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Purchase the CPA Canada Guide to Audit Data Analytics, which is designed to assist and encourage practitioners to make use of technology-based data analytics in the audit of financial statements.
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In response to a changing environment, increased use of audit data analytics (ADAs) is important in maintaining the relevance of the financial statement audit and in helping to improve its effectiveness and efficiency. These data analytics are audit procedures used to discover and analyze patterns, identify anomalies, and obtain other useful information from data populations relevant to the audit. Because of the power of advanced analytical tools, auditors using ADAs are able to perform procedures that may, in some cases, cover 100 per cent of the items in large data populations.
The main objective of auditors who make use of ADAs is to improve audit quality. For example, some data analytics may allow the auditor to use more complex data models to increase the rigour of audit procedures. Their use may improve the auditor’s ability to assess the risks of material misstatement in various accounts through analysis of up to 100 per cent of relevant data for those accounts. The use of ADAs also provides deeper insights into an organization’s systems and controls. A process-mining example of ADAs may be effective in identifying controls deficiencies. Such insights may be a valuable by-product of the financial statement audit with the potential to improve communications with management and those charged with governance. Additionally, the use of ADA may enable many routine aspects of the audit to be automated, allowing auditors to devote more time to challenging matters requiring significant use of professional judgement.
This non-authoritative guide has been adopted by CPA Canada from the AICPA audit guide of the same title. It was developed by a team of experts who have hands-on experience working with ADAs, which can be used to perform a variety of procedures to gather audit evidence.
This guide will:
The use of ADAs has the potential to enhance traditional audit procedures, contribute to every phase of the audit and offer a new way of visualizing and analyzing results.
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