Robotic Process Automation RPA in Banking: Enhancing Efficiency with Applied Financial Technology
The use of IoT in financial services holds immense
promise in this sphere, offering new possibilities for enhanced customer
experiences, streamlined operations, and data-driven decision-making. RPA automates mundane and time-consuming tasks, allowing bank employees to focus on more strategic and value-added activities. This streamlining of processes not only saves time but also reduces the risk of human errors, ultimately leading to improved operational efficiency. Banking has come a long way from the traditional brick-and-mortar model to a digital landscape that relies heavily on technology. The digital transformation of the banking industry has been fueled by the need to meet customer demands, enhance security, and improve operational efficiency.
In recent years, intelligent automation in banking has evolved from a novelty to a necessity. Across all industries, companies are deploying AI as a tactical advantage, but it is in banking that automated AI functionality can really shine. Of course, intelligent automation for instant loan approvals benefits anxious customers but also bored staff. Along the way, AI can collect information about the loan decisioning process, unlocking insights about how to make this process more efficient. The financial services sector is an early adopter of intelligent automation and is encountering its governance challenges sooner than most. Gartner reports that organizations across industries aim to lower their operating costs by 30% by 2024 through a synthesis of hyper-automated technologies and redesigned operational processes.
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Gartner reports that 80% of finance leaders have already implemented or plan to implement RPA initiatives. For those already on the journey, here is another opportunity to collaborate with core providers. Technology providers may utilize a wide range of technologies or methodologies to deploy faster solutions, including Agile, cloud transformation, iterative releases and implementation solution assurance.
Many factors come into play when talking about how to improve business processes and what to automate. Institutions should discuss BPI opportunities with internal staff and their core provider to ensure those factors are beneficial. The first approach to making banking technology more efficient is through programmatic automation. Programmatic automation involves rewriting software so that automation is fixed (or programmed) into a technology provider’s system. Examples include improvements to streamline account opening, teller hold or positive pay.
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Increasingly, customers expect their bank to be present in their end-use journeys, know their context and needs no matter where they interact with the bank, and to enable a frictionless experience. Numerous banking activities (e.g., payments, certain types of lending) are becoming invisible, as journeys often begin and end on interfaces beyond the bank’s proprietary platforms. For the bank to be ubiquitous in customers’ lives, solving latent and emerging needs while delivering intuitive omnichannel experiences, banks will need to reimagine how they engage with customers and undertake several key shifts.
In recent years, the onset of Artificial Intelligence and Machine Learning has led to an increase in widespread technology automation. Simply put, automation technology enables processes to occur automatically, by predetermining criteria, relationships and related actions. Offloading redundant and simple tasks to computers is done with little to no human intervention –not only does this greatly reduce labor costs and time, but humans are freed up to use that time in more efficient and meaningful ways. Some sources estimate that, on average, workers spend nearly five hours each week performing duplicate tasks that can be automated. For this reason, robotic process automation (RPA), or using bots to perform these recurring tasks, is also gaining steam across the industry. Some applied examples include automated employee onboarding, purchase order approvals, workflows and automating data entry to remove specific manual processes altogether.
The Evolution of Banking
Banks and the financial services industry can now maintain large databases with varying structures, data models, and sources. As a result, they’re better able to identify investment opportunities, spot poor investments earlier, and match investments to specific clients much more quickly than ever before. Customers want to get more done in less time and benefit from interactions with their financial institutions. Faster front-end consumer applications such as online banking services and AI-assisted budgeting tools have met these needs nicely. Banking automation behind the scenes has improved anti-money laundering efforts while freeing staff to spend more time attracting new business.
Ultimately, the lessons for the banking industry maybe to anticipate and proactively shape how automation will spur innovation, increase demand, and alter the competitive dynamics, beyond operational transformation. Interestingly, as ATMs expanded—from 100,000 in 1990 to about 400,000 or so until recently—the number of tellers employed by banks did not fall, contrary to what one might have expected. According to the research by James Bessen of Boston University School of Law, there are two reasons for this counterintuitive result.
The Future of Robotic Process Automation in Banking
In this sense, automation is an enabler that frees up urgently needed resources. Traditional software programs often include several limitations, making it difficult to scale and adapt as the business grows. For example, professionals once spent hours sourcing and scanning documents necessary to spot market trends. Today, multiple use cases have demonstrated how banking automation and document AI remove these barriers.
