This presents an opportunity as well as a challenge to the sell-side. If they can help their clients streamline and enhance workflows to reduce manual intervention, minimise errors, and accelerate trading and investment decisions, and if they can provide them with a way to lower operational costs while also enabling fast and profitable responses to market opportunities to better generate alpha, they can gain a serious competitive advantage.

Servicing the buy side ecosystem

With multi-asset strategies becoming more and more common, firms increasingly look to their sell-side providers to facilitate trading across a diverse range of instruments and asset classes through a single interface – whether UI or API – and to handle complex orders involving multiple instrument types, such as structured trades or multi-asset baskets for example, across different trading venues and diverse markets.

There is also an increasing emphasis on data-driven decision-making. While systematic and quantitative traders have always relied on data and models, fundamental and ‘quantamental’ firms are increasingly relying on data-driven insights to drive – or at least support – their investment and trading strategies. Firms now seek from their sell-side providers not only market data, analytics, and research, but also well-documented open APIs that allow them to seamlessly integrate such data into their proprietary models to inform and execute their trading strategies.

“The real challenge for the sell-side is adopting a technology strategy that balances their own internal needs with the ever-changing needs of their clients, one that effectively serves both,” observes Medan Gabbay, Chief Revenue Officer of multi-asset trading solutions vendor Quod Financial. “The buy side have their own technological ecosystem, made up of Portfolio Management Systems, Order Management Systems, applications for creating and managing trading strategies, various types of analytics tools, spreadsheet-based models, and a wide range of other systems they use in their day-to-day trading activities across the front, middle and back office. Forward-looking sell-side firms understand that a key part of their role is to facilitate this ecosystem, by using their technology to help clients trade their chosen markets in the way they want to trade them, as well as providing the necessary analytics and data in a format that helps them identify trading opportunities and manage their investment strategies.”

The key question for the sell side is, how to achieve the necessary agility in technology that will enable them to respond to the changing demands of their clients?

Moving beyond the buy-build debate

Several options exist. There are a number of well-established vendors who sell ‘off-the-shelf’ trading platforms, which can address many of the sell side’s needs. These platforms provide a range of essential features such as liquidity access, connectivity, order and execution management, analytics, and market data handling. However, while such off-the-shelf systems are generally adequate for day one requirements, they often lack the flexibility to rapidly adapt to changing customer needs and the dynamic nature of the markets. Firms relying solely on these platforms might therefore find themselves constantly behind the curve, limited as they are by their vendor’s upgrade and development cycles.

At the other end of the spectrum, firms may opt to build their own bespoke platforms tailored to their own specific requirements.  While this offers maximum control over the design and development process, it’s an expensive and complex undertaking, and is out of reach for most firms, other than tier one banks with substantial technology budgets.

A third option is becoming increasingly popular amongst forward-looking firms, that of buy and build. Vendor platforms that are built on modern, scalable, and adaptable technology, can be quickly deployed to meet a firm’s immediate needs and then adapted, customised and expanded as requirements evolve.

This type of approach offers various benefits, according to Gabbay. “Platforms built on this type of architecture are highly interoperable, easily integrating with other systems on both the front end – through desktop widgets for example – and the back end, through APIs. They are also much more scalable, capable of being deployed on hosted services including Cloud, on-premise, or a hybrid of the two, which leads to improved performance and better customisation to the clients specific infrastructure requirements. Additionally, being built around a component-based architecture, they offer flexibility and allow for rapid customisation, as individual modules can be created and adapted to suit specific customer requirements, new areas of functionality, evolving business processes, or changing regulatory and market structures.”

Gabbay points out that trading platforms architected in this way can also be more easily integrated with clients’ trading desks. This level of integration benefits both the client – for example through more efficient and transparent trade execution and real-time order/position monitoring – and the sell-side firm itself, by providing a better understanding and greater visibility of their clients’ activities and workflow.

