Why Big Banks Are Turning To Robotic Process Automation

Jennifer Horowitz

At BNY Mellon, profits have been growing, thanks to the bank’s launch of robot-driven pilot projects to automate processes. In 2016, the bank adopted robotic process automation (RPA), which integrates web robots to increase efficiency and accuracy while reducing risk and costs.

Web robots are basically software applications that are designed to run automated tasks. Machine learning is predicted to become an increasing trend across many industries, including the financial sector. At BNY Mellon, an RPA team is actively working with business leaders, while a transformation team identifies locations to use web robots.

According to BNY Mellon, bots have streamlined trade settlement by performing research on orders, resolving discrepancies, and clearing trades. Web robots, for example, are able to reconcile a failed trade in just a quarter of a second, while these tasks take human workers up to ten minutes. Doug Shulman, senior executive vice president and global head of client service delivery at BNY Mellon, stated in American Banker magazine,“If you think about smart automation, robotics is a piece, workflow is a piece, and we’re combining smart forms, optical character recognition, workflow and robotics to get momentum around automating tasks.”

Today, it’s clear that automation is already significantly impacting asset management areas and all other industries across the board. According to the International Federation of Robotics (IFR), at a global level, automation adoption is accelerating, driven by increased global competitiveness and the need to boost productivity and quality while expanding production lines. Although automation could be a threat to some jobs, the IFR argues robots have the ability improve the quality of work by taking over dangerous, dirty, and tedious jobs that are not possible or safe for humans to perform.

BNY Mellon’s efforts to transition staff members to more cost-effective venues by turning to robotics and automation have resulted in huge sustained cost savings and increased productivity. The projects have created better accuracy and faster processing, reducing transaction time and eliminating manual steps. This enables the organization to redeploy resources to activities that create greater value for its clients.

Despite BNY Mellon’s success, limitations remain. When improving operational efficiency, leaders should be able to:

  • Maximize value from existing outsourced operations.

  • Avoid costly investment in technology transformation while achieving planned objectives.

  • Support business growth, processes, products, and innovations within the business model without high-cost technologies.

Big banks can leverage automated robotics and machine learning tools to eliminate “non-value-added work” and increase efficiency through automated workflows.

Automation and digitization have the potential to free human workers from mundane and repetitive tasks and focus on industry knowledge and expertise to create greater value.

For more on emerging technology in the financial industry, see Pinpointing The Value Of Intelligent Banking.

Jennifer Horowitz

About Jennifer Horowitz

Jennifer Horowitz is a management consultant and journalist with over 15 years of experience working in the technology, financial, hospitality, real estate, healthcare, manufacturing, not for profit, and retail sectors. She specializes in the field of analytics, offering management consulting serving global clients from midsize to large-scale organizations. Within the field of analytics, she helps higher-level organizations define their metrics strategies, create concepts, define problems, conduct analysis, problem solve, and execute.