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For financial services firms, the effort to do more with less seems like a never-ending goal. Now, with advanced digital technologies such as artificial intelligence (AI), machine learning (ML), cognitive computing, and other modern initiatives to streamline legacy processes and help reduce costs, the effort is gaining renewed ground.

Automation in banking began in earnest decades ago. In the early 1950s, Bank of America began working with Stanford Research Institute to develop a computer-based check processing system and machine-readable checks that would help the bank more efficiently handle the growing amount of paperwork involved in bookkeeping. 

At the time, banks struggled to keep up with the flow of paper and the manual check-clearing processes involved with billions of checks being written each year. Engineers developed Electronic Recording Machine, Accounting (ERMA), and the M/CR, or magnetic-ink character recognition check coding system. Then in the late 1960s, automated teller machines (ATMs) came onto the scene, fundamentally impacting banking servicing.

Fast forward to today, and robotic process automation (RPA) is poised to digitally transform business processes in the banking and financial sector. RPA in its most general form is the application of software bots to perform tasks typically performed by humans. This includes processing a transaction, providing assistance, manipulating data, triggering responses, and communicating with other digital systems. While RPA is still a burgeoning technology, the RPA global market is expected to reach $3.11 billion by 2025, according to a study by Grand View Research, Inc.

Red Hat has joined forces with WorkFusion, combining  Red Hat Process Automation Manager (formerly JBoss BPM Suite) and WorkFusion’s RPA solutions to help customers digitally capture business logic and develop applications which automate business operational processes and decisions. 

The solutions integrate process management, rules management, resource optimization, and complex event processing (CEP) technologies into a single, integrated, open source platform. This can help simplify business operations, streamline tasks and reduce the time-consuming, error-prone manual data tasks, which in turn can increase speed and accuracy.

Even greater value to operational efficiencies might be had by embedding AI/ML and cognitive computing technologies into business processes - providing the capability to adapt to new events and goals - and such insights actioned based on decisioning defined to the system. Business operational efficiencies are no longer beholden to the limits of humans' ability to do tasks, only to the limits of underlying processing power of the systems on which they run.

For a good primer on AI and machine learning, read Red Hat’s blog post on the two technologies and the roles they are playing in digital transformation. And learn more about the future roles of AI and machine learning in the banking sector including its use to mitigate risks and combat fraud and money laundering.

Transactional efficiencies could get a boost from advanced digital technologies, but there’s also the expectation that modernizing core banking systems will improve efficiency. More and more banks are evolving their legacy, closed systems to digital banking systems that use application programming interfaces (APIs) to create more flexible and streamlined operational and transactional environments.

By using open APIs, banks can more easily integrate data from disparate systems and sources. They may also positively impact business development by helping to accelerate partnerships and streamline partner integrations. The open nature of APIs can foster creativity and increase the rate of innovation to improve transactional insights leading to better actions. To learn more about open APIs, see IDC’s InfoBrief, sponsored by Red Hat, Beyond banking through open APIs.  

No matter where the data comes from, strengthening your business operations environment relies on innovations, and an open source technology foundation provides a stable yet flexible platform that can scale and adapt so that customers receive a streamlined experience that meets their expectations.

To learn how to modernize your banking operations for a digital world, watch our on-demand webinar series covering how to get started, which technologies can drive efficiencies, how to streamline processes with a foundational approach, how to break down barriers between the front and back offices, and much more.

About the author

Described as a pioneer and one of the most influential people by CRMPower, Fiona McNeill has worked alongside some of the largest global organizations, helping them derive tangible benefit from the strategic application of technology to real-world business scenarios.

During her 25 year professional tenure, she has led teams, product strategy, marketing, and consulted across a wide range of industries, while at SAS, IBM Global Services, and others. McNeill co-authored Heuristics in Analytics with Dr. Carlos Andre Pinheiro, has previously published both in academic and business journals, and has served on the board of the Cognitive Computing Consortium. She received her M.A. in Quantitative Behavioral Geography from McMaster University and graduated with a B.Sc. in Bio-Physical Systems, University of Toronto.

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