Banking Business Process Outsourcing BPO Services

Employees will inevitably require additional training, and some will need to be redeployed elsewhere. Lenders rely on banking automation to increase efficiency throughout the process, automation in banking operations including loan origination and task assignment. Traditional software programs often include several limitations, making it difficult to scale and adapt as the business grows.

Keeping customers happy throughout a transformation process can also be a tricky maneuver. When building these new systems, it’s critical to have clearly defined metrics and a way to understand outcomes and receive customer feedback. All of this starts with the design process and the recognition that customer expectations are informed by all digital experiences, not only the ones in banking. While this research is not specific to financial services, it underscores the value of automation and makes evident its applicability for banking. This leaves limited time and resources for higher-value activities, such as innovation, relationship-building and analysis.

Banking operations fit for the future

A global bank reinvented its auto loans process–boosting car loan sales by 50% and cutting total costs. A European bank used automation, analytics and top talent to cut operating costs by 20-30%—freeing up resources to reinvest. Automation is key to survival in a hyper-competitive market and increasing customer and employee satisfaction levels. However, throwing AI at an individual problem or experimenting with automation on the side is no longer sufficient. Indeed, as banks attempt to put customer needs at the center of their strategies while simultaneously doing away with human jobs, they create a paradox inside their own ecosystem.

The following paragraphs explore some of the changes banks will need to undertake in each layer of this capability stack. Deloitte refers to one or more of Deloitte Touche Tohmatsu Limited, a UK private company limited by guarantee (“DTTL”), its network of member firms, and their related entities. DTTL and each of its member firms are legally separate and independent entities. DTTL (also referred to as “Deloitte Global”) does not provide services to clients. In the United States, Deloitte refers to one or more of the US member firms of DTTL, their related entities that operate using the “Deloitte” name in the United States and their respective affiliates.

Four obstacles to change

Robotic process automation, or RPA, is a technology that performs actions generally performed by humans manually or with digital tools. Many, if not all banks and credit unions, have introduced some form of automation into their operations. According to McKinsey, the potential value of AI and analytics for global banking could reach as high as $1 trillion. Another European bank launched a strategic initiative to shrink its cost base and increase competitiveness through superior customer service. Upon completion of the first successful pilots, the bank’s automation program consisted of three phases.

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. 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. These gains in operational performance will flow from broad application of traditional and leading-edge AI technologies, such as machine learning and facial recognition, to analyze large and complex reserves of customer data in (near) real time. 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.

Intelligent Finance Operations

Automating repetitive tasks enabled Credigy to continue growing its business at a 15%+ compound annual growth rate. Check our article on back-office automation for a more comprehensive account. Automated invoicing and responsive customer service helped one bank cut costs by 50%. The future will look very different for banks and their customers in 2030. Banks have a unique opportunity to lay the groundwork now to provide personalized, distinctive, and advice-focused value to customers. Instead of waiting on hold or being pinballed between different representatives, customers could get instant, efficient automated customer service powered by advanced AI.

Additionally, banks will need to augment homegrown AI models, with fast-evolving capabilities (e.g., natural-language processing, computer-vision techniques, AI agents and bots, augmented or virtual reality) in their core business processes. Many of these leading-edge capabilities have the potential to bring a paradigm shift in customer experience and/or operational efficiency. Faced with these challenges, few banks have had the appetite for reengineering their operations-related IT systems. Given the relatively strong growth banks experienced before the recession, most did not have to change their business processes. Now, however, the new economics of banking requires much lower back-office costs. And with regulators and consumers pressuring banks for greater transparency, better credit and portfolio risk management, and heavily expedited data processing for customer accounts, bank leaders are realizing they must take a different approach.

Benefits of Automation in Banking

This reduces employee workload and enables them to focus on the customers that will generate profit. 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.

It managed to reduce costs through productivity gains by 35 percent and saw a 40 percent lift in its net promoter score. After pursuing the customer journey-led transformation, the bank embarked on a center-led transformation—systematically transforming each operations center. This effort is targeting a further 25 percent savings in small processes (e.g., RPA to automate account closure, optical character recognition and RPA to reduce manual rekeying for incoming mail). 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. Among the obstacles hampering banks’ efforts, the most common is the lack of a clear strategy for AI.6Michael Chui, Sankalp Malhotra, “AI adoption advances, but foundational barriers remain,” November 2018, McKinsey.com.

AI-bank of the future: Can banks meet the AI challenge?

Two additional challenges for many banks are, first, a weak core technology and data backbone and, second, an outmoded operating model and talent strategy. By bringing everything together and connecting loose ends, automation enables the banking sector to deliver the cost-saving that it needs, while simultaneously delivering value to customers. 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.

These time-sensitive applications are greatly enhanced by the speed at which the automated processes occur for heightened detection and responsiveness to threats. Increasing customer expectations, stringent regulations and heightened competition are making it more important than ever for banks to optimize and modernize their operations. Automation is helping banks worldwide adapt to organizational and economic changes to reduce risk and deliver innovative customer experiences. 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.

Intelligent finance operations

It’s how they can flex fast to respond to volatility and lay the foundation for a more sustainable, resilient business. We use SynOps, a unique human + machine platform, to combine intelligent technologies, data, analytics, talent and cloud with proprietary tools and assets to transform operations. Reimagine Banking Operations is how banks can stay a step ahead of change and deliver sustainable growth.

• Implementing RPA can help improve employee satisfaction and productivity by eliminating the need to work on repetitive tasks.
• Rather, banks need a unified, organization-wide strategy that accounts for internal and external communication, workflow issues, business strategy, security, design practices and the realities of a world disrupted by Covid-19.
• New technologies and ways of working help banks transform their operations, offering human-like digital experiences while improving cost & compliance.
• This holds true particularly in areas such as artificial intelligence (AI), analytics and automation, each of which would complement banking’s strong data capabilities.
• 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.
• A global bank reinvented its auto loans process–boosting car loan sales by 50% and cutting total costs.

Effective balance sheet merging involves decisions on retaining, restructuring or selling parts of the loan portfolio. Timesheets, vacation requests, training, new employee onboarding, and many HR processes are now commonly automated with banking scripts, algorithms, and applications. 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. Customers expect fast, personalized experiences from onboarding to any future interactions they have with the bank. Having access to customer information at the right point in an interaction allows employees to better serve customers by providing a positive experience and promoting loyalty, ultimately giving them a competitive edge. Orchestrating technologies such as AI (Artificial Intelligence), IDP (Intelligent Document Processing), and RPA (Robotic Process Automation) speeds up operations across departments.

Automation can help improve employee satisfaction levels by allowing them to focus on their core duties. But after verification, you also need to store these records in a database and link them with a new customer account. Cybersecurity is expensive but is also the #1 risk for global banks according to EY. The survey found that cyber controls are the top priority for boosting operation resilience according to 65% of Chief Risk Officers (CROs) who responded to the survey.

But in a world marked by financial and economic woes, banks need to find faster, more economical, and lower-risk approaches to reducing costs and improving customer service. Fortunately, the market for integration support solutions and alternative IT-development approaches has become more reliable over the past ten years, unlocking the key to rapid, large-scale automation of business processes. Banking automation has become one of the most accessible and affordable ways to simplify backend processes such as document processing.