Robotic process automation (RPA)—which uses computers to tackle repetitive tasks—has very human benefits for mid-sized banks in 2019. It frees up staff for higher value work, streamlines operations, reduces costs–and without question, plays a vital role in the digital transformation needed to compete with larger retail banks.
What does that look like on a granular level? Areas that can benefit from RPA include customer service, accounts payable, mortgage processing, fraud detection, compliance, credit card processing and deposits. Introducing bots to these manual processes can lower processing costs by 30 to 70 percent, according to AutomationEdge. For example, simple validation of customer information from two systems can take bots seconds instead of minutes—while the time to process a mortgage application can drop from days or weeks to minutes.
RPA expenditures in banking and financial services were estimated at $200 million in 2018 and forecast to increase to $1.2 billion in 2023. Large banks have moved aggressively to take advantage of this technology. For example, JPMorgan Chase established in 2016 an internal center of excellence to drive best practices for RPA implementation. As a result, they planned to achieve more than $30 million in run rate saves in 2017.
And in 2018, Chase began to deploy virtual assistants (robots driven by artificial intelligence) to maintain internal help desks, track errors and route inquiries. These technological solutions streamlined internal processes and product support processes such as loan underwriting, which greatly improved the customer experience.
Ten key success factors to implement RPA
Mid-sized retail banks ready to implement RPA need to keep these ten action steps, pitfalls and insights in mind:
1. Start small and move fast.
Identify low-hanging fruit and automate simple processes first. Quick wins can boost credibility and garner support for the proof of concept (PoC). Minimize the risk of negative customer impacts by piloting internal processes rather than customer-facing ones.
2. Set realistic goals and expectations for your proof of concept.
Set achievable, realistic cost-saving and return on investment (ROI) targets in the short and long term. Many PoCs fail to gain momentum due to misalignments in expectations.
3. Select the right RPA vendor and implementation partner.
Not all RPA vendors suit every organization, even if their marketing materials say otherwise. Many have evolved with specific industries and functions in mind. Choosing the right tool and implementation partner can strongly impact project outcomes.
4. Remember: Not everything is a nail.
RPA represents just one tool in a modern bank’s digital toolkit. Others—such as application programming interfaces (APIs) and optical character recognition (OCR)—need to be part of an operating model redesign. If RPA becomes the singular focal point on the proof of concept, the project risks a limited outcome: the equivalent of a toolbox that only contains a hammer. In that case, everything starts to look like a nail.
5. Simplify the process rather than make an inefficient process faster.
A key tenet in the business case for RPA centers on the ability to reduce the time to complete a given process. RPA offers a promising way to automate highly manual and repetitive processes. Yet overly complex ones require a great deal of manipulation and thus are weak candidates for automation. In such cases, the solution—perhaps more challenging to implement—is to streamline the process.
6. Ensure adequate in-house knowledgeto manage the RPA toolset.
RPA is intuitive enough for non-technical personnel to maintain, provided they are trained. Despite that major benefit, many PoCs miss the critical need for training as part of the transition and change management process. Banks often hire an outside firm to manage the RPA PoC but fail to communicate how to manage the process afterwards. Without this knowledge, in-house staff face an uphill battle to adopt RPA.
7. Develop a centralized governance structure.
A center-of-excellence type of governance structure can sustain RPA for the long term. Automated processes require the monitoring of data, upstream/downstream processes and potential system changes. Any changes may interrupt the automated process, so upstream or downstream impacts require assessment, with the automated process adjusted accordingly.
8. Treat RPA as business-focused rather than IT-focused.
Some RPA PoCs fail due to the lack of business participation in the initial pilot, based on the misconception that this tool is IT-driven. RPA stands out as especially attractive because of its ease of use; non-technical personnel can readily acquire the necessary skill set. Without proper guidance and involvement of the business to determine which processes rate as candidates for automation, any pilot is likely to fail.
9. Ensure consistent executive sponsorship.
RPA adoption demands strong leadership support to create a proof of concept. Without it, further adoption faces a formidable obstacle.
10. Implement change management programs.
This all-important step addresses the concerns and educational needs of bank employees. Many could succumb to the exaggerated fear that this new technology will lead to job losses. You must stress that the majority of RPA bots have been implemented to relieve people of onerous, repetitive tasks. In addition, you can show employees how gaining RPA implementation skills will improve their career prospects. Strong change management champions play an essential role in the success of the pilot.
Putting it all together: Automation arrives at the station
These touchstones can help mid-sized banks gain a competitive advantage in a crowded market by outlining to the path to successful digital transformation.
Throughout this process, a partner with proven expertise in RPA can bring important benefits to mid-sized retail banks. And already, there is the future to think about. Able partners can also guide the transition from RPA to next-gen tools such as cognitive process automation (CPA) and beyond.
As you embark on your journey, keep in mind that no tech provider possesses a digital wand to make all this happen in an instant. For while digital machines can automate many a process, it takes committed, confident bankers to launch the process of lasting digital change.
Persistent inflation and higher interest rates will challenge banks’ ability to meet capital needs and cash flow. That means treasury departments need digital solutions that are timely, capture data from across the institution and anticipate changing economic trends.