Finance Technology: The Ultimate Guide for CFOs

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Gain insights into the cutting-edge finance technology strategy that is transforming the finance function. Download the CFO’s guide to finance technology.

New types of software vendors are building intelligent applications that use AI in finance to solve common problems. Our research shows that leading AI finance organizations are 71% more likely to purchase software platforms with embedded AI features. A growing number of vendors are differentiating themselves by building intelligent finance applications that natively leverage AI in common back-office processes like accounts receivable, accounts payable and audit.

Robotic process automation uses software scripts with if-then rules to execute defined processes leveraging structured data. RPA can have a huge impact on the finance function, as much of the work that finance teams do follows clear process steps and a defined set of rules. Programming a robot, or team of robots, to undertake this work can eliminate the risk of human error and, in many cases, complete the task in half the time it takes a human.

RPA does have limits. RPA is designed for “doing” and is therefore inappropriate for complex, dynamic processes that require analysis and judgment. Also, each RPA deployment is stand-alone, designed to automate a specific process and not scalable beyond its original use case. However, for most organizations, the use of RPA for finance is a cost-effective way of improving accuracy and increasing productivity, which is central to finance’s long-term strategy. And unlike traditional finance IT solutions such as an ERP installation or upgrade, implementing RPA doesn’t require a “standardize then automate” approach. In fact, RPA can automate individual tasks or components within a process that make the overall process more efficient.

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