Whether in response to an industry shift, market hiccups, or a single competitive threat, finance leaders and professionals are stepping back to reevaluate their accounting and finance systems, operations, and business processes.
Leaning on technology, companies are engaging in digital transformation by employing Robotic Process Automation or RPA to automate and simplify processes; drive greater efficiency; and leverage data to inform smarter and faster decision-making.
Like other areas of business, finance is filled with repetitive manual tasks that are ripe for automation using technology.
Defining Robotics Process Automation
Although there are various software platforms on the market designed to help ease finance and accounts payable challenges, many tasks are still done manually.
This may be a result of a lack of strategic solutions, a fear of trusting tasks to tech, or budget concerns.
However, global events and market shifts have provoked an expressed interest and need for digitization, including automation, leading to the adoption of robotics process automation.
Growing as a popular solution in finance and accounting, RPA refers to software technology or “software robots” with artificial intelligence (AI) and machine learning (ML) capabilities, allowing it to autonomously emulate human behavior; the “software robots” have the ability to learn and complete a high volume of rules-based, repetitive tasks and business processes.
Software bots, like people, can interact with any application or navigate any systems.
They just have the capacity to operate much faster, with 100% precision and reliability, around the clock – without the need for bathroom or coffee breaks.
Along with RPA, finance professionals should be aware of both business process automation (BPA) and digital process automation (DPA) – two commonly used automation technologies that robotics process automation can be paired to optimize and streamline a digital transformation.
Other Process Automation & AI
RPA vs BPA
BPA refers to the use of technology to automate complex, multi-step workflows, typically very specific to a company’s core business functions. As one step of a workflow is completed, the next step is automatically initiated.
Further, business process automation has the capability to work across numerous enterprise systems and applications to get the job done.
BPA and RPA are similar in that both technologies aim to lessen the manual processes, offloading the work to computers.
An important difference to note is that a RPA deployment typically has a lower cost, given its narrow scope of automation (tasks vs multi-step processes).
Also, when it comes to complexities, BPA involves coding and development (ie. integration, database access, APIs), often requiring the role of an IT department. RPA uses minimal to no–code features, empowering users to create their automation tools.
Overall, the good news is RPA and BPA can work in tandem to boost efficiencies and enhance digital transformation initiatives within the financial space.
RPA vs DPA
Often confused with BPA, digital process automation technology, offers dual power by automating processes from end to end, and optimizing common workflows that involve external human interactions (ie. sales, management).
From purchase orders to loan and credit approval, to collections, DPA is used to eliminate friction, increase speed, create rich customer experiences, and augment efficiencies within companies.
In contrast to robotics process automation, DPA is generally used for longer, more complex processes that contain a number of decisions that RPA bots would find difficult to handle.
Moreover, just as the case with BPA, companies can couple a RPA platform with DPA deployments – RPA bots would be responsible for the routine, laborious tasks within the larger DPA-focused processes.
RPA vs AI
Separately, RPA and AI are quite powerful, but leveraging them together is undoubtedly advantageous to any financial institution or accounting department – from streamlined AP workflows to accelerated efficiency, to cycle time reduction.
Robotics process automation software, as mentioned above, performs monotonous tasks, at a level of accuracy, speed, and scale that humans can’t compete with. However, it is strict in its capabilities; RPA bots can mimic human behavior, but they have no decision-making or judgement abilities.
Hence, the need to implement AI to do the thinking.
When deployed together, artificial intelligence is the “brains” behind RPA’s bots.
With a growing CAGR of 30.9% from 2021 to 2030, it is clear that the benefits of RPA or potential benefits speak for themselves. In fact, Gartner says 80% of financial leaders have implemented or have intentions to implement robotics process automation.
RPA in Finance
According to Deloitte’s December 2020 Global Intelligent Automation survey, 73% of global organizations have adopted the use of automation technologies, up from 2019’s 58%.
While there are subtle nuances and major differences in purpose, requirements, capabilities, and outcomes regarding automation technologies, the word “automation” has become a buzzword to include all computer technologies that enable machines to perform human tasks.
Despite their distinctions, the finance space continues to adopt automation and remains ripe for disruption. In Analytics Insight’s latest survey, over 55% of BFSI companies (banking, financial services, and insurance) identified RPA as a key driver to improve process efficiencies and service quality, and have plans to deploy it by 2025.
While RPA is being implemented, hyperautomation for most organizations is not yet on the horizon.
The Benefits of RPA in Finance
Mirroring the upward growth of global finance automation adoption, the RPA market within the financial services industry is set for tremendous growth over the next decade.
More specifically, the global RPA in financial services market size is forecasted to reach nearly $5 million by year 2030 (valued at $341 million in 2020), per a recent report by Allied Market Research.
With a growing CAGR of 30.9% from 2021 to 2030, it is clear that the benefits of RPA or potential benefits speak for themselves. In fact, Gartner says 80% of financial leaders have implemented or have intentions to implement robotics process automation.
Due to the high-volume of routine, repetitive, and mundane tasks in finance; RPA’s usage can have a vital impact on increasing the effectiveness of finance functions and accounting practices.
