Derivatives Market Prepares for Emerging Tech Implementation

It is a common belief among many participants in the derivatives space that 2018 will be the year that distributed-ledger technology (DLT) will eventually justify the reputation it has gained over the last years. In 2017, blockchain’s hype began wearing off—apparently, no one would speak with the same enthusiasm about it, and even the media fell mostly silent. Did this mean that everyone stopped believing in DLT? 

“At some point, all the talking needed to stop and focus on working on creating real blockchain products,” says Dr. Lee Braine, from the investment bank CTO office at Barclays.  

Braine says that for investment banking, blockchain didn’t seem to be the way to go when the technology became known a couple of years ago, because of data privacy issues, the technology’s performance, and its relative immaturity. “It has since evolved with industry input and guidance, and we expect to start going live with some blockchain products from this year,” he adds. 

R3 is perhaps the most well-known, born out of the collaboration between the world’s largest financial institutions. But even though the consortium had the support and funding of some of the industry’s most powerful and influential banks, it had to overcome technology hurdles to transform DLT into a mainstream technology. 

James Carlyle, chief engineer at R3, says one of the most significant concerns was the immutability of the distributed ledger. “If we have something that’s truly immutable, we have to think carefully about why we might need to change it,” he says. “We have to make sure it’s right at the point of deployment because it is immutable and change becomes harder.”

R3 had to work hard on quality assurance. Carlyle says there are a number of mature frameworks for automated testing of traditional software and engineers required the same level of rigor in terms of testing smart contracts. “Platforms and languages are brand new for distributed ledgers, and so we don’t have these frameworks already in place,” he says. “One of the things we do is work with existing mature technologies like Java to support the development of smart contracts.”

Abysmal Results

When quality is not ensured, results can be abysmal. Carlyle recalls a number of examples where public blockchains were full of bugs, which allowed for completely inappropriate behavior of the technology. “It has caused major debates about what to do when that happens, how to correct it, whether to fork these ledgers, effectively creating a second version of them, or whether to try and manage and allow people who have lost out to live with their losses,” he adds. 

Despite the technical difficulties, Barclays’ Braine says he believes distributed-ledger technologies will help save huge amounts of money for banks in the long run. “Third-party reports estimate that the industry savings could be in the range of $5 billion to $40 billion and this was one of the reasons we put so much effort in this,” he says. “Those potential cost savings would typically be the result of simplification and rationalization; by reducing both variation and duplication, you also reduce the need to reconcile.”

That is also the reason why banks chose to invest so heavily in DLT, despite the profound challenges they might face after deploying the technology.

Artificial Intelligence

While AI has been part of the fintech upswing for some time now, it wasn’t until last year that the derivatives industry became convinced about the impact it might have on their day-to-day operations. Within the investment banking sector, firms have already started using sophisticated optimization algorithms, including complex statistical techniques, to offer a specialized solution. 

When deploying machine learning, Braine says there are some complex issues that need to be resolved if firms want to operate efficiently. “Consider, for example, the legal and regulatory implications if unsupervised machine-learning techniques are used that lack ‘explainability,’ meaning that the system cannot provide the explanations behind certain decisions,” he says. “It’s very difficult to provide simple, accurate explanations for the outcomes of sophisticated trained systems such as those based on multi-layer neural networks. Even if you can inspect the neural network to identify the connection topology and the weights, that typically still doesn’t provide a human-understandable explanation.” 

For Braine, there is a very important problem with identifying applications of AI in investment banking. “Certain classes of problems lend themselves more naturally to sophisticated algorithmic techniques where there are already known approximations or solutions,” he explains. “Leveraging or further refining those techniques may be the most expedient method of progressing.”

Vendors’ Role 

Third-party technology providers have been proven to be an essential ally for banks that wish not only to overcome the challenges associated with deploying emerging technologies, but also to enjoy the benefits this evolution is sure to bring. Braine says the introduction of each new technology poses its own risks.

From a standards and architecture perspective, the risk should be managed via a rigorous product life cycle process. From a pure technology perspective, however, banks should typically work with vendors, where both can learn about novel business applications of technology innovation.

“This result may be a product that is initially deployed only within a limited scoped environment, or it may result in changes or enhancements to the product to help it better progress through assessments by security, information and risk management, etc.,” he says. “In each case, both parties win: The vendor gets a product that’s more suitable for deployment in a banking environment, and the bank gets a better product.”

This win–win scenario has indeed resulted in a proliferation of solutions. Some have already gone live, while others are waiting for the green light. Below are three technologies/projects that are set to become operational sometime this year. 

CLS

Foreign-exchange (FX) data and technology provider CLS is on the cusp of unveiling a DLT service.

