Are robots really more efficient than live employees? Robotics in banking operations can perform specific tasks up to 745% faster than humans, eliminate the probability of mistakes, work around the clock, and allow teams to focus on more strategic jobs. That’s the reason why Robotic Process Automation (RPA) is gaining traction across industries, including the financial and banking sectors.
The rapid penetration of RPA impacts industries globally. Thus, the overall RPA market size is forecasted to reach $23.9 billion by the end of 2030.
The banking and financial industries have been growing exponentially over the past several years. Deeply affected by technological advancements and the aftermath of the pandemic, these sectors are reinforcing their online presence and implementing breakthrough techniques to adapt to the changing environment.
RPA in finance is deemed a powerful tool for institutions to reach an edge over the competition by enhancing operational efficiency and elevating client experience. Specifically, RPA in banking is envisaged to attain $1.12 billion by 2025.
How exactly can RPA in financial services aid companies address their challenges, and how can they implement those solutions for maximum prosperity? This article is dedicated to the RPA banking term and seeks to find the right answers.
The distinctive feature of financial and banking robotic process automation software is that it automates activities by accessing user interfaces without influencing underlying programs. It allows benefitting from systems integration with minimal investment.
Currently available technologies empower the automation of multiple jobs in different spheres. Noteworthy, only a few occupations can be entirely replaced by technology solutions, while most jobs have a specific array of activities that can be automated. Thus, 60% of all occupations have at least 30% technically automatable processes.
Let’s proceed to discover what RPA implies in the financial and banking sectors.
What is RPA in banking? In short, RPA in banking includes solutions that aim to automate monotonous, high-volume, routine business procedures and enable banks to save time, expenses, and resources. The respective financial process automation technologies and CRM integration services allow customers to process payments, withdrawals, and deposits and provide other banking activities without the need for human intervention. Such RPA raises consumer experience and increases ROI for banks.
Furthermore, banks can combine automation with artificial intelligence, which allows them to replace even more types of repetitive jobs. AI capabilities add value and have stunning effects on business operations.
As the technology continues to advance, RPA in banking acquires more and more applications. People immerse themselves in digital banking, mobile payments, cryptocurrencies, and other opportunities of Web 3.0. These and other implications of RPA and AI in banking continue to spur the technological growth of the sector.
Let’s see the breakdown of AI-powered RPA solution types applied in banking by the total funds raised.
As is evident from the chart, the highest demand is directed to the applications associated with forecasts, communication, compliance, and risk management.
Financial services embrace a vast range of functions, from routine number crunching to high-value, goal-oriented business thinking. RPA in finance is applicable in all of these processes since it allows for saving the most precious resource: time.
While financial departments may experience a scarcity of time and resources, other departments will always require structured financial information and discerning analysis that enable smart and timely business decisions.
Financial robots keep evolving from specific task automation to entire process automation that drives financial analysis and prognosis accuracy. RPA in financial services promises maximum benefits if combined with intelligent automation technologies. This is a way to take a stand against competition and address the challenges presented by the evolving financial market. Advanced RPA solutions allow organizations to automate routine assignments, mitigate errors, minimize costs, enhance accuracy, match compliance requirements, and increase overall operational efficiency.
Specific benefits of RPA in banking include the following:
As was mentioned before, only a few business processes can undergo complete automation. In the financial industry, some tasks can rely on robots to a great extent; others cannot be automated with the available technologies. Let’s have a look into which operation types have the highest potential for RPA implementation and, thus, discover the RPA meaning in banking.
As you could expect, mundane and tedious tasks, such as general accounting procedures and cash disbursement, compose the greatest field for RPA. However, automation is also broadly applicable in the sphere of analysis, planning, controlling, and reporting. Even such strategic functions as business development and external relations can partly be performed by technology, though, to a substantially lesser percentage than the previous categories.
