The reality of digital disruption has been clear to finance executives for years now and for many, if not most, the disruption is already well underway. New Accenture research into the current state of the finance function reveals two contradictory insights into finance’s digital transformation journey.

On the one hand, CFOs seem confident: 77 percent agree that finance should set the agenda for the implementation and rollout of new technologies across the enterprise. On the other hand, more than half (53 percent) of CFOs worry that the finance function is too reactive. Many CFOs (64 percent) are concerned about being out of sync with the rest of their company when it comes to driving enterprise-wide efficiency by adopting digital technologies.1

How can these executives proactively harness today’s digital technologies to their company’s advantage? Most finance functions have a long way to go. Even by 2021, CFOs anticipate that less than 50 percent of all finance tasks will be performed by machines.2 Forward-thinking CFOs need to declare that position unsustainable. Accenture Strategy estimates that 70 percent to 80 percent of backward-looking accounting activity can be automated, resulting in limited to no human intervention.

Real transformation

Part of the promise of AI, as the authors of the book "Human + Machine" write, is not in the technology itself but in the transformation of business processes that the technologies enable. The finance function has been through several waves of “transformation” focused on either the centralization or standardization of processes—sometimes both—but neither approach has been truly transformative.

Now, the rise of user-centric design, combined with the improved quality and speed that comes from in-memory computing, opens doors to facilitate more financially savvy business decisions using a “finance on-demand” approach. To compete in today’s fast-paced, volatile economy, business leaders need daily sales and near-real-time profitability reporting to make the right decisions to drive growth and maintain business agility.

This is a major paradigm shift: moving finance away from a mere reporting function to one that puts information at the fingertips of executive leadership in near real time. According to our research, 78 percent of CFOs are embracing the future of self-service and the liberation of the function from running reports and crunching numbers.3

The benefits are broad, including an improved customer experience and increased functional excellence—all at a lower cost to serve.

Seventy-seven percent of CEOs agree that finance should set the agenda for the implementation and rollout of new technologies across the enterprise.

A new world of possibilities: Real-time data, freed-up time

To unlock the value of digitalization, CFOs must develop a comprehensive artificial intelligence (AI) strategy as part of a broader digital road map. To the extent they are working in digital, most finance functions are focused on conducting pilots in Robotic Process Automation (RPA). Although this is a fine place to start, RPA is only appropriate for linear, rules-based processes. Transformative value comes from more sophisticated forms of AI. For example, machine learning is already being used by leading finance functions to achieve “continuous close.” The days of closing books on a monthly and a quarterly basis are over.

Companies can use machine learning to process, validate or correct journal entries at the time of booking. The same machine learning capabilities can perform continuous reconciliations between systems, ledgers and intercompany transactions. This dramatically decreases the need for humans to perform time-consuming reconciliations, and the need for control testing largely goes away. Continuous accounting enables continuous cognitive auditing, accelerating the remaining tests to a real-time basis.

Annual financial planning is another painstaking, time-consuming process. Now, however, the combination of historical, internal and often unaccounted-for external data sources—e.g., market reports, weather, geo-political events, etc.—can produce a far more accurate financial plan than anything based entirely on human intuition. When it comes to predicting operational and financial performance, use the insights from machines. They have less bias and bring less baggage to their decisions and forecasts. Then, unleash the creative and collaborative powers of humans to identify new growth opportunities or assess previously unidentified risks and rewards.

Progress along overlapping growth curves

Graphic shows adoption curves for established to scaling to emerging technologies in the Finance organization.

Jumping the S-curve

Achieving a digital finance function is neither linear nor incremental. Getting started is the first step but leaders will jump the S-curve (see Figure 1). They will look comprehensively at their digital strategy, identifying opportunities to move beyond the digital basics of RPA into true AI—cognitive computing and algorithm-based predictions and advisory services. Look at the series of growth curves in the figure. Where are you on that progression? Are you stuck in the “established” category? Are you riding a curve that is in decline? Then what? If you’re only doing RPA, it’s time to make the wise pivot to capabilities like predictive analytics and dynamic risk analysis.

Be bold. Stop thinking only in terms of testing and piloting. Think strategically and holistically. Build an ever-green, rolling 18-month digital road map for the entire function. Look comprehensively at data, technology, talent and culture. The pace of change is only getting faster. The new imperative for business is exponential growth. If the finance function moves too slowly with digitalization, that’s a real growth inhibitor.

Unleash your digital future, today.

1 Accenture 2018 CFO Reimagined research.

2 Ibid

3 Ibid

Cherene Powell

Managing Director – Accenture Strategy, CFO & Enterprise Value


Digital finance moonshot

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