Contrarily, stakeholders continue to have increased expectations for higher quality and more comprehensive audits at reduced costs – understandably so given the audit and accounting profession’s current reputational challenges. Because of this expectation they continuously challenge the practitioner to provide more innovative ways to improve audit effectiveness while showing deep insights. As a result, conventional auditing approaches can’t keep up with exponential change and growing demand for more insightful assurance.
Those charged with governance sometimes have a distorted understanding of their data quality and data management processes, leading to a misaligned expectation of how data can be used in the audit – a challenge for the practitioner.
Another misperception is that the first run of an analytical routine provides you with the optimal result set, however in my experience adopting audit analytics in the first year of implementation (for each organisation) highlights a lack of understanding of:
In either event, multiple iterations are required to refine an effective analytical output. This execution effort (in the first year), assists in eliminating false positives and thus the lack of trust in the analytics.
Given these challenges, I still see a benefit in adopting a data driven audit/audit analytics.
The abovementioned two matters emphasise the business imperative of a data driven audit and we know that the auditing profession is under scrutiny. Minimum control testing and sampling of transactions is inadequate in data rich environments, and is becoming acceptable to the regulators. In interactions with regulatory and professional bodies, I see that their views about the use of sophisticated technology and audit analytics are changing.
The South African Institute of Chartered Accountants (Saica) is accelerating support in driving innovation into the auditing and accounting profession. Martin Baumann, former chief auditor and director of professional standards at the Public Company Accounting Oversight Board (PCAOB), commented in an interview for the Journal of Accountancy that: “We wouldn’t want auditing standards to be an inhibitor that might otherwise allow technological audit achievements to move ahead.”
Audit analytics gives us the opportunity to analyse large data sets that were too voluminous to make sense of. Current technologies allow us to provide full population analysis in the risk assessment and execution phases, and to eliminate a one dimensional lens of a process and provide a holistic picture of transactions across business processes, thus aiding in the practitioners’ ability to perform a more informed risk assessment.
Universities, professional bodies and regulators such as the Saica, Public Company Accounting Oversight Board (PCAOB) and our standard setters’ board – The International Auditing and Assurance Standards Board (IAASB) - are already in the midst of revising skill set requirements to create the chartered accountant/auditor of the future, not only because of the need, but also to ensure our profession remains relevant and attractive.
Most practitioners are familiar with electronic spreadsheets, but many are not as skilled with robust technology. I am already seeing a transition of skill sets. Practitioners are empowering themselves and their audit teams to perform analytics, instead of reverting to a data or analytics expert. Our new generation yearns to be part of audit and assurance engagements.