Future of finance: Extreme automation

Transforming finance operations with disruptive technology

Disruptive technologies are the largest drivers of change in business today. In fact, technology is shifting so fast that organizations such as Samsung, Ford, and NATO are enlisting science fiction writers to help them visualize the future and consider opportunities for innovation.1

Meanwhile, the combination of connected sensors, massive data gathering, and machine learning is driving unprecedented changes at home and work, with Amazon’s Alexa and Google’s Nest becoming standard fixtures. In addition, robots are maturing in both their accuracy and their interactions with humans, creating new applications from remote surgery to autonomous aircraft navigation.2

Technological disruption is affecting all corners of business, and finance is no exception. Indeed, extreme automation—the confluence of cloud applications, blockchain, cognitive automation, natural language processing, and more—is expected to create an all-new operating model. It is expected to empower finance to deliver more value with less effort, respond quickly to the needs of the business, and truly shift from traditional processing to strategic partnering.

The winners in finance will reimagine their operating model and develop a long-term strategy to harness extreme automation. Read this whitepaper to explore considerations for getting into action.

Extreme automation
The winners in finance will reimagine their operating model and develop a long-term strategy to harness extreme automation.


Implementing technology at new extremes

According to a recent KPMG study, 97% of chief executive officers see technological disruption as more of an opportunity than a threat,3 so it’s no wonder that almost every finance organization is in some stage of implementing data and analytics (D&A) and considering where to focus. Some are piloting robotic process automation (RPA) for manual tasks like creating journal entries or purchase orders, while others are battling legacy finance technology by moving to cloud financials. Still, others are experimenting with machine learning in such areas as contract review.

However, most of these efforts today are for one-off solutions and are not yet embedded into day-to-day operations. The “extreme” in extreme automation refers to the integration of multiple disruptive technologies—all at once—across all processes. In the next three to five years, for example, organizations are likely to have robotics and artificial intelligence (AI) everywhere, with electronic brains assisting in human decisions.


From scorekeeper to strategic business partner

Extreme automation is expected to create never-before-seen levels of maturity in finance operations. In addition to automating core finance and accounting processes and reducing labor requirements by up to 70 percent,4 it may enable finance to harness the data inside those processes and become a strategic interpreter, providing new kinds of insights.

For example, financial planning and analysis (FP&A) includes a lot of manual processes that may be automated, and that automation may also surface key data for advanced analytics on pricing strategies, market expansion opportunities, and other areas. In FP&A of the future, some finance professionals may have more formalized roles as business partners, working with analytics to provide predictive and prescriptive insights to help business units make better decisions.


A new labor footprint and service delivery model

As routine activities such as regulatory reporting or accounts payable become highly automated, labor requirements are expected to decline significantly. However, the automation of other areas of finance—such as reporting and planning—may result in an increase in the number of humans who will work with intelligent automation to provide strategic insights to the business.

An automated environment may help finance compete for the best talent, and that talent will bring an entirely new set of competencies, from advanced analytics to business partnering. Another critical role will be the data scientists who prepare data for use by machine learning, but as demand for data scientists continues to exceed the supply, finance may need a strategy for outsourcing this work.

As extreme automation changes the size of finance teams and the types of services, it is expected to also dramatically change the service delivery model. For example, instead of embedding financial planners in each part of the business, FP&A can use advanced analytics and cloud-based enterprise performance management (EPM) to create an integrated view of the front, middle, and back offices. As such, companies may effectively replace the “F” in FP&A with a “B,” creating a new business planning process that integrates finance forecasting with operations, supply chain, sales, marketing, and other functions.


Related insights


1 The New Yorker, Better Business through Sci-Fi (July 30, 2017)

2 KPMG LLP, The Changing Landscape of Disruptive Technologies (2018)

3 KPMG LLP, 2019 U.S. CEO Outlook

4 Estimate from KPMG LLP