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  • Writer's pictureJohn San Filippo

The Robots Are Taking Over Your Credit Union! Or at Least They Should Be.

Part 1 of a Two-Part Series


By John San Filippo


At Finopotamus, we listen to our readers. Reader Mike Lantrip of SIU Credit Union asked us to write about robotic process automation (RPA), so that is exactly what we did. Specifically, we tracked down and interviewed these RPA experts:

  • John Best, CEO, Best Innovation Group (BIG)

  • Claudio Garcia, Director of Growth and Digital Transformation Consulting, Baker Tilly

  • Joseariel Gomez, Founder and CEO, Shastic

  • Lini Susan John, Head of Marketing, Zuci Systems

  • Phil Schmoyer, Director, Baker Tilly

  • Janaha Vivek, Senior Marketing Specialist, Zuci Systems

We present our findings here in this two-part series.


The word robotic often conjures up images of hundreds of identical, shining androids chasing Will Smith down a futuristic superhighway (and hoping they don’t get slapped). Of course, robotic process automation has nothing to do with physical robots. RPA refers to small programs, or bots, that perform various repetitive tasks in a computer system in lieu of manual processing. But even among the technologically savvy, some misconceptions about RPA persist.


Some believe RPA can only perform the simplest of tasks. Today’s RPA can manage a wide range of complex operations.


Some fear that RPA will lead to job loss as automation replaces people. It won’t, at least not in an intelligently run organization.


Some feel that RPA is unnecessary because of the many advances in application programming interface (API)-level integration across disparate systems. The truth is, the industry is years if not decades away from full API integration across all systems.


It Starts with Culture


As with any new technology, credit unions should never commit to RPA and then start looking for ways to use it. Instead, they should start by identifying problems – bottlenecks, inefficiencies, errors, etc. – that need to be fixed. RPA might be appropriate for some and not for others. But how does IT even find out that a problem exists in, for example, the lending department?

Phil Schmoyer

According to Baker Tilly’s Schmoyer, it all starts with a collaborative culture across the credit union. “We like to see a culture of continuous improvement that's happening within the business,” he said. It’s the responsibility of the various business units to identify broken processes That information is then “fed into IT so that they can work with the business units to define what those requirements are, what is broken, what are the pain points of the process. Then those should all be evaluated from a prioritization perspective.”


“You need to bring together all of the participants in your process, not just the back office,” said Shastic’s Gomez. “You need to bring together the knowledge workers with the users, the members, and even the third parties.”


Joseariel Gomez

Evaluating RPA Software

The choice of RPA software depends largely on the sophistication of the credit union’s IT staff and how much staff time the credit union is willing to commit to RPA. For a credit union with a large IT staff that wants maximum control for a minimum cost, there are open-source RPA solutions. The experts Finopotamus spoke with all agreed that this is not the best option for most credit unions.

“In my opinion, the four leading RPA platforms are Automation Anywhere, UiPath, Blue Prism and Pega,” said Baker Tilly’s Garcia. “They're leaders because they make very, very good software and so certainly any one of those systems is quite capable of getting the job done with respect to an automation challenge.”

Claudio Garcia

When BIG’s Best evaluated RPA software on behalf of multiple credit unions in 2015, he landed on UiPath. “We created some scenarios and we got everybody working in it, because one of our beliefs is that experiential knowledge is much more valuable than bot knowledge,” he said, “meaning that if you hire some expert to come in, they still have to catch up on all the culture of the organization.”


Best pointed out that because he was working with a group of credit unions all using the same RPA platform, those credit unions were able to leverage the credit union spirit of cooperation and share their solutions with each other. The broad lesson here is that it makes sense to consider what RPA software your peers are using. Their success could offer a shortcut to your success.

John Best

From a delivery standpoint, Gomez said that the cloud is superior to on-premise servers for flexibility and scalability. “We need to move away from the servers on premise and go to AWS (Amazon Web Services), something like that,” he said.


“It needs to be tailored for financial services right now, too,” he added, claiming that his company, Shastic, is the only provider of an RPA platform designed specifically for financial institutions.


RPA vs. APIs


In a perfect world, all systems across the entire enterprise would be fully integrated, freely and easily sharing data, with no need for robotic process automation. The current environment is anything but perfect.


“The financial services industry right now is focused on customer experience, trying to make it frictionless for the consumer from end to end,” said Schmoyer. “APIs are driving a lot of that, but so are connected RPA solutions.” He doesn’t see RPA going away any time soon.

“Look at Fiserv, which owns a lot of products,” noted Best. “They’re still working on integrating their own products, much less any third-party products. That’s not a knock against Fiserv. Everybody’s in that boat.”


“RPA is a great substitution for integration so that we can talk to any system that lives in the desktop and be able to orchestrate it,” added Gomez. “The traditional rails that you can use to talk to different systems internally are very limited or they're walled off gardens and opening the door takes superhuman effort.”


In other words, RPA is here to stay for the foreseeable future.


Topics covered in Part 2 include:

  • Artificial intelligence and machine learning

  • Maintaining RPA solutions as environments change

  • Employee perception

  • Measuring success

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