For sell-side firms with limited resources, or those that believe their resources can be better invested in creating IP and not rebuilding existing technology, this approach can offer the best of both worlds – the rapid implementation and comprehensive functionality of a vendor platform, together with the flexibility, adaptability, scalability and capacity for integration of a custom-built solution. By adopting such an approach, a firm can distinguish itself from competitors who use generic or outdated vendor platforms, and compete more effectively with larger tier one banks that have developed their own solutions.

Artificial intelligence and machine learning

Another strategic choice for the sell-side is how to make best use of Artificial Intelligence (AI) and Machine Learning (ML). Although neither are new in Capital Markets, interest in AI has exploded since OpenAI introduced ChatGPT in November 2022. Since then, firms have identified a wide range of applications for Generative AI (GenAI) and the use of Large Language Models (LLMs).

One area where GenAI can add significant value in modern, component-based trading platforms, explains Gabbay, is its ability to accelerate the development and testing lifecycle, by automating coding processes and influencing all disciplines involved in defining, building, testing, operating, and supporting complex requirements. This allows firms to bring new functionality to market much more quickly than was previously possible.

“GenAI can generate test scenarios automatically by analysing the code base and understanding the purpose of different components,” he says. “It can then identify potential test cases, simulate different scenarios, and generate test data, thereby eliminating the need for manual test scenario creation. Additionally, by leveraging ML and AI algorithms, it can simulate user interactions, input test data, and validate the expected outputs. This automation reduces the reliance on manual testing, speeds up the testing process, saves time and effort, and improves overall efficiency.”

Outside of GenAI, modern trading platforms can also utilise ML within algorithmic trading, identifying and exploiting patterns in trade execution by analysing market conditions, liquidity, and order book dynamics. By scrutinising vast amounts of historical and real-time order book data to identify patterns and trends, ML-trained algorithms can determine the optimal timing, price, and quantity for executing trades, thus minimising transaction costs and market impact.

ML is also being increasingly used to develop intelligent Algo Wheels. These allow firms to analyse their incoming flow, so that the right execution strategies and order routing destinations can be automatically chosen, and optimised based on current market conditions and client-specific requirements.

Primary considerations for the sell side

Given the numerous challenges that sell-side firms face from a trading technology perspective, and the various choices they have available, what are the key considerations they need to take into account when evaluating trading platforms?

First of all, support and training are vital aspects of any technology implementation. Even the most intuitive platforms require a period of adaptation, and comprehensive training is crucial to maximise their potential. Vendors should provide robust support services to assist with both onboarding and continuous usage. This includes not only technical support but also strategic guidance to help teams leverage the platform’s full capabilities. Adequate training and support ensure that any investment in trading technology yields the maximum possible return.

Interoperability is another key factor. “A new trading platform should integrate seamlessly with existing systems to avoid operational disruptions,” advises Gabbay. “Ensuring smooth interoperability minimises the risk of data silos and ensures that all parts of your trading ecosystem can communicate effectively. This not only streamlines operations but also enhances data accuracy and decision-making processes.” Platforms that fail to integrate well can lead to significant headaches, requiring additional resources to bridge gaps between systems and potentially leading to costly errors.

Scalability is also essential for any trading platform. As trading volumes increase and new asset classes are added, the platform must scale efficiently to handle these changes. Scalability includes the ability to automate processes and manage higher trading volumes without performance degradation. “A scalable platform supports business growth by ensuring that system performance remains robust even as demands increase,” says Gabbay. “This scalability is not just about handling volume but also about expanding capabilities and accommodating new functionalities as trading strategies evolve.”

Flexibility around customisation is also important, according to Gabbay. “The platform should be capable of swiftly adapting to evolving workflows without causing bottlenecks,” he says. “Your technology shouldn’t become an obstacle, but a facilitator of change. Customisable platforms ensure that you can tailor the tools to meet specific trading needs.”

