Three practical ways AI will help finance shape up for the future

Erik Zahnlecker Profile picture for user Erik Zahnlecker April 19, 2021
AI in finance is capable of much more than shortening processes by a few days here and there. Erik Zahnlecker of Sage AI Labs shares three concepts that make the most of the growing financial data available to customers.

Business man holding lightbulb on coins AI insights concept © maeching chaiwongwatthana - Shutterstock
(© maeching chaiwongwatthana - Shutterstock)

Recently, I read a book to my five year old nephew about Dorothy Vaughan. She was a mathematician who worked as a human computer at Langley Research Center. The idea of a human computer performing mathematical calculation feels very distant and strange to me today, but it's a profession that existed at least since the early 17th century. With the emergence of electronic computers, the book describes Dorothy's transformation to become one of the early programmers making significant contributions to the US space program.

At Sage, we have talked with our customers extensively and believe that we will witness a transformation in finance enabled by AI over the next five to ten years that is on a similar scale to Dorothy's experience. What today are still largely slow, manual, and error-prone processes, will be automated by computers – thus opening space for something new, and redefining the role that humans play in the world of finance and business at large.

This is in part made possible due to an ever-growing amount of financial data that lives in the cloud and is now accessible in ways they have never been before. This is enabling accounting and finance to move away from processes that traditionally rely on monthly or yearly cycles – and toward continuous, real-time practices in three primary areas – accounting, trust, and insights.

My team and I at Sage AI Labs are dedicated to driving Sage's AI transformation at large to realize the following three concepts.

Accounting – eliminating the close

For many years, forward-thinking financial professionals have pursued an ambitious and elusive goal – to eliminate the dreaded closing process (whether monthly, quarterly, or annually). At last, with the power of AI, this goal seems to be more in reach than ever before.

First, we must capture all business activity in real-time. Second, we must transition to continuous reconciliation. Finally, we must train AI-driven systems to make continuous adjustments as our business environments evolve. Accruals, allocations, and other period-end adjustments should occur automatically and continuously. In this manner, virtually every business day is a closing day where you're capturing, reconciling, and adjusting transactions in real time.

AI can facilitate this in a variety of ways, including tools and technologies to automatically capture and code data (e.g. T&E charges, invoices), smart reconciliation engines, and intuitive conversational interfaces, all underpinned by machine learning models that grow smarter over time.

While some of you might still be struggling to get your current monthly close process even just a day or two faster, we see AI eventually offering a complete change to how you view the close. Instead of being something that happens a several times a year, the goal is to have the close process be ongoing and continuous – thus eliminating the need to have a stand-alone process for it.

Continuous assurance – building trust

Just as we seek to move accounting into an ongoing, real-time process, we similarly want to elevate audit and assurance into a continuous activity. After all, the heart of all financial activity is trust. Key stakeholders such as investors, bankers, and regulators trust that the finance team will not only be compliant, but also provide guidance grounded on accurate information.

The continuous audit starts with continuous detection – the AI-powered ability to review and detect irregular activity in real-time. We can also capitalize on new graphical user interfaces that help users review and make intelligent decisions when AI flags irregularities. As users and AI technology learn to work together on continuous audit, we can improve our controls and assurance models to minimize exceptions.

Rich data sets and powerful cloud computing allow us to build machine learning models that learn how to understand accounting transactions and detect anomalies to expose inaccurate, non-compliant, or even fraudulent activity. Where humans might have the time/ability to review a small subset of transactions to find anomalies, AI and machine learning-based systems can review massive quantities of data in seconds – providing added assurance in your financials.

Furthermore, with AI working on continuous accounting and continuous trust, your team is free to apply its talents to more strategic activities. We often hear from customers who are concerned AI will replace them. To the contrary, AI has the potential to eliminate some of the mundane, grunt work that takes up time each day and elevate their role to a more strategic level that is focused on the future. This is perhaps the most exciting advantage AI can provide.

Insights – knowing the unknowns

In a sense, AI helps us know the unknowns by making better predictions about the future. Armed with this insight, professionals will ultimately make smarter decisions and be comfortable taking decisive action. The real magic is AI doesn't sleep; it continuously watches activities, identifies exceptions and patterns, and alerts you when the future will change in unexpected ways.

We hear from customers all the time that forecasting is a very intensive process, and as a result it's only feasible to get a reasonably accurate forecast a few times per year. But with AI-powered forecasting, we gain unprecedented speed without sacrificing accuracy. We also know when the forecast changes in real time and understand the factors affecting the change. Ultimately, we can reallocate resources to capitalize on opportunities, respond to previously unseen threats, and drive to a better outcome.

As finance leaders begin to integrate AI into their daily finance workflows, we believe that CFOs will continue to rise from their traditional back-office roles to organizational leadership. They'll gain a new voice and a distinctly clear and prescient view of the business.

That said, we understand that there is still a lot of misunderstanding and uncertainty around AI technology and the role it will play in finance. These changes won't happen overnight and the key is learning and being prepared. If you want to learn a bit more about this topic, I participated in a great panel discussion a few months ago on How AI Will Transform Financial Management. It covers an AI primer and also addresses some of the main questions we've heard from talking with our customers about the future of AI.

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