Advanced Computing in the Age of AI | Wednesday, May 18, 2022

Why Finance Departments Are Embracing Intelligent Automation 

Enterprises use intelligent automation to automate a wide variety of manual tasks, thereby freeing up their employees to spend more time on creative, higher-level activities. As a result, employees are empowered to deliver their customers better products, services, and experiences. Benefits like these have driven enterprises to rapidly adopt intelligent automation. According to Gartner, “the Robotic Process Automation (RPA) software market grew 38.9% in 2020 to $1.9 billion and held its position as the fastest-growing segment in the enterprise software market.”*

Finance departments have been among the largest adopters of intelligent automation solutions that combine RPA with AI. For example, in its Robotic Process Automation (RPA) State of the Market Report 2021, Everest Group found that Finance and Accounting processes represented one of the largest segments of the RPA software market, with a market share of 27%.

What is Driving Finance To Use Intelligent Automation?

One key reason finance departments have been at the forefront in the adoption of intelligent automation is the type of work they do. Unlike many other business units, they are not tasked with collecting, moving, or processing raw materials, finished products, or other physical objects. They collect, move, and process data. This makes much of their work well-suited to be supported by digital workers that are designed to handle data quickly and accurately.

Another reason why finance departments have been at the forefront in using intelligent automation is that digital workers are built to follow rules and log the actions they take. When the finance team designs a digital worker, they can ensure it follows all the necessary regulations and accounting standards. This strengthens controls and fosters transparency by creating an audit trail of its actions.

What does an Intelligently Automated Financial Task Look Like?

Here’s an example of what a finance department’s use of intelligent automation would look like for invoice processing. Finance uses an RPA- and AI-enabled intelligent automation solution to scan incoming emails for supplier invoices. The digital worker detaches these PDF invoices from the emails and uses AI to extract names, addresses, quantities, and other data from the PDFs – data that it inputs into the department’s Enterprise Resource Planning (ERP) or invoice processing system.

The digital worker then validates the invoice data against an existing purchase order and/or goods receipt. If it is unable to validate the data, it alerts a department employee that there is an exception to review. After the invoice has been validated by the digital worker, or, in the case of an exception, by an employee, the digital worker approves the invoice and triggers a payment to the supplier. In this scenario, a digital worker can reduce the time it takes to process an invoice from 20 minutes to as little as 6 minutes.

Finance departments can create similar types of digital workers to automate customer billing and other accounts receivable processes, consolidated cash reporting, manual reconciliations, and other financial operations.

How RPA and AI Work Together to Automate Financial Tasks

Even without AI, finance departments can use RPA digital workers to automate financial processes. However, by combining AI with RPA, finance can move beyond just automation to intelligent automation – automating the development and implementation of the automation itself.

For example, AI can analyze finance processes to discover which tasks currently being performed by employees could instead be performed by a digital worker – and which of these tasks will save the most time and deliver the highest ROI if automated. New AI-powered recorders can even enable non-technical employees to build their own digital workers with little or no coding expertise. In addition, AI technologies like computer vision, natural language processing (NLP), and machine learning (ML) can extract and organize unstructured data (like invoice PDFs) into structured data that RPA can then use to complete tasks.

How Finance Can Maximize the Value of Intelligent Automation Investments

Research shows that finance departments and other business functions can realize significant returns on intelligent automation investments. In a recent survey administered by Enterprise Technology Research (ETR), organizations reported average ROI from RPA across functions and industries of 250%.

Top performing organizations achieved a higher average ROI of 380% on their RPA investments. By implementing many of the practices the survey identified as characterizing these top performers, finance departments can improve the ROI of their own intelligent automation investments.

One of these practices is to establish an intelligent automation Center of Excellence (CoE) that works closely with finance and other business units to design, implement, and manage digital workers. Another practice is to rollout citizen developer programs that enlist business line employees, with some CoE oversight, to build digital workers themselves, rapidly expanding the use of automation across the enterprise. In addition, high performers use cloud-based platforms to deploy intelligent automation. This allows organizations to minimize their infrastructure costs and quickly scale up intelligent automation deployments.

Intelligent Automation is the Next Stage of Digital Transformation for Finance

Intelligent automation represents the next stage of digital transformation for finance departments – creating digital workers to work side-by-side with human beings. In doing so, intelligent automation not only increases finance employees’ efficiency and accuracy, but also liberates employees from performing boring, repetitive tasks, allowing them to concentrate on more fulfilling, strategic business activities for their organization.

*Gartner, “Market Share Analysis: Robotic Process Automation, Worldwide, 2020”, Fabrizio Biscotti,, et al, 26 May 2021. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.


About the Author

Ken Mertzel is Global Industry Leader, Financial Services, at Automation Anywhere. Automation Anywhere’s enterprise-grade platform uses software bots that work side by side with people to do much of the repetitive work in many industries. It combines sophisticated RPA, cognitive and embedded analytic technologies. 

About the author: Tiffany Trader

With over a decade’s experience covering the HPC space, Tiffany Trader is one of the preeminent voices reporting on advanced scale computing today.

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