Intelligent automation in financial services: Use cases and risks

“You might have centres of excellence in different divisions or geographies, depending on what work is being delivered, and those are under the governance of a centralised body. Automate calculation changes, notifications, and extraction of data from letter of credit applications. You should consult with a licensed professional for advice concerning your specific situation. Steve Comer discusses the impact this strategic lever has on the banking industry and best practices for implementation. With our modern, open and cloud-native platforms, you can build strong connections and keep evolving.

According to Capgemini, the financial services industry is expected to add around $512bn in global revenues by implementing intelligent automation, and there is no question about the ROI when the deployment is executed thoughtfully. The best way to look at intelligent automation in the future is as a solution that can deliver improvements across the entire customer journey. Intelligent automation is transforming the banking industry by driving digital transformation and enhancing efficiency. Banks must address challenges and considerations when implementing intelligent automation solutions. These challenges have led to the need for digital transformation in the banking industry, with banks embracing technology to drive efficiency, reduce costs, and enhance customer experience.

Intelligent automation in financial services: use cases

Banks can speed up administration processes and improve SLAs (service-level agreements) this way. The financial services sector is an early adopter of intelligent automation and is encountering its governance challenges sooner than most. So then, what are the next steps for banks interested in using intelligent automation.

This transition from classic, data-driven AI to advanced, generative AI provides increased efficiency and client engagement never seen before in the banking sector. According to McKinsey’s 2023 banking report, generative AI could enhance productivity in the banking sector by up to 5% and reduce global expenditures by up to $300 billion. According to a report by Accenture, the adoption of intelligent automation technologies in the banking industry could result in annual cost savings of up to $70 billion by 2025. This staggering statistic highlights the immense potential of intelligent automation in revolutionizing banks’ operations.

Automation is helping banks worldwide adapt to organizational and economic changes to reduce risk and deliver innovative customer experiences. Banking, financial services, and insurance are the top1 industries where RPA solutions are implemented. This article focuses on RPA use cases in the banking industry, where RPA is seen the most. The implementation of artificial intelligence in the banking business has significantly enhanced client experience. AI-powered technologies, notably chatbots and advanced analytics, have changed how banks interact with their customers, enabling degrees of customization and responsiveness that were before unavailable. Artificial intelligence is transforming the banking industry, with far-reaching implications for traditional banks and neobanks alike.

This stretches as far as AI-powered decision making, but so far most use cases exploit AI’s potential to process unstructured data, such as text and images, to automate steps in a process that would otherwise require human perception. Chatbots that are powered by AI are now a staple in customer service for many banks, providing instant responses to customer inquiries and round-the-clock assistance. Bank of America’s AI chatbot Erica surpassed 1.5 billion interactions since its launch in 2018. It provides 24/7 customer support, efficiently handling queries and transactions, leading to reduced waiting times and improved customer satisfaction. AI’s position in banking began with work automation and data analysis but has now expanded to encompass sophisticated applications in risk management, fraud prevention and tailored customer service.

Some have installed hundreds of bots—software programs that automate repeated tasks—with very little to show in terms of efficiency and effectiveness. Some have launched numerous tactical pilots without a long-range plan, resulting in confusion and challenges in scaling. Other banks have trained developers but have been unable to move solutions into production.

Cash management operations

In no uncertain terms, these capabilities are an integral portal into an organization’s 21st-century business strategies. When ChatGPT launched to the public in late 2022, many wondered if generative AI was a fad or a genuinely transformative phenomenon. One year later, banking has moved from the question of whether the technology will change banking to where we should start and what the ultimate impact will be. Finally, if you believe your enterprise would benefit from adopting an RPA solution, we have a data-driven list of vendors prepared in our RPA hub. Creating centres of excellence is a common approach to governing automation, says Burnett, although they must be well integrated into the business they are to succeed.

Over several decades, banks have continually adapted the latest technology innovations to redefine how customers interact with them. The 2000s saw broad adoption of 24/7 online banking, followed by the spread of mobile-based “banking on the go” in the 2010s. With NLP and OCR technologies, intelligent bots can also scan legal and regulatory documents rapidly to check non-compliant issues without any manual intervention. One such solution is intelligent automation, which holds the promise of transforming the industry landscape and enabling organizations to thrive in this rapidly evolving environment. As banks and financial institutions (FIs) navigate rapidly shifting customer preferences, the imperative to transform is urgent.

Examples abound in industries as different as banking, shipping logistics, or fashion retail. The advantages continue as the machine learning algorithms that drive intelligent automation constantly learn from their data sets, improving or suggesting process design optimizations over time. Intelligent automation systems are designed to help businesses work more efficiently. For example, an intelligent automation process might help a customer get a quick answer from a chatbot without human intervention, or a business partner receive an automated purchase order based on low inventory levels. It does this by enabling a workflow that tracks business data in real time and then uses artificial intelligence to make decisions or recommend best next steps.