Key success factors

It’s clear that the dynamic nature of the buy-side presents both challenges and opportunities for sell-side firms. To stay competitive, banks and brokers need to consider a technology strategy that balances their internal needs with the ever-evolving demands of their clients. Whether choosing off-the-shelf platforms, bespoke solutions, or a hybrid approach, sell-side firms might want to prioritise agility, integration, and scalability in their technology stack.

Additionally, the strategic use of AI and ML can significantly enhance trading efficiency and decision-making processes. By embracing these advanced technologies and maintaining a flexible, client-centric approach, sell-side firms can not only meet the complex requirements of today’s market but also position themselves for sustained success in the future.

Robust support and training, seamless interoperability, and the ability to scale and customise are also critical factors that will determine the sell-side’s ability to capitalise on market opportunities and deliver superior value to their clients.

The post Evolving with the Market: Technology Strategies for Modern Sell Side Firms appeared first on A-Team.

The launch of EWIN represents a significant technological advancement for the exchange group. Developed in collaboration with McKay Brothers, the independent microwave network provider, and leveraging the faster transmission speeds of microwave technology, EWIN offers a direct and highly efficient communication pathway, reducing the time required to send orders from London Equinix LD4 to Euronext’s Optiq matching engine in Bergamo IT3 to under four milliseconds, around half the latency of existing fibre links. EWIN is also designed to ensure seamless and efficient order handling, offering 100% resilience, thanks to its full fibre back-up.

Major financial firms Goldman Sachs and Morgan Stanley have already adopted the new technology.

“After establishing our new IT3 data centre in Bergamo, near Milan, we realised from a few large tier-one brokers that they were interested in exploring the performance benefits of microwave technologies,” explains Nicolas Rivard, Global Head of Cash Equity and Data Services at Euronext, in conversation with TradingTech Insight. “Although microwave networks have been around for some time and are relatively established for certain participants, it is a costly and complex technology with a high barrier to entry. Typically, you cannot buy a small amount of bandwidth, which makes the solution expensive. Additionally, there is a technical aspect because you need to develop IT capabilities to route your orders through the microwave. By default, if you buy bandwidth from a microwave provider, it’s not plug-and-play; you need to develop your protocol into the technology.”

Euronext has worked closely with McKay Brothers to address these challenges, says Rivard. “To lower the barrier to entry in terms of cost, we have purchased a bulk of bandwidth and are offering it to clients in slices, starting from 1 Mbps upwards. This means that clients can try it for six months at 1 Mbps for example, and then scale up as needed, rather than committing to a costly solution from the outset. And to address the technical complexities, the solution we’ve developed together with McKay Brothers allows clients to use the microwave link as if it were any other standard connectivity, making it very plug-and-play.”

The microwave route, provided by McKay Brothers, has been operational for two years, since Euronext went live on IT3 in Bergamo in June 2022. But this is the first time McKay’s technology has been used to underpin an exchange’s own solution.

“The development and design of this service has been quite new compared to our usual offerings,” says Stéphane Tyc, Co-Founder of McKay Brothers. “Typically, when a client purchases microwave bandwidth, they need to undertake significant internal development to integrate with the network. However, Euronext’s end clients don’t need to perform any additional integration work; they simply need to set up logical access to Euronext’s matching engine, a process they are already familiar with. And then they can benefit from a fast network that competes with the microwave products used by market makers. The important thing here is that firms who want to use this link can now just go direct to the exchange to access it, without having to put in place dedicated technology.”

Given that microwave networks are susceptible to weather and other atmospheric conditions, how does Euronext ensure resiliency? “We have two routes, one microwave and one fibre, and they work seamlessly together,” says Rivard. “We have ensured, with McKay and our internal IT team, that every order gets sent twice, once via microwave and once via fibre. The first order that reaches the IT3 datacentre is processed, and the other is blocked by the system. This guarantees 100% redundancy, increasing the overall availability of the service.”

