Murray Pozmanter, DTCC Managing Director and Head of Clearing Agency Services and Global Ops
In times of stress, it is often easy to lose sight of the fundamentals underpinning our business – providing risk management and secure, efficient processing for trillions of dollars of securities transactions on a daily basis. As technology continues to evolve and advance, however, so must the underlying processes of our central counterparty businesses. To be nimble and adaptive, there is always the next step to take – and innovation is never complete.
Gaining Trading Insights with AI
Businesses are investing heavily in more precise algorithms and faster computing power as artificial intelligence (AI) promises to turn mountains of data into competitive insights that can fuel business growth. At DTCC, we’re exploring the possibilities of using cognitive technology and data mining to dramatically enhance our clients’ understanding of their trading activity or, as with our Mutual Fund Profile Service II, give them unparalleled speed, accuracy and capacity to make sense of the overwhelming volume of data in mutual fund prospectuses. AI is allowing us to significantly improve data management capabilities in a flexible, innovative system that’s continuously learning, growing and adapting.
Pushing the Limits of DLT
A question I often get asked is whether DLT will be a transformative technology. It all depends on if it can meet the performance levels and scalability for adoption in high-volume, regulated markets. A benchmark study we conducted last year with Accenture demonstrated that the technology can support U.S. equity market trading volumes. These were groundbreaking results, and they served as a critical starting point for understanding how DLT could potentially be used for trade settlement. While this study generated a lot of excitement, we still need to determine if DLT will be able to meet the resiliency, security, operational needs and regulatory requirements of the existing clearance and settlement system.
Using Advanced Algos to Accelerate Settlement
One of the most important lessons we’ve learned over the years is that innovation in fintech is usually built on a foundation of things we already know. The key to thinking about a challenge differently is to look at it from a new perspective or toss out all assumptions. For example, what if we could reimagine, from scratch, the system for processing securities transactions? What would be possible today that wasn’t previously imaginable? That’s how we brainstormed ways to accelerate settlement in the U.S. after the transition to T+2. The system hadn’t changed fundamentally in over two decades, but when we reframed the issues, the creativity began to flow. This enabled us to take a huge step forward with our proposal for Settlement Optimization – an innovative, automated algorithmic-driven enhancement to the settlement cycle.
Striking a Balance Between Old and New
Firms are experimenting with fintech and investing in R&D at record levels, but innovation is beneficial only if it creates a stronger value proposition – and with it, increased safety, stability and resiliency across the global marketplace. The key is to understand how to use the infrastructure that’s been proven over many decades, while still taking advantage of new systems and processes optimized for the future. As we’ve learned with several use cases involving distributed ledgers, the best solution doesn’t always require the newest technologies. Sometimes, enhancing existing systems and processes yield better results than building something from scratch.