What is audit data analytics (ADA)?
According to the AICPA, Audit data analytics (ADAs) are a technique that can help you leverage current technologies and move toward a more data-driven approach to planning or performing an audit.
This is basically saying that if you utilize the currently data and analytics tools that are currently on the market, then you’ll be able to better analyze data and spot anomalies in the data (i.e. potential misstatements or issues with the internal control environment). The most common tools available on the market include Alteryx, Tableau, Power BI, and Python. Some of the larger public accounting firms have designed their own data analytics tools.
The biggest benefit of audit data analytics is that audit sampling doesn’t need to be used because we can audit the entire population (yeah that is right, the entire population). So if the company has 1,000,000 sales transactions, we can test the full 1,000,000 rather than the 100 transaction that we “haphazardly” selected.
Now I know we have painted a beautiful sunset when it comes to data analytics in an audit, but the main issue is that most clients still don’t have quality data. To effectively use data analytics in an audit, the client needs to provide high quality data. That means that its accurate in the system, the data is complete, and it includes the necessary fields to be effectively used for audit procedures.
Now, don’t assume that you’ll work less hours in busy season. Technology and data analytics in audit will allow audit teams and accountants to work smarter and more efficiently.
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