In our recent Acuiti whitepaper, Future-Proofing Clearing: Investment Priorities for the Modern FCM, we examined the factors bringing change to the futures market’s post-trade infrastructure. Long defined by incumbency and sticky client demand, the vendor systems that underpin much of the listed derivatives market could be facing new competitive pressures as technological advances open the doors to lower barriers to entry.
As with other vendor systems, any question of technology investment in the current day comes hand in in hand with discussion about artificial intelligence, and what its ultimate effect will be on the market.
For many firms, the possibilities of AI are promising. It has the potential to reduce operational costs, lower barriers to entry, reduce reliance on manual intervention and improve processing speed and scalability.
Focusing more acutely on the futures clearing space, AI could help expand the pool of development skill, which is currently concentrated in a small number of providers.
What happens to post-trade infrastructure as the developers who built it come to end of their careers is still an open question. AI could potentially plug any succession gaps in terms of the knowledge and coding required to build and maintain this essential piece of market infrastructure.
With AI capabilities still not fully realised though, there is still a tension in predicting just how much it can take on in carrying these responsibilities for the industry. And ultimately, whether it can truly replace human expertise.
The Changing Nature of Expertise
Much of post-trade infrastructure has already evolved through automation designed to streamline workflows such as reconciliations, settlement matching and reporting. As found in the whitepaper, increasing automation remains the primary driver behind future post-trade investment decisions.
The current discussion surrounding AI, however, goes beyond process efficiency and raises broader questions around whether technology can meaningfully support forms of operational judgement traditionally developed through years of market experience.
Despite years of investment in automation, manual intervention continues to represent a significant operational challenge across the industry. According to our whitepaper, almost half of surveyed FCMs still face operational issues linked to manual processes such as reconciliations.
Experienced operations teams understand settlement breaks, collateral disputes, market anomalies and the practical realities of managing operational risk during stressed market conditions. At times of crisis, such as during a cyber-attack on the systems themselves, their practical knowledge becomes indispensable as firms revert to manual processing.
So, while AI may increasingly assist operational workflows and analytical processes, replicating the contextual judgement developed through years of navigating stressed market conditions remains a far more complex challenge.
Financial markets are rarely static or fully predictable. During periods of stress, historical data can become less reliable and operational judgement becomes more important. This raises a broader question for the industry: what will the eventual role of AI be in operational exercises to manage highly abnormal or unprecedented market events?
Lower Barriers to Entry and Rising Competitive Pressure
While AI’s impact on crisis management is still ambiguous, its ability to lower developmental and operational costs seems much more foreseeable.
Across industries, smaller firms and newer market participants are increasingly leveraging intelligent workflows to shorten time to market and lower project spend. These are promising concepts for futures market participants.
We found that over half of FCMs believe there is currently not enough choice in the market for third-party post-trade vendors. AI-enabled platforms may begin to change this dynamic by lowering the cost and complexity of building competitive post-trade services.
Lower barriers to entry could also encourage innovation, increase vendor competition and reduce concentration risk within the market. On the other hand, it may intensify pricing pressure and commoditise operational functions that were once considered differentiating capabilities.
The Pragmatic Path Forward
AI may prove to be one of the most significant shifts in the evolution of post-trade infrastructure. Yet the complexity of AI lies in the fact that its benefits and risks are deeply interconnected.
Pressure to modernise is intensifying, with more than a quarter of FCMs firmly planning to replace their core post-trade platforms within the next five years. Yet in adopting the technology, there should also be caution about how best to maintain institutional memory.
To learn more, download the full Acuiti and Nasdaq Whitepaper here.