You may have heard how robotic process automation (also known as “RPA”) is transforming the financial sector, taking on tasks that once required countless hours of staff time.
For some financial executives, the advent of RPA is a long-awaited revolution. To others, it may seem like a frightening disruption, conjuring images of androids, cyborgs and other dystopian machines intent on bringing Blade Runner to life.
And what’s the cost of RPA? Surely, integrating artificial intelligence into your finance team’s workflow would be time-consuming and expensive?
These suspicions are understandable, given the misinformation floating around the Internet about what RPA can and can’t do.
No matter how you view it, though, automated technology has a future in finance. A recent survey of 378 CFOs by Grant Thornton found that 25% of them had adopted some form of artificial intelligence for their companies in 2019—up from 7% in 2018.
According to Grand View Research Inc., worldwide spending on RPA has surged over the past four years. It’s expected to be an $8.75 billion business by 2024.
The machines are coming, so we might as well learn how to put them to work. As the cognitive scientist Marvin Minsky once put it, “Will robots inherit the earth? Yes. But they will be our children.”
Below, we dispel six common myths about RPA and the impact it can have on your financial team:
#1: You’re Going to Need a Robot
Despite the name, robotic process automation does not involve a walking, talking robot. It’s not an artificial intelligence virtual assistant (like Apple’s Siri) or a sentient computer (like Hal from 2001: A Space Odyssey). RPA is software technology that uses machine learning to master tasks that are time-consuming and repetitive. The bots that do all of this work operate within the RPA software.
Rather than being metallic, physical forms, these bots consist of algorithms designed to perform particular tasks. They mimic humans only in the ways they interact with various software applications—just with fewer errors and zero coffee breaks.
#2: RPA Kills Jobs
RPA doesn’t so much replace workers as it reduces the kind of manual work that humans hate to do. Dull, administrative work like data entry, invoicing, email routing and digital interactions can all be automated with RPA.
According to several studies, RPA can perform these kinds of tasks up to 70% faster than humans. Rather than triggering layoffs, automation can free up more of your financial team’s time, letting them perform more high-value work.
Finance is one of several industries affected by the “Fourth Industrial Revolution” of automation. However, full automation—and a large-scale elimination of jobs—is still many years away. Current technology like RPA is expected to fully automate less than 5% of occupations worldwide, according to a report from McKinsey & Co.
#3: Implementing the Software is Time-Consuming
The advantage of RPA software is that it learns quickly with minimal oversight and coding from developers. Through machine learning and natural language processing, RPA bots “watch” how human users perform a task and can soon duplicate that work. Typically, RPA can be implemented—and integrate multiple IT systems—within a few weeks.
A common misconception among financial chiefs is that a process has to be standardized across an organization for RPA to work. In fact, the set of rules in an RPA script can be adjusted to perform a task—and work with different software programs—from one site in an organization to another.
In other words, 20 regional purchasing managers do not have to operate in the exact same manner in order for RPA to take work off their plates.
#4: RPA Software is a Big Investment
RPA is actually a cost-effective bolt-on because it works with any legacy software systems your company already has.
Within a short time of using RPA, you’ll potentially save hundreds of hours of work, allowing your team to focus on more complicated projects like financial forecasting, interpreting rules and finding new use cases.
Likewise, any rudimentary work you once outsourced to other providers can now be performed by the bots. The time your people once spent on tasks like bank reconciliations, data entry, and matching payments to invoices can now be used on strategic work that helps reduce costs and grow the business.
According to a survey by McKinsey & Co., RPA can generate an ROI of 30% to 200% within the first year of implementation. Oh, and unlike its human counterparts, bots don’t keep an 8-to-5 schedule. The technology works around the clock, continuously improving your team’s speed and efficiency.
#5: RPA Never Makes Mistakes
When implemented, RPA will greatly reduce the number of errors that humans make doing the same kind of financial work.
However, the bots are only as accurate as developers or users have instructed them to be. They lack the advanced cognitive ability to read and react to changes in the data that are not preconfigured in the RPA software. Scripting a process in a clear, logical, and thorough manner will improve the accuracy and effectiveness of automation.
#6: RPA Can Automate Anything in Finance
While RPA represents a revolutionary approach to finance workflow, it definitely cannot duplicate all functions of a finance team. There are strict limitations to the kind of work that today’s RPA technology can perform. Rule-based, highly structured data that is repeated in a high volume is RPA’s sweet spot.
A successful approach to automation could start by assigning simple tasks and building up from there. For example, instead of handing your entire expense reporting process to a bot, have it start with a sub-process like flagging inconsistencies in the reporting. As the machine learning adapts to your process, it can take on more advanced, time-saving work.
Embracing the Bots
Ultimately, the rules-based logic of RPA is a perfect fit for many financial tasks. Instead of dreading the changes it might bring, consider how the technology can lower costs and free your team to do more dynamic work.
When applied to the right set of processes, RPA can be a powerful tool—one that many companies worldwide are already starting to utilize.