Are Droids Running Your Finance Office--Yet?

In the same way that R2D2, the faithful droid from the Star Wars movie franchise, travels the far reaches of the galaxy righting wrongs, the software algorithms that guide Robotic Process Automation (RPA) travel the constellations of data collected by companies, resolving anomalies.

Agile Finance Revealed: The New Operating Model for Modern Finance, a recent study by Oracle and the American Institute of CPAs (AICPA), predicts that RPA and the related technologies of machine learning and adaptive intelligence will become increasingly important in finance automation as they help finance professionals free up their time for more strategic pursuits. Here’s how:

• RPA allows employees to configure software “bots” that interact with applications and perform high-volume, repetitive tasks such as account reconciliation
• Machine learning gives computers the ability to understand without being explicitly programmed and to optimize business processes such as internal audit and fraud detection, based on patterns and historical trends
• Adaptive intelligence, which combines the automated analysis of big data with human knowledge, helps financiers compare data-rich information, like sales of many online competitors

Oracle Vice President Loren Mahon explains that because so many tasks in finance are repetitive in nature, they are prone to human error. Mahon, who works in the CFO’s office and is an expert in large-scale transformation using new technologies, predicts that savvy finance teams will embrace automation as a way to “move away from these repetitive tasks and spend more time looking at insights and identifying risk and fraud.”

That ability to pivot is a core characteristic of “agile” financial leaders—finance experts who embrace new digital technologies, are responsive to change, and offer insight and strategic guidance to the companies they serve, according to the AICPA/Oracle report.

“Machine learning and robotic systems will ruthlessly automate many routine businesses,” the authors predict, “freeing up your finance team to spend 75% of its time on decision support and predictive analysis, guided by artificial intelligence and input from statisticians, data scientists, behavioral economists, and even anthropologists.”

Oracle’s Mahon ticks off a list of financial processes that are just right for automation:

• “Swivel chair” activities where financial analysts enter data in one system and then turn around and enter the same information into another
• Importing and entering supplier invoices
• Matching customer payments to accounts receivable
• Managing revenue recognition
• Performing account reconciliation
• Meeting regulatory requirements
• Speeding the monthly close
• Entering international currency and exchange rates

Software Never Needs A Day Off

Mahon believes that the evolving capabilities of process automation will appeal to modern finance organizations for three main reasons:

1. Automation reduces the processing time for routine tasks, saving the company time and money
2. Automation improves the accuracy of the results because computers are generally more accurate than humans when performing routine tasks
3. Companies can run these calculations outside the busiest processing times because “software never needs a day off”

“Finance is doing things that it never could before, thanks to digital technologies,” the report authors write. “End-to-end multidimensional data access is enabling total visibility into both enterprise and customer data. The result? The finance organization will evolve from an expense control, spreadsheet-driven accounting and reporting center, into a predictive analytics powerhouse that creates business value.”

Looking toward the future of RPA, Mahon believes that more and more companies will take advantage of evolving technologies to analyze financial data, customer experience data, and support data for end-to-end insights.

“I don’t have a crystal ball,” she says, “but I think we’re on the cusp of many new capabilities that combine process automation and machine learning. The potential is huge.”