sample Size (n) Where: α = planned level of risk of incorrect rejection zα = reliability coefficients for the risk of incorrect rejection Pre = precision per item in the population sd = standard deviation of the population to be sampled TE = tolerable error (material amount) N = number of items in population zβ = reliability coefficient for risk of incorrect acceptance risk

  37. Probability Proportional to Size (PPS) Sampling • Defines the sampling unit as individual dollar in an account balance • Auditor will select individual dollars for examination • Auditor will verify entire “logical unit” containing the selected dollar • Accounts receivable: Customer account • Inventory: Inventory item

  38. Advantages of PPS Sampling • Results in smaller sample sizes • Includes transactions or components reflecting larger dollar amounts • Effective for overstatement errors • Generally simpler to use than classical variables sampling

  39. Disadvantages of PPS Sampling • Provides a conservative (higher) estimate of misstatement • Not effective for understatement or omission errors • Expanding a PPS sample is difficult if the initial conclusion is to reject account balance • Requires special consideration for accounts with zero or negative balances

  40. PPS • Calculate sample size using • Calculate sampling interval using

  41. Probability Proportional to Size Invoice No. AmountIntervalSample? 1 $ 700 700 NO 2 400 100 YES 300 3 900 500 YES 400 4 300 300 NO 5 400 100 YES 300 6 1700 500YES 800 YES 400 7 400 400 YES

  42. Next Time Completing the Audit