The link is now operational, with Morgan Stanley and Goldman Sachs having gone live on day one, 10th July. “The technology has delivered on its promise so far, with latency below four milliseconds and very stable performance,” says Rivard. “Clients are currently only sending specific order types via EWIN to improve certain latency sensitive execution strategies, such as IOC (immediate or cancel) and other aggressive orders. The number of packets going through the microwave is what we expected. And of course, this is just the beginning.”

Both Euronext and McKay Brothers talk of this new service as a way of further democratising the market, bridging the gap between prop trading firms/market makers and banks/brokers. So will it be rolled out to other European centres?

“First, we need to make sure it works from London, to prove that it has an impact and is beneficial for our clients. That will take a few months to confirm,” says Rivard. “But we already have clients interested in having the same service from other locations and asset classes in Europe.”

The post Euronext Launches EWIN Microwave Link Between London & Bergamo, Halving Order Transmission Latency appeared first on A-Team.

By integrating Boltzbit’s AI technology, Liquidnet can now offer members and partner syndicate banks faster access to trading and data distribution, processing and displaying bond deals at a rate significantly faster than its previous parsing technology. This ensures that bonds are quickly available through the company’s deal announcement dashboard and new issue order book.

“This partnership improves the speed at which we can process messages, create, and then send structured data directly to our clients, which in turn allows them to quickly populate their OMS and prepare for trading,” says Mark Russell, Head of Fixed Income Strategy at Liquidnet, in conversation with TradingTech Insight. “The quicker we can do this, the better it is for those clients. Beyond this, the clients of our new issue Trading Platform (grey market) benefit as we are able to launch the new bonds on the screen earlier, giving those clients earlier access and more time to trade.  More trading time on our visible trading platform means more transparent data points, which is very useful for the syndicates and issuers as they get a view as to what is going on in the market.

“Structuring the bond data is not done in a single step, during the bond creation process we need to interpret the market chat, back and forth messaging, that drives the final structure of the bond,” explains Russell. “Our system needs to be able to capture and update any changes to the meta-data, such as coupons, issuers, benchmark, maturity etc. that describe the bond and feed those changes into the trading platform and other information platforms.”

He continues: “We’ve automated this process extensively with our partners at Boltzbit, creating a tool that handles the heavy lifting of structuring this data into a comprehensible bond format. Our partnership with Boltzbit is focused on speeding up and enhancing accuracy, bypassing traditional parsing tools and leveraging artificial intelligence instead.”

Boltzbit’s GenAI technology utilises the data captured from messages exchanged across various mechanisms and channels to create a large language model (LLM) that transforms the information into a structured and usable format.

“This process might seem simple, but it was actually extremely challenging,” explains Dr Yichuan Zhang, CEO and co-founder at Boltzbit. “Firstly, it involves very complex business processes. It’s not just about parsing one email; understanding the context of the conversations and the associated business processes is essential. Secondly, this is a highly specific solution, requiring the model to be extremely accurate and to follow the precise logic of the business flow around new issues. Finally, the solution needed to be highly secure and deployed in a way that allowed Liquidnet full control.”

Since the launch of its primary markets offering in 2022, Liquidnet has achieved record trading volumes in its new issue order book and increased participation from over 35 European syndicate banks, highlighting the company’s commitment to modernising primary markets and delivering substantial value to clients and the industry.

In addition to partnering with Boltzbit, Liquidnet has previously collaborated with NowCM and BondAuction, reinforcing its dedication to fostering efficiencies and connectivity for investors, banks, and issuers through strategic partnerships.

The post Liquidnet and Boltzbit Collaborate, Utilising GenAI to Accelerate Bond Primary Markets Workflow by 90% appeared first on A-Team.

The facilities are aimed at helping firms address the post-trade implications of a Securities and Exchange Commission (SEC) July 2023 rulemaking that mandated central clearing for a wide range of U.S. Treasury (UST) securities transactions including cash, repurchase agreements (repos) and reverse repos.

