The Impact of Robotic Process Automation on Financial Services

 As technology continues to advance at a rapid pace, financial institutions all across the world are under intense pressure to improve efficiency, reduce costs and boost productivity. Indeed, there is now a considerable global need for the financial-services industry to evolve comprehensively from traditional, age-old business models. In response, automation has come to represent a hefty chunk of that evolution, with robotic process automation (RPA) in particular set to play a pivotal role in task execution within financial institutions during the next few years.

Combining robotic automation and artificial intelligence, RPA is the process of automating across applications and systems to perform repetitive tasks that were once performed by humans. It is sometimes also known as “smart automation” or “intelligent automation” and thus refers to any software system that can be programmed to perform tasks that previously required the input of human intelligence to be successfully completed.

“RPA is at the forefront of human-computer technology and provides players in the financial services industry with a virtual workforce that is rule[s] based and is set up to connect with your company’s systems in the same way as your existing users,” Accenture stated. “With robotics, you automate and build an automation platform for your front office, back office and support functions.”

And with several repetitive, often mundane tasks currently being completed by employees now set to be carried out by this automation platform, RPA clearly has profound implications for the financial-services industry in terms of transforming the nature of work within banks, delivering significant gains in customer experience as well as reducing costs and allocating scarce productive resources more efficiently.

Some of the key benefits of handing over such tasks to robotics include cost savings; time savings, with RPA freeing up time for employees to work on more complex tasks; a reduction, or perhaps even elimination, of human error; and scalability, with robots capable of performing tasks at speeds unmatched by any human. What’s more, scalability means that automated solutions will cope with much higher volumes and tasks will be delivered in record times. Account opening is one such example of a process that is typically repetitive, tedious and unnecessarily time-consuming for employees to undertake. But through automation, these tasks can be done quickly and more accurately. And in the long run, RPA can significantly improve the integrity and quality of account data within financial institutions’ systems.

Account opening is just one of many areas within banking that could be seriously transformed by RPA. Indeed, according to its 2018 research, McKinsey found that currently demonstrated technologies can “fully automate” 42 percent and “mostly automate” a further 19 percent of finance activities. With turnaround times having become one of the most important metrics for gauging overall customer experience, banks can now use robots to handle a variety of tasks pertaining to such areas as account, loans and fraud enquiries. With customer-services teams currently handling such issues, the use of RPA as a replacement will free up considerable time for those teams to concentrate on more important queries that require more intelligence and nuance.

Another important area of banking in which RPA is now triggering a dramatic transformation is in mortgages and lending. Given the number of routine processes involved in buying a house—employment verification, credit checks, title orders and inspection reports, to name just a few—RPA has become a prime candidate to take over many of these tasks without the need for human intervention, thereby greatly boosting efficiency, reducing loan-processing times and drastically lowering total turnaround times. OCBC (Oversea-Chinese Banking Corporation), for instance, uses RPA extensively in this area, which has enabled the Singaporean bank to reduce the time taken to re-price home loans from 45 minutes to just one minute. OCBC’s RPA bot checks customers’ eligibility to re-price, recommends appropriate re-pricing options and even drafts the recommendation e-mails to customers. All this means that it can handle a substantially heavier workload than was previously possible, processing up to 100 re-pricing applications per day.

Perhaps most notably for lending-based activities, RPA manages to enhance the visibility of each specific task that needs to be carried out as part of the overall process. “With workflow automation, each step of the lending process is electronic, which means that you can collect data with each step. Hunting down a loan application to figure out its current status is now a thing of the past,” stated RapidValue, a digital-product engineering firm focused on RPA. “You can search for the document within your document management system and immediately find out its process status.” As such, it can greatly improve the overall lending experience for the customer.

RPA will also have a significant impact on banks’ compliance activities, which is especially advantageous given the rising costs banks have borne to adhere to mounting regulatory requirements over the last decade or so. In particular, RPA can eliminate the need for manual processes associated with know your customer (KYC) and anti-money laundering (AML). Automating significant chunks of these important requirements will help to minimise human error, reduce costs and greatly improve the efficiency of the onboarding process for new clients. Fraud detection, similarly, will benefit from automation, particularly given the rapidly rising number of cases banks have confronted in recent years, making it more challenging for compliance teams to manage. But with RPA, a bot can be programmed to identify patterns of fraud and instantly escalate those occurrences to the appropriate divisions within the bank.

Perhaps most crucially over a longer time horizon, RPA can continually monitor changes and updates to regulatory laws and quickly incorporate the findings into the financial institutions’ AML policies. “This ongoing process of collecting and processing data from both external and internal sources helps the RM [relationship manager] to stay on top of their client portfolio and remain in compliance,” Breana Patel, founder and chief executive officer of New York-based management consulting firm Bonova Advisory, wrote in Finextra in October 2017. “The ongoing monitoring process of client behaviour becomes more efficient with RPA since it’s done automatically.” Patel cites the example of a client’s credit-card usage, with the RPA identifying marked deviations in spending behaviour from historical patterns. It will also notify the client and close the credit card before costly fraudulent transactions result in potentially hefty losses for the bank.

Many of the potential gains mentioned above will ultimately be achievable thanks to the advancements being made in the technologies that underpin RPA. The development of artificial intelligence (AI), for instance, will play a pivotal role in the overall growth and capabilities of RPA over the coming years. According to Business Insider’s Insider Intelligence’s “AI in Banking” report, financial institutions’ implementation of AI could account for $416 billion of the total potential AI-enabled cost cuts across industries, which are estimated to be $447 billion by 2030. “RPA has proven to reduce employee workload, significantly lower the amount of time it takes to complete manual tasks, and reduce costs,” the publication acknowledged. “With artificial intelligence technology becoming more prominent across the industry, RPA has become a meaningful investment for banks and financial institutions.”

And in September, Gartner estimated that global RPA-software revenue would reach $1.89 billion in 2021, 19.5 percent more than 2020 levels, despite the economic pressures inflicted by the COVID-19 pandemic. “The key driver for RPA projects is their ability to improve process quality, speed and productivity, each of which is increasingly important as organizations try to meet the demands of cost reduction during COVID-19,” said Fabrizio Biscotti, research vice president at Gartner. “Enterprises can quickly make headway on their digital optimization initiatives by investing in RPA software, and the trend isn’t going away anytime soon.”

Indeed, Gartner expects the RPA market to grow at double-digit rates through 2024, which only further illuminates just how much potential banks anticipate this technology to have in the long run. With AI and automation set to dictate much of the way the world operates, therefore, it would only seem reasonable that those financial institutions that implement RPA across a broad range of business units as soon as possible stand to gain the most in terms of efficiency improvements and cost reductions. With that in mind, the race to “go robotic” is evidently well and truly on.