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The Paradox of Plenty

Part 3: Putting Budgets to Work

How are UK banking technology leaders are allocating resources, and how do they approach innovation?

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Having unpacked some of the challenges banking and capital markets (BCM) technology leaders are facing, how these factors are influencing their strategies and the outcomes being targeted, in Part 3 of our article series we look at where resources are being allocated as budget holders seek to put their plans into action.

And, as Figure 1 below shows, 73% of the technology decision-makers we surveyedi for our study told us they were allocating their budgets to one-of-four core technology areas – Cloud (23%), Analytics (20%), Open Banking (16%) and AI (13%). A further 7% was dedicated to projects in the blockchain and wider distributed ledger technology (DLT) space.

 Figure 1: Firms across the BCM space are prioritising their investments in data.

The remaining balance, accounting for an average one-fifth of UK banking and capital markets technology budgets, is angled towards general maintenance, legacy technology spend and other day-to-day investment activity required to run the bank. This also includes any other technology programmes happening around the firm not aligned to the other investment areas listed above.

As a reminder, in our previous article [LINK] we noted that 74% of budgets were typically allocated to business as usual (BAU) activities, with the remaining 26% dedicated to innovation. Hence, the allocations we see here across different areas of technology reflect this same blend of so-called ‘run’ and ‘change’ spend, augmenting existing layers of organisational technology as well as piloting and implementing new tools and platforms.

Figure 2 below helps us understand this more readily by providing a zoomed out view of the relative maturity of each of these key technology areas.

 Figure 2: Stages of maturity of a range of key BCM technology investment areas

We asked respondents to describe the programmes they had running in each of these technology areas using one of five maturity categories: ‘nascent’, ‘evaluating’, ‘piloting’, ‘implementing’ or ‘in production’ (referred to here as ‘fully deployed’). Overall, more than three-quarters (77%) of projects in these five key areas are in the pilot, implement or deploy phases of maturity. However, Cloud and Analytics are by far the most mature areas of investment here, with at least 60% of respondents reporting they are either implementing or deploying in these areas.For a fuller view, in the bullets below, we reflect on both budget intensity and the levels of maturity respondents reported in each key technology area.

  1. CLOUD: Cloud accounted for almost one-quarter of spend overall, covering a wide range of service and infrastructure investments. These are required by firms to deliver flexible and cost-effective storage, management and processing of data. While many of the larger players have mature cloud programmes, some smaller institutions are at an earlier stage in their cloud journeys, and a surprising 40% of respondents to our survey said they are still in the evaluation and pilot stages of development.

  2. DATA & ANALYTICS: closely related to this is the 20% of investment going into data analytics. Spend here is dedicated to acquiring and operating the tools, technologies and processes needed to collect, analyse and interpret data. This includes data sourced from internal systems as well as, increasingly, external and ‘alt data’ suppliers such as exchanges, ratings agencies, satellite monitoring providers and others, which institutions use to augment and enrich their own data holdings. Again, the majority of respondents (63%) reported mature capabilities in this area, with 37% at a more nascent stage of development, either evaluating or piloting analytical tools.

  3. OPEN BANKING: Building on the ‘alt data’ trend, many firms are also dedicating resources to open banking, which seeks to allow customers greater ownership of their financial data, together with new tools and services, as a way of promoting competition and switching. This involves creating and extending digital frameworks to allow third-party developers to build applications and services around institutions. This investment covers myriad areas of the bank and typically involves the development and management of application programming interfaces (APIs) that enable third-party software applications to interact and exchange data with the bank in a secure, standardised way with the full consent of the customer. Such investments could also extend to security measures including more robust authentication protocols to protect customer data and comply with regulations such as the latest European Payments Services Directive (PSD2). Open Banking activities can also include co-investment with FinTech partners to develop bespoke integrations, as well as targeted upgrades to data infrastructure to boost performance and scalability under higher loads as API traffic increases. In contrast to both cloud and analytics, open banking is at a relatively earlier stage of development, with more than half of respondents (57%) telling us their programmes were still at the evaluation or pilot stages, with a further 9% describing their investment in open banking as ‘nascent’.

  4. ARTIFICIAL INTELLIGENCE: It might be surprising in the midst of the current Generative AI boom to find that respondents are only dedicating 13% of their budgets to AI right now. In interpreting this result though it is helpful to reflect on the interconnectedness of spend we’re seeing in these results, given that much of the investment going into cloud and analytics will be specifically targeted at supporting AI-related projects. Rather, this chunk of spend reflects investments in tools for the development of models and algorithms, as well as the banks’ computational infrastructure itself – comprising established high-performance computing (HPC) and newer GPU-based solutionsii – required to deliver the processing power needed to support more complex and expansive AI systems. On top of this, firms must also invest in training, anti-bias tools and ethical advice concerning their AI strategies, as well as in developing valuable use cases to utilise the power of the systems they are building. AI can perhaps best be described as the “oldest new technology”iii emerging as a theme in academic and technical debate in the middle of the last century. Nevertheless, only 39% of respondents describe themselves as having mature AI programmes in place today. A matching proportion (40%) were busily piloting though, with the remaining 21% at an earlier stage of development. We anticipate the advent of Generative AI will concentrate minds further, and our forthcoming eminence focusing on how firms are responding to the challenge of integrating Generative AI for value will explain these dynamics in more detail.

