The explosion in digital technology is transforming the job of chief financial officer.
For a role that didn’t really exist until the late 1970s, chief financial officers, or CFOs, have assumed greater strategic importance in a relatively short time. These crucial executives have gone from being thought of as “number crunchers,” armed with spreadsheets and calculators to being key architects of growth and performance targets.
Most remarkably they’ve attained this with relatively little in the way of sophisticated technologies: just a Microsoft Excel spreadsheet, finance and accounting software or an enterprise resource planning (ERP) system—and, if they’re lucky, well-honed instincts.
But with the explosion in digital technologies—application programming interfaces (API), robotic process automation (RPA), mobile phones, data analytics, blockchain, cloud computing, artificial intelligence (AI) and machine learning—CFOs are now faced with a dizzying array of choices when it comes to technologies that promise to transform how they do their job. How do they distinguish between what is just “noise,” and technologies that could really benefit their organizations?
Amy Shelly, CFO at the Options Clearing Corporation (OCC), based in Chicago, the world’s largest equity derivatives clearing organization, says finance professionals are by nature risk-averse. “Our job is to protect the assets of a firm, not to expose a company to the latest shiny new toy,” she says. “That doesn’t mean I’m not going to take some calculated or well-informed risks.”
Shelly recognizes that many new technologies could be truly game-changing, so she remains “cautiously optimistic.” Meanwhile, “digital natives,” a term for people raised from earliest youth with digital technology, are starting to fill the employment ranks. Finance in the future, according to The Changing Face of Finance, an October 2018 report by financial analytics provider Metapraxis, will not be tied down by labor-intensive bookkeeping and reporting, but instead use “analytics and AI to provide the insights [that] add real strategic value to the business.”
More than half of the 400 young workers in finance at large US and UK companies who were surveyed by Metapraxis for the report believe that “advanced analytics offer a transformational opportunity” for finance, while 33% expect that “AI and machine learning will have a big impact.” More than 60% recognize that the “automation of core processes and strategic decision support … could threaten their role,” but a larger majority (78%) “see automation as an enabler.”
This optimistic outlook is widespread among finance professionals. Andy Power, CFO at Digital Realty, which specializes in data centers for companies working in health care, financial services and social media, believes more-sophisticated data analytics will free CFOs to do more than count beans. “Data will give the CFO an even more strategic seat at the table,” he says. “We’ll be able to look at things with a more analytical framework. A lot of the manual processes within financial reporting that are fraught with risk and human error will be derisked, resulting in quicker and more accurate financial reporting. We’ll no longer be dependent on Excel spreadsheets.”
David Carney, a principal in Deloitte Consulting’s finance and enterprise performance practice, which advises Fortune 500 CFOs and other finance executives, equates the finance function’s current transformation to the introduction of mainframe accounting systems in the 1960s, when companies moved from paper to the green screen. In many respects, he says, the current technology explosion is even more radical than what went before. “It means finance will be transformed from being less focused on creating accurate financial reporting for Wall Street, and more of a catalyst for change.”
James Buckley, vice president and director for Europe at financial software provider Infosys Finacle, says instead of “fighting fires,” AI will let CFOs gain greater data clarity from internal risk systems, freeing them up for more predictive forecasting—fiscal “fire” prevention, so to speak. “Low-level decision-making will be completely automated in five to 10 years,” he says. “Treasury and cash management will become more like algorithmic trading, with systems doing the job for you. It’s only when you have some form of systemic failure that you’ll need to intervene.”
A 2018 Gartner survey of more than 400 organizations found that more than a fourth “expect to deploy some form of AI or machine learning in their finance department by 2020.” Half are set to deploy predictive analytics. “CFOs and other finance leaders are looking for new ways to reduce costs, improve controls and uncover fresh insights that could drive competitive advantage,” says Christopher Iervolino, managing vice president at Gartner. The technologies that CFOs are using to achieve these ambitions, according to Gartner, include predictive analytics (50%), mobile financial process support (32%), robotic process automation (29%), integration of external data (27%) and AI/machine learning (27%).
Finance is about to get a much-needed injection of technology, which will help better predict financial and risk outcomes and their impact on the overall business. “Instead of relying on gut instinct, [the finance function] will be more precise, based on a data-driven approach and less overall human error,” says Digital Realty’s Power. “But I don’t think we’re moving to a world where the CFO’s job gets any easier. New challenges will be anticipating what’s next and using technology for further transformation. We’ll also need to think more globally.”
Power says it will be another five to 10 years before more-sophisticated technologies like AI are fully adopted by finance teams. Companies will need extensive “cleaning up” to rationalize the number of ERP systems—or different versions of the truth. “The challenge is that few companies have a single ERP system,” says Deloitte’s Carney. “The way data is defined varies across different ERP systems. To do more-sophisticated regression analysis and more-accurate forecasts, you need to pull data from a single ERP system.”
Will financial professionals need to become computer programming experts or even data scientists? “CFOs will not need deep technology expertise, but they will need to understand how these technologies are used,” says Natalia Nikolova, director of the Advanced MBA program at the University of Technology Sydney. “You can’t rely on data coming out of AI if you don’t understand how this data has been generated.” The university teaches financial professionals about data analytics and computer algorithms as well as more-traditional finance and accounting subjects.
Shelly, at the OCC, says computer science skills may be needed going forward. “But CFOs don’t need to become subject-matter experts in these various technologies,” she adds. “We need to have enough of an understanding to know what we’re looking to achieve, what problems we’re trying to solve and what processes we’re looking to make more efficient.”
Shelly believes CFOs of the future will enjoy an even closer partnership with technologists, so they can ensure that outcomes are most favorable for the organization. “If you don’t choose the right system, you’re not going to end up in the right place; and it won’t have the impact you envisaged,” she explains, “so we need those broader insights. We all want to do things better and faster, because there is more demand on us. But we need to find the best way of using these technologies to help us get there.”