The UST market sees daily transactions averaging over $700 billion in cash and $4.5 trillion in financing, making it vital for U.S. government funding, monetary policy, and as a safe haven for global investors. The market has grown rapidly and disproportionately where currently, 87% of this trading activity is cleared bilaterally.

Several liquidity events over the past decade highlighted vulnerabilities in the treasury market where the systemic risk of a non-participant failing required mitigating. The SEC’s final rule, adopted in December 2023, aims to expand central clearing to mitigate such counterparty and systemic risks.

The new rule seeks to transition a substantial portion of the daily US $4.9 trillion treasury market activity to central clearing through a central counterparty (CCP). Currently, the only authorised CCP for the UST market is FICC. However, other CCPs have expressed interest, among them London Clearing House (LCH).

Tools of the Trade

The first of the new FICC tools, a Capped Contingency Liquidity Facility (CCLF) Calculator, is designed to increase the transparency into the financial obligations associated with membership in the FICC Government Securities Division (GSD).

The CCLF is a critical risk management facility designed to provide FICC with additional liquidity resources to meet cash settlement obligations in the event of a default by the largest netting members (see DTCC Risk Management Tools). By allowing firms to estimate their potential CCLF obligations, the calculator aids in better liquidity planning and risk management. This can make FICC membership more attractive and manageable for a broader range of market participants, including smaller institutions and buy-side firms.

The calculator helps firms anticipate and plan for the liquidity commitments required under the new SEC clearing mandates. By providing upfront attestations regarding their ability to meet CCLF obligations, firms can ensure they are prepared to comply with the expanded central clearing requirements for U.S. Treasury securities.

Tim Hulse, Managing Director of Financial Risk & Governance at DTCC, emphasized that VaR is a key risk management concept and a primary component of GSD’s Clearing Fund requirements. The calculator uses historical data, volatility, and confidence levels to estimate VaR, thus enhancing market transparency. It allows market participants to calculate potential margin obligations for given positions and market values using FICC’s VaR methodology.

Hulse highlighted the urgency of evaluating firms’ risk exposure with the expansion of U.S. Treasury Clearing, noting that the VaR calculator offers increased transparency into these obligations.

These tools are public and not restricted to member firms This means that as firms consider their optimal approach to access central clearing for compliance with the the new clearing rules, these risk tools can provide the necessary transparency and support as firms evaluate the different types of membership and models with GSD.

The SEC has introduced several measures to make FICC access more inclusive. FICC offers multiple membership models, including Netting Membership, Agented Clearing, Sponsored Membership, and Centrally Cleared Institutional Triparty (CCIT) Membership, catering to a wide range of market participants from large banks to hedge funds. The SEC has provided temporary regulatory relief to address custody and diversification concerns for registered funds.

CCIT membership primarily benefits institutional cash lenders such as corporations, asset managers, insurance companies, sovereign wealth funds, pension funds, municipalities, and State treasuries. It allows these entities to engage in tri-party repo transactions with enhanced risk management and operational efficiency provided by FICC. The central clearing of these transactions helps reduce counterparty risk, ensure the completion of trades, and potentially offer balance sheet netting and capital relief for participants.

The Securities Industry and Financial Markets Association (SIFMA) is actively coordinating multiple work streams that involve both buy-side and sell-side members. These efforts aim to accelerate the necessary transitions for the clearing mandates. Key aspects include engaging with the SEC and other regulatory agencies to address market access issues, particularly for registered funds and margin transfers, which are crucial for ensuring a smooth transition to central clearing.

Developing an operations timeline with key milestones is another critical task. This timeline will guide the transition to full central clearing by June 2026 for repos. Addressing issues related to market plumbing and connectivity is also vital to support the increase from 13% to 100% clearing. This involves ensuring that all participants can effectively connect to and use the central clearing infrastructure.

Regular communication with market participants is planned to keep them informed about progress and strategies for meeting the clearing deadlines. This will include updates on the status of various strategies and the overall progress towards the deadlines. SIFMA will also engage in regular discussions with the SEC and other agencies to ensure they are aware of the progress and any potential needs for timeline adjustments or phased rollouts.

