Banking operations for a customer-centric world

Use decision engines to efficiently identify, review, and validate files, simplifying your banking and finance processes. ATMs provide convenience for customers by allowing quick self-service actions like deposits, cash withdrawals, bill payments, and transfers. From business operations to IT management, we offer AI-driven automation to support your workflow. To understand what business users need for RPA tool setup, check out our blog for more details.

IBM Consulting’s advanced automation services help businesses go beyond basic task automation to manage crucial, customer-facing processes that drive revenue, with easy adoption and scalability. Operations teams will have new roles and will need to develop different skills. For a smooth transition, it’s best to start in areas with fewer challenges.

Customers increasingly expect banks to be present throughout their journey, understanding their needs at every touchpoint and offering seamless experiences.

This automation tool is valuable for improving efficiency in the banking sector, where many systems and applications are in use. For example, Bank of America has introduced fully automated branches where customers can perform banking tasks at self-service kiosks. Some locations have a teller available to assist with troubleshooting or questions. Old Mutual, a leading South African financial group, integrated multiple systems into one platform, giving employees a comprehensive view of customers and services. This led to a faster customer onboarding process, shorter queues, and better sales results.

For instance, XYZ Bank applied RPA to loan origination, then expanded it to other areas like customer onboarding, payment processing, and data analytics. This boosted efficiency, cut costs, ensured better compliance, and improved the customer experience. Banks now offer standardized products, like 30-year mortgages or rewards credit cards, managed by various teams overseeing specific rules and benefits.

AI and RPA reduce the need for human involvement, but they do so in different ways. AI assistants, also known as bots, are trained to work with humans or independently to handle specific tasks. They use skills like machine learning, computer vision, and natural language processing. Intelligent automation, a more advanced form, combines AI, process management, and RPA to optimize decision-making across organizations. Automation helps businesses cut costs and improve efficiency, and banks are finding innovative ways to implement it.

OneTrust “Locks In” a Sutherland Automation Solution

In the future, many tasks will be automated, leading employees to focus more on product development. For more information on AI customer service and the role of artificial intelligence and natural language processing (NLP), check out the details. Instead of manually evaluating credit risks or approving mortgages, staff will work with automated systems to offer customers more flexible and personalized mortgage options. Traditional banking models hinder their ability to innovate and adapt to these changes.

Areas of expertise will include general financial planning, career development, lending, retirement planning, tax prep, and credit services. The real advantage of AI-driven automation is its ability to speed up processes and reduce customer wait times. The future AI-first bank will be fast and adaptable, much like today’s digital-native companies.

Predictive analytics can greatly improve operational management. By using this technology, operations leaders can make more accurate predictions. Automation tools like RPA can connect to older systems and work with various applications through front-end integrations, mimicking human tasks like logging in and transferring data between systems.

Banks could also use predictive modeling to identify customers likely to need assistance and reach out to them proactively. For example, if a bank knows that older customers often call within the first week after opening an account or receiving a new card, an AI-powered customer service representative can contact them first. The key difference between RPA and AI is that RPA is process-driven, while AI is data-driven. RPA bots follow user-defined steps, while AI bots use machine learning to detect patterns in unstructured data and improve over time. In short, AI aims to simulate human intelligence, whereas RPA simply replicates human actions.

The FinTech Industry’s Outsourcing Needs

The bots also update customer records, generate reports, and send status updates to both customers and bank staff throughout the loan application process. RPA creates a virtual workforce that can perform a variety of tasks, such as data entry, data extraction, form filling, report creation, and more. These bots interact with different systems and applications, including CRM systems, ERP systems, and banking platforms, to carry out tasks smoothly and efficiently.

Some banks have trained developers but struggle to implement solutions in real-life scenarios. Others have started automation but lack the necessary capabilities to advance the process or fully transform their banking operations. A great example is the Australia and New Zealand Banking Group, which implemented RPA on a large scale and is now saving over 30% annually in specific areas.

We and our partners process data to provide:

Branch automation can simplify routine tasks, allowing human tellers to focus on helping customers with more complex needs. This creates a faster and more enjoyable experience for both the teller and the customer, while also reducing wait times for others. With the right tools in place, banks can assess the potential value across all areas of their business, from capital markets and retail banking to HR, finance, and operations.

Enhance and improve your extracted data to gain deeper insights and take actionable steps. Many cards now come with a chip that transmits data to the machine. Basic ATMs allow cash withdrawals and provide account balance updates. Learn about process mining, a method that uses specialized algorithms to analyze event log data and uncover trends, patterns, and how processes unfold. This helps speed up development, reduce unplanned downtime, and lower management time while ensuring top-notch security, governance, and availability.

Managers often view automation as an IT-driven initiative. This leads to businesses using mismatched tools that only automate certain parts of the process. While this approach can capture a small portion of automation’s potential, unlocking its full benefits requires a different mindset. Using RPA in banking ensures accurate compliance without heavy reliance on human resources. It helps banks save money spent on maintaining compliance.