The bank also used the intelligent automation platform to expedite its document custody procedures. Consider, for example, the laborious paperwork that is typically required to refinance homes. Similarly, Deutsche Bank saw substantial returns on investment when it embarked upon a comprehensive digital transformation journey where it deployed software to introduce both attended robotic process automation and unattended intelligent automation. If you want to explore IoT adoption in your organization, consider contacting
the experienced team at Softermii for
fintech app development services.
The banking industry, in particular, benefits from a range of use cases for intelligent automation. In fact, according to research from Futurum, 85% of banks have used intelligent automation to automate core processes. As we contemplate what automation means for banking in the future, can we draw any lessons from one of the most successful innovations the industry has seen—the automated teller machine, or ATM? Of course, the ATM as we know it now may be a far cry from the supermachines of tomorrow, but it might be instructive to understand how the ATM transformed branch banking operations and the jobs of tellers. Automation will also extend further into personal banking and finance, through the apps, sites and digital tools we’re already accustomed to. Investing will be easier for people not considered “experts” because they will have the same access to the data the AI is giving that everyone else has.
- These digitally-first banks have even been appealing to high-wealth clients who view the ease of doing business online or through their phone as reason enough to open a new account and transfer funds.
- However, banks must resolve several weaknesses inherent to legacy systems before they can deploy AI technologies at scale (Exhibit 5).
- Yet banking automation is also a powerful way to redefine a bank’s relationship with customers and employees, even if most don’t currently think of it this way.
- While the list of benefits is lengthy, a few of the more prominent use cases are listed below.
- It begins with sincerely evaluating business processes, and determining whether they could improve, change or be removed altogether.
By adopting IoT
solutions, financial institutions can stay ahead of the curve, offering
innovative services and gaining a competitive edge. Whether it’s leveraging
IoT for personalized experiences, optimizing operations, or improving risk
management, the potential for growth and efficiency is vast. By connecting
devices and exchanging real-time data, IoT automates various banking
operations. They include everything from routine tasks such as data entry and
reporting to more complex processes like loan origination and compliance
checks. Automating these tasks improves operational efficiency and accuracy
and reduces costs for banks.
Additionally, organizations lack a test-and-learn mindset and robust feedback loops that promote rapid experimentation and iterative improvement. Although automation may bring a host of benefits, embracing it means eliminating some human-occupied posts and retraining staff. According to a 2019 report by Wells Fargo, 200,000 jobs could be eliminated over the next ten years in the banking industry due to chatbots and other automated software. For example, Axis Bank has been able to reduce the turn-around time on savings account opening by about 90 percent using RPA. Citigroup, Capital One and JPMorgan Chase are already using AI-fueled automation to drive efficiency on tasks such as validating customer data for Know Your Customer (KYC) or keeping track of audit trails for compliance.
Thus, banks must use strong encryption methods and secure data
transmission protocols. It’s also crucial to have stringent data privacy
regulations when banks implement IoT. At Softermii, we understand the evolving needs of the financial sector and
have leveraged our expertise to create impactful fintech solutions. Our team
has a proven track record of developing cutting-edge financial apps like
SmartStart. Our experience developing
advanced applications demonstrates our commitment to driving innovation and
delivering exceptional results in banking and finance. Let’s take a closer look at a real-world example to illustrate the tangible benefits of RPA in banking.
QuickLook is a weekly blog from the Deloitte Center for Financial Services about technology, innovation, growth, regulation, and other challenges facing the industry. The opinions expressed in QuickLook are those of the authors and do not necessarily reflect the views of Deloitte. Since their modest beginnings as cash-dispensing services, ATMs have evolved with the times. Book a discovery call to learn more about how automation can drive efficiency and gains at your bank.
- Instead, they can coordinate with bankers to make positive additions or modifications through incremental updates.
- Your employees will have more time to focus on more strategic tasks by automating the mundane ones.
- Internally, the AI-first institution will be optimized for operational efficiency through extreme automation of manual tasks (a “zero-ops” mindset) and the replacement or augmentation of human decisions by advanced diagnostic engines in diverse areas of bank operations.
- As we mentioned earlier, much of the previous automation efforts in banking have centered on the idea of digitization rather than digitalization.
- This involves allowing customers to move across multiple modes (e.g., web, mobile app, branch, call center, smart devices) seamlessly within a single journey and retaining and continuously updating the latest context of interaction.
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