10 real world cases of robotic process automation (RPA) in accounting
The future of robotic process automation (RPA) is looking brighter and brighter, as software robots become more and more prevalent cross-industry. The Deloitte Global RPA Survey estimates not more than 5 years before near-universal RPA adoption.
Accordingly, we’re taking a look today at the effects and application areas of robotic process automation in accounting, as software robots are expected by people from within to revolutionise the industry.
In fact, intelligent automation is the new buzzword in accounting. And this is the case for very good reasons. Accounting processes, such as order to cash, procure to pay, finance transformation, etc., require collection and analysis of large amounts of data, while also being rule based and repetitive. Moreover, precisely due to features such as these, they also trigger employees’ long faces and migraines. So robotic process automation in accounting seems to be a match made in heaven.
A McKinsey report confirms, by estimating a global automation potential of 43% for finance and accounting. Relatedly, UiPath specifies an automation rate of 80% for common processes like accounts receivable or accounts payable.
Let’s take a closer look at some robotic process automation real world use cases and learn some strategic steps towards leveraging RPA in accounting.
Robotic process automation (RPA) use cases in accounting
The list of 10 concrete application areas of robotic process automation in accounting is meant to assist you in conceiving a ‘roadmap’ of means towards your business objectives. The processes that we’re going to discuss are meant to assist you in devising an efficient automation journey.
1. Accounts payable (AP)
We were saying that such tasks seem to hold the lead when it comes to leveraging RPA in accounting. Software robots can transfer inbound invoice information (like invoice number, data received or dollar amount) from PDFs into SAP web applications, and internal spreadsheets. Consequently, they can place a PDF duplicate on an internal server. This is a very useful thing to do in order to ensure regulatory compliance, and it can reduce up to 60% of vendor invoice processing cycle times.
2. Accounts receivable (AR)
Bots can handle more easily (i.e., faster and more accurately) the maintenance of customer master files and credit approvals. The same goes for order, and AR cash receipts processing. As a nice final touch, late notices can be sent by email more quickly, thereby minimising the hassle that naturally comes with last-minute notifications.
3. Controller function
Bots can automatically reconcile the current period invoice data feed against the last period, whenever the controller opens the data file. This drastically reduces the processing time needed to compare data across different periods.
Data that cannot be so easily handled, i.e., that trumps automatic reconciling, are the exceptions, and those are delivered for processing to human accountants. The results are much faster, and the employees can deal only with slightly more exciting data, or data ‘with a twist’.
4. Cost allocation
Automation easily merges data from different sources (like emails, Excel spreadsheets, Google documents, etc.) into a master file, which can then be uploaded directly into an Enterprise Resource Planning (ERP) and data management program. This can be done by software robots in no time, i.e., less than one minute.
5. Financial close and reporting
This is an epitome of inter-departmental, multisystem processing. We believe there is no exaggeration to say that posting tax entry data from various business units is a monotonous, headache-provoking task. Which is why it’s worth to have a software robot mitigate it. Moreover, its error-proof potential also adds value to the process.
6. Accounting reconciliation
Accounting data calls for reconciliation of subaccount balances taken from a variety of sources, such as Excel sheets, or customer invoices. You can automate the process and download the data into desired format. Data validation and exception search can then be performed much faster. This is the case because balancing journal entries are created, and judiciously used to handle invoice discrepancies.
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