Optimizing financial audit using statistical sampling

The advantages of a statistical sample

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The challenge financial audit is facing is to deliver high(er) quality with less man hours. The use of statistical sampling allows to give an unqualified opinion for the financial statements with minimal effort. Statistical sampling also provides a sound base for the identification of risks and therefore optimizes prioritization of audit work streams.

If a sample contains errors, a quantifiable result in terms of precision and reliability can be quickly obtained. One of the great advantages of sampling is that both expected and non-expected errors can be identified.

A key question within audit is how to reduce sample sizes accounting for the control information obtained in earlier phases of the audit. There are several models to support this, most of which operate as a black box and/or cannot be validated.

What we offer

We provide in-house training on the applicability of statistical sampling as part of the audit methodology using examples and case studies from our experience. We explain the different models and demystify these and show models that in our opinion are better in the way that the assumptions in the model can be validated.

We support audit organizations (internal and external) in incorporating a sampling methodology in their audit approach as well as in developing or adjusting tooling (e.g. ACL, IDEA) to implement the methodology.

We support organizations in designing a statistical sample and evaluate the results as part of their audit procedures following the international Auditing and Assurance Standards.

For questions please contact us.

Our flyers

Take aways 

  • Improvement of quality of audit (AFM report)
  • Quick insight in occurance of risks (and opportunities)
  • By counting only a limited number of items (locations, product types, article numbers) the value of inventory can be adequately monitored
  • Improvements plans can be quickly defined on the basis of errors found in the sample
  1. Scope definition: determination of the population and the construction (= which metadata are needed) of the population; requirements for the sample; determining what should be audited, including the documentation thereof
  2. Delivering data: data files are provided based on the recommendations from the KEY Group
  3. Selection of the sample: the KEY Group draws the sample using audit software
  4. Review: the auditor assesses the individual transactions on the basis of the source data and determines the audit values of the transactions
  5. Quantification: if errors are noted KEY Group quantifies the maximum impact
  6. Further research: KEY Group can support in prioritizing next steps based on errors found

Examples of application of statistical sampling in tax environment.

  • Set up a project charter that will take effect preferable during feasibility but ultimately during design
  • Write a business case and problem statement
  • Define scope of the project
  • Define objectives and goals of the project
  • Involve stakeholders and define priorities
  • Set measurable milestones
  • Ensure that the right sponsors provide buy-in.
  • Identify (project) risks and how to manage them
  • Jointly validate and refine the project plan and develop a roadmap to success
  • Hold regular meeting to track progress of the various work streams