Using data analytics to improve audit quality

Data analytics enable auditors to explore large data sets to assess risk and identify outliers, resulting in improved audit quality. How easy is it, then, to implement data analytics in an audit?

At a recent symposium on the future of auditing held by CPA Canada and the Institute of Chartered Accountants of Scotland (ICAS), participants cited "higher quality audit (over increased efficiency) as the largest benefit from using audit data analytics (ADAs). ADAs enhance the auditor's risk assessment and identify unusual or unexpected characteristics of transactions, providing a strong basis upon which the auditor designs the nature, timing and extent of their audit approach.

The use of ADAs could automate many routine aspects of the audit. This would give auditors increased time to focus on challenging matters requiring significant use of professional judgement, resulting in extra insights of interest to management and a more value-added audit.

With these advances in technology, there are many opportunities — and with those opportunities come challenges. Challenges in obtaining permissions to access, extract and cleanse data, as well as running the appropriate analytics and analyzing the results.

New guidance in Canada

We recognize these challenges. That's why CPA Canada has a dedicated ADA committee and a selection of resources focusing on this emerging area, in addition to a recently issued Guide to Audit Data Analytics. The guide is intended to:

  • introduce auditors who are not familiar with ADAs to basic concepts underlying their use
  • provide examples of how ADAs might be used in practice
  • assist auditors in using ADAs in each phase of the financial statement audit, in accordance with the Canadian Auditing Standards (CAS)

International activity related to data analytics

While we're providing guidance in Canada to support practitioners to implement ADAs under the CAS, there are actions being taken internationally to consider changes to the standards. The International Auditing and Assurance Standards Board (IAASB) assembled a Data Analytics Working Group (DAWG) to:

  • examine emerging developments in the effective and appropriate use of technology, including data analytics, to enhance audit quality
  • explore how the IAASB can most effectively respond to these emerging developments via new or revised International Standards on Auditing (ISA) or non-authoritative guidance, and in what timeframe

The DAWG issued a Feedback Statement which includes key messages from the responses to the requests in the Request for Input, Exploring the Growing Use of Technology in the Audit, with a Focus on Data Analytics.

Additionally, at the June IAASB meeting, the American Institute of Chartered Professional Accountants (AICPA) Task Force on Audit Evidence presented a status report on its project to revise the AICPA's audit evidence standard that is based on ISA 500, Audit Evidence. The project is addressing the use of emerging technologies by both prepareres and auditors in the context of the relevance and reliability of audit evidence. Potential changes relate to a definition of audit data analytics, the classification of audit procedures and expanded guidance to evaluate the sufficiency and appropriateness of audit evidence. Considering our symposium participants identified the greatest driver to increase the use of ADAs as the evolution of auditing standards, I look forward to hearing the results of the discussion and monitoring the progression of the project.

Keep the conversation going

What challenges do you face when implementing ADAs on your audit? Where have you found the most benefit? Post a comment below or email me directly.

About the Author

Taryn Abate, CPA, CA, CPA (IL)

Director, Audit and Assurance, CPA Canada

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