  5. DISTRIBUTED LEDGER TECHNOLOGIES: An average 7% of tech budgets were dedicated specifically to blockchain-focused projects, although engagement varies. Respondents from universal banks dedicated 10% of budgets to DLT versus only 5% of dedicated SME banks and digital natives. Nevertheless, these small sums are still significant, representing a commitment to investment in this area. And the growing interest of financial services in tokenisation for a range of use cases could see budget intensity ramp up over time. As we discuss in our recent FutureMoney seriesiv, alternative options for the storage and exchange of value using decentralised digital assets and currencies are continuing to evolve, although the path ahead remains unclear. Nevertheless, the rise of Central Bank Digital Currencies (CBDCs) could presage a meaningful shift towards less volatile, more regulated digital assets, and many firms will look to DLT-based solutions in search of greater efficiency, security and competitive advantage. Compared to the better-established technology areas above though, right now DLT remains relatively immature. On average, 13% of respondents described their engagement as ‘nascent’ with a further 81% merely evaluating or piloting POCs in this area. So, while blockchain is on the map, banking and capital markets technology leaders are putting much more focus into adjacent areas of investment, for now.

While investment across these areas will cover a wide range of practical objectives, technology leaders are united in wanting their spend to drive meaningful and impactful outcomes. And yet, when it comes to innovation, we see a wide range of approaches to achieving that ambition.

For example, as Figure 3 below shows, almost half of all survey respondents (47%) told us they were focused on delivering the most meaningful and impactful elements of their technology strategies first, with fewer than one-quarter (22%) favouring more of a ‘tick box’ approach. Meanwhile, almost one-third of respondents (31%) aimed to deliver both impactful and comprehensive delivery.

There was also significant variation between banking and capital markets sub-sectors. In most categories, the majority of respondents prioritised impact over ticking every box in the strategy – in particular the 30 respondents from mutuals and universal banks we surveyed. In contrast, the high street retail banks take a more balanced approach, with 55% targeting impact and a clean sweep of strategy priorities, which as many tech decision-makers know can be very hard to achieve in practice.
Figure 3: Striking a balance between impact and covering all elements of innovation strategies.

And we see a similar range of views when it comes to the nature of the innovation firms are engaging in. Figure 4 below shows how firms are thinking about the balance between innovation activity aimed at solving specific issues versus more open-ended innovation favouring the exploration of new ideas, markets and technologies.

 Figure 4: BCM firms are evenly split on whether to pursue open-ended vs. goal driven innovation.

Interestingly, there is an absolute dead heat between both sides of the argument, with 32% favouring one or other option while the remaining 36% seek to balance both approaches. Inevitably though, the blend of responses changes as you dig into different sub-sectors. So, while 60% of respondents from dedicated SME banks chose to focus their investments on specific outcomes and issues, two-thirds (67%) of digital natives took the opposing view, prioritising open-ended innovation.

Clearly then, there is no ‘one-size-fits-all’ approach to innovation, and firms must choose the model that best suits their individual needs. And this is where culture can play a role, particularly when it comes to establishing norms around what to do with ideas that aren’t working, as well as the controls and measures needed to define and evaluate success quickly. Given the important role that failure plays in innovation, these are essential tools for decision makers, allowing for swift course correction.

This is especially important in institutions where innovation is driven down into the lines of business. Getting the culture and processes right across the organisation is essential if innovation is a distributed activity. Stakeholders will need to rally around one or more of the best ideas to pursue together and take forward at scale. Nevertheless, while there are always choices to be made concerning the ‘how’ of innovation, when it comes to the successful delivery of new and existing projects, firms will share many of the same hardships.

In the next instalment of this series, we will look at the barriers to success banking and capital markets technology leaders face, focusing on the crucial challenge of how to measure success.

 To read more on this, please see our full five-part series linked below:

  1.  The long and winding road… key challenges facing today’s BCM tech leaders after decades of banking transformation.
  2. Show me the money… what resources do UK BCM tech decision makers have to work with? 
  3. More money, more problems… navigating the potholes along the path to business impact.
  4. Solving the paradox… how should high performing tech leaders in BCM respond to these challenges?



iOur survey was run in September 2023 with the assistance of an external B2B survey company called Coleman Parkes. The survey itself was anonymous, reaching 151 senior technology decision-makers at 68 separate BCM organisations across the UK satisfying a discrete set of criteria. The Long & Winding Road in this series provides more detail on these criteria, showing the constituency we reached as well as the roles and responsibilities of the respondents who answered our survey – 80% of whom held CxO technology titles. Our respondents represent firms across UK retail, digital and SME banking as well as mutuals and wholesale and capital markets, the latter of which included the UK operations of various US and International investment banks. All were asked a series of questions concerning their technology investments, of which a cross-section of results is presented here.

ii.Graphics processing Units (GPUs) like those found in gaming PCs have significant architectural advantages over traditional central processing units (CPUs) when it comes to managing AI workloads. This is as a result of their superior processing power and improved efficiency when it comes to the parallel processing demands in areas such as machine-learning (ML).

iiiOn the subject of AI being the “oldest new technology”, it is worth remembering that the first academic paper concerning neural networks, by McCulloch and Pitts, was published in 1943, closely followed by Alan Turing’s seminal work “Computing Machinery and Intelligence”, which was published in 1950. This introduced the concept of the “Turing Test” as a way of measuring intelligence. The term “Artificial Intelligence” itself was first coined seventy years ago by John McCarthy at the Dartmouth Conference in 1954, an event widely regarded as the birth of AI as a field of study. The recent explosion we have seen in AI across industries is reflective of the great advances made in compute power in recent decades, which enabled many of the theories posited in the first half of the 20th century to be tested and engineered into tools and solutions.

ivThis series of articles discusses what the future of money might be by 2035, unpacking the growing ubiquity of digital assets, particularly as more central bank digital currency (CBDC) projects go live, and more customers begin to engage with tokenised assets of all types across their ever-evolving financial lives. More details can be found here:

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