In an earlier blog, I explored the scale, scope and interrelated nature of the industry-wide disruption facing all participants in today’s capital markets. I went on to argue that firms could only succeed in such an environment by adopting a new approach to organizational change that we call ‘reinvention’.

What does this mean? In simple terms, reinvention is about developing specific capabilities that could help transform how a firm operates or elevates its growth trajectory. As firms consider how to achieve this, generative AI—with its human-like ability to learn language, context and intent—will play a pivotal role in whatever reinvention efforts they decide to undertake.

With this in mind, I’d like to take a deep dive today into what reinvention could look like in investment banking—and provide you with a glimpse of how next-generation technologies could help to turn it into reality.

Intensifying cost pressures…

Let me start with some industry context. In 2023, the top 15 global investment banks generated combined investment banking net revenues of roughly US$292 billion, compared to US$252 billion ten years earlier according to Accenture research. But over the same period of time, the overall cost-income ratio on an industry-wide level has hardly changed, fluctuating somewhere between 65 to 70 percent for most years.

That’s not to say firms have been sitting idly by. Far from it. Among other initiatives, they’ve been revisiting and revamping their location strategies and business lines. Embracing new technologies such as cloud computing. And investing in process simplification and task automation.

But why has none of it moved the needle significantly in terms of cost overall for the industry? There are several reasons why. For example, take new regulatory demands, which have required significant investments and loaded further pressure onto already constrained budgets. Or the fact that while trading volumes have been increasing, they’ve also been becoming more granular, also driving costs upwards.

These are just two of the myriad factors that have propelled the industry to where it is today on the cost side. And one of the biggest cost blocks today is still the middle- and back-office costs—which we estimate to account for up to 30% of most investment banks’ total costs.

…warrant a fresh look at reinvention

Such a situation calls for some thinking of what reinvention might involve. But when applying this concept to investment banking operations, it’s important to grasp that reinvention is not necessarily about driving the cost-curve further down. Rather, it’s about leveraging next-generation technology and operations to put this capability on an entirely new level—including a different cost curve.

At the heart of such a transformation sits the creation of a set of digitally enabled end-to-end business processes—all working across core processing systems and the organizational silos that still might exist in many firms today. To design and build those end-to-end processes, it’s vital to examine first how work is done today, pinpoint any inefficiencies, and think through how these could be best addressed by leveraging technologies such as generative AI to help augment human capabilities.

Take a process … and then reimagine it

Applying this lens, take a moment to consider what happens today if the settlement of a trade fails. In all likelihood, a series of emails between various parts of the organization need to be sent, read, answered, and acted upon to rectify the situation. And guess what—there is a high probability that this process is slow, clunky, and largely manual.

Now picture a very different scenario: imagine that your firm has implemented a work orchestration solution that manages the whole process end-to-end through a single interface. And that this solution is supplemented by a set of generative AI-powered tools handling specific tasks like predicting failing trades, writing emails, and routing those emails automatically to the right person or team.

Of course, such a reimagined and reinvented process will still require human intervention and oversight. But it could save time and effort, freeing up your operations teams to focus on more value-adding tasks.

And this is just one example among potentially hundreds across any investment bank. But it hopefully illustrates my wider point: that generative AI has become an extraordinarily powerful force for enabling reinvention across the entire value chain of any capital markets firms. True, it is by no means the only technology that will help achieve these goals, and further breakthroughs will likely come. But it may soon become table stakes for successful reinvention.

What’s next?

While I’ve focused here on generative AI’s potential to help transform processes, there are also other aspects and impacts of this technology that need to be considered to help deliver reinvention. Aspects like generative AI’s effects on work and talent; how to use it in a responsible way; how the underlying and surrounding technology estate needs to change; and how data can best be deployed to support adoption at scale.

These topics and more are on my list to tackle in my next blogs. So, stay tuned. And if you enjoyed reading this post, feel free to comment here or contact me.

Thanks to my colleague Dominic Stanyer who contributed to this blog.