When we talk about Intelligent Automation (IA), we refer to coordinating various automation tools to solve more complex issues. IA can automate tasks ranging from simple rule-based processes to complex activities like data analysis and decision-making. By implementing RPA carefully, banks can maximize automation’s benefits, improving productivity, accuracy, and compliance. The future of RPA in banking is bright, especially as AI, machine learning, and process optimization continue to advance. RPA is revolutionizing the banking industry by streamlining operations, reducing costs, improving accuracy, enhancing customer experiences, and helping banks stay competitive.

In the ideal future state, a bank could have different platform teams: Business platforms focused on customer or partner-facing tasks, such as consumer lending, corporate lending, and transaction banking, delivering products and services to customers or other internal platforms.

Challenges Faced by Banks Today

Faster front-end applications, like online banking and AI-assisted budgeting tools, have successfully met customer needs. Behind the scenes, banking automation has enhanced anti-money laundering efforts and allowed staff to focus on generating new business. Automating processes reduces human bias in decision-making and minimizes errors, giving employees more time to handle complex, large, or sensitive customer issues that automation can’t address.

At one global financial institution, the CFO plans to reduce a quarter of the 20,000-person shared services team within the next two years. While this is disruptive, it’s important to acknowledge the reality of automation and its impact. Automated systems can quickly fill in details and generate error-free reports. These systems can also extract data from internal or external sources, fact-check reports, and generate documents like quarterly performance or transaction reports.

Banks introduced ATMs in the 1960s, card-based payments in the 1970s, 24/7 online banking in the 2000s, and mobile banking in the 2010s. Today, AI-driven solutions help automate business and IT processes at scale, just like traditional RPA but with greater ease and speed.

We can tailor an automation solution specifically for your organization, working alongside your existing systems. Managers in financial institutions often make decisions based on raw data or external research, which lacks full context. RPA can help analyze internal data to track customer spending patterns and preferences. By investing in customer-centric technologies that streamline data and processes, companies can meet customer experience (CX) and anti-money laundering (AML) compliance needs. RPA and intelligent automation reduce repetitive tasks, improve quality, scalability, and controls, and run 24/7. As technology evolves and banks adopt more automation, RPA will continue to be a key tool for operational excellence.

Let’s explore how XYZ Bank successfully used Robotic Process Automation (RPA) to improve efficiency. If you remember the old drive-thru banking, where your deposit was sucked up into a pneumatic tube and delivered to a teller, that’s an early example of automation.

Each layer of automation has a specific role. Failing to invest in even one layer can weaken the entire system. Schedule a meeting with experts at no cost to discover how intelligent automation can improve your business. Basic automation streamlines tasks like distributing onboarding materials, forwarding documents for approval, or sending invoices automatically. However, automation in transactional roles often leads to changes in organizational structures, redefined roles, and sometimes layoffs.

Remember to endorse the back of checks and write “For Deposit Only” for added security. Using your own bank’s ATM is usually free, but using one from another bank often comes with a fee. According to MoneyRates.com, the average fee for out-of-network ATM withdrawals was $4.55 in 2022. Some banks reimburse these fees if no nearby ATM is available. RPA also speeds up the actioning of AI insights, eliminating the need to wait for manual implementation.

Loan Origination and Processing

While it may seem counterintuitive, automation can actually strengthen human connections. Customers now expect fast, personalized experiences from the moment they begin onboarding and throughout their relationship with the bank. By having the right customer information at the right time, employees can provide better service, foster loyalty, and gain a competitive edge. Our team uses technologies like RPA, AI, and ML to automate your processes.

Hyperautomation is an approach that combines various technologies and tools to automate a wide range of business and IT processes, workflows, and environments efficiently. The role of Chief Automation Officer (CAO) is rapidly growing due to automation’s positive impact on businesses. The CAO oversees decisions on business processes and IT operations to determine the best automation platform and strategy for each business initiative.

Automation and digitization can reduce paper usage and eliminate the need for storing physical documents. Implementing automation strengthens both legacy and new systems by automating across your infrastructure. For example, Credigy, a global financial organization, uses RPA for its consumer loan due diligence process. The bots work more accurately and tirelessly than humans—no need for breaks or sleep. Automation helps transform banks and non-banks, driving sustainable revenue growth and improving efficiency.

Applying business logic to data analysis removes simpler decision-making from employee workflows. Additionally, RPA bots complete tasks more quickly and without breaks. For instance, customers should be able to open a bank account quickly once they submit their documents. This allows your employees to focus on more strategic tasks by automating the routine ones.

You’ve likely seen headlines predicting that disruption is not just approaching the financial services industry, but already here. And while it’s not all doom and gloom, there’s truth to these predictions. Despite some initial challenges, fintech has delivered on its promise to transform the way banks operate, with 88% of legacy banks now fearing revenue loss to financial tech companies. Intelligent automation (IA) covers a broad range of technologies designed to enhance how bots interact and perform tasks.

The banking industry has always been quick to adopt new technology to improve operations and customer experience. From online banking to mobile payments, banks have continuously innovated to stay competitive in the digital age. One bank uses automation to automatically reject loans that don’t meet minimum requirements during the loan origination process.