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In a prior blog, I addressed the extent, scope and interwoven nature of the industry-wide upheaval affecting all players in today’s financial markets. I went on to suggest that organizations could only prosper in such an environment by adopting a new approach to organizational transformation that we term ‘reinvention’.
What does this mean? In simple words, reinvention is about building particular talents that might assist modify how a business runs or boosts its growth trajectory. As corporations explore how to do this, generative AI—with its human-like capacity to understand language, context and intent—will play a vital part in any reinvention initiatives they chose to pursue.
With this in mind, I’d want to take a deep dive today into what reinvention may look like in investment banking—and present you with a taste of how next-generation technology could assist to transform it into reality.
Intensifying Cost Pressure
Let me start with some industry perspective. In 2023, the top 15 global investment banks produced combined investment banking net revenues of around US$292 billion, up to US$252 billion ten years earlier according to Accenture study. But throughout the same length of time, the total cost-income ratio on an industry-wide basis has rarely altered, ranging at between 65 and 70 percent for most years.
That’s not to imply corporations have been sitting quietly by. Far from it. Among other measures, they’ve been examining and reworking their geographical strategy and business lines. Embracing new technology such as cloud computing. And investing in process simplification and task automation.
But why has none of it moved the needle considerably in terms of cost overall for the industry? There are various reasons why. For example, consider increased regulatory expectations, which have demanded large investments and placed extra pressure onto already tight budgets. Or the fact that although trade volumes have been growing, they’ve simultaneously been becoming more granular, therefore driving expenses skyward.
These are only two of the countless causes that have drove the business to where it is now on the cost side. And one of the major cost blocks today is still the middle- and back-office expenditures—which we estimate to account for up to 30% of most investment banks’ overall costs.
Warrant A Fresh Look At Reinvention
Such a circumstance demands for some thought about what reinvention may include. But when applying this approach to investment banking operations, it’s vital to appreciate that innovation is not always about driving the cost-curve farther down. Rather, it’s about using next-generation technology and processes to put this capacity on a whole new level—including a distinct cost curve.
At the center of such a transition rests the construction of a set of digitally enabled end-to-end business processes—all operating across core processing systems and the organizational silos that still could exist in many organizations today. To design and construct such end-to-end processes, it’s necessary to assess first how work is done now, spot any inefficiencies, and think through how these may be effectively handled by employing technology such as generative AI to assist augment human skills. You may also read this: How to Become an Investment Banker
Take A Process And Then Reimagine It
Applying this viewpoint, take a minute to evaluate what occurs now if the settlement of a deal fails. In all probability, a series of emails between various divisions of the company need to be written, reviewed, responded, and acted upon to remedy the problem. And guess what—there is a good possibility that this procedure is sluggish, awkward, and entirely manual.
Now image a totally different scenario: assume that your organization has installed a work orchestration system that handles the full process end-to-end through a single interface. And that this solution is supported by a series of generative AI-powered tools handling particular tasks like forecasting unsuccessful trades, drafting emails, and routing those emails automatically to the relevant person or team.
Of course, such a redesigned and reinvented process will still require human interaction and monitoring. But it might save time and effort, freeing up your operations personnel to focus on more value-adding duties.
And this is only one example among perhaps hundreds throughout any investment bank. But it also demonstrates my bigger point: that generative AI has become an enormously strong engine for allowing innovation across the whole value chain of any capital markets business. True, it is by no means the sole technology that will assist attain these aims, and other advancements will undoubtedly come. But it may soon become table stakes for successful reinvention.
What’s Next?
While I’ve concentrated here on generative AI’s ability to assist alter processes, there are many other characteristics and implications of this technology that need to be explored to help provide innovation. Aspects including generative AI’s implications on work and talent; how to utilize it in a responsible way; how the underlying and surrounding technology estate has to evolve; and how data may best be leveraged to promote adoption at scale.
These subjects and more are on my agenda to tackle in my forthcoming posts. So, keep tuned. And if you enjoyed reading this content, feel free to comment here or contact me.
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