How Banking Automation is Transforming Financial Services Hitachi Solutions

Learn how to elevate your AML compliance operations while enhancing CX, reducing cost, and driving business growth. Learn how to overcome industry challenges with agility and innovation by investing in the right tools, technology, and talent. Any automation solution, no matter how prescient, is only as good as its execution. This is where PwC excels—by offering proven expertise in managing complex implementation programs from start to finish.

The bank’s newsroom reported that a whopping 7 million Bank of America customers used Erica, its chatbot, for the first time during the pandemic. A digital portal for banking is almost a non-negotiable requirement for most bank customers. The company decided to implement RPA and automate the entire process, saving their staff and business partners plenty of time to focus on other, more valuable opportunities. Implementing RPA can help improve employee satisfaction and productivity by eliminating the need to work on repetitive tasks.

IT automation is the creation and implementation of automated systems and software in place of time-consuming manual activities that previously required human intervention. IT automation helps accelerate the deployment and configuration of IT infrastructure and applications and improve processes at every stage of the operational lifecycle. For example, virtual agents that are powered by technologies like natural language processing, intelligent search, and RPA can reduce costs and empower both employees and external customers. Such automation contributes to increased productivity and an optimal customer experience.

Automation in Banking: What? Why? And How?

Automating compliance procedures allows banks to ensure that specified requirements are being met every time and share and analyze data easily. This frees compliance departments to focus on creating a culture of compliance across the organization. In addition, automated systems can identify and flag suspicious activity that poses a threat to the bank and its customers. This in turn reduces employee workloads, helping them to feel more fulfilled and productive as they are equipped with the data and the time they need to provide the best possible experience for customers. Increasing customer expectations, stringent regulations and heightened competition are making it more important than ever for banks to optimize and modernize their operations.

By making faster and smarter decisions, you’ll be able to respond to customers’ fast-evolving needs with speed and precision. With cloud computing, you can start cybersecurity automation with a few priority accounts and scale over time. Using automation to create a cybersecurity framework and identity protection protocols can help differentiate your bank and potentially increase revenue.

They figure out when exceptions can be made for customer approvals and help the bank comply with money laundering rules, to name but a few. Equally important is the design of an execution approach that is tailored to the organization. To ensure sustainability of change, we recommend a two-track approach that balances short-term projects that deliver business value every quarter with an iterative build of long-term institutional capabilities.

Most traditional banks are organized around distinct business lines, with centralized technology and analytics teams structured as cost centers. Business owners define goals unilaterally, and alignment with the enterprise’s technology and analytics strategy (where it exists) is often weak or inadequate. Siloed working teams and “waterfall” implementation processes invariably lead to delays, cost overruns, and suboptimal performance.

The key to an exceptional customer experience is to prioritize the customer’s convenience wherever possible. From expediting the new customer onboarding process to making it easy for customers to get answers to pressing questions without having to wait for a response, banks are finding ways to reduce customers through the power of automation. As an added bonus, by eliminating friction around essential tasks, banks are also able to focus on more important things, such as providing personalized financial advice to help customers resolve problems and obtain their financial goals. Banks can also use automation to solicit customer feedback via automated email campaigns. These campaigns not only enable banks to optimize the customer experience based on direct feedback but also enables customers a voice in this important process.

See how a major mortgage lender is processing 2,000 transactions monthly while cutting 160 personnel hours off its rate lock process leveraging Sutherland automation technology. It’s time to reinvent AML by prioritizing the customer using Sutherland AML’s customer-centric approach to drive efficient and effective compliance processes. You can foun additiona information about ai customer service and artificial intelligence and NLP. Join us for a webinar where industry experts discuss emerging fintech trends in generative AI, compliance, digital banking, and more. In this webinar, industry experts cover how experience management is evolving the financial back-office. In the next sections, we will explore the specific benefits of RPA in banking, along with common use cases and real-world examples of how banks are implementing this transformative technology.

Enhance loan approval efficiency, eliminate manual errors, ensure compliance, integrate data systems, expedite customer communication, generate real-time reports, and optimize overall operational productivity. Based on our work with major financial institutions around the world and from McKinsey Global Institute research on automation and the future of work, we see six defining characteristics of future banking operations. The amount that you can withdraw from an automated teller machine (ATM) per day, per week, or per month will vary based on your bank and account status at that bank. You may be able to get around these limits by calling your bank to request permission or upgrading your banking status by depositing more funds. Incumbent banks face two sets of objectives, which on first glance appear to be at odds.

