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The regulator's reading

Katharine Bagshaw assesses the findings of the recent Audit Quality Thematic Review into data analytics in external audit

When auditing standards were first developed in the 1970s, it was not possible to test every single transaction in a population, hence the need for controls, risk analysis and sampling. Were standards drafted from scratch now, they might look very different.

The tone of a recent International Auditing and Assurance Standards Board (IAASB) paper (see box) suggests that there is little appetite for a radical rethink, which is not surprising given IAASB’s status as a mature, global standard setter.

Nonetheless, the fast-moving area of data analytics is having an impact on the profession. Larger firms have invested heavily in analytics, and off-the-shelf offerings for smaller audit firms have recently been launched by Inflo and Validis (as outlined in February’s Audit & Beyond).

Hopefully, changes made by standard setters will enable large firms to keep the data analytics their clients currently value so highly within the external audit (rather than hive it off into consultancy practices) and offerings for smaller firms will enable them to develop their own data analytics offerings. The approach of audit regulators in all of this will be critical.

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