While process automation is not a new concept in our industry, an evolutionary shift toward new technology called Robotic Process Automation (RPA) has started in financial services. Over the last two decades, there has been steady adoption of software solutions – e.g. Visual Basic macros-- that have helped to incrementally advance manual task automation to lower processing costs. Today, however, RPA robots are being designed to do much more than just eliminate basic repetitive tasks - they are now being used to support humans in more complex process management scenarios across multiple disconnected systems and applications.

Many asset managers, banks, and other financial institutions are in the early stages of applying RPA to a wide array of critical operational areas like trade processing, cash forecasting, reconciliations, account opening, and fund administration. What makes today’s robotics solutions attractive over previous software-based enterprise automation approaches is that RPA software is now much more user-friendly and intuitive, which makes meaningful process improvement that much more accessible and impactful to the business users who need it most.

The benefits of investing in an enterprise Robotics Process Automation program go well beyond the quick-hit, automation of manual tasks in the headlines today the real value comes simply from digitizing manual steps of very processes that were thought to require RPA in the first place. What is even more valuable long-term is that an RPA program can not only reduce cost and risk of basic manual work, but also force a re-engineering of legacy processes.

Reducing Cost, Increasing Efficiency, and Redeploying Talent

Most middle and back office operational workflows include repetitive, routine, and uninteresting tasks. Any automation that replicates human behavior —like RPA does — enables companies to move closer to the long-term goal of redeploying highly-educated, motivated, and talented workers to higher-value, decision-oriented roles. Unlike a manufacturing robot that performs just one step in a process, RPA bots can automate manual tasks across multiple disconnected systems and applications that require multiple steps. By automating these manual processes, financial institutions can achieve up to 50% cost savings by improving efficiency and accuracy.1

Fixing a Bad Process is Always the Best Plan

RPA can serve an important role to provide a new focus, framework, and approach to reevaluating process design. Before the introduction of RPA software, the task of completely reengineering core systems or business processes was often too daunting or expensive to even start. RPA software can bridge the gap and offer a more accessible starting point for the industry that often has shorter time-to-market, is cheaper than replacing legacy systems outright, and presents a lower deployment risk. While the potential savings from RPA is usually compelling for most use cases, more comprehensive enterprise automation options can sometimes result in higher potential return on investment in the long-term.

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For example, today’s RPA solutions likely stop short of the improved ROI of artificial intelligence and cognitive information processing, since they are not designed to go beyond eliminating repetitive tasks and cannot support humans in more complex problem-solving pattern recognition.

Robots are only programmed to follow instructions, so an RPA bot cannot create new steps or instructions on its own. Since the robots are using actual webpages and online applications, process latency is dependent less on the robot’s own processing capacity and more on that of the underlying applications with which the robot interfaces. Despite the potential for bots, programs are limited by existing processes. If humans would normally have to use programs that are inefficient or slow, the robot version will also replicate those inefficiencies, albeit at a faster pace. True process reform is needed to address underlying inefficiency– even if it takes away the need for RPA as a result. The opportunity is not about software, but about process redesign in pursuit of process improvement.

Beyond RPA

In reality, RPA is only one component of a bigger process digitization program every firm should have today. An automation program might start by introducing teams of RPA bots to augment and supplant human work, but in the end, the program should actually aim to fully digitize processes and eventually put most of those bots out of a job entirely. This approach is helping Brown Brothers Harriman’s process digitizing team make greater progress towards digitization than ever before — even when the ultimate decision may not be to employ an RPA solution over the long-term. For example, we are implementing machine learning in our daily Net Asset Value review process to help detect and eliminate process exceptions instead of just deploying lower tech bots to manage the exceptions after the fact.

RPA provides a new lens through which the industry can view automation — one that can drive great use cases for reducing the cost and risk of basic manual work as well as help service providers and asset managers realize a digital transformation across all aspects of the business.

Getting Started with RPA

Have we convinced you yet to get moving with your RPA program? To launch your RPA initiative, consider the following:

Start by identifying processes that can test use-cases. They should have a series of repeatable, manual steps; have extensive rule-based workflow with limited exceptions; be a structed and well-documented process with no complex judgement required; and have a high daily volume.

Next, you will need to evaluate feasibility and technical complexity of automating these processes. Make sure your RPA software is compatible with your existing technology. To keep the process moving smoothly, you will need to educate both business and technical users before getting started. Target the highest value workflow, then you can launch your proof-of-concept phase and simulate RPA with limited exception handling in a test environment. After you build and run your bot, back test and record performance. Finally, establish governance by implementing a change management method. This will ensure accountability and oversight of your program.

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1 CapGemini, Robotic Process Automation for Financial Services, 31 May 2016