by Akhil Babbar, Raghavan Janardhanan, Remy Paternoster, and Henning Soller
Digitalization has become an imperative for banks. As we have seen in our review of our case examples, a successful digital transformation can lead to better business outcomes, including higher balances for current account savings accounts, lower cost-to-income ratios, increased customer acquisition and retention rates, and faster time to market.
However, only 30 percent of banks that have undergone a digital transformation report successfully implementing their digital strategy, and the majority fall short of their stated objectives.1 This low success rate holds true for most industries and has remained constant for many years despite significant technological and organizational innovations, though technology-focused companies typically fare better.
In this post, we discuss why banks often fail to execute their digital transformations—and what they can do to tilt the odds in their favor.
Common traps to avoid
Banks often argue that if they had a sufficient technology budget, their transformations would be successful. But we have seen several banks in recent years allocate significant resources to their digital transformations and still struggle to execute them.
The nature of the banking industry poses specific challenges. For one, banks have invested in technology for decades and thus typically have developed a significant amount of technical debt, along with a siloed and complex IT architecture. Separation between the business and IT makes it more challenging to implement the necessary cultural shifts. Finally, banks also face an aging workforce, particularly compared with purely digital fintechs.
We have identified a common set of execution challenges that threaten to derail banks’ digital transformations, and follow with a set of recommendations for how to overcome them.
Underestimating complexity and cost
A digital strategy begins with a business case, and every business case is calculated with a specific time to impact. Once transformation initiatives extend beyond the expected project duration, the increase in cost can often overtake the projected value of the original transformation or lead to its cancellation.
More than half of digital banking transformations exceed their initial timeline and budget—or fail.2 Leaders often underestimate the complexities of executing a digital transformation, which typically involve complicated interfaces, data management, and interdependencies across initiatives. Common mistakes include not fully involving all stakeholders in the development of the strategy and blueprint, miscalculating the extent to which existing business processes need to change, and not sufficiently implementing the magnitude of changes required to truly reap the benefits of the transformation. These challenges are especially relevant for banks, given that the business side is often removed from technology developments, business processes are assumed to be fixed, and the IT architecture landscape is particularly complex.
Initial budgets often fail to account for these factors, which can lead to a delay in the impact and the impression that costs have spiraled “out of control” when, in reality, the program was never feasible in the way it was originally envisioned. According to our research, 70 percent of digital transformations exceed their original budgets, and 7 percent end up costing more than double the initial projection.3
Underestimating technical debt
The need to address technical debt—by cleaning up legacy technology stacks, unused applications, and excessive infrastructure—is often missing from initial transformation budgets or perceived to be less important than other transformation initiatives. It is, however, a critical prerequisite to executing a digital transformation at pace, even if the work does not generate an immediate financial gain. Therefore, banks need to assess and prioritize the work of addressing technical debt from the beginning of a digital transformation.
In general, because banks have many legacy IT applications, they have higher technical debt compared with other industries, making it harder for them to create the platform they need for the digital future (exhibit).
Challenges in measuring impact
As the saying goes, what gets measured gets done. Yet few organizations effectively measure, and therefore deliver, top- and bottom-line value over the course of a digital transformation. Banking leaders must identify critical impact metrics, baseline the current state, and track the impact during and after the transformation. Only then can they achieve the full financial benefits of the transformation effort.
In our experience, banks struggle to accurately quantify and track the impact of their digital strategy and to establish a clear link between specific initiatives and their revenue and profit growth. Too often, leaders do not capture the full value of their digital strategy because they lack well-defined success parameters, inadequately engage the full set of end users (customers, employees, and other stakeholders), and fail to consider the potential adverse effects on customer satisfaction.
Slow pace of change
Large banks typically lag their competitors on innovation speed and productivity. A reliance on traditional operating models, coupled with limited adoption of agile ways of working, can hinder the success of their digital transformation. A McKinsey banking survey conducted in 2021 found that while fintechs and neobanks release new product features every two to four weeks on average, traditional banks have product rollout cycles of four to six months. Our research also shows that large banks are 40 percent less productive than digital natives.4 This slow pace of change can cause banks to give up on their digital transformations rather than attempt to overcome the underlying cultural barriers that inhibit the speed of the transformation.
While traditional banks know how to hire banking talent, the same is not always true for tech talent. Typically, banks are not the preferred destination for tech talent—but talent is a key prerequisite for making the digital transformation work. Our research suggests that at least 50 percent of employees involved in the transformation should be in-house—and that risks increase significantly when 70 percent or more of the employees involved in the transformation are outsourced.5 To ensure the success of their digital programs, traditional banks need to refine their employee value proposition to attract more tech talent—for example, by providing incentives and work environments that rival those of fintechs.
A successful digital transformation relies on close collaboration and coordination across the organization. However, many banks continue to operate in traditional functional or business silos, which leads to conflicting or misaligned priorities, lack of clarity, and a fragmented approach to execution. In our experience, banks often have duplicate systems and solutions, such as customer-relationship-management (CRM) platforms and small and medium-size enterprises (SME) channels, across business lines. Similarly, banks with strong country-level operating models typically overlook efficiency gains that could result from reusing existing functionalities across geographies.
A better path forward
Meeting these challenges requires banking leaders to take a holistic approach across the business, technology landscape, and operating model. However, our experience shows that going all in on a digital transformation can help banks avoid some of the most common pitfalls and yield significant benefits. For example, one major European bank redesigned its operating model and reset roles and responsibilities to embed agile practices throughout the organization. At the same time, it revamped its core banking system, including a complete overhaul of its integration architecture and data architecture. These measures generated cost savings of 30 percent and enhanced the bank’s capacity to deliver value well into the future.
Imperatives for success
Banks can address these challenges by taking several actions, not all of which are intuitive:
- Reduce complexity (which may require simplifying interfaces and addressing dependencies) and avoid surprises by budgeting the necessary time and resources up front (for example, by using micro front ends and reusable APIs and by implementing DevSecOps as a standard across digital initiatives).
- Estimate the technical debt and ensure that the initial budget includes the cost to remove it; otherwise, the debt will lead to delays and cost increases.
- Overinvest in the cultural shift, even if it might not be directly related to technology.
- Attract tech talent and do not try to outsource the transformation.
- Break down organizational silos and design a holistic transformation road map (not just by business area).
To measure the change, agile practices and processes such as quarterly business reviews should be in place to allow for effective prioritization and value tracking. Traditional oversight should be replaced by cross-functional collaboration, cross-silo performance management, and a new concept of joint accountability across the business and IT. Along the way, leaders can highlight “lighthouse” projects to inspire employees and build momentum.
A large-scale digital transformation is not easy, and it is not surprising that most banks struggle to achieve their business objectives on time and within budget. However, banking leaders can take steps to avoid the most common mistakes by defining clear goals and metrics that reflect not only the business change but also the cultural and technical changes required. By doing so, banks can increase their chances for success and reap the full potential of their digital transformations.
Akhil Babbar is a knowledge expert in McKinsey’s Gurugram office, Raghavan Janardhanan is a partner in the Chennai office, Remy Paternoster is a partner in the Madrid office, and Henning Soller is a partner in the Frankfurt office.
1 McKinsey and Oxford Global Projects study on large-scale IT projects, 2001–21.
4 Average of 15 digital bank examples in comparison to five fintechs in terms of IT productivity.
5 McKinsey and Oxford Global Projects study on large-scale IT projects, 2001–21.