Intelligent automation is not autonomous: Six best practices for capital markets business leaders who want to drive change
CIOs know that there is a big gap between what a lot of technology promises and what it delivers. Every day, news feeds bombard us with information about innovation, yet very few of the most transformative advancements directly affect most of us. Cars can drive themselves, and yet the last taxi you took was driven by a person. Capital markets firms have talked about different flavors of front-to-back transformation for the better part of a decade, but they have often been left with suboptimal results and an operating model still riddled with repetitive, labor intensive tasks. In many cases, these “improved” operating models actually lead to operational expenses that are higher than they need to be, bring greater operational risk, and produce an overall customer experience that is less than appealing.
Someday, much of the redundant work in capital markets will go away as the result of a wholesale digital transformation, be it blockchain/ distributed ledger technology or some other innovation. For now, though, incremental intelligent automation can really pay off. Financial services firms still have plenty of unnecessary and inefficient processes representing costs that are not tied to activities that differentiate the firm. As robotic process automation (RPA) and intelligent automation (IA) tools grow smarter, they can perform more and more tasks that previously required human judgment. Leading capital markets firms already use RPA and IA to make practical changes with transformational potential. As these technologies begin to gain acceptance, we can learn a lot from the first movers.
Here are six best practice recommendations that we have seen in helping our clients control the risks and reap the rewards that RPA and IA offer.
Know thyself. Start by asking yourself the hard questions, such as “Do we really understand our business processes and pain points?” Instead of first deciding on a specific technology like RPA or AI and looking at where to apply it, begin by analyzing your business processes to determine the ideal future state. Then, as you go through the future state business process mapping, you’ll be able to take advantage of the wide range of tools that are now available, giving you both short-term and sustainable business value. Armed with this information, you can develop a practical automation roadmap as part of a cohesive transformation plan. Still not sure how to identify your starting point?
That can be automated as well. There are process-identification tools that can help you find pain points in existing operations and identify automation opportunities.
Look at the forest, not the trees. Look at processes in a broad context. Individual processes are part of a broader system, and the interactions are not always obvious. Like reengineering and offshoring efforts, if the objective is not understood, automation efforts are not likely to add real value. Most successful projects combine process analysis with organizational analysis to get everyone on board and validate potential benefits from the start.
Choose wisely. In driving down costs to improve ROE, there are options. And remember, even plug-and-play tools aren’t really plug-and-play. While most of the easy cost-cutting opportunities have already been seized, RPA and IA still offer an array of benefits to capital markets firms. But different automation tools come with different costs and benefits, and it’s important to analyze each business process closely to see how you can generate the most efficiency with the least overall cost.
Map out the path. The industry faces an ongoing challenge on how IT should be managed. Before navigating the path toward automation, leaders should establish a transformation strategy. However small, automation tools are most useful as part of a long-term, top-down strategy. Critical considerations include whether IT management should be handled on a centralized or federated basis, and whether it should be led by users or corporate IT. If you have a clearly defined strategy framework, roles and responsibilities can be clarified and agreed upon from the start. CIOs have seen this movie before. They do not need to control everything, but there are plenty of functions (standards? governance? purchasing?) that might be handled most effectively at the center.
Set it and forget it? Forget it. Given the highly regulated environment of the capital markets industry, it is imperative to create appropriate change control processes and governance structure. But, bots are not “set and forget.” They need maintenance, particularly when there are changes to applications that the bots use. Just as employees require retraining when things change, bots do too. More broadly, you have to have robust change management mechanisms in place to identify these disconnects and determine how you’ll handle exceptions. Regarding risk and security implications of AI implementation, it’s best to involve IT at the start.
Tackle the humans-versus-machines conundrum. Make people and culture the heart of your automation strategy. Leaders should put energy toward addressing the people issues that arise with automation so that everyone can get accustomed to being part of an organization that is constantly evolving. By linking automation efforts to what already makes teams strong can tap into energy, pride, and motivation. Frankly, if employees are part of the change, experience its benefits, and see the potential for their career growth, they will likely embrace automation. If they are not, they probably will not. Be transparent about what that means for employees—and provide the tools and upskilling needed to thrive in an evolving environment.
The automation process is not automatic. Firms need leaders and advisors who think about the topic from a top-down, strategic approach, as well as the change agents on the ground who know “how things really work.” RPA and IA are now stable technologies, and they deserve a prominent place in the capital markets CIO’s toolkit. But as with most technology projects, success stems from how automation is implemented rather than the performance specs of a particular application. Leading CIOs know this, and that is how they bridge between what technology promises and what it delivers.