I still hear auditors questioning the value of audit data analytics.
Here are eight reasons why you might NOT be seeing the potential benefit:
You “bash the balance sheet” taking a mindset that if the opening balance sheet was audited, and you focus your audit effort on the closing balance sheet, then the income statement is just the difference and must be correct.
You test journal entries as one of the last tasks on the audit. You scan through an Excel list of “manual journals” posted at the yearend and add some discussion to the file as to why everything is already audited, or as you expected.
You test revenue through substantive analytical review, plotting a few charts to show how seasonality is normal, or how a high-level back-of-the-envelope reasonableness test perfectly predicts the client’s actual revenue figure.
Your sample size calculator has a cap. That means that even in areas where you should be testing a large sample size, such as revenue testing, you aren’t.
Your preliminary analytics is something you do to complete the checklist. The client’s financial performance and balances do not impact your risk assessment decisions.
You think the most efficient audit process is to do Same-as-last-Year. You roll forward as much as you can from the prior year audit file and perform near-identical audit work.
You satisfy the requirements to communicate to those charged with governance through an informal chat, or by sending a dry, boilerplate, text-heavy management letter.
You have no interest in adding value to your clients.
Before exploring audit data analytics, you should make the following adjustments to your approach:
Focus more on the income statement and how transactions are recognized throughout the financial statements. This naturally makes you think about business cycles and controls (even if you don’t test them) which leads to a more effective and more valuable audit.
Recognize that fraud can occur at any time of the year, and that if you aren’t testing IT controls you can’t exclude automated entries from your testing. You need to consider all transactions posted throughout the entire year.
Only allow substantive analytics to be performed in very specific circumstances (e.g. where an independent expectation can be set from reliable external data sources) – which likely won’t exist for revenue. Substantive analytics is typically a weak audit test with too many flaws. There is good reason why hardly any of the largest firms allow this - when I was at PwC substantive analytical review on revenue was banned in 2012!
Prepare to justify to regulators the logic of a sampling cap. This is a hot topic for many regulators – if you can’t soundly defend the logic then you need to remove the cap from your sampling calculator.
Use client financials as the basis for your risk assessment discussions and decision making, so your audit approach is more tailored. Focus more effort on higher-risk areas, and conversely less effort on lower risk areas. Even better, remove from scope balances or assertions where there is no realistic risk of material misstatement.
Be selective over which parts of the audit file you adopt the same approach as last year. Changes in standards are promoting greater tailoring of the audit each year. Dynamic macro-economic environments and developments in technology should result in greater variation in your audit from year-to-year.
Take a step back to critically consider the outputs from your audit. Would you value the informal communications or the management letters you provide if you were a client buying your audit service?
Ask your client if they want to get more value from your audit services. And if they do, would they be willing to pay more for a more valuable, insightful audit process?
It turns out that none of the above can be fixed by buying a cool audit data analytics tool.
What you need to change is:
Your mindset – view your audit service as a premium compliance service which can add tangible value to your clients.
Your audit methodology – update your methodology or embrace new ones to help your teams perform high-quality audits and using more advanced technologies.
Your audit software – you can have data analytics tools working alongside your existing audit software. But if you’re stuck performing your audit in a desktop solution it will slow down your innovation efforts.
Audit data analytics adds huge value to the external audit process. But like any change, the value it offers to you specifically depends on what you currently do…