To Empower Employees

The 2021 Digital Banking Consumer Survey from PwC found that 20%-25% of consumers prefer to open a new account digitally but can’t. You can implement RPA quickly, even on legacy systems that lack APIs or virtual desktop infrastructures (VDIs). Start automating instantly with FREE access to full-featured automation with Cloud Community Edition.

Modernization drives digital success in banking, and bank staff needs to be able to use the same devices, tools, and technologies as their customers. For example, leading disruptor Apple — which recently made its first foray Chat GPT into the financial services industry with the launch of the Apple Card — capitalizes on the innovative design on its devices. No one knows what the future of banking automation holds, but we can make some general guesses.

Ensure accurate client identity verification and regulatory compliance, flag suspicious activities, and expedite customer onboarding through enhanced data analysis and real-time risk assessment. Customers can contact their bank any time through internet, mobile, or email channels and receive quick, real-time decisions. On the back end, systems would perform almost instant data evaluation about the dispute, surveying the customer’s history with the bank and leveraging historical dispute patterns to resolve the issue. Difficulty in scaling

While RPA can perform multiple simultaneous operations, it can prove difficult to scale in an enterprise due to regulatory updates or internal changes.

By carefully addressing these challenges and considerations, banks can successfully implement RPA and harness its benefits while ensuring a smooth and efficient transformation of their operations. The bank collaborated with a trusted RPA service provider to design and develop the automation solution. The RPA software was integrated with XYZ Bank’s existing loan origination system, allowing seamless interaction between the bots and the system’s interfaces. Robotic Process Automation (RPA) brings numerous benefits to the banking industry, revolutionizing the way banks operate and interact with their customers. A big bonus here is that transformed customer experience translates to transformed employee experience.

Enterprise platforms deliver specialized capabilities and/or shared services to establish standardization throughout the organization in areas such as collections, payment utilities, human resources, and finance. And enabling platforms enable the enterprise and business platforms to deliver cross-cutting technical functionalities such as cybersecurity and cloud architecture. Delivering personalized messages and decisions to millions of users and thousands of employees, in (near) real time across the full spectrum of engagement channels, will require the bank to develop an at-scale AI-powered decision-making layer. Exhibit 3 illustrates how such a bank could engage a retail customer throughout the day.

However, the accountholder’s bank may charge a transaction fee or a percentage of the amount exchanged. Many ATMs don’t list the exchange rate on the receipt, making it difficult to track spending. Travel experts recommend using foreign ATMs as a source of cash abroad, as they generally receive a more favorable exchange rate than they would at most currency exchange offices. Most ATMs in banks are multifunctional, while off-site ATMs are generally only for cash withdrawals. You can now buy and sell Bitcoin and other crypto tokens via Bitcoin ATMs, Bitcoin ATMsare internet-connected terminals that will dispense cash in return for crypto. The first ATM appeared at a branch of Barclays Bank in London in 1967, though there are reports of a cash dispenser in use in Japan in the mid-1960s.

ATM, or automated teller machine, is a machine that lets you get cash from your bank account without visiting a teller. Some ATMs are simple cash dispensers, while others allow a variety of transactions such as check deposits, balance transfers, and bill payments. Before you make a withdrawal, make sure you understand what fees you will have to pay. Achieve faster ROI with full-featured AI-driven robotic process automation (RPA). By integrating business and technology in jointly owned platforms run by cross-functional teams, banks can break up organizational silos, increasing agility and speed and improving the alignment of goals and priorities across the enterprise. Over several decades, banks have continually adapted the latest technology innovations to redefine how customers interact with them.

Since little to no manual effort is involved in an automated system, your operations will almost always run error-free. Working on non-value-adding tasks like preparing a quote can make employees feel disengaged. When you automate these tasks, employees find work more fulfilling and are generally happier since they can focus on what they do best.

With it, banks can banish silos by connecting systems and information across the bank. This radical transparency helps employees make better decisions and solve your customers’ problems quickly (and avoid unsatisfying, repetitive tasks). Imagine, for instance, a bank launching a new credit card in which the card member gets to define the rewards points they can obtain–perhaps 30 percent of rewards going to an airline, 30 percent as cash back, and 40 percent at a specific retailer. Or maybe a bank decides to offer loans that allow customers to specify their repayment plan and due dates. Today, these scenarios would be a nightmare for banks to orchestrate—each card or loan would almost require its own operations team. But soon, operations will use their knowledge of bank processes and systems to first develop customized products and then leverage technology to manage and deliver them.

