Automation in Banking and Finance AI and Robotic Process Automation

A practical way to get started is to evaluate how the bank’s strategic goals (e.g., growth, profitability, customer engagement, innovation) can be materially enabled by the range of AI technologies—and dovetailing AI goals with the strategic goals of the bank. Once this alignment is in place, bank leaders should conduct a comprehensive diagnostic of the bank’s starting position across the four layers, to identify areas that need key shifts, additional investments and new talent. They can then translate these insights into a transformation roadmap that spans business, technology, and analytics teams. Each layer has a unique role to play—under-investment in a single layer creates a weak link that can cripple the entire enterprise.

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. Furthermore, depending on their market position, size, and aspirations, banks need not build all capabilities themselves. They might elect to keep differentiating core capabilities in-house and acquire non-differentiating capabilities from technology vendors and partners, including AI specialists. 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.

Intelligent Automation in Banking

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. One of the benefits of intelligent automation is that the machine learning algorithms should continue to improve. Getting the most out of any intelligent automation requires a process of constant feedback and iteration. Intelligent automation streamlines processes that were otherwise composed of manual tasks or based on legacy systems, which can be resource-intensive, costly and prone to human error. The applications of IA span across industries, providing efficiencies in different areas of the business.

Intelligent automation is being used in nearly every industry, including insurance, investing, healthcare, logistics, and manufacturing. The application of intelligent automation is growing in pace with the surging capabilities of artificial intelligence. This integration leads to a transformative solution that streamlines processes and simplifies workflows to ultimately improve the customer experience. Many, if not most, organizations begin their automation journey with a goal of cost savings, often trying to reduce headcount with very clean ROI calculations. Many early-stage organizations at this conference seemed destined to follow the same path.

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Coupled with the increased customer demand for self-service, enterprises are still investing heavily in external communication channels such as chatbots. For each use case, we further discuss the business challenge said technology solves, the data being leveraged in the process, and the distinct benefit that AI applies to the operations therein. If would like to learn more about how automation can accelerate your bank’s transformation efforts, download our free ebook, The Essential Guide to Modernizing Banking Operations. Intelligent Automation can reduce turnaround times from days or weeks to minutes by integrating all stages of the process.

The pervasive reach of generative AI means it won’t exclusively or even primarily be a cost-saving technology, in banking its most important contribution will be to drive growth. Accenture’s analysis of the potential use of the technology across different banking roles suggests this is only the beginning. Bots have been used to find all the customer accounts’ year-end balances, and then return the audit to the audit clerk in the form of a Word document. This can speed up the task duration of an audit from several days to a couple of minutes. Business process management (BPM) is best defined as a business activity characterized by methodologies and a well-defined procedure. Make it a priority for your institution to work smarter, and eliminate the silos suffocating every department.

Glass combines market data and bank models, utilizing machine learning techniques to identify industry trends and predict client demands. This not only helps to provide individualized investment advice but also can position the bank as a pioneer in using AI for strategic financial insights. IA can improve the customer experience by anticipating needs and boosting productivity even as financial services organizations increasingly rely on remote workforces. While intelligent automation offers numerous benefits for banking and financial services brands, unlocking its true potential requires careful and strategic implementation within an organization. With these six building blocks in place, banks can evaluate the potential value in each business and function, from capital markets and retail banking to finance, HR, and operations.

Hyperautomation in Banking: Use Cases & Best Practices

Intelligent automation can improve customer experience by providing faster response times and personalized services. Banking’s digital transformation is being driven by intelligent automation (IA), which taps artificial intelligence (AI), machine learning and other electronic processes to build robust and efficient workflows. IA can deliver information, reduce costs, improve speed, enhance accuracy and remove bottlenecks with fewer human touchpoints. These tasks might include handling a customer service interaction using a chatbot that can understand intent and deliver answers using a natural language generator or successfully guiding a document through the many handoffs of an insurance claim. Both tasks are assisted by an AI model that’s trained on vast amounts data to make decisions and recommendations.

This included how banks stipulated interest rates for lending, identified creditworthy cohorts and facilitated banking transactions. Total revenue increased 26% to $2.4 billion and non-GAAP net income jumped 36% to $3.11 per diluted share. In addition, remaining performance obligation — contracted revenue that has not yet been recognized — increased 29%, signaling strong top-line momentum in the coming quarters.

Nevertheless, the risks identified by Accenture underscore the need to hold suppliers to account for cybersecurity. “A SolarWinds-type hack on [RPA suppliers] UIPath or Automation Anywhere would be devastating,” says WTW’s Stoeckel. Happily, he says, RPA vendors are “starting to put significant investment into the security layer”. IA  can detect and prevent fraud by creating a baseline safe zone for specific application data and flagging patterns outside that safe zone. The following paragraphs explore some of the changes banks will need to undertake in each layer of this capability stack. Hyland connects your content and systems so you can forge stronger connections with the people who matter most.

