Amid an economic triple-whammy of new credit demand slowdown, increased delinquencies, and interest rate shock, we’ve entered a “cost takeout” era in banking. Banks traditionally respond to similar disruptions by cutting budgets for technology and consulting, scaling back on new investments, reducing workforces, pausing hiring, and eliminating high-cost centers such as in-house operations or custom technology with inflexible fixed costs.
The cost of technology typically accounts for 12‒15% of a bank’s revenue; the cost of operations is closer to 30% or even 40%. In this fraught environment, banks need to explore a new frontier for cost reductions that reimagines operational expenses while also creating open, agile and flexible systems that reduce technology expenses. This requires transforming the expense mix from “run the bank” to “change the bank” and redeploying resources rather than simply finding the least-painful areas to trim budgets.
The Four-Pronged Approach to Next-Gen Cost Takeout
Opportunities to re-think cost takeout span the banking enterprise, from automating lending processes and call center operations to streamlining fraud management and embracing cloud transformation. It should surprise no one to hear that deploying an AI and automation strategy alongside traditional budget reductions can help accelerate cost takeout objectives. What may be surprising is to learn that such an approach can also help avoid the budget-cut pitfalls of reduced productivity and a degraded customer experience.
As they pursue impactful synergies between cost savings, improved customer experience, and product innovation, banks will find the most powerful levers in the areas of process transformation, automation, new location and productivity approaches, and technology transformation.
For the past 20 years, banks have instituted numerous process transformations on top of largely legacy core platforms. While omni-channel approaches, customer self-service capabilities and decision engines have allowed them to innovate and squeeze efficiency out of 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 process metrics extraction-based analysis and redesign using tools such as Celonis.
Generative AI is opening further process-transformation horizons. Some banks have been more comfortable using generative AI tools for internal use cases (for example: agent assistance), but these tools will increasingly evolve to support direct customer interactions through chatbots, voice assistance, and authentication. From there, generative AI will expand to support use cases across the front, middle, and back offices, including employee education and training, virtual banking assistance, know-your-customer (KYC) verification, and even underwriting.
Banks have been relying on optical character recognition (OCR) for more than 20 years to reduce the need for costly manual data entry. Recent advances have bought predictive capabilities to OCR algorithms, making OCR more accurate than ever. This increased accuracy allows OCR to work more seamlessly with robotic process automation (RPA) and is solidifying industry confidence that automation and straight-through processing rates are at an inflection point. While some complex products, like home mortgages, will not be subject to complete auto-decisioning any time soon, 30‒40% of the home mortgage process is now ripe for complete automation. On the cost-takeout front, this means banks will spend less time hiring and training for roles that involve manually correcting inaccurate data capture and can instead focus on hiring and retraining for higher-level jobs.
In parallel to OCR improvements, voice-recognition software has reached new heights and will be able to advance cost takeout insofar as it can be used not just for call escalation and analysis, but also to provide truly automated responses to high-volume customer inquiries.
Location and Productivity
Until recently, European banks tended to be more comfortable than US banks when it came to business process outsourcing (BPO). In many cases, this hesitancy among US banks stemmed from concern about regulatory requirements and third-party risk management burdens. However, as they battled relentless attrition during COVID and the “great resignation,” US banks changed their tune. It helped that new digital monitoring tools gave banks confidence that they could validate the quality of service they received from outsourced contact centers (whether nearshore or offshore).
With call center attrition near all-time highs, the most frustrating cost burden on banks is not so much customer service agent salaries themselves as it is the cost of maintaining an HR operation big enough to constantly hire and train new customer service talent amid unprecedented churn. To mitigate these costs, a strategy that creates significant space for BPO can be a lifesaver.
At the same time, banks have found more interesting product-based BPO propositions in areas like fraud and dispute management. Particularly in the case of fraud management, a digital platform-enabled BPO approach often ends up being faster, cheaper, and more accurate, and banks can absolve themselves of the difficult task of staying on top of the accelerating volume and variety of digital fraud schemes.
When it comes to technology transformation, cloud migration is the wave of the future in banking. Compared to many other industries, banks have been conservative about jumping into cloud. But recent interest rate hikes and resulting drops in loan volumes have banks seriously re-thinking their investments in expensive data centers, which carry high fixed costs (both technology and people) regardless of processing volumes. Cloud spends, by contrast, are variable and can rapidly scale up or down as processing volumes shift, offering massive cost savings during periods of low activity.
Fortunately, cloud is about much more than cost savings. It is also about agility and developer velocity. For example, in a traditional mainframe-based world, building a new capability like a contact center chat function requires a lengthy process of RFPs, requisitions, infrastructure builds, and sourcing team involvement, not to mention large and dedicated operations and technology teams to support the chat servers. A cloud-based solution, on the other hand, can in a matter of weeks be running a functional chat program that supports most major customer support themes. As banks strive to be ever-more product-driven, cloud adoption is one way to ensure that cost takeout is compatible with accelerated product innovation. In conjunction with their cloud journeys, banks are also finally becoming more comfortable with open-source software with software license cost rationalization and new capabilities pushing the banks towards open source.
Integrated Cost Takeout: The New Imperative
Like every commercial sector today, banks are under incredible pressure to cut costs. As they look for ways to find further efficiency gains, banks need to achieve their strategic cost takeout objectives while also improving the customer experience — a critical differentiator in this hyper-competitive market. Plus, they need to ensure that their cost takeout strategies don’t choke any future potential for growth. An integrated approach to cost takeout focuses on changing the bank rather than just doing the same things with fewer resources. That means reducing technology costs, yes, but also boldly transforming operations to be more agile, so that banks are prepared to seize new opportunities when the winds of change shift.