In this research, we’ll explore various use cases and case studies of intelligent automation in the financial services industry. ​The UiPath Business Automation Platform empowers your workforce with unprecedented resilience—helping organizations thrive in dynamic economic, regulatory, and social landscapes. During 2023, financial institutions were looking to boost by at least ten percent their investment in a variety of digital services, including mobile banking and asset management applications and online trading.

Reimagining the engagement layer of the AI bank will require a clear strategy on how to engage customers through channels owned by non-bank partners. All of this aims to provide a granular understanding of journeys and enable continuous improvement.10Jennifer Kilian, Hugo Sarrazin, and Hyo Yeon, “Building a design-driven culture,” September 2015, McKinsey.com. Third, banks will need to redesign overall customer experiences and specific journeys for omnichannel interaction. 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.

A number of financial services institutions are already generating value from automation. JPMorgan, for example, is using bots to respond to internal IT requests, including resetting employee passwords. The bots are expected to handle 1.7 million IT access requests at the bank this year, doing the work of 40 full-time employees. And at Fukoku Mutual Life Insurance, a Japanese insurance company, IBM’s Watson Explorer will reportedly do the work of 34 insurance claim workers beginning January 2017. Intelligent automation presents many challenges due to the complexity of the technology and its continuous evolution, and that artificial intelligence is still fairly new as an everyday enterprise software tool. When it comes to implementing intelligent automation, think of the challenges in two main buckets—technical challenges and organizational challenges.

As we celebrate 25 years of the digital revolution in banking, it’s evident that the industry has undergone fundamental transformations. Branches witness significantly reduced foot traffic while the use of cash dwindles amidst the rise of new payment methods. Even mature automation in banking programs that we talked to at the conference are still seeking big returns that have thus far eluded them. They have tested or implemented a tool or two and found limited success, but not yet found a truly valuable solution.

The Newgen low-code platform can help banks develop business applications in only weeks from ideation to deployment instead of months or years. Today, customers want to be met, courted and fulfilled through any organization that wants to establish a relationship with them. They also expect to be consulted, spoken to and befriended in times, places and situations of their choice. Wall Street expects ServiceNow to grow sales at 20% annually over the next five years.

This combination of robotic process automation and artificial intelligence can eliminate tasks that are repetitive yet not entirely predictable, improving a process while allowing employees to focus more on high-value and nuanced work. Robotic Process Automation (RPA) is a rule-based software solution that automates repetitive tasks without any self-learning capabilities. This includes RPA applications in banking where some form of AI, such as computer vision or natural language processing, is a part of the automation workflow.

Despite some early setbacks in the application of robotics and artificial intelligence (AI) to bank processes, the future is bright. 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. The bank also used the intelligent automation platform to expedite its document custody procedures.

Reduce application to approval time on credit cards, mortgages, and loans by automating standardized elements of the process such as validating applicant information and carrying out fraud checks, releasing your people to focus on more complex cases. SS&C Blue Prism enables business leaders of the future to navigate around the roadblocks of ongoing digital transformation in order to truly reshape and evolve how work gets done – for the better. Unlike the digital revolution or the advent of the smartphone, banks won’t be able to cordon off generative AI’s impact on their organization in the early days of change. It touches almost every job in banking—which means that now is the time to use this powerful new tool to build new performance frontiers.

NelsonHall estimates that Capgemini’s intelligent automation services revenues will grow by 22% per year over the next three years. Many bank processes involve unstructured data formats (invoice PDFs, bank statements images, etc.) which machines are incapable of understanding. Businesses can benefit from document capture technologies, such as OCR, that are integrated with RPA, to automate the processing of paper-based forms. RPA can compare data from multiple systems to ensure accuracy and identify discrepancies, thereby streamlining financial reconciliation.

Anti-Money Laundering (AML) regulations, Know Your Customer (KYC) guidelines, GDPR and other regulatory elements demand accurate data to prove compliance. Automation technologies could contribute an additional $US 1 trillion annually in value across the global banking sector – through increased sales, cost reduction and new or unrealized opportunities. For instance, a UK-based bank9 leveraged RPA to automate 10 processes including direct debit cancellation, account closures, CHAPS, payments, foreign payments, audit reports, internet applications, and Card and Pin Pulls. In this case, the audit process was conducted in one minute, versus 6-7 hours manually. Trade finance involves multiple international parties coordinating and ensuring the delivery of goods and payments. Banks and companies communicate through letters of credit (LC), bank guarantees (BG), and other documents that need to be processed.

