October 16, 2023
Banks now actively turn to robotic process automation experts to streamline operations, stay afloat, and outpace rivals. We help to figure out the most potent use cases for robotic process automation in banking, outline real-life RPA application examples, define the implementation mindset, and provide tips on adopting the technology in your business.
additional AI value for the global banking industry annually
McKinsey
the estimated global RPA and Hyperautomation market size in 2027
Research and Markets
the estimated RPA services and software market size in 2025
Forrester
Now let’s figure out some of the most potent RPA in banking use cases:
Banks have vast amounts of customer data that are highly sensitive and vulnerable to cyberattacks. There are many machine learning-based anomaly detection systems, and RPA-enabled fraud detection systems have proven to be effective.
Instead of relying on human judgment and largely manual data manipulation, banks can apply RPA tools to continuously monitor customer transactions, detect anomalies based on an elaborate rule-based system, flag them as potentially fraudulent, and send alerts to human employees for further review. Rather than spending valuable time gathering data, employees can apply their cognitive abilities where they are truly needed.
There are several important steps to consider before starting RPA implementation in your organization.
Conduct a detailed assessment, choosing the right use cases
Evaluate RPA vendor’s ability to meet all your requirements
Build a comprehensive execution framework
Selecting the right processes for RPA is one of the major prerequisites for success. Banks have thousands of repetitive processes for potential RPA automation, and relying on intuition rather than objective analysis to select use cases can be detrimental. Selecting use cases comes down to a company-wide assessment of all the banking processes based on a clearly defined set of criteria.
Below we provide an exemplary framework for assessing processes for automation feasibility. The processes above a cutoff point can be selected for automation.
Selecting a trustworthy RPA implementation partner is not easy and requires careful consideration. Check out the following factors:
Vendor choice should first of all stem from vendor experience in the banking sector. Consider the vendor's ability to expand beyond rule-based automation and introduce intelligent automation that usually involves AI and data science.
While on-premise solutions still exist, it is more than likely that you will need to migrate to the cloud in the future. Today, all the major RPA platforms offer cloud solutions, and many customers have their own clouds.
Make sure you distinguish vendors and partners. For example, UiPath, the leading RPA platform on the market today, provides the means of implementing this technology. Meanwhile, Itransition is a UiPath silver partner that helps organizations to adopt it.
Requirements gathering
Backup plan
Running a pilot
Performance assessment
While retail and investment banks serve different customers, they face similar challenges. Regardless of the niche, automating low-value-adding tasks is one of the most effective ways to realize employees’ full potential, achieve superior operational efficiency, and significantly increase customer satisfaction.
Postbank, one of the leading banks in Bulgaria, has adopted RPA to streamline 20 loan administration processes. One seemingly simple task involved human employees distributing received payments for credit card debts to correct customers. Even such a simple task required a number of different checks in multiple systems. Before RPA implementation, seven employees had to spend four hours a day completing this task. The custom RPA tool based on the UiPath platform did the same 2.5 times faster without errors while handing only 5% of cases to human employees. Postbank automated other loan administration tasks, including customer data collection, report creation, fee payment processing, and gathering information from government services.
CGD is the oldest and the largest financial institution in Portugal with an international presence in 17 countries. Like many other old multinational financial institutions, CGD realized that it needed to catch up with the digital transformation, but struggled to do so due to the inflexibility of its legacy systems. When it comes to RPA implementation in such a big organization with many departments, establishing an RPA center of excellence (CoE) is the right choice. To prove RPA feasibility, after creating the CoE, CGD started with the automation of simple back-office tasks. Then, as employees deepened their understanding of the technology and more stakeholders bought in, the bank gradually expanded the number of use cases. As a result, in two years, RPA helped CGD to streamline over 110 processes and save around 370,000 employee hours.
KAS Bank, an independent Dutch bank founded over two centuries ago, is a leading European provider of custodian services to institutional investors and financial institutions. KAS Bank wanted to solve one of the most recurring problems a modern bank faces: high operational costs. After subpar results of conventional cost reduction strategies, KAS Bank opted for RPA. Like CGD, KAS Bank carefully explored RPA use cases, conducted multiple proofs of concepts, and only then engaged in the enterprise-wide implementation. This calculated approach helped the bank to reveal various IT bottlenecks and discover the most value-adding RPA use cases. With five RPA bots, the bank automated 20 financial business processes, including treasure operations, obligation payments, internal invoicing, and calculating and booking. Importantly, while the focus of this RPA strategy was to reduce costs, automation significantly improved the quality of KAS Bank’s business processes.