One of the ways in which the banking sector is meeting this ask is by adopting new technologies, especially those that enable intelligent automation (IA). According to a 2019 report, nearly 85% of banks have already adopted intelligent automation to expedite several core functions. Microsoft is well known for its Windows operating system, Office productivity software, SQL database, Azure cloud computing services, and Xbox hardware and gaming content. Indeed, the company enjoys a strong presence in each of those product categories, but its most compelling growth prospects lie in enterprise software and cloud computing. Founded in 1993, The Motley Fool is a financial services company dedicated to making the world smarter, happier, and richer.

Banking, inherently a business of digital transactions and trust, stands to reap unparalleled benefits from AI adoption. While AI won’t alter banking’s core functions, it promises to revolutionize its operational landscape. Automation is about work being done more quickly and efficiently; implementing automation should be, too. Conference attendees are looking for value in the near-term, which aligns to WorkFusion’s supreme focus of time-to-value with pre-trained bots, even on AI-focused use cases that can be in production within weeks. While the challenge for the desk team was to answer these repetitive questions, the opportunity for the company was to automate with an AI-based chatbot that could help get suppliers’ questions answered faster.

Leading consumer internet companies with offline-to-online business models have reshaped customer expectations on this dimension. Some banks are pushing ahead in the design of omnichannel journeys, but most will need to catch up. Leveraging intelligent automation can enable better loan decisions, boost operational efficiency, and improve the customer experience.

Leading South African financial services group Old Mutual integrated multiple systems into one platform to provide employees with a holistic view of both customers and services available. This helped them to onboard customers 10x faster and provide 9x shorter queues in branch, plus an uplift in sales from service. intelligent automation in banking Create flexible capacity by augmenting your team with an RPA digital workforce to support high demand for mortgage loan refinancing. Meet client service level expectations and remain 100% compliant with regulatory requirements, such as dispositioning all new mortgage applications within 5 business days.

Another example might be a shipping or manufacturing process that uses computer vision to accurately identify objects and help workers make quick decisions on the fly. It’s an AI-driven solution that helps you automate more business and IT processes at scale with the ease and speed of traditional RPA. IBM Consulting’s extreme automation consulting services enable enterprises to move beyond simple task automations to handling high-profile, customer-facing and revenue-producing processes with built-in adoption and scale. Middle managers will need to shift their focus on the more human elements of their job to sustain motivation within the workforce. Automation will expose skills gaps within the workforce and employees will need to adapt to their continuously changing work environments.

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Although intelligent automation is enabling banks to redefine how they work, it has also raised challenges regarding protection of both consumer interests and the stability of the financial system. This article presents a case study on Deutsche Bank’s successful implementation of intelligent automation and also discusses the ethical responsibilities and challenges related to automation and employment. We demonstrate how Deutsche Bank successfully automated Adverse Media Screening (AMS), accelerating compliance, increasing adverse media search coverage and drastically reducing false positives. This research contributes to the academic literature on the topic of banking intelligent automation and provides insight into implementation and development. Intelligent automation can improve a business process by letting automation take on tasks such as data entry, document processing, and increasingly complex customer service responses.

Use AI to reliably improve efficiency, accuracy and the speed of document processing. Embracing these best practices will enable financial services brands to stay ahead of the curve and succeed in delivering excellence to their valued customers. Business and technology leaders in banks and FIs have had their eyes on these digital transformation priorities. However, a robust strategy around reliable, all-encompassing solutions is often elusive.

Riya covers B2B applications of machine learning for Emerj – across North America and the EU. She has previously worked with the Times of India Group, and as a journalist covering data analytics and AI. Intelligent Automation can deal with the routine elements such as checking for available funds swiftly and efficiently, only invoking human intervention for checking and compliance.

In today’s banks, the value of automation might be the only thing that isn’t transitory. The language of the paper have benefited from the academic editing services supplied by Eric Francis to improve the grammar and readability. Nitin Rakesh, a distinguished leader in the IT services industry, is the Chief Executive Officer and Director of Mphasis.

For regular cases, RPA bots can speed up processing times, improve security and compliance, and reduce error rates for these customer-facing processes. Arguably the most sophisticated applications of intelligent automation seek to replace human decision making with AI. Although, banks ready to utilize intelligent automation – which includes AI and robotic process automation – should seek areas that would stand to gain the most benefits in terms of enhancing their digital transformation and workflow efficiencies. Not to mention, many banks struggle to determine which technologies should be prioritized to get the most out of their investments and which ones can align best with their business objectives. In 2020, most consumers and banking institutions are generally familiar with artificial intelligence driving intelligent automation in banking. Today, many organizations are taking the conversations to the next level and deploying AI-based technologies company wide.