Legal and enforceability issues will be addressed by obtaining netting enforceability opinions in relevant jurisdictions to support large-scale clearing. This step is closely tied to the development of market standard documentation. Additionally, new documentation approaches that leverage modern communication methods will be evaluated to increase efficiency.

Stakeholder engagement is essential to confirm the status of various strategies and ensure alignment with the clearing deadlines. SIFMA plans to reach out to market participants regularly to keep them informed and engaged. This will help ensure that all participants are on track to meet the clearing mandates.

Lastly, future planning includes preparing for additional publications and podcasts to keep the membership and broader public informed about ongoing efforts around Treasury clearing. This will ensure that everyone remains updated on the progress and any developments related to the central clearing mandate.

The post DTCC FICC Releases Tools to Help Firms Address Incoming SEC Central Clearing Mandate appeared first on A-Team.

Earlier this year, OSTTRA partnered with Baton Systems to launch a new FX PvP (Payment vs Payment) settlement service, aimed at mitigating bilateral settlement risk in FX markets. This initiative is part of OSTTRA’s broader strategy to enhance the market structure of OTC markets and reduce counterparty exposures.

TradingTech Insight sat down recently with Joanna Davies, Head of Trade Processing, and Steven French, Head of FX and Securities Product Strategy, to discuss how this and other OSTTRA initiatives are addressing some of today’s most pressing post-trade challenges.

TTI: Jo, what are some of the key trends and challenges you are seeing in the post-trade space, particularly with the transition to T+1 settlement?

JD: The realm of post-trade activities is no longer confined to the back office but is increasingly impacting front-office operations. This shift is evident in the transition to T+1 settlement, which has underscored the critical importance of efficient post-trade processes. Traditionally, areas such as liquidity management, credit risk, and liquidity provision were handled separately from post-trade operations. However, with the advent of automation in these domains, there is a growing convergence. The T+1 settlement initiative has illustrated the necessity for robust infrastructure and comprehensive risk management strategies. While there are differing views on the industry’s preparedness—whether it was a result of meticulous planning or the inherent flexibility of existing systems—the transition has undeniably focused attention on post-trade processes. Significant efforts have been dedicated to preparation, especially in managing settlement risk and liquidity provision. The integration of these functions into the front office highlights the evolving landscape where post-trade efficiency is paramount to overall financial operations.

TTI: Steve, where are the main areas of settlement risk, and how is OSTTRA helping the industry mitigate these risks?

SF: The significant daily risk of FX settlement outside of Continuous Linked Settlement (CLS) is a pressing concern, given the estimated daily exposure of $2.3 trillion settled outside the utility today. This substantial risk is particularly pronounced for emerging market currencies, which struggle due to the absence of a suitable settlement platform. The infrastructure and legal complexities required to establish such a platform are substantial, creating barriers to adoption.

Addressing this issue, OSTTRA, in collaboration with Baton Systems, has developed an innovative PvP (Payment vs Payment) settlement orchestration platform specifically targeting non-CLS currencies. The initial focus is on the Chinese yuan (CNH), with major banks such as HSBC and Wells Fargo already onboard. This platform aims to mitigate settlement risk by providing a structured and reliable solution for managing PvP settlement of these currencies, paving the way for broader participation and increased security in the settlement process. By targeting these high-risk areas first, OSTTRA and Baton Systems are setting the foundation for a more secure and efficient global settlement infrastructure.

TTI: What kind of appetite is there for such a new settlement infrastructure?

SF: There is a strong industry interest in reducing settlement risk, demonstrated by the active participation of multiple banks in discussions aimed at expanding the new settlement platform. Recently, we convened a working group and are open to adding any other participants eager to collaborate on this initiative to join. The discussions to date have moved beyond the feasibility of the platform and are now focused on practical steps for implementation, such as how to onboard and make the system work effectively.