When large enough, these opportunities can quickly become beacons for the full automation program, helping persuade multiple stakeholders and senior management of the value at stake. Banking automation has facilitated financial institutions in their desire to offer more real-time, human-free services. These additional services include travel insurance, foreign cash orders, prepaid credit cards, gold and silver purchases, and global money transfers. Today, many of these same organizations have leveraged their newfound abilities to offer financial literacy, economic education, and fiscal well-being. These new banking processes often include budgeting applications that assist the public with savings, investment software, and retirement information. Today, many operations employees perform dozens or even hundreds of similar tasks every day–reviewing customer disputes on credit or debit cards, processing or approving loans, making sure payments are processed properly, and so on.

You can get more business from high-value individual accounts and accounts of large companies that expect banks to have a top-notch security framework. Banks are already using generative AI for financial reporting analysis & insight generation. According to Deloitte, some emerging banking areas where generative AI will play a key role include fraud simulation & detection and tax and compliance audit & scenario testing. Banking automation helps devise customized, reliable workflows to satisfy regulatory needs.

For example, AI, natural language processing (NLP), and machine learning have become increasingly popular in the banking and financial industries. In the future, these technologies may offer customers more personalized service without the need for a human. Banks, lenders, and other financial institutions may collaborate with different industries to expand the scope of their products and services. Banking automation involves handing over repetitive business processes in financial institutions like banks and credit unions to technologies like robotic process automation (RPA), artificial intelligence (AI), and machine learning (ML).

Learn how a leading South Korean pharmaceutical company automates a core process for drug safety monitoring. Integration is the connection of data, applications, APIs, and devices across your IT organization to be more efficient, productive, and agile. Landy serves as Industry Vice President for Banking and Capital Markets for Hitachi Solutions, a global business application and https://chat.openai.com/ technology consultancy. He joined Hitachi Solutions following the acquisition of Customer Effective and has been with the organization since 2005. Truth in Lending Regulation Z, Federal Trade Commission guidelines, the Beneficial Ownership Rule… The list goes on. With a dizzying number of rules and regulations to comply with, banks can easily find themselves in over their heads.

The technology is rapidly maturing, and domain expertise is developing among both banks and vendors—many of which are moving away from the one-solution-fits-all “hammer and nail” approach toward more specialized solutions. InfoSec professionals regularly adopt banking automation to manage security issues with minimal manual processing. These time-sensitive applications are greatly enhanced by the speed at which the automated processes occur for heightened detection and responsiveness to threats.

Observability solutions enhance application performance monitoring capabilities, providing a greater understanding of system performance and the context that is needed to resolve incidents faster. Automation software and technologies are used in a wide array of industries, from finance to healthcare, utilities to defense, and practically everywhere in between. Automation can be used in all aspects of business functions, and organizations that wield it most effectively stand to gain a significant competitive advantage. Automation is already reshaping the future of work in the finance function, and the opportunity to boost performance will fuel the trend. Adapting to disruption is challenging, but CFOs who build a clear early perspective on the nuances of the automation journey will be well positioned to thrive. Most banks perform KYC (Know Your Customer) by manually verifying customer details.

In this article, we explored the concept of RPA and its numerous benefits in banking. We discussed how RPA enhances operational efficiency, reduces costs, ensures accuracy and compliance, and fosters scalability and flexibility. We also examined common use cases of RPA in banking, highlighting its applications in account opening, payment processing, customer service, and risk management. banking automation definition Robotic Process Automation (RPA) is revolutionizing the banking industry by streamlining operations, improving efficiency, reducing costs, and enhancing the overall customer experience. Through the automation of repetitive and rule-based tasks, RPA enables banks to allocate their resources more strategically and focus on high-value activities that require human expertise.

Built for stability, banks’ core technology systems have performed well, particularly in supporting traditional payments and lending operations. However, banks must resolve several weaknesses inherent to legacy systems before they can deploy AI technologies at scale (Exhibit 5). Core systems are also difficult to change, and their maintenance requires significant resources. What is more, many banks’ data reserves are fragmented across multiple silos (separate business and technology teams), and analytics efforts are focused narrowly on stand-alone use cases. Without a centralized data backbone, it is practically impossible to analyze the relevant data and generate an intelligent recommendation or offer at the right moment. Lastly, for various analytics and advanced-AI models to scale, organizations need a robust set of tools and standardized processes to build, test, deploy, and monitor models, in a repeatable and “industrial” way.

Fees are commonly charged for cash withdrawals by the bank where the account is located, by the operator of the ATM, or by both. Some or all of these fees can be avoided by using an ATM operated directly by the bank network that holds the account. Using an ATM abroad can cost more than using one in the U.S. due to exchange rates or transaction fees. Amanda Bellucco-Chatham is an editor, writer, and fact-checker with years of experience researching personal finance topics.

