Sampling and Audit Control Evaluation

Course Overview

  • Instructor addresses class disruption due to inability to meet in person.
  • Material in the video aims to substitute for in-class discussion, particularly concerning auditing and sampling.

Review of Previous Class

  • Subject matter focuses on sampling in auditing.
  • Sampling Definition: Testing less than 100% of a population during an audit.
  • Importance of obtaining a representative sample while acknowledging the impossibility of certainty without total population testing.

Sampling Risks

  • Sampling Risk: The risk of not having a representative sample affects audit conclusions.
  • Auditors sample to limit audit time and costs, as full population testing is economically impractical.
  • Non-sampling Risks also arise due to the potential for mistakes during the audit process.
  • Auditing provides a reasonable level of assurance, not absolute assurance on financial statements.

Sample Size Determination

  • Sample size can be determined through:
    • Statistical Methods and non-statistical methods.
    • Note on Table 15-8 provided for statistical sample size calculations.
    • Non-statistical sample sizes rely on auditor judgment.
    • Important for exam preparation to understand how to determine and use statistical sample sizes.

Sampling Methodology

  • Selection of items based on probabilistic or non-probabilistic methods.
  • Attribute Sampling: Involves testing for specific characteristics, usually in a yes/no format (e.g., did something occur).
    • Exceptions result in either controlled deviations (for control tests) or monetary misstatements (for substantive tests).

Review of Steps in Sampling

Step 1 and 2 Recap

  • Three Variables to Determine Sample Size:
    1. Tolerable Exception Rate (TER)
    2. Acceptable Risk of Overreliance (ARO)
    3. Estimated Population Exception Rate (EPER)
  • Understanding these variables is critical for statistical sample size determination.
  • Both Table 15-8 and Table 15-9 are provided for reference and use in evaluating sample sizes and evaluations respectively.

Steps 3 and 4 Preview

  • Discussing how auditors conclude based on their testing.
  • Differentiation between exceptions found during substantive tests of transactions and control tests is essential.

Evaluation of Test Results

Step 3: Conclusion Based on Test Results

  • The auditor evaluates results to establish whether deviations occurred.
    • Deviations Types:
      • Controlled Deviations (for controls)
      • Monetary Misstatements (for substantive tests)
  • Importance of distinguishing between statistical and non-statistical evaluations:
    • Auditor judgment plays a role in non-statistical evaluations.
Sample Exception Rate (SER)
  • Definition: The number of items identified as exceptions over the sample size.
  • Example Calculation: Testing 100 items with 5 exceptions results in an SER of 5%.

Allowance for Sampling Risk

  • Definition: The difference between TER and SER.
  • Evaluating if the allowance for sampling risk allows for effective conclusion on control effectiveness.
  • Comparison of TER and SER to assess the risk regarding control operation:
    • If SER > TER, reject the control.
    • If SER < TER, further steps are necessary to confirm control effectiveness, considering sampling risk.

Detailed Example Analysis

  1. Example with No Deviations:
    • Tested 60 items, SER is 0%, allowance for sampling risk is 5% (5%-0%); auditor concludes control is effective.
  2. Example with Deviations:
    • 2 deviations out of 60, SER is 3.3%, allowance for sampling risk is 1.7%. Possible conclusion: control not effective due to insufficient allowance.
  3. Larger Sample Size Effects: Increased sample sizes provide higher confidence in the sample exception rate reflecting true population exception rates.

Evaluation Process for Non-Statistical Samples

  • Description of planned and actual audits reveals how deviations are evaluated.
  • Comparison of calculated SER, allowance for sampling risk decisions lead to conclusion on control effectiveness.

Transition to Statistical Sample Evaluation

Key Terms and Concepts for Statistical Methodologies

  • Sequence of calculation necessitates determining the Computed Upper Exception Rate (CUER) based on ARO and comparing CUER with TER to denote control effectiveness.
  • If CUER < TER, control is effective; otherwise, auditing judgment must be applied.

Advantages of Statistical Sampling

  • Clear parameters for control conclusions reduce ambiguity in auditor's evaluation.
  • Use of statistical tables and methodologies assures systematic evaluation of exceptions and control effectiveness.

Final Analysis of Exceptions

  • Post-evaluation tasks include analyzing character and potential causes of exceptions.
  • Auditors must exercise professional skepticism when evaluating exceptions to discern if they are indicative of greater issues or routine errors.
  • The auditor's findings should always support professional judgment in making their conclusions about the control.

Conclusion and Next Steps

  • Reminder to students: review all terms, format of statistical conclusions, and practice problems solidifying understanding of material covered.
  • Review practice problems and calculations to reinforce understanding of sampling rates and exception evaluations in relation to overall control assessments.