Evaluate RPA’s impact to make smarter finance technology decisions
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Use Finance RPA to Drive Productivity and Lower Process Costs
Finance RPA (robotic process automation) eliminates repetitive tasks and is a foundational step toward hyperautomation in finance.
Despite broad adoption of RPA in finance, many finance leaders still struggle to assess the business impact of their finance RPA programs.
Download the Gartner report on 3 Tactics to Demonstrate RPA's Impact in Finance to explore how finance leaders are:
- Connecting finance RPA to larger business objectives — not just hours saved
- Prioritizing metrics based on finance RPA program maturity
- Identifying where and when RPA may have a lower relative impact compared to alternative solutions
About Finance RPA
RPA, or, finance robotic process automation, is an umbrella term for advanced software systems that can be programmed to perform a series of tasks that previously required human intervention. Finance teams have been piloting and adopting finance RPA because it’s a low-cost way to improve the speed, efficiency and accuracy of specific tasks. For example, the routine, rule-based tasks and basic operations that employees find repetitive and mundane could potentially be ideal for finance RPA implementation.
Some key considerations regarding finance RPA:
- Finance RPA is not one particular product or tool. There are multiple finance RPA solutions in the marketplace, and each one is designed to perform in different ways. If you decide to adopt finance RPA, you need to evaluate various products to identify which offering best fits your company.
- Finance RPA runs separately from applications and underlying systems. RPA software runs separately from your underlying systems and can be implemented and altered relatively easily. It does, however, require human work for quality control and maintenance.
- Finance RPA is faster, cheaper and easier to program. RPA doesn’t require the same level of IT involvement that traditional automation does. Business analysts with a clear understanding of process and workflow can program finance RPA technologies without training or coding knowledge.
- Finance RPA is scalable. There is no limit to the number of human activities or processes that are candidates for RPA. The best-candidate processes for automation are definable and rule-based, making reporting, accounts payable, customer feedback capture and sales quote preparation among the most popular candidate processes. Ultimately, the only limit to finance RPA’s scalability is a company’s ability to keep pace with the change management needed to sustain it.
Finance RPA FAQs
What is the difference between traditional automation and finance RPA?
The Institute for Robotic Process Automation uses the analogy that traditional automation is like cruise control on a car and finance RPA is more like a self-driving car. Traditional automation keeps your organization moving at one speed, but can’t easily adapt to shifts in the environment. Finance RPA identifies different conditions on the basis of a given set of rules and adjusts for those changes by following the rules. RPA, as a selfdriving car, would stop at a red light — if given that rule to follow.
How does Finance RPA connect to the larger AI landscape in finance?
Advanced technologies like machine learning (ML) and finance RPA have the potential to generate useful analytic insights and further improve the efficiency of finance processes. Finance RPA is a low-cost way to improve the speed, efficiency and accuracy of specific tasks, whereas machine learning uses past data to make predictions about the future. Finance RPA and machine learning compliment each other well in cases of finding patterns in historical data to identify relevant information and comparing outcomes to recommend next steps and inform decisions.
How do I scale finance RPA while ensuring I have the right data governance structures in place to support it?
In pursuing a path to finance RPA, CFOs often launch automation initiatives without considering the necessary governance structures and policies. There is no one-size-fits-all governance model for all finance teams, but to scale finance RPA, CFOS should:
- Define a governance model that takes into account existing internal capacity for finance automation projects.
- Define automation task owners by assessing the different strategic, operational and tactical activities required to launch and manage the finance RPA initiative.
- Streamline the finance RPA demand management process using a framework that includes an assessment of automation feasibility, activity complexity and volatility as well as team and business impact.
- Determine the right metrics to monitor their automation efforts given the stage and maturity of the automation program.