It will innovate rapidly, launching new features in days or weeks instead of months. It will collaborate extensively with partners to deliver new value propositions integrated seamlessly across journeys, technology platforms, and data sets. Automate business workflows, seamlessly integrate business systems, gain insights into operations, and create a stronger, more productive workforce.

In Canada, banks need to ensure they are complying with the statutes of the Proceeds of Crime (Money Laundering) and Terrorist Financing Act, 2000. Depending on your location, compliance requirements might include ongoing risk-based assessment, customer due diligence, and educating staff and customers about AML laws. Manually checking details on each document is time-consuming and leaves room for error. On the other hand, intelligent document processing (IDP) helps streamline document management. By eliminating room for error, automation ensures improved customer experience, increased quality assurance, and the number of cases processed each month, according to a McKinsey study. Customers want a bank they can trust, and that means leveraging automation to prevent and protect against fraud.

Financial institutions need to do big picture, board-level thinking about how to prepare for the revolutionary impact digital technology will have on banking operations. With operations consuming 15 to 20 percent of a bank’s annual budget (Exhibit), transforming these functions will lead to significant improvements in profitability and return more capital to shareholders. It can also boost revenues by enabling banks to provide better products and services to customers. In order for RPA tools in the marketplace to remain competitive, they will need to move beyond task automation and expand their offerings to include intelligent automation (IA). This type of automation expands on RPA functionality by incorporating sub-disciplines of artificial intelligence, like machine learning, natural language processing, and computer vision.

On the one hand, banks need to achieve the speed, agility, and flexibility innate to a fintech. On the other, they must continue managing the scale, security standards, and regulatory requirements of a traditional financial-services enterprise. Connect applications, data, business processes, and services, whether they are hosted on-premises, in a private cloud, or within a public cloud environment. Artificial intelligence, or AI, is technology that enables computers and machines to simulate human intelligence and problem-solving capabilities.

Companies in the banking and financial industries often create a team of experienced individuals familiar with the entire organization to manage digital acceleration. This team, sometimes referred to as a Center of Excellence (COE), looks for intelligent automation opportunities and new ways to transform business processes. They manage vendors involved in the process, oversee infrastructure investments, and liaison between employees, departments, and management. Automation and artificial intelligence, already an important part of consumer banking, will penetrate operations far more deeply in the coming years, delivering benefits not only for a bank’s cost structure, but for its customers. Digitizing the loan-closing and fulfillment experience, for instance, will speed the process and give customers the flexibility and freedom to view and sign documents online or with their mobile app. Typically, US consumers have to wait at least a month to get approval for a mortgage—digitizing this process and automating approvals and processing would shrink wait time from days to minutes.

To Deliver Faster, Personalized Customer Experiences

To do so, they need to understand what customers want, and how and when they want it. Instead of a major cost center, operations of the future will be a driver of innovation and customer experience. RPA combines APIs and user interface (UI) interactions to integrate and perform repetitive tasks between enterprise and productivity applications.

Few would disagree that we’re now in the AI-powered digital age, facilitated by falling costs for data storage and processing, increasing access and connectivity for all, and rapid advances in AI technologies. These technologies can lead to higher automation and, when deployed after controlling for risks, can often improve upon human decision making in terms of both speed and accuracy. The potential for value creation is one of the largest across industries, as AI can potentially unlock $1 trillion of incremental value for banks, annually (Exhibit 1). Document processing solutions use artificial intelligence technologies like machine learning and natural language processing to streamline the processing of business documents. Business automation refers to technologies used to automate repetitive tasks and processes to streamline business workflows and information technology (IT) systems.

How Branch Automation Works

We integrate these systems (and your existing systems) to allow frictionless data exchange. During the pandemic, Swiss banks like UBS used credit robots to support the credit processing staff in approving requests. The support from robots helped UBS process over 24,000 applications in 24-hour operating mode. Learn how top performers achieve 8.5x ROI on their automation programs and how industry leaders are transforming their businesses to overcome global challenges and thrive with intelligent automation. Instead of waiting on hold or being pinballed between different representatives, customers could get instant, efficient automated customer service powered by advanced AI.

