I have written previously about Robotic Process Automation (RPA) and its potential impact on the financial services industry and more specifically on the finance and risk functions within the institutions. Most financial services firms have started exploring how to benefit from RPA – using software to mimic the actions a human would perform on a PC, then scaling up these actions as needed – and many have already automated a number of the repetitive, rules-based processes that are the typical starting points for RPA. Some firms that have implemented these tools have already seen dramatic reductions in average handling and/or cycle times.
Across the industry, companies have been looking for ways to help address high variable costs and stagnant productivity growth against market challenges. The proliferation of new regulations – as well as firms’ own initiatives to improve compliance and reduce risk – have driven up the demand for and market cost of finance and risk talent. And in parallel, the need to demonstrate strong controls to the regulator requires that solutions need to be proven and robust.
And companies have not been standing still. In their efforts to transform finance and risk operations, companies have also explored other paths to greater productivity. These include centralization (creating Centers of Excellence to concentrate and improve common processes); relocation (moving operations to lower-cost regions); standardization (identifying common process elements and making them uniform throughout global operations); optimization (simplifying processes and removing wasted effort); and digitization (computerizing document management, adding self-service options and establishing data warehouses).
But while all of these approaches have their merits, RPA offers significant potential for both short- and long-term efficiency gains.
The Value Proposition
Companies implementing RPA-based solutions often see returns on their investments in as little as one quarter. And importantly, the solutions are typically extendable – not requiring all processes and systems to be converted at the same time.
While freeing up workers for more complex tasks – particularly those requiring human analysis and judgment – is a major benefit, so is the elimination of rework and errors as the bots execute the transactions. Unlike their human counterparts, bots work 24 hours a day, seven days a week, and leave a clear record of the completed transaction, making compliance-related activities easier to track and monitor.
Growing Interest In RPA
RPA is generating considerable excitement in the world of finance and risk, and many firms are moving at pace with their RPA implementations. They typically begin exploring high-volume, low-complexity processes such as travel and expense management, review and payment of incoming vendor invoices, and monitoring of customer credit. RPA bots, for example, can scan invoices and automatically prepare payments, using logic and rules to validate invoices and routing exceptions to appropriate teams for review and approval. Leading firms are pushing into new areas with potential for further automation.
One of the most promising areas for RPA deployment is in compliance functions charged with fulfilling requirements for regulatory initiatives such as KYC (Know Your Customer), anti-money laundering (AML), and counterparty risk reporting. RPA bots can handle many of the activities associated with account openings, evaluating credit limits, and identification and explanation of changes in risk exposure. The use cases continue to expand.
Although RPA is a well-established approach to cost reduction, quality improvement and productivity enhancement, we are still in the early days in terms of recognizing its full potential. We foresee even more opportunity and transformation as analytics, machine learning and artificial intelligence follow behind this RPA wave.
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