Fewer samples, more insights

Revenues are key risks. This equally means that auditing revenues is a key aspect of an auditor’s daily workload. We usually take a significant number of samples from all revenue transactions to confirm the complete and accrual-based recognition of revenues. However, the sample-based approach allows only for limited qualitative insights about the complete revenue population holistically. It would be great if this could be reversed: fewer samples but more transparency about the revenue stream(s) and their financial recognition methods. This is possible thanks to a data-driven audit approach when auditing revenue.

Methodology

Through the help of data analytics we can analyse all sales transactions in the general ledger regarding their account combinations and offsetting entries. As an initial step we define those transactions, that follow an expected posting process. We then can audit the result of this analysis through other existing audit procedures. The result: assurance for all revenue transactions following the standard (or expected) process flow. For unexpected transactions we can then perform targeted audit procedures addressing this sub-population, if needed from a materiality perspective.
The analysis of all revenue transactions for the relevant sales accounts is performed in two steps: Firstly, the contra accounts for all sales accounts are evaluated and defined. Then, a contra account analysis is performed for all revenue transactions on trade receivable accounts through the use of data analytics.

Application and suitability

Data analytics when auditing revenues is recommended, provided the following preconditions are met:

• The accounting logic for the sales revenues and trade receivables is straightforward, thus not complex, and the revenue is recognised at a point in time; for example, no revenues from long-term contracts as well as contracts consisting of several components.
• Sales are mainly offset directly by payments or against receivables.
• Auditors have an in-depth understanding of the client’s sales process and revenue flows.
• In previous audits, the auditors have not identified significant findings in revenue testing.
  

Advantages

In the first-year, certain investments are required to determine the expected flow(s) for revenue transactions. Such investments are, however, limited to a manageable level whereby the account mappings can be reused in subsequent years thus significantly reducing the effort required for performing the analysis of revenue transactions over multiple years.
With the use of data analytics, manual samples of individual revenue postings can be decreased, and the quality of the revenue audit increases overall. This means, the auditors’ revenue statements are not just based on a limited number of manual samples being tested but on the total population being 100% of all revenue transactions. And in an environment where the operating effectiveness of the controls in revenue accounting can be leveraged, the auditor can reduce his audit procedures and efforts further. Furthermore, the approach allows for more qualitative discussions between the client and their auditor by focussing on anomalies and insights gained.
Data analytics provide more transparency on the posting methodology being applied and identifies posting patterns quickly and easily. Using data analytics when auditing revenue increases the level of confidence and provides deeper insights into the sales process as a whole.
This effective and efficient audit approach, which intelligently leverages the opportunities from data analytics, creates a ‘win-win’ situation for client and auditors alike.