5 Major Revenue Recognition Risks and How Finance Automation Can Help

Revenue recognition poses significant risks to organizations –  when revenue has been improperly or incorrectly recognized due to error or fraud, potential penalties and reputational damage can occur.

In the US for example, the Securities and Exchange Commission (SEC) has detailed guidelines on revenue recognition in its Staff Accounting Bulletin No. 101. The overarching guiding principle is that revenue should not be recognized until it is realized or realizable and earned, which is generally when the following conditions have been met:

• Persuasive evidence of an arrangement exists
• Delivery has occurred or services have been rendered
• The seller’s price to the buyer is fixed and determinable
• The ability to collect the revenue is reasonably assured

However, many finance processes and controls around revenue recognition are still manual, which can lead to unintentional errors or leave the door open to deliberate fraudulent activity. Here are five of the main revenue recognition risks and how finance automation can help address them.

1. Fraud

One of the most frequent types of management fraud involves fictitious or premature revenue recognition to enhance earnings. At WorldCom, manual journals were used to inappropriately capitalize expenses as fixed assets, which inflated net income and total assets by $3.8 billion. In another example, HealthSouth Corporation inflated its earnings by $2.8 billion over six years using manual journals in the same way.

Despite large investments in modern ERP and finance systems, manual accounting processes such as journal entry continue to leave businesses exposed to significant human error or fraudulent activities. This ultimately creates the opportunity for the material misstatement of financial results and its consequences.

2. Recognizing the right revenue

Not only must organizations ensure they are properly recognizing revenue in accordance with accounting financial standards, but they must also ensure they are recognizing the right revenue. For example, if you’re not managing your stock effectively, or if you’re not tracking goods in transit between you and a customer, there is the potential for not actually reporting the right revenue figures – simply because of flaws in the process that lead to incorrect figures rather than fraud.

3. Selling price calculation

This is about selling goods and services at the right price and margin to ensure you are optimizing revenue recognition. One of the challenges around selling price calculations is that they are often based on complex pricing algorithms within ERP software. Because these algorithms are complex, there are assumptions that aren’t always checked and might not be correct. For example, the overhead recovery rate in SAP might not actually be recovering all your overheads, which in turn means your profit margins may not be as planned.

Finance automation can help tackle this by doing an automated check and analysis of your costings and sale prices. Automation can also help provide greater insight into profitability by taking the reports that SAP produces to do a deep dive on where you are making profit and where you are not, and across which customers and product combinations, taking into account the cost to serve. The data and reports are all there but finance often doesn’t have the staff resources and time to manually drill down and make sense of it.

4. Triggering of revenue recognition

Organizations must only recognize revenue at the correct trigger point in accordance with accounting standards. There are cases when this is done fraudulently to recognize revenue earlier than it should be to inflate earnings for financial reporting. And there are cases where it is done incorrectly simply due to flawed processes. This can be complex and a lot of the revenue recognition triggers are often manual and open to error or fraud. For example, in industries such as IT and software, the trigger is that the customer must have accepted the software before you are able to recognize it. Then you also have to calculate how you recognize the revenue of a perpetual software license over the life of the contract. All of this can be automated to ensure that revenue is only recognized at the appropriate trigger point.

5. Aggregating and analyzing data

More generally, if you aren’t aggregating and analyzing data, then you aren’t governing revenue recognition effectively. This applies not only in terms of legal and accounting best practice but also from a corporate governance and commercial perspective: you must be able to demonstrate if you are maximizing margins on sales – or whether you are actually selling at a lower margin or loss or lower margin. Utilizing automation to unify disparate sources of data during the close will help produce a comprehensive view of your business, helping your team focus on analysis rather than low-value manual tasks and becoming a better partner across the enterprise.

Find out how Redwood’s finance automation can help you reduce manual effort and increase efficiency and accuracy.

More on related topics:

Article: The human cause of 4 major accounting errors and how to eliminate them

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Podcast: How to automate controls and validations in SAP