From customer onboarding and loan processing, the way banks operate provides unprecedented levels of efficiency, speed, and agility. Exhibit 3 illustrates how such a bank could engage a retail customer throughout the day. Exhibit 4 shows an example of the banking experience of a small-business owner or the treasurer of a medium-size enterprise. By combining automation solutions, such as RPA, with AI technologies such as machine learning, NLP, OCR, or computer vision, financial services companies can move from automating specific tasks to end-to-end processes. Using intelligent automation, an organization can increase productivity and efficiency, improve the customer experience, lower costs, and make better decisions faster.

Intelligent bots can monitor regulatory announcements for upcoming changes and compare notifications to display what has changed. This reduces the time spent on tracking regulations and decreases the possibility of fines due to manual errors. Automation helps banks streamline treasury operations by increasing productivity for front office traders, enabling better risk management, and improving customer experience.

With RPA and automation, faster trade processing – paired with higher bookings accuracy – allows analysts to devote more attention to clients and markets. Discover smarter self-service customer journeys, and equip contact center agents with data that dramatically lowers average handling times. Reach out to our team of automation experts to see how we can help create a customized intelligent automation solution that will transform your organization and help you stay ahead in today’s dynamic marketplace.

• IPA also promises to enhance efficiency and improve turnaround times and customer journey experiences in ways that are not scalable through normal RPA.
• Another example might be a shipping or manufacturing process that uses computer vision to accurately identify objects and help workers make quick decisions on the fly.
• Banking organizations are constantly competing not just for customers but for highly skilled individuals to fill their job vacancies.
• UiPath claims its Document Understanding platform delivers IPA to extract and interpret data from different documents.
• The bank combines prescriptive business rules with predictive data modelling to assess applicants’ eligibility for credit, Combs says.

The company also achieved a renewal rate of 99% in the fourth quarter, up from 98% in the previous year, signaling a high degree of customer satisfaction. The report also claims SAP’s platform also provided better services for suppliers, and the chatbot was available to answer invoice queries 24 hours a day. You can foun additiona information about ai customer service and artificial intelligence and NLP. These capabilities allowed staff to focus on more-specific, nonstandard questions during the COVID-19 lockdown as inquiries surged. Manual invoice processing may involve several steps, such as data entry, approvals, and validation, each requiring significant time. Alter Domus leveraged intelligent automation with UiPath solutions, including Document Understanding, AI Fabric and UiPath Orchestrator. The company claims its Automation Hub software helps companies centrally manage automation opportunities, increase automation programs’ ROI by better-prioritizing automation ideas and broaden the availability of automation.

In response, the company adopted an intelligent document processing-based system to increase employee efficiency and enable them to concentrate on more critical and value-adding activities. Capgemini is a global business and technology transformation partner, helping organizations to accelerate their dual transition to a digital and sustainable world, while creating tangible impact for enterprises and society. It is a responsible and diverse group of 340,000 team members in more than 50 countries. With its strong over 55-year heritage, Capgemini is trusted by its clients to unlock the value of technology to address the entire breadth of their business needs.

Few technologies have moved from theoretical potential to game-changing impact as quickly as generative AI. In cases where legacy systems are not capable of storing complex limit orders, RPA bots could step in to help. However, this is more of band-aid remediation, as in the long run, moving to a sophisticated and capable trading system would be a prudent investment, given how it could improve trading and reduce the load of traders. Studies show that banks are spending an average of $60 million annually on KYC compliance. And that 89% of corporate treasurers have had a bad experience with the KYC process, leading 13% of them to change banks.

Consider, for example, the laborious paperwork that is typically required to refinance homes. ServiceNow is a recognized leader in several relevant software categories, including enterprise service management, digital process automation, and low-code application development platforms for professional developers. In addition, the company placed No. 19 on the Future 50 list in 2023, an annual report compiled by Fortune and Boston Consulting Group that ranks the world’s largest companies based on future growth prospects. Meanwhile, Microsoft is gaining market share in cloud computing due in part to strength in artificial intelligence infrastructure and machine learning services. Microsoft Azure accounted for 24% of cloud infrastructure and platform services spending in the fourth quarter, up two percentage points from the prior year.

Firms that understand and implement IA in time can be certain of sustained success, while those that haven’t must choose relevant automation tools to help them stay ahead of evolving customer expectations. For its unattended intelligent automation, the bank deployed a learning automation platform. The platform helped it seamlessly integrate its own systems with third-party systems for time and cost savings. The bank’s teams used the platform’s cognitive automation technology to perform several tasks quickly and effortlessly, including halving the time it used to take to screen clients as a part of the bank’s know-your-customer process. The main tools involved in intelligent automation are business process automation software, operational data, and AI services.