Amid a quadruple economic whammy – marked by new macroeconomic and political uncertainty, a slowdown in credit demand, rising delinquencies, and high interest rates – we are observing a stronger push towards “cost efficiencies” in banking. Traditionally, banks have responded to similar disruptions by cutting technology and consulting budgets, scaling back new investments, reducing workforce size, pausing hiring, and eliminating high-cost centers such as in-house operations or custom technologies with inflexible fixed costs.
Technology represents a significant cost item for banks, absorbing, on average, more than 10% of revenues, according to a proprietary database from BCG’s Expand Research. In this challenging environment, banks need to explore new frontiers for cost reduction—reimagining operational expenses while also creating open, agile, and flexible systems that help reduce technology expenses. This requires transforming the expense mix from “run the bank” to “change the bank” and redeploying resources rather than simply identifying the least painful areas to trim budgets.
The Four-Pronged Approach to Next-Gen Efficiency
Opportunities to rethink cost efficiency span the banking enterprise, from automating processes and call center operations to streamlining fraud management and embracing cloud transformation. It should come as no surprise that deploying an AI and automation strategy alongside traditional budget reductions can accelerate cost efficiency objectives. However, what may be surprising is that such an approach can also help avoid budget-cut pitfalls, such as reduced productivity and a degraded customer experience.
As banks seek impactful synergies among cost savings, enhanced customer experience, and product innovation, they will discover the most powerful levers in areas such as process transformation, automation, new location and productivity strategies, and technology transformation.
Process Transformation
For the past 20 years, banks have implemented numerous process transformations on top of largely legacy core platforms. While omnichannel approaches, customer self-service capabilities, and decision engines have fostered innovation and helped extract efficiency from the legacy systems, efficiency gains from these standard process transformation levers have largely been exhausted. One emerging lever to help banks uncover additional process improvements is the analysis and redesign based on the extraction of process metrics, using tools such as Celonis.
Gen AI has opened up new horizons for process transformation. While banks have been more comfortable using Gen AI tools for internal use cases—such as agent assistance, knowledge base enhancements, and improvements in middle and back-office processing—these tools are increasingly evolving to support direct customer interactions through chatbots, voice assistants, and authentication. From there, Gen AI will expand to support use cases across the front, middle, and back offices, including virtual banking assistance, know-your-customer (KYC) verification, and underwriting.
Automation
Banks have depended on optical character recognition (OCR) for over 20 years to minimize the need for expensive manual data entry. Recent advancements have brought predictive capabilities to OCR algorithms, enhancing their accuracy more than ever. This increased precision allows OCR to work more smoothly with Agentic AI-based functions such as document summarization, processing, and exception identification. This has bolstered industry confidence that automation and straight-through processing rates are at a turning point.
While some complex products, like home mortgages, may not achieve complete auto-decisioning in the near future, 30‒40% of the home mortgage process is now ready for full automation. On the cost-efficiency front, this means banks can reduce the time spent hiring and training for roles focused on manually correcting inaccurate data capture and instead shift their focus to hiring and retraining for higher-level roles.
Alongside OCR advancements, voice-recognition software has made significant strides. It now holds the potential to reduce costs through call escalation and analysis, as well as by delivering truly automated responses to high-volume customer inquiries.
Location and Productivity
Until recently, European banks were generally more comfortable than their US counterparts with business process outsourcing (BPO). In many cases, US banks’ hesitancy stemmed from concerns about regulatory requirements and the challenges of third-party risk management. However, during the COVID-19 pandemic and the “Great Resignation,” US banks began to shift their stance. The adoption of new digital monitoring tools enabled banks to effectively validate the quality of service they received from outsourced contact centers, whether nearshore or offshore.
With call center attrition at near all-time highs, the most frustrating cost burden for banks is not customer service agent salaries, but rather the expense of maintaining a large HR operation to continuously hire and train new customer service staff in the face of unprecedented churn. To mitigate these costs, a strategy that makes greater use of BPO can prove invaluable.
At the same time, banks have uncovered more compelling product-based BPO opportunities in areas such as fraud and dispute management. Specifically, BPO for fraud management that is enabled by digital platforms often proves to be faster, cheaper, and more accurate, allowing banks to offload the complex task of keeping up with the increasing volume and variety of digital fraud schemes.
Technology Transformation
When it comes to technology transformation, cloud migration is the future of banking. Compared to many other industries, banks have been relatively conservative in adopting cloud technologies. However, recent interest rate hikes and the subsequent decline in loan volumes have prompted banks to reevaluate their investments in costly data centers, which incur high fixed costs (both for technology and personnel) regardless of processing volumes. In contrast, cloud spending is variable and can scale up or down quickly as processing volumes change, offering significant cost savings during periods of low activity.
Fortunately, cloud adoption offers more than just cost savings; it also enables greater agility and developer velocity. For instance, in a traditional mainframe-based environment, building a new capability such as a contact center chat function involves a lengthy process of RFPs, requisitions, infrastructure setup, and sourcing a team, along with large, dedicated operations and technology teams to support the chat servers. In contrast, a cloud-based solution can deliver a functional chat program within weeks, meeting significant customer service needs.
As banks aim to be more product-driven, cloud adoption provides a means to align cost reduction with faster product innovation. In their cloud journeys, banks are also growing more comfortable with open-source software, motivated by the rationalization of software license costs and the availability of innovative capabilities.
Integrated Cost Efficiency: The New Imperative
Like every commercial sector today, banks face immense pressure to drive cost efficiencies. As they pursue greater efficiency, they must achieve their strategic cost reduction goals while also enhancing the customer experience — a critical differentiator in today’s hyper-competitive market. Additionally, they must ensure that their cost reduction strategies do not hinder future growth potential. An integrated approach to cost reduction emphasizes transforming the bank rather than merely performing the same tasks with fewer resources. This entails lowering technology costs and making operations more agile so that banks are prepared to seize new opportunities when the winds of change shift.