Financial organizations, with their accounting and procurement departments, have multiple business functions known for repetitive and time-demanding mundane tasks like data input, reporting, cross-checking, and record managing, which are excellent food for RPA tools. Furthermore, most processes are decently structured and rule-based so that no exceptions or human interference are required.
Targeted automation utilizing RPA for banking can provide considerable value if applied for the proper use cases in financial operations. Some of the most rewarding robotic process automation examples in banking are introduced in the list below.
With the limited physical communication and the overwhelming penetration of digital channels, financial organizations face tremendous numbers of incoming calls to their support centers. RPA in banking can aid in handling this traffic. For instance, bots can address routine requests, while more sophisticated queries will be transferred to appropriate human specialists.
By implementing robotic process automation in investment banking, banks can scale their trade operations and facilitate their presence in the financial supply chain. Thus, RPA in banking automates jobs associated with issuing, managing, and closing letters of credit, which are popular trade finance tools. The automation enhances the overall turnaround time, elevates process visibility, and reduces operational costs.
The client onboarding procedure in financial organizations can be daunting. Particularly time-consuming tasks include manual verifications of identity documents. Know Your Customer (KYC) processes are obligatory and indispensable to the onboarding routine.
For some institutions, the cost of conducting compliance procedures and customer due diligence can reach several hundred million dollars annually. Intelligent automation tools can save considerable costs and effort and remove human error.
Mandatory for financial institutions, these processes have a data-intensive and resource-consuming nature. However, this makes them perfect candidates for RPA. Such activities as detecting suspicious banking transactions, conducting verification procedures (for example, through optical character recognition), or performing numerous other manual tasks can be successfully automated.
An illustrative example of robotic process automation in banking is the automation of the entire AML investigation. The task involves substantial manual operations and can take up to 40 minutes per case. Since the process is highly monotonous and rule-based, it’s easy to automate with RPA, with the consequential reduction of turnaround time.
An exceptionally time-intensive assignment, bank reconciliation requires the efforts of knowledge workers to collect a pile of transactional data that encompasses multiple banks and balance the figures. Instead, adequately programmed robots can effectively substitute human effort. Rule-based automation allows for quick verification of each payment against other records and reconciles the records if a match is attained. In case of discrepancies, robots transfer the respective records for additional verification.
Financial institutions and banks can streamline the loan application process through RPA. Typically, loan and appraisal requests take the form of huge chunks of documents when accumulated. The teams must extract data from those applications, verify them against numerous identity documents, and manually evaluate creditworthiness. Not to mention how much time and effort this job may require. AI-enabled RPA solutions can automate a range of these procedures, if not all of them.
With the implementation of robotic process automation in financial services, the opening and closing of accounts have become more straightforward, fast, and accurate. Automation eliminates potential mistakes and enhances the data quality of the system.
Robots successfully perform checks of document availability, dispatch emails, update information in the system, and fulfill multiple other assignments. Therefore, knowledge workers receive more time to focus on productive operations.
This process is an integral part of many financial institutions’ activities. Like multiple other tasks connected with document processing, mortgage lending is severely time-consuming. RPA in banks can substitute a range of manual jobs in this procedure, including loan initiation, customer data processing, quality control, and more. Ultimately, companies will accelerate task completion and drive satisfaction for each customer service bank’s deal.
Reports take a considerable share of effort in the banking industry. Institutions can utilize RPA to replace human work associated with the generation of financial statements, including data gathering from internal and external systems, consolidating the process of data aggregation, developing report templates, and reconciling reports.
Credit card application handling is another use case where RPA in the banking industry can bring sensational benefits. Thanks to effective automation, organizations can become empowered to issue credit cards within hours. Robots can expeditiously navigate through systems, verify data, perform the required background checks, and finally approve or reject the application.
Making purchase orders is a mundane yet indispensable activity that takes a large amount of staff’s time. AI-powered software robots can be trained to scan orders for critical data, make the respective inputs in the system, and establish approval requests.