CLSNet, the firm’s first blockchain initiative, is an automated bilateral payment netting service for both the buy side and sell side, using hyperledger fabric to implement the distributed ledger. Ram Komarraju, managing director, technology at CLS Group, says that while the company has been serving more than half of the FX market, settling 18 currencies, it realized that there was a gap in the market to provide risk mitigation services for other elements of foreign exchange.

“We understand that netting does take place, with much of it done on a bilateral basis, and that there are some systems that offer netting as part of their suite of services, but it is not standardized,” he says. “The solution CLSNet provides is to offer standardization in the way we match trades, provide legal confirmation and calculate net positions.”

The development of CLSNet was not an easy task because it had to resolve two major issues, the first being ensuring that the use-case would solve a real business problem. CLS didn’t want to build a proof-of-concept that might never have a commercial value. The second challenge was to make the original product fast and ensure that it wouldn’t impact the already existing critical infrastructure. “Eventually, we took our 15-year experience and looked at what it means to build a secure network on top of which we can run a distributed ledger,” Komarraju explains. “You have to provide a platform where users feel secure.” 

As for the integration with legacy systems, Komarraju says this was the most onerous and complex aspect of building the platform. “We want to ensure that we provide the bridge that enables the banks to transition to these technologies more gradually,” he says. “For example, when we launch CLSNet, we will give them the option to connect not only via distributed ledger but also over existing Swift channels.”

DTCC

The Depository Trust & Clearing Corp. (DTCC) has been working with emerging technologies for quite some time now, exploring applications of DLT, quantum computing, AI, and big data. To that end, it has set up a specific fintech sector that works on applying the new technologies across its entire product line. Jennifer Peve, co-head of fintech strategy at the DTCC, says the firm’s most important work is set to go live within 2018. “We are in the process of re-platforming our Trade Information Warehouse (TIW) solution, using DLT and cloud computing,” she says. 

The DTCC’s TIW platform—a record-keeping, lifecycle events, and payment management system for more than $11 trillion of cleared and bilateral credit derivatives—is a 12-year-old project and one of the firm’s most popular offerings among its clients.

The re-platforming project was initiated in 2016, when the DTCC started working in collaboration with IBM, Axoni and R3, to build a proof-of-concept with respect to how to apply blockchain technology across the TIW platform, while migrating it into the cloud. 

According to Peve, the blockchain version of TIW is scheduled to replace the legacy system midway through this year and that the project will consist of three phases. “In the first phase, users can expect to have the same functionality via the GUI, reports, and messaging in the re-platformed system that they have today,” she says. “Up until the final stage, TIW will be 100 percent integrated into the users’ systems.” 

Peve says that innovations leveraging DLT and cloud computing are typically large infrastructural modifications, so it takes time to see any transformational change. “Transformational change in the long term can be achieved through incremental improvements in the short term,” she says.  Collaboration and establishing a common set of standards will be the keys to realizing the full potential of technology innovations and achieving significant improvements for the entire industry.”

Isda 

With much of the industry’s emerging technology focusing on the global derivatives markets, the International Swaps and Derivatives Association (Isda) stepped in, in late 2017, and coordinated the efforts of introducing a golden standard for the use and implementation of the new technologies by its members.

Clive Ansell, head of market infrastructure and technology at Isda, says that large numbers of market participants have their own technologies and ways of processing their derivatives transactions, which makes new technology deployment particularly challenging. “One of the biggest challenges is that because everyone represents the same processes and data differently, the effort and cost to implement each instance is tremendous,” he says. 

Isda’s objective is to ensure that all its members have the same deployment process, securing easier and fairer adoption. While the association is and will remain technology agnostic in terms of not favoring one emerging technology over another, it does think of promoting the idea of hierarchical representation in terms of participants, parties and products.

“We’re trying to do it in a way that’s common across the industry because that’s the fundamental point,” he says. “Absent a standard, we would enter a new world where the full opportunity offered by new technology would not be realized, as implementations will do the same thing but differently, recreating to some degree the complex interactions that exist today.” 

Ansell says the market still appears to be suffering from technologists’ lack of understanding of how the industry works, and there are legal and jurisdictional implications as well that prevent technologies from fully conquering the financial world. “We want to create a marketplace where ideas around potential solutions can be shared and obstacles can be identified and addressed, be they business, legal, jurisdictional or otherwise,” he says. “Isda can facilitate discussions around some of the legal challenges and help with identifying technology opportunities.”

During a recent conference in London, Isda and its members agreed that the industry has to realize that the technologies per se are not going to benefit or even transform their sector. As Ansell puts it, “it’s all about finding the right parts of the derivatives ecosystem, where different technologies can be deployed most appropriately.”