By automating complex banking workflows, such as regulatory reporting, banks can ensure end-to-end compliance coverage across all systems. By leveraging this approach to automation, banks can identify relationship details that would be otherwise overlooked at an account level and use that information to support risk mitigation. With threats to financial institutions on the rise, traditional banks must continue to reinforce their cybersecurity and identity protection as a survival imperative. Risk detection and analysis require a high level of computing capacity — a level of capacity found only in cloud computing technology. Cloud computing also offers a higher degree of scalability, which makes it more cost-effective for banks to scrutinize transactions. Traditional banks can also leverage machine learning algorithms to reduce false positives, thereby increasing customer confidence and loyalty.

AI, process automation and data analysis help modernize legacy systems, channel communications and improve customer relationships. Read our 7 proven banking automation strategies for financial service organizations. Looking towards the future, RPA is set to transform banking operations even further. With intelligent automation, hyperautomation, and enhanced customer experience, RPA will continue to drive innovation and operational excellence in the banking industry.

Using automation in banking operations can help free up the hours you spend on manual verification. First, XYZ Bank identified the key pain points in their loan origination process and conducted a comprehensive analysis to determine the optimal areas for automation. They recognized that repetitive tasks such as data collection, document verification, and eligibility calculations could be automated using RPA. Branch automation is a form of banking automation that connects the customer service desk in a bank office with the bank’s customer records in the back office. Banking automation refers to the system of operating the banking process by highly automatic means so that human intervention is reduced to a minimum.

Timesheets, vacation requests, training, new employee onboarding, and many HR processes are now commonly automated with banking scripts, algorithms, and applications. 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. Digitize document collection, verify applicant information, calculate risk scores, facilitate approval steps, and manage compliance tasks efficiently for faster, more accurate lending decisions. Enhance decision-making efficiency by quickly evaluating applicant profiles, assessing risk factors, leveraging data analytics, and generating approval recommendations while ensuring regulatory compliance.

About a third of the opportunity in finance can be captured using basic task-automation technologies such as robotic process automation (RPA). Working atop existing IT systems, RPA is a class of general-purpose software often referred to as “software robotics”—not to be confused with physical robots. RPA and complementary technologies, like business-process management and optical character-recognition tools, have been applied successfully across a number of activities in finance (Exhibit 2).

• Banking organizations are constantly competing not just for customers but for highly skilled individuals to fill their job vacancies.
• Sutherland helps leading lending platform increase efficiency with Sutherland Robility™ bots.
• Artificial intelligence for IT operations (AIOps) uses AI to improve and automate IT service and operations management.
• In some cases, they will need to design new processes that are optimized for automated/AI work, rather than for people, and couple specialized domain expertise from vendors with in-house capabilities to automate and bolt in a new way of working.
• The 2000s saw broad adoption of 24/7 online banking, followed by the spread of mobile-based “banking on the go” in the 2010s.

At some US banks, we have seen up to five to ten percent of all debit card disputes processed with errors. Today, many bank processes are anchored to how banks have always done business—and often serve the needs of the bank more than the customer. Banks need to reverse this dynamic and make customer experience the starting point for process design.

For years, a global pharmaceutical company had outsourced its procure-to-pay finance activities, such as processing invoices and paying suppliers. Savings from low-cost labor and improved processes had yielded savings, but managers were eager to explore whether automation could unlock new opportunities. In the end, the pharmaco managers decided not to bring the outsourced elements home to automate. But they did renegotiate the company’s BPO contract, saving 40 percent or more over the next three years. We can create tailor-made automation software solutions based on your banks’ needs to minimize manual work and improve process efficiency.

Discover how AI for IT operations delivers the insights you need to help drive exceptional business performance. FinOps (or cloud FinOps), a portmanteau of finance and DevOps, is an evolving cloud financial management discipline and cultural practice that aims to maximize business value in hybrid and multi-cloud environments. Read how IBM HR empowers human workers to devote more time to high-value tasks by using AI assistants to automate data gathering.

As in other business settings where automation has become increasingly viable, its implications in finance look to be disruptive for companies and outsourcers alike. The trend raises issues that executives must consider as they adopt a more automated finance operating model, whether internally or through outsourcing. For starters, automating the finance function may be enticing conceptually, but benefits can be elusive. CFOs will need a clearer understanding of what kinds of activities can be automated. To take full advantage of the opportunity, they’ll also need to rethink processes and organizations around the technology in a fundamental way. And they will need to manage the disruption to get through the effort without breaking an already stretched function.

You can think of RPA as “doing” tasks, while AI and ML encompass more of the “thinking” and “learning,” respectively. It trains algorithms using data so that the software can perform tasks in a quicker, more efficient way. Despite billions of dollars spent on change-the-bank technology initiatives each year, few banks have succeeded in diffusing and scaling AI technologies throughout the organization.