Here are seven major benefits of implementing finance automation:
- Saves time and money: Accenture estimates RPA can minimize the time it takes to complete specific tasks up to 90%. Likewise, robotics automation may realize a cost-savings up to 80%.
- Minimize human errors: Humans are simply prone to mistakes, especially when manually processing invoices or sorting Excel spreadsheets. Because financial RPA is very systematic and streamlined in the way it handles tasks, it eliminates errors.
- Scalability: RPA enables companies to scale operations seamlessly. RPA bots can manage and respond to volume requests or any other programmed tasks in record time – without needing a break.
- Low cost startup: Implementing RPA in finance does not require any significant modifications in infrastructure, as it’s a layer that sits on top of existing applications (UI layer). Therefore, companies are not faced with excessive startup costs.
- Better decision-making: Robotics process automation can be leveraged to collect real-time data (extracted from legacy and new data from existing systems), which offers deeper insights about problems, inconsistencies, and opportunities for growth.
- Compliance & risk reporting: In finance, remaining compliant requires a high level of detail. Robotic automation solutions allow companies to generate full audit trails for every process to ensure accuracy, and decrease business risk.
- Transparency: Typically, financial processes are often manual, and involve multiple channels and people. Many times, the left hand is unaware of what the right is doing, and vice versa. Mistakes are made and the ball is dropped with no one claiming responsibility. RPA’s structured processes change that.
Use Cases for RPA in Finance
Here are six opportunities highlighting the use of RPA to automate labor-intensive finance processes; all demonstrating an almost immediate ROI.
- Accounts payable: AP is a critical, repetitive function of finance teams, which is time-consuming when done manually. Not only do employees need to validate the fields, they have to digitize vendor invoices, then process the payment.
When RPA is utilized in AP Automation Software, incoming invoices are distributed to the appropriate recipient automatically. As well, late payments can be avoided by scheduling reminders.
- Data management: Data is vital in every industry, especially finance and accounting. Robotics process automation is a great solution to improve data management. RPA bots can be tasked to easily move, collect, and transfer data between systems to execute processes, conduct analysis, and generate insightful reports.
- Know Your Customer (KYC): Becoming more prevalent in the digital age, finance departments and institutions are enlisting KYC to verify customers’ identities, and assess and monitor customer risk. Not only is KYC costly in time, many companies are faced with compliance sanctions.
Leveraging and incorporating RPA into KYC protocols will accelerate customer onboarding and minimize errors, while enhancing overall customer UX.
- Reporting: Financial reporting requires preciseness, particularly when providing reports and forecasts to stakeholders.
From P&L, income statements, and variance analysis to balance sheets, regulatory/management, and reconciliation reports, RPA can efficiently gather and analyze data from diverse sources, present it in a coherent format, and generate highly accurate reports.
- Discrepancies & inaccuracies: Bad data can spread across multiple systems like a wildfire, inviting the need for significant data cleaning.
Robotics process automation has the capacity to scan data, identify issues across systems, and alert an employee to review.
What’s more, the RPA bot, by utilizing multiple rules-based processes, can determine the source of inconsistencies and correct the issue programmatically, across all the affected systems.
- Combat fraud: In accordance with recent statistics, the anti-money laundering process is “highly manual”. Analysts are said to spend only 10% of their time on analysis, while up to 75% goes towards collecting data and 15% is allotted for data entry and management.
Because bringing money laundering activities to a halt is time-sensitive, RPA technology would be a great solution.
For instance, rules could be designed to reduce analysts’ time – freeing them to focus on more pertinent tasks.
Data entry can be automated using data capture and input, as is the case with AP Automation software. Or, the rules could be set to flag a potential threat, if a specified number of transactions were made within a specified period of time.
RPA in Finance Best Practices
Investing in finance automation may yield unexpected opportunities to outperform competitors, improve employee engagement, reduce costs, and scale.
Follow these steps to get started with RPA implementation:
- Audit & assess: In order of priority and complexity, list all of your high-volume, recurring processes that require human intervention.
- Identify & document: Refer to the list, omit anything useless, then document every single step involved in each process, along with the person(s) responsible.
- Research & choose: Consider the type of robotics process automation you require. Do you need a basic level of automation or an advanced RPA software that includes ML capabilities? Is there a dedicated software for the tasks you are looking to address? Create a list of vendors and reach out with your questions and concerns, or for additional information.
Be sure to choose a reputable vendor with experience in your industry and preferred RPA tech stack. Make sure you are 100% onboard with moving forward.
- Be patient: Automation can be time-consuming upfront; it’s a gradual process. It could take a few months to automate simple processes from scratch, and up to a year for more complex processes.
Also, keep in mind legacy systems may be a challenge to automate.
- Be practical: It is common practice to start small with parts of selected processes, and allow employees to intervene when automation isn’t applied yet.
As RPA implementation continues, employees can be phased out.
However, they may still need to monitor the results and take over from time to time.
Enhance Your Finance Processes With RPA
The age of robots is here, as the future is now.
The companies that take the time to educate themselves on the benefits of process automation technologies and invest in software like RPA, will be the ones that will future-proof their growth and remain competitive in the marketplace.Fac