And enabling platforms enable the enterprise and business platforms to deliver cross-cutting technical functionalities such as cybersecurity and cloud architecture. The emerging set of new technologies that combine fundamental robotic process automation and artificial intelligence is Intelligent Process Automation (IPA). IPA also promises to enhance efficiency and improve turnaround times and customer journey experiences in ways that are not scalable through normal RPA. Banks have begun embracing intelligent automation to digitize and automate their processes, enabling them to deliver services faster, with greater accuracy, and at a lower cost.

What does it mean to automate at scale?

This process could include automating data collection, document verification, and KYC (Know Your Customer) checks. Join experts from TELUS International and Automation Anywhere, a top cloud automation platform, to learn how banks and financial services firms can leverage automation to enhance the customer experience, optimize operations and foster customer loyalty. While they are both used to automate tasks, you can think of intelligent automation as a smarter version of robotic process automation.

• Branches witness significantly reduced foot traffic while the use of cash dwindles amidst the rise of new payment methods.
• Intelligent automation is crucial in driving digital transformation in the banking industry.
• Customers expect an easy omnichannel onboarding experience with zero manual intervention.
• Trade finance involves multiple international parties coordinating and ensuring the delivery of goods and payments.
• The platform helped it seamlessly integrate its own systems with third-party systems for time and cost savings.
• HSBC Holdings is a multinational banking and financial services holding company and is ranked 99th on the Fortune 500 list.

It also liberates your employees from tasks that require monotonous accuracy better suited to software and allows them to focus on providing business value where robots cannot – through personal service with a human touch. Recent advances in natural language processing (NLP) have improved chatbots’ ability to understand customer requests and form naturalistic responses, explains John Murphy, head of intelligent automation at accounting and consultancy provider Grant Thornton. “It is an area where machine learning and AI have made huge leaps and bounds in the last few years,” he says.

The governance challenges that arise from many intelligent automation use cases are similar to those of RPA. At WTW, Stoekel has established a centre of excellence that runs automations developed by business users through a series of governance checks. These include security and other technical controls, privacy impact assessments, and quality measures.

Similarly, if another user often transfers money internationally, the app may adapt to make these services more apparent, optimizing their banking experience. Automation holds the key to revolutionizing front- and back-office operations, driving unprecedented efficiency and enhancing the overall customer experience. Turning to the future, SaaS revenue is projected to increase at 13.7% annually through 2030, and cloud computing revenue is projected to grow at 14.1% annually during the same period.

Peak inquiry volumes combined with time-consuming transactions create a vicious cycle of poor employee and customer experiences. You can foun additiona information about ai customer service and artificial intelligence and NLP. Applying RPA + AI to customer service processes enables elimination of wait-time queues for requests, consistent and auditable monitoring for 100% of customers, and reduced cycle time and effort by up intelligent automation in banking to 80%. Business Process Automation (BPA) provides a unique opportunity to radically transform banking’s administrative burdens for both customers and employees. Repetitive yet critical processes can now be conducted by an ‘always on’ digital workforce at a fraction of the cost, many times the speed and with 100% accuracy.

Also, automate repeatable processes in both the supply chain and around working capital. If you’re interested in and would like to dive into learning about the top intelligent automation trends we have predicted for 2023, please stop by our other informative blogs on intelligent automation. Intelligent automation can mask sensitive information to protect customer privacy and ensure compliance with data protection regulations. IA can help banks manage customer accounts by automating routine tasks such as balance checks, account updates, and account closure requests. For many banks, ensuring adoption of AI technologies across the enterprise is no longer a choice, but a strategic imperative. Envisioning and building the bank’s capabilities holistically across the four layers will be critical to success.

As AI advances, we may expect to see even more inventive applications that improve the efficiency, security and personalization of banking services. IA can also build credit risk models and identify a band of low credit risk for an applicant. Based on this, if the applicant qualifies for a higher loan, organizations can carry out upselling. IA can be integrated with existing banking CRM (Customer Relationship Management) and LOS (Loan Origination System) systems, enabling banks to streamline processes and improve data accuracy. Banks can use intelligent automation to extract data from ID and financial documents, reducing the need for manual data entry. This article will explore the importance of intelligent automation in banking, its applications, benefits, challenges, and future trends.

He graduated from Bogazici University as a computer engineer and holds an MBA from Columbia Business School. Today’s consumers demand fast and efficient digital channels to conduct financial transactions. BAI, a nonprofit that provides research, training and thought leadership in financial services, recently discussed key industry trends with Hyland’s Steve Comer. Steve, Hyland’s assistant vice president of financial services and insurance sales, has more than two decades of experience in financial services.