Banking

What credit unions need to know about robotic process automation

Credit unions are always on the lookout for improvements that will help them to increase productivity, lower operating costs and, most importantly, enhance the level of service they offer to members. Perhaps that explains why robotic process automation (RPA) has caught on with so many institutions around the country.

At its most basic, RPA automates a wide range of repetitive, rules-based processes, vastly reducing the time spent on routine tasks – as well as the potential for human error which often accompanies such work – while freeing up employees to handle more meaningful assignments. Credit unions have found that RPA makes sense for everything from member onboarding and accounts payable to compliance handling and fraud detection.

Despite RPA’s obvious benefits, more than half of all automation projects have failed to meet their objectives and nearly a quarter never break even. Frequent break-fix cycles require automations to be pulled out of production and lead to significant maintenance costs, all of which cuts into expected return on the RPA investment. They also decrease RPA’s ability to deliver on the promise of increased efficiency and improved quality of service.

That doesn’t mean credit unions should take a pass on RPA. Properly implemented, RPA is capable of improving productivity by as much as 86% and reducing costs by nearly 60%, according to Deloitte. But it is important for credit unions to have their eyes wide open regarding the real cost of RPA and what they can do to improve their odds of RPA success.

To that end, credit unions should start by determining what the actual price of automation is. Obviously, this depends in part on the number of automation units (“bots”) and the software components that are required to implement RPA. On average, though, a single bot can cost anywhere from $5,000-$15,000, depending on its complexity.

Software and bot licensing, however, only account for about a quarter of the total RPA cost. Credit unions also need to budget for a wide range of other costs which accompany RPA implementation. These range from annual license fee renewals and infrastructure set-up charges to the costs for training, RPA vendor consulting and complementary software packages (such as process mining and process discovery software). In addition, RPA breaks will still occur, so budgeting for downtime, repairs and regular maintenance is essential.

That last item can be particularly difficult to predict because bots routinely break or need maintenance for a variety of reasons. Changes or updates to the user interface of the applications with which bots interact, for example, will cause a bot to produce an error and break. Similarly, any time a new regulation or policy is introduced or an existing regulation or policy changes, the bot must be pulled off production then modified to account for the change, tested, and redeployed. All of this spells downtime, which negatively impacts the return on RPA investment.

The right upfront design can help to reduce such issues. To that end, credit unions considering RPA should identify every dependency the process will have before implementation even begins. Doing so will enable each dependency to be connected to specific process steps, as opposed to relating them to the entire process. This will create a direct mechanism to understand how future changes or updates impact the entire process and exactly where the process is going to be affected. Ultimately, making all dependencies clear at the outset will help RPA developers to generate a better initial design and lessen downtime when an outrage or maintenance issue does occur.

While the right design can make a significant difference, maximizing RPA uptime doesn’t stop there. True process improvement also demands cross-functional teamwork. That means that there must be a real commitment to cross-functional collaboration between the credit union’s business functions and its IT functions. Without it, RPA simply cannot achieve its objectives.

In the same way, credit unions need to understand that process improvement is essential to process automation. Optimizing a business process before automating it creates the proper environment for successful RPA implementation. Just as important, it enables automations to be more readily scaled to meet future growth needs.

Properly implemented, RPA can deliver on its promise of improved productivity and increased member satisfaction. But to be successful, credit unions must recognize that RPA is not a turnkey solution. It simply doesn’t happen without the right strategy in place, the complementary tools to make it effective and the buy-in from all impacted parties. By making the effort to understand what RPA really costs, how it works and what steps need to be taken in order to minimize downtime and maximize ROI, though, credit unions can add a critically important element that can drive efficiency and increase business value.



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