Audit sampling requires that the auditor collect only a relatively small sub-sample of data, thereby initiating...

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Accounting

Audit sampling requires that the auditor collect only arelatively small sub-sample of data, thereby initiating detectionrisk, i.e., the risk. . . that, based on the sample the auditortakes, the auditor will fail to detect a material misstatement inthe financial statements. Data analytics seems to present a panaceato that notion of risk because, by auditing 100% of the sample,detection risk by definition is lower.
It seems like data analytics is the perfect answer to the auditrisk problem. So, comment on a variety of reasons that auditorsmight not be willing to rely on data analytics to drive audit riskdown.
Which do you think is costlier: sampling or data analytics?What are the different costs between sampling and dataanalytics?
What role does cost-benefit play in the choice betweenemploying statistical sampling versus data analytics?
Data analytics enables auditors to audit all transactions,rather than just a sample of transactions.
Do you think that as the use of data analytics increases onaudit engagements, the need for sampling will decrease?
What role might the PCAOB or AICPA play in helping auditorsdetermine when and how to incorporate data analytics into theaudit?

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Audit sampling enables the auditor to obtain and evaluate audit evidence about some characteristics of the items selected in order to form or assist in forming a conclusion concerning the population from which the sample is drawn When designing a sample the auditor determines tolerable See Answer

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