The processing of invoices can challenge employees, especially if those invoices vary drastically by format. Robotic process automation in finance can unburden back-office staff since robots streamline repetitive and rule-based assignments.
An extremely tedious procedure, loan processing already became a candidate for RPA a while ago. However, as the technology develops, the task can be automated further. Thanks to progressive automation, financial institutions will continue reducing processing time, relieving the load on employees and delighting consumers.
Banking and financial sector players usually deal with large volumes of common client queries. Addressing these requests quickly can become a challenge for support teams. By applying automation, companies cut turnaround times and optimize their internal workflows.
Customers, in turn, also win, as they can get instant responses whenever they contact an institution.
Considering the striking potential of RPA solutions, how should companies implement them to maximize value?
The case study of leading businesses demonstrates that a combination of automation technologies with specific application techniques is particularly fruitful.
The following four techniques proved beneficial in the RPA adoption process:
Now that we’ve stated the powerful use cases of the technology and techniques, let’s compose the overall picture of the process of RPA deployment in banking and finance. It can be split into four essential steps.
Analyze your company operations and functions and determine which of them would benefit most from RPA implementation. Discover the issues that your organization faces and which of them could be solved with the help of automation. Prioritize the issues according to the degree of their impact on the business processes and the potential effect of the implementation of RPA in banking.
Based on the earlier outlined use cases of RPA in banks, you can get an idea of your own stellar case study. Correlate those examples with your company and estimate the investment vs. gains that RPA will bring. Study the RPA requirements in your specific situation and evaluate the time, resources, and efforts necessary for the implementation.
While the two previous steps shape the background for your automation path, at this stage, you should start creating a strategy relying on the collected information.
Select an operating model and workforce for your RPA tasks and adjust it to your company’s goals for seamless implementation. You may consider cooperating with software development experts for a comprehensive approach and optimized investment.
Now it’s time to put your robots to work. Let the automated solutions start bringing the much-anticipated ROI. Your team will also need to adapt to the new processes so that all stakeholders will enjoy greater efficiency and higher speeds of task completion.
By analyzing the outcomes, you’ll determine your demand for the future, your opportunities to scale, and your abilities to further develop your business.
Advanced technology solutions, like robotics in banking, have become integral to the financial sector. Modern organizations could hardly retain a competitive edge without implementing the appropriate software tools. Robotic process automation in the banking industry can optimize multiple banking processes and enrich both businesses and their customers.
What companies need is to approach the implementation process wisely, with thoughtful analysis and evaluation.
With the help of a reliable software engineering partner, you can streamline your journey toward automation mastery and celebrate incredible results for your business.
Robotic process automation enhances productivity, drives the efficiency of employees, ensures fast and reliable employment verification, and elevates customer satisfaction while keeping costs low. Financial operations embrace a huge array of repetitive, tedious, and rule-based jobs, which are excellent candidates for RPA. By implementing automation tools, companies eliminate the opportunity for human error, accelerate processes, and free up resources. Finally, RPA provides high scalability that drives businesses and expands their growth opportunities.
RPA is already reshaping the financial and banking industries, and it holds even broader opportunities for the future. As RPA in banking continues to advance, more breakthrough features are going to shift the ways of doing business. Intelligent automation will impact processes and workflows and enrich the experience of those who keep up.
With the opportunity to process invoices quicker, your organization can also take advantage of early payment discounts. You can avoid delays by paying invoices before a deadline comes. In turn, your organization can cut operational costs.
Banking automation can significantly alter accounting operations; however, it can hardly substitute humans. With the automated procedures in place, financial teams can switch from routine tasks like transactional data processing to more strategic assignments, such as high-value financial analysis and forecasts, for smarter business decisions.
Having more than 15 years of experience in commercial banks and IT business Roman helps CEOs and IT Directors of commercial banks and agile fintech startups embrace digital transformation and deliver benefits to their clients through cutting-edge technologies.
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