CFOs could benefit from digital technologies in finance

Find out why emerging digital technologies like chatbots, blockchain, AI and machine learning are not only beneficial to finance, but can also serve as useful tools for the CFO.

Several emerging technologies that are transforming all of IT and the business, including analytics, AI, chatbots and robotic process automation (RPA), also have the most potential to digitally transform the work of the CFO.

When CFOs look at their finance functions, they're really trying to deliver two fundamental tasks for the business: governance and guidance. These are the two pillars of the role of the CFO, said Ash Noah, managing director of Chartered Global Management Accountant (CGMA) learning, education and development at the Association of International Certified Professional Accountants.

"When you look at governance, it's all about making sure controls, policies, compliance [and] accuracy of reporting [have a] true and fair view of the financial position of the company and that it's governed according to those policies and procedures," he said. "And that has always been the core."

Business guidance, on the other hand, is about helping businesses continue to make the right decisions, especially about where to invest and to ensure that operating costs are minimized and profits are maximized. Business guidance is really all about business decision-making and analysis, according to Noah.

The governance aspect of the CFO's role is more predictable, rule-based and repeatable. Consequently, it's been easier to adopt technologies such as ERP systems and robotics to help automate accounting operations, he said.

"So accounting operation technologies, which are really helping the CFO to automate large volumes of transactions into a computerized digital environment, have been happening for a good part of 10 years," Noah said.

Digital technologies in finance for the CFO

Now, decision-making on the business guidance side of the CFO's role is being supported by technology. However, the technologies themselves will not deliver anything to the CFO unless those technologies are taking good advantage of the large amounts of data to provide insights to the business.

"Visualization, in-memory computing, cognitive computing and advanced analytics -- those really have helped the CFO in processing and leveraging large amounts of data in order to present alternative views, scenarios, and then make the right decisions," Noah said.

For Henner Schliebs, vice president for ERP and finance at SAP, the most important technology for the CFO is AI because it's the overarching technology that includes the underlying technologies such as RPA and machine learning that make the finance department "intelligent."

"[These technologies] provide insights in real time, which was unheard of until we had [AI]," he said. "They also make good suggestions for what's coming in the future, that is, predictive forecasting. So at the beginning of a month, CFOs can look at how the month would end."

John Van Decker, research vice president at Gartner, agreed that the system of record, i.e., core financials and the financial close, are ripe for AI and machine learning use cases.

"We're seeing vendors provide functionality now, as well as having fairly robust plans in the future in terms of giving more capabilities and addressing more use cases," he said. "We're seeing it in the case of invoice management, in the case of disbursements [and] cash management. Not just chatbots saying, 'if you do this, this happens,' but we're seeing it in cases projecting that if you do this type of cash move, you're going to have these issues."

Now, decision-making on the business guidance side of the CFO's role is being supported by technology.

Because of what's happening with AI and machine learning, Gartner recommends that enterprises upgrade to cloud products that include those capabilities.

"I think that the official AI [and] machine learning strategy for finance is going to be to take advantage of functionality that's provided in your core applications," Van Decker said. "You're probably not going to go out and buy a separate AI [and] machine learning package, nor are you going to hire data scientists to comb through general ledger data."

Another technology that can also be advantageous to the CFO is blockchain because it reduces fraud and cuts down on errors in intercompany relationships, according to Schliebs.

"Whenever I have cost, somebody else has some form of revenue and whenever I have revenue, somebody else has some form of cost," he said. "So why do we have to keep everything in separate books if we could have the relationship between your company and my company in the blockchain book, where both of us have access to this data, but we don't have to reconcile it?"

Digital technologies assist with business goals

Digital transformation is disrupting the business environment worldwide through the rapid introduction of new technologies and the emergence of new business models, and "fierce competition is exacerbated by growing economic unease," according to the "2019 CFO Agenda: Building Next-Generation Capabilities" report from The Hackett Group.

As such, companies and finance organizations are aiming to reduce costs, as well as differentiate themselves by offering better customer experience. To reach these goals, finance organizations surveyed by The Hackett Group have identified five imperatives for 2019:

  • Reducing operating costs
  • Modernizing application platforms and taking advantage of new technologies
  • Improving analytics capabilities
  • Redeploying capacity to value-creating activities
  • Aligning skills with business needs

What The Hackett Group found is that the most active areas for digital technologies in finance are cloud and SaaS-delivered business applications, RPA, advanced analytics, master data management and data visualization, said Nilly Essaides, senior research director of the finance and EPM advisory practice at The Hackett Group and one of the authors of the report.

"We also see great increases in overall adoption of these technologies," she said.

For example, RPA is growing because of poor connectivity between companies that have legacy business applications, such as ERP and different systems for planning different parts of the organization.

"You need to somehow quickly synchronize [and] integrate all that, so the systems automatically exchange data and produce activities that used to be manual," Essaides said. "RPA solves that problem."

Bhaskar Himatsingka, chief product officer at Adaptive Insights, a Workday company, said that machine learning is also important when it comes to the transactional part of finance, such as how to make the close process be continuous.

The process currently is that the whole accounting department works hard at the end of the month to ensure all the numbers add up, he said.

"But what if the system has entries coming in and [finance] could figure out which journal entries they really needed to spend energy on and which they didn't? That way, they could smooth the curve of how and when they spend their time," Himatsingka said. "And they could get into a continuous accounting process, rather than an end-of-month or end-of-quarter accounting process."

The reason for the increase in digital technologies in finance, specifically advanced analytics, is because the business landscape is changing so quickly, according to Essaides. In many cases, disruptive technologies and new business models are completely transforming the business environment for companies.

"And the impetus for having the right information and good insight into how to adjust course quickly has grown tremendously," she said. "So it's imperative for finance in support of management decisions to develop the analytical tools, such as predictive capabilities, even prescriptive analytics, that look forward and provide insight so management and senior leadership can make effective decisions."

Underlying advanced analytics is master data management, another one of the most important digital technologies in finance.

"Because if the data is not consistent across the organization, it's very hard to come up with good analytics with good insight," she said.

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