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RPA in Finance
Robotic Process Automation (RPA) can be traced to the early 2000s, but the technology entered mainstream Finance transformation solutions around 2015. To put this into context, a KPMG paper published in 2015 cited research that found only 12% of financial services firms had gone live with RPA solutions, 24% of firms were only talking about RPA and 43% hadn’t even thought about it. (source)
Flash forward to today and RPA, an umbrella term for software that can be easily programed to learn and then automate processes using structured inputs and logic, was valued at $1.8Bn in 2021 and expected to grow at double digit rates through 2024. (source). A mature vendor market has been established with providers like Blue Prism, Automation Anywhere, and UiPath broadening out their offerings and undertaking highly valued IPOs.
CFOs have long been considering how RPA can be applied to the Finance function and replicate the enormous value delivered by automating industrial processes. There are some emerging learnings from the last five years which can guide Finance Change leaders on how to maximize value from Finance RPA programmes.
Value - Better, Faster, Cheaper
Initially, RPA programs in Finance focused on low hanging fruit within the function which had historically lagged in digitization efforts. There are some obvious processes that are basic yet heavily reliant on manual tasks that provide opportunities for pilot programs. Areas like accounts payable, accounts receivable, simple and high-volume reconciliations, and payroll are easy places to start.
Do these deliver value? Yes. However, like all Finance transformations it is important to be clear where and how the value will be delivered (as opposed to simply selecting a technology solution and hoping value will arise). Simply put, and just like any other transformation, it should deliver a process or a function that is:
Finance RPA programs of the last few years certainly did automate many of the mundane, repetitive tasks within Finance which were at the lower end of the value chain. These programmes have delivered value to the Finance function whether that’s in the form cost savings or improving employee job satisfaction.
However, Finance functions are complex beasts that have evolved over many years, both organically and through acquisition, and the scope for processes that can easily be automated is quickly exhausted. In reality, Finance processes exhibit complexities in terms of multiple systems, complex handoffs and a large number of individuals who are, together, a link in a complex chains of events.
A Cautionary Tale – how not to do it
In the late 1990s and early 2000s, finance professionals started to seriously exploit the ability to write their macros and other automated routines in desktop-based software like Microsoft Excel and Access. These macros became ever more sophisticated, suffused by difficult to follow VBA code that would reside on the user’s C drive. For a while, these “End User Computer” solutions checked the better, faster, cheaper boxes. They gave finance access to more data, reduced reporting times and eliminated some manual work. But there were limitations because these EUCs lacked integration into a control framework and were technologically unstable.
After the collapse of Enron and the subsequent introduction of the Sarbanes-Oxley regime in 2002, CFOs became personally accountable for the accuracy of their statutory returns which was incompatible with the proliferation of EUCs in Finance. The resulting audit and cleanup of EUCs was great for consulting firms but destroyed all the value delivered in the early days overnight.
The risk for robotics in Finance is exactly the same: if Finance departments just apply robots throughout the department it may initially make things a bit Better, Faster, Cheaper but will invariably result in expensive audit requirements in the not-so-distant future.
Maximizing the value of RPA
As a quote in a recent Forbes article notes, “…you can find a lot of the RPA vendors dropping bots on everything that moves. In the short term, the automation-fix might feel good, but the automation-tax is going to be high once those bots start limping and eventually breaking down. This approach has proven to be brittle and fail when the business changes, because it automates steps regardless of the business context, process situation, management objectives, etc. It assumes there is always one-way to execute things – which is never the case in business.” (source)
I do think there is a way to approach RPA that doesn’t pose the danger outlined above.
First, finance should look across their many processes to assess where the greatest value can be found. While most RPA may be targeted towards high volume/low complexity processes, there may also be value in implementing RPA solutions to low volume/high complexity task where the value isn’t necessarily cost savings but increased control or reduced risk.
Next, it’s essential to do the ‘boring’ work of taking that selected process and looking at the efficiency of the process first. Most finance processes typically have an inefficient, legacy component and teams should apply a process optimization methodology (Six Sigma, Lean, Agile) to address such issues. Otherwise, it is likely that Finance functions are automating substandard or poor finance processes.
Once optimised, it is now possible to analyse the ideal components of the process to apply an automation solution. It may only be at certain points along the process chain. The final process should be clear, documented, and auditable. Critically, applying robotics at key, selected points in the process increases its sustainability.
Robotics has and will continue to deliver value to the finance department. However, it’s critical to be clear on the ‘why’ and the ‘how’ and ensure it’s a sustainable process that can continue despite team turnover or budget impacts. The true value of RPA will be realized when finance looks beyond the quick fixes and merges RPA with the refining of existing processes and the transformation of the operating model as a whole.
This content is provided by an external author without editing by Finextra. It expresses the views and opinions of the author.
David Smith Information Analyst at ManpowerGroup
20 November
Konstantin Rabin Head of Marketing at Kontomatik
19 November
Ruoyu Xie Marketing Manager at Grand Compliance
Seth Perlman Global Head of Product at i2c Inc.
18 November
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