Robotic process automation (RPA) can help financial services firms increase efficiency and transparency – but RPA implementations can be challenging unless the right approach is used.
For financial services firms facing increased pressures on costs – as well as demands for greater efficiency, accuracy and transparency in a wide range of transactions and functions – robotic process automation (RPA) offers potential for delivering significant benefits within a relatively short period.
Some financial services firms undertaking large-scale RPA implementations, however, have found the undertaking to be more challenging than they originally anticipated. RPA requires changes both to business and to IT processes. In addition to the difficulties inherent in evaluating and selecting RPA software as well as the right business process candidates, there are potential problems in areas ranging from company culture to data management.
Our experience in helping financial services firms with RPA implementations has underscored the importance of identifying and addressing key considerations including:
- Managing Expectations. RPA is a valuable new technology, but it should be seen as part of a continuum beginning with process improvements (to maximize benefits from automation) and, eventually, to the use of machine learning and artificial intelligence. There is a need for the right governance structure from the beginning and for clear ownership of the change process. Firms can help themselves by starting with relatively small, finite projects, using early success to build momentum and support and learning quickly about what does and does not work in the specific organizational environment.
- Addressing Cultural Concerns. The implementation team should be able to spell out the impact of RPA on people. It is vital to a successful implementation that people understand that RPA will help them do the important parts of their jobs better by freeing them from performing tedious and repetitive processes.
- Getting Process-Ready. Internal process re-engineering teams should be involved upfront to see how processes can be further re-engineered to maximize the benefits from RPA. This requires a good understanding of what RPA can and cannot accomplish. There should also be a clear view of other planned change initiatives –addressing systems and processes across the organization – that could affect the business process or processes subject to automation through RPA.
- Getting Data Ready. To accurately evaluate the RPA opportunities and set manageable business expectations, it is important to have access to the correct data (such as baseline FTEs, volumes, etc.). Many organizations find it difficult to provide this data in a readily available form, and they underestimate the effort involved in getting this data in place to support the RPA design teams.
- Assessing Current Technological Readiness. The RPA implementation team needs to know that the required technological infrastructure is in place, including on-time availability of test environments and test data. Even small delays can reduce the anticipated benefits of RPA implementation.
Finally, we have learned that RPA should be implemented with a view to the future. New solutions in areas including cognitive robotics and artificial intelligence are developing quickly. Initial RPA implementations should factor in the possibilities of enhanced automation. A well thought through, holistic intelligent automation strategy and roadmap, with participation from all internal stakeholders, is worth considering. RPA vendors and implementation partners can help firms meet immediate cost-reduction targets, but intelligent automation is a major, long-term strategic concern.