UBS is a multinational investment bank present in more than 50 countries. After the Swiss Federal Council allowed commercial companies to apply for loans with zero interest rates because of the pandemic, UBS, like many other investment banks, had to deal with an unprecedented spike in the number of loan requests. When they could not process the amount of loans using conventional methods of loan request processing, UBS turned to RPA. In collaboration with Automation Anywhere, the bank implemented RPA just in 6 days, resulting in a reduction of request processing time from 30-40 minutes to 5-6 minutes.
RPA has been really helpful to actually show the people on the ground that we can break barriers pretty quickly, which probably previously using other tools and traditional methods of development wouldn’t be as agile and fast.
According to Gartner, 80% of leaders in the financial sector are already using some form of RPA for various purposes. Here are some of the most prominent benefits of financial process automation:
Scales operations
Saves time
Minimizes IT department interference
Cuts down expenses
Facilitates compliance reporting
Increases employee efficiency
Reduces human errors
Implements seamlessly
Benefits
Despite numerous benefits RPA can bring and its comparatively undisruptive implementation, adopting this technology is not easy. Here are the three most recurring challenges that financial institutions face when trying to integrate RPA into their banking operations:
Regardless of the promised benefits and advantages new technology can bring to the table, resistance to change remains one of the most common hurdles that companies face. Employees get accustomed to their way of doing daily tasks and often have a hard time recognizing that a new approach is more effective.
That is why change management is pivotal to successful RPA adoption. As soon as it becomes clear that RPA implementation is the right thing to do from a business standpoint, banks need to create comprehensive change management programs to help employees shift their mindsets and make the transition as smooth as possible.
In a nutshell, the more complicated the process is, the harder it becomes to adopt RPA. In the RPA implementation context, the process complexity correlates with standardization rather than the number of branches on a decision tree. When it comes to global companies with numerous complex processes, standardizing becomes difficult and resource-intensive.
RPA adoption often calls for enterprise-wide standardization efforts across targeted processes. A positive side benefit of RPA implementation is that processes will be documented. Bots perform tasks as a string of particular steps, leaving an audit trail, which can be used to granularly analyze what the process is about. This RPA-induced documentation and data collection leads to standardization, which is the fundamental prerequisite for going fully digital.
While employees are reluctant to change because of the mindset, IT departments often have too much weight on their shoulders to support RPA implementation. In this current age of digital transformation, bank IT departments are already spending considerable resources to overcome challenges associated with cloud migration, legacy system maintenance, and implementing new ERPs.
While RPA is much less resource-demanding than the majority of other automation solutions, the IT department's buy-in remains crucial. That is why banks need C-executives to get support from IT personnel as early as possible. In many cases, assembling a team of existing IT employees that will be dedicated solely to the RPA implementation is crucial.
RPA can help organizations make a step closer toward digital transformation in banking. On the one hand, RPA is a mere workaround plastered on outdated legacy systems. On the other hand, RPA is a bridge to digital transformation. Still, instead of abandoning legacy systems, you can close the gap with RPA deployment.
With the right use case chosen and a well-thought-out configuration, RPA in the banking industry can significantly quicken core processes, lower operational costs, and enhance productivity, driving more high-value work. Reach out to Itransition’s RPA experts to implement robotic process automation in your bank.
An average bank employee performs multiple repetitive and tedious back-office tasks that require maximum concentration with no room for mistakes. RPA is poised to take the robot out of the human, freeing the latter to perform more creative tasks that require emotional intelligence and cognitive input. According to Gartner, process improvement and automation play a key role in changing the business model in the banking and financial services industry.
Augmenting RPA with artificial intelligence and other innovative technologies is a definitive next step toward digital transformation. According to McKinsey, the “AI-first” institution will yield greater operational efficiency via the extreme automation of manual processes (a “zero-ops” mindset), and the replacement or augmentation of human decisions by advanced diagnostics.
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