Four Ways Data Will Define Banks’ Digital Trajectories

Digital transformation has become a top priority for banks in recent years as they've looked to capitalize on new streams of revenue, customer experiences and market expansion.

As part of this, over 90% of banks have started the process of moving away from legacy systems to more flexible and modern cloud-based infrastructures. With these projects now well underway, banks need to quickly demonstrate value as they work to recap initial investments in digitization. 

Fortunately, banks already have everything they need to do so. With digital infrastructures in place, banks are in the unique position to leverage their decades of data around historical customer trends, market movements, product performance and more in a previously inaccessible way. Not to mention, this depth of data is one of banks main competitive advantages over digital newcomers that don’t have anywhere near the same history.

As banks enter into the next phase of their digital futures, here are four main ways that data will define their success.

Introduce a never-before-seen level of efficiency in the financial industry

Banks are in the age of automation—meaning that there are more ways than ever before to do more with less. Optimizing how they access and analyze data is central to banks’ ability to turn previously manual tasks into new efficiencies.

For example, the near-limitless capacity and extreme computing power offered by cloud environments enables banks to combine real-time insights with their massive amounts of historical data to power better decision making across everything from product development to staffing, future roadmap planning and more. Using these holistic insights, banks can more efficiently target their resources to the initiatives that are projected to have the biggest impact on their bottom line.

Digital infrastructures are also breaking down the data silos that have historically made it difficult for banks to access and process data for decision making that spans the entire organization. Whereas it used to take organizations several days to process a data request, and then check the data for accuracy when pulling data from multiple on-premise systems, modern systems can complete this same process instantaneously.

As a result, organizations will spend significantly less time querying data and more time on the actual decision-making processes that leads to revenue. 

Accelerate banks’ ability to launch new customer-facing offerings

Banks are looking to integrate new offerings at a rapid rate in response to a combination of rising consumer demands, internal business needs and shifting industry regulations. On the consumer side, for instance, banking customers have made it clear that they want hyper-personalized experiences from their financial providers. Yet, our research shows that only 27% of consumers feel that their bank offers them services suited to their personal financial situations.

The challenge with this isn’t that banks don’t have the information they need to create personalized offerings. Rather, they have so much data about each of their customer’s financial histories and preferences, but their legacy operations have stood in the way of their ability to put it to work in an efficient way. 

This is now changing as banks bring more of their systems into the digital era. With a full understanding of their customers’ finances in one place, banks will be able to quickly roll out new offerings that provide customers the level of personalized financial advice they expect.

Market expectations are changing on the regulatory front as well. For example, with Europe’s Payment Services Directive 3 (PSD3) set to go into effect in 2026, many institutions are already working to ensure that their instant payments offerings are in compliance with the new regulations so that they’re not left scrambling a few months out. In these situations, data can enhance banks’ product roll out strategy by providing insights around when and how to launch their new offerings, while setting realistic success metrics. 

Positioning banks at the center of their customers’ lives

Banks are already privy to some of the biggest moments in consumers’ lives—from homebuying to saving for college to cashing out their retirement savings. This unique vantage point and the data it brings provides banks with an opportunity to expand the products and services they offer both directly to their customers and indirectly through various distribution channels. 

On the retail banking side, for instance, a customer buying a larger house can serve as a signal to their bank that this individual might also be looking for financial guidance in other areas outside of just a mortgage. That customer will likely welcome insights from their bank about how to modify or add a new homeowners’ insurance policy, or even a recommendation on when would be the best time for them to purchase a new car if they’re looking to accommodate a growing family. Whether banks choose to offer these non-traditional banking services themselves or through a partner, they’ll not only deepen their relationships with their customers, but create new streams of revenue in the process. 

Banks can also use external distribution channels to strengthen their relationships with end consumers. In other words, they’ll go through relationships with other businesses in the financial ecosystem, rather than from bank to consumer directly. Through these relationships— whether the customer knows the bank powering the transaction or not—banks are still at the center of the transaction. 

Consider a scenario in which a consumer is looking to lease a car. While that consumer is sitting down at a dealership speaking with a sales person about financing options, on the back end, the sales team is communicating their information to a lender who will provide financing for the loan. This entire financing process needs to happen quickly—we’re talking minutes or less—so as not to lose the consumer’s interest. For lenders, this means processing customer data in real time and as cost-effectively as possible. In doing so, lenders will increase both the speed and volume of the loans they can offer dealerships without increasing the manpower or costs—ultimately helping them reduce fees and increase efficiency that extends all the way to the consumer. 

In both of these customer and business-facing use cases, processing data with precision, at scale, enables banks to offer additional services to customers.

Create even further data-powered opportunities through open banking 

Data is at the core of open banking, a business model that puts consumers in control of who they share their personal financial information with — be that another bank or a third-party technology provider.

Before now, this new level of data sharing would have been difficult for traditional banks to offer considering that their legacy infrastructures made it difficult for them to interact with tech-forward providers. And on top of this, accessing and analyzing the increased amount of data that is created through open banking would have been a costly and complex undertaking for banks.

By digitizing their internal systems and architectures, banks are now in the position to integrate application programming interfaces (APIs) that can be activated with the press of a button to seamlessly share information between parties. As a result, both banks and their partners will have access to a deeper level of data that can be used to create more intuitive, personalized offerings for consumers.

With all of these new data-powered use cases in front of them, even banks that are still early on in their digital transformation can begin putting their data to work to demonstrate the return on their digitization projects before they’re even complete.