Automation in the banking industry QuickLook blog Deloitte US

Deliver hyper-relevant contact center experiences to customers, anytime and anywhere. Safeguard financial health by transforming principal accounting processes to optimize business performance and make better decisions. Support growth and control costs by transforming operations without changing legacy systems. Organizations that achieve a high level of maturity become “future-ready.” automation in banking operations They are fully focused on digital transformation (i.e. Digital Focused) and gain the agility and resilience needed to thrive amid uncertainty. They also—probably as a result—realize higher market valuations and derive more profit. This means the careful implementation of multiple automation approaches, from integrating basic robots to the full digitization of processes and systems.

In another example, the Australia and New Zealand Banking Group deployed robotic process automation (RPA) at scale and is now seeing annual cost savings of over 30 percent in certain functions. In addition, over 40 processes have been automated, enabling staff to focus on higher-value and more rewarding tasks. Leading applications include full automation of the mortgage payments process and of the semi-annual audit report, with data pulled from over a dozen systems. Barclays introduced RPA across a range of processes, such as accounts receivable and fraudulent account closure, reducing its bad-debt provisions by approximately $225 million per annum and saving over 120 FTEs. A major European bank followed this “recipe” to transform its top 15 end-to-end processes using a customer journey-led approach.

The Automation Advantage in Retail Banking

To compete successfully and thrive, incumbent banks must become “AI-first” institutions, adopting AI technologies as the foundation for new value propositions and distinctive customer experiences. No one knows what the future of banking automation holds, but we can make some general guesses. 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.

For example, Credigy, a multinational financial organization, has an extensive due diligence process for consumer loans. Implementing RPA can help improve employee satisfaction and productivity by eliminating the need to work on repetitive tasks. Banks are already using generative AI for financial reporting analysis & insight generation.

Challenges Faced by Banks Today

The integration of automation in M&As is a clear indicator of a bank’s readiness to embrace change and lead in a transformed banking world. Such platforms offer enhanced data analytics, providing clear insights into the merged loan portfolios. This facilitates informed decisions regarding asset allocation, risk management and strategic planning. It’s a critical process during the post-merger integration phase, where aligning financial strategies and objectives of the combined entity is essential. InfoSec professionals regularly adopt banking automation to manage security issues with minimal manual processing.

When combined with classic Six Sigma rigor and data-driven design thinking, and capitalizing on strategic managed-services relationships, these engines can help banks achieve compressed transformation. This will enable them to deliver more personalized and relevant customer and employee experiences while dramatically improving cost and compliance. Changes of this magnitude often disconnect revenue growth from expense, increasing margins and expanding the art of the possible in banking. To enable at-scale development of decision models, banks need to make the development process repeatable and thus capable of delivering solutions effectively and on-time.

Voices of Change

We integrate these systems (and your existing systems) to allow frictionless data exchange. Using traditional methods (like RPA) for fraud detection requires creating manual rules. But given the high volume of complex data in banking, you’ll need ML systems for fraud detection. You’ll have to spend little to no time performing or monitoring the process.

• And with technology fundamentally changing the financial and consumer ecosystems, there has never been a better time to take the next step in digital acceleration.
• These additional services include travel insurance, foreign cash orders, prepaid credit cards, gold and silver purchases, and global money transfers.
• In this article, we’ll explore why the banking industry needs hyperautomation, its use cases, and how banks can get started with their hyperautomation journey.
• Keeping customers happy throughout a transformation process can also be a tricky maneuver.
• However, banking automation can extend well beyond these processes, improving compliance, security, and relationships with customers and employees throughout the organization.
• Maximize day-one readiness, decrease average handling time and reduce rework.

We live in a digital age and hence, no institution of the global economy can be immune from automation and the advent of digital means of operations. In fact, banks and financial institutions were among the first adopters of automation considering the humongous benefits that they get from embracing IT. 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.

In the event of an M&A, if a bank’s loan trading desk is managing loans manually, using spreadsheets and traditional methods, the integration process can become cumbersome and error-prone. An automated approach to loan participation and syndication management can streamline this process significantly. During M&As, banks need to scrutinize and harmonize their loan portfolios. This process is crucial in identifying loans that may not align with the acquiring bank’s balance sheet strategies, such as those overly concentrated by borrower, geography or asset class.

According to a 2019 report, nearly 85% of banks have already adopted intelligent automation to expedite several core functions. As a result, it’s not enough for banks to only be available when and where customers require these organizations. Banks also need to ensure data safety, customized solutions and the intimacy and satisfaction of an in-person meeting on every channel online. Connect with top banks, financial services, and insurance firms at Forward VI. As RPA and other automation software improve business processes, job roles will change. As a result, companies must monitor and adjust workflows and job descriptions.

Compliance as a Service

Automation is the focus of intense interest in the global banking industry. Many banks are rushing to deploy the latest automation technologies in the hope of delivering the next wave of productivity, cost savings, and improvement in customer experiences. While the results have been mixed thus far, McKinsey expects that early growing pains will ultimately give way to a transformation of banking, with outsized gains for the institutions that master the new capabilities. Banks’ traditional operating models further impede their efforts to meet the need for continuous innovation.

Increase accuracy, speed to approval and customer satisfaction, while reducing credit and operating costs and minimizing risk. 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. Our team deploys technologies like RPA, AI, and ML to automate your processes.

Makes Processes Scalable

Employing IDP to extract and process data faster and with greater accuracy saves employees from having to do so manually. Over several decades, banks have continually adapted the latest technology innovations to redefine how customers interact with them. Banks introduced ATMs in the 1960s and electronic, card-based payments in the ’70s. The 2000s saw broad adoption of 24/7 online banking, followed by the spread of mobile-based “banking on the go” in the 2010s. 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. Top industry analysts believe Accenture’s innovation-led approach will help banks reimagine the role of banking operations.

To get the most from your banking automation, start with a detailed plan, adopt simple-but-adequate user-friendly technology, and take the time to assess the results. In the right hands, automation technology can be the most affordable but beneficial investment you ever make. Automation enables banks to respond quickly to changes in the market such as new regulations and new competition. The ability to make changes at speed also facilitates faster delivery of innovative new products and services that give them an edge over their competitors.

These highly paid individuals will focus on innovation and on developing technological approaches to improving in customer experience. They will also have deep knowledge of a bank’s systems and possess the empathy and communication skills needed to manage exceptions and offer “white glove” service to customers with complex problems. Operations staff will have a very different set of tasks and thus will need different skills. Instead of processing transactions or compiling data, they will use technology to advise clients on the best financial options and products, do creative problem solving, and develop new products and services to enhance the customer experience.

Author: telegramsamvad