Earlier this year, DTCC’s Office of Fintech Strategy commissioned a research project to better understand the performance and scalability of distributed ledger technology (DLT). Jennifer Peve, Managing Director & Head of Solutions Business Development & Co-Head of the Office of Fintech Strategy from DTCC discusses the results of the study.
DTCC partnered with Accenture to execute a DLT Benchmark study with U.S. equities post-trade processing as the target use-case. The results of the study will be leveraged to inform the DTCC Business & Technology Strategy as to when and where DLT technology could play a role in enhancing the post-trade process.
Why did DTCC commission this study?
DTCC has been actively involved in DLT projects for more than three years, including the on-going effort to re-platform its Trade Information Warehouse on DLT. During that time, we’ve seen these platforms continue to mature, but concerns have loomed around the scalability of DLT. The ability for a technology to scale and support the transaction volumes is one of our critical adoption factors. Our efforts to advance the use of DLT led us to commission a study to assess whether the technology would be able to support the scalability requirements of the U.S. equities markets.
This study also aligns with our mission to investigate emergent fintech - technologies and vendors - to gain an understanding of the applicability of these technologies to industry requirements.
What did the results of the study reveal?
The study, conducted by Accenture with additional support provided by the technology providers Digital Asset (DA) and R3, proved that DLT can support average daily trading volumes in the US equity market of more than 100 million trades per day. Specifically, DLT performed at levels necessary to process an entire trading day’s volume based on trading activity during a peak time of day of 6,300 trades per second for five continuous hours, which equates to 115,000,000 daily trades.
A particularly interesting finding is that public blockchains supporting crypto-currencies operate at single or double digit per second performance, which until now was the only indication of the potential volume a private DLT would be able to support. Also, public blockchains have built in specific inefficiencies to combat things like censorship resistance and the need for dealing with unknown and untrusted parties. Capital markets do not share the same considerations - they are highly regulated and are willingly dependent on KYC. As a result, private or permissioned blockchains can be more efficient and scalable in closed and private networks because they allow for censorship and ensure that only known and trusted parties are participants in a network.
Can you provide specifics on the DLT performance test?
During the 19-week study, DTCC and Accenture ran DLT performance tests using commercial enterprise grade DLT platforms offered by DA and R3, whose engineers provided support on performance tuning. Our main objective was to analyse DLT’s ability to process the massive trading volumes of the US equities market.
Accenture built a network of more than 170 participant nodes to model the financial ecosystem of exchanges, market participants and broker/dealers supported by DTCC. The prototypes were designed to test the capture of matched equities trades from exchange DLT nodes, novation of those trades with DTCC acting as the central counterparty (CCP) to maintain anonymity on the ledger, creation of netted obligations and settle the obligations. The test environment for this study was setup in our AWS cloud environment.
Does this mean that DLT is now ready to support the requirements of the existing U.S. equity clearance and settlement system?
No. While the study results were quite positive, and provided useful insights into performance and scalability, additional work needs to be done to prove whether the technology can meet the resiliency, security, and regulatory performance and scalability requirements of DTCC’s existing clearance and settlement system. In addition, testing beyond basic functionality will be needed to understand the implications of downstream activities, such as asset servicing.
Will DTCC plan to test the scalability of other commercial providers?
Our main objective was to analyse DLT’s ability to process the massive trading volumes of the US equities market, not the capabilities of individual commercial platforms. This work, however, enabled us to develop a framework to test additional platforms as they develop. As these platforms evolve, we will use this framework to further test their enterprise readiness.
What’s next? Is DTCC moving equities clearing and settlement to DLT?
It’s too premature to speculate on a specific US equities market project or timing at this point. While we determined that DLT can meet basic processing requirements for equities clearing, additional work will be necessary for DTCC to determine if DLT can meet the resiliency, security, operational needs and regulatory requirements of its existing clearance and settlement system.
That said, we are encouraged by this research and look forward to continuing to work collaboratively with the industry as we further test DLT’s capabilities. We will also leverage the results of this study to inform the on-going evolution of our business and technology strategy.