Achieving critical mass is seen as essential, with the participation of a few additional major banks likely to drive broader adoption across the industry. Currently, HSBC and Wells Fargo are already on the platform, and the inclusion of just two or three more major players could significantly move the needle.

The primary hurdles to adoption are not technical but involve changes in treasury operations, particularly concerning the management and agreement of nostro accounts. Overcoming these operational challenges is key to leveraging the already established network and technological infrastructure, thereby facilitating a smoother and quicker transition to the new system.

TTI: Can you both provide more details on your technology initiatives, particularly the integration between OSTTRA and Baton Systems?

SF: Essentially we’re leveraging OSTTRA’s robust matching engine in conjunction with Baton’s advanced shared ledger technology, to ensure secure and efficient settlement processes, which are critical. The matching engine, which has been thoroughly tested and widely adopted, is now connected to Baton’s next-generation shared ledger, which provides atomic settlement -. This means that PvP transactions will only be executed once both parties have agreed, thus ensuring transaction finality.

JD: We are also developing advanced tools designed to identify and resolve trade breaks proactively. Recognising the inefficiencies of current processes, where the resolution of trade discrepancies often involves manual communication and guesswork, we’re leveraging artificial intelligence (AI) and historical data analysis to predict and manage trade failures. By integrating enhanced monitoring and exception management, this adds crucial context to trade data, allowing for a more accurate diagnosis of where and why a trade might fail. This innovative approach provides an understanding of the specific conditions leading to trade disruptions. By analysing past trading volumes and incorporating real-time feeds, OSTTRA can forecast spikes in trading activity and pre-emptively address potential issues. This proactive and context-rich method marks a significant advancement in post-trade processes, reducing settlement risk and operational inefficiencies, and ultimately providing a more reliable and transparent trading environment.

We are also enhancing the synergy between pre-trade and post-trade services by expanding the asset classes supported by our sophisticated pre-trade limit checking service initially designed for interest rate swaps and credit default swaps. This service ensures low-latency risk checks are performed before orders are sent to the market, helping to address a client’s regulatory requirements and minimising potential risks. Developed in response to the CFTC Dodd-Frank requirements and EU regulations for MTFs, this unique solution has been operational for over a decade, continuously evolving to support additional asset classes such as FX. By integrating pre-trade and post-trade services, OSTTRA aims to provide a comprehensive end-to-end solution that significantly enhances transparency and operational efficiency. This integration allows for seamless monitoring and management of trades throughout their lifecycle, from order initiation to settlement, ensuring a high level of accuracy and reducing the risk of trade failures.

TTI: Looking ahead, what role might distributed ledger technology (DLT) and decentralised finance (DeFi) play in the future of post-trade?

JD:  We continue to maintain a watchful eye on the developments in DLT, blockchain and DeFi, recognising their potential while remaining cautious about adopting these technologies until they are fully production-ready. In contrast to many industry peers who have proposed various blockchain use cases that are not yet ready for real-world application, OSTTRA has identified a practical and viable use case for blockchain in change of ownership scenarios. This particular use case is advantageous as it circumvents the common issues of latency and throughput, providing a more efficient solution.

By utilising an extensible architecture, OSTTRA is prepared to leverage blockchain technology in a manner that is both practical and forward-thinking. This approach not only addresses current operational challenges but also positions the company to explore and integrate other asset classes in the future. As blockchain and DeFi technologies continue to evolve, we remain committed to evaluating and implementing these innovations in a measured and strategic manner, ensuring they meet the rigorous demands of production environments.

TTI: Thank you both.

The post Post-Trade Evolution: Insights from OSTTRA’s Leadership on Industry Challenges appeared first on A-Team.

“It’s crucial for people to understand what we’re measuring, as context is important with such low numbers,” Olivier Cousin, Director of FGPA Solutions at Exegy, tells TradingTech Insight. “The STAC T0 report measures the latency of a system ingesting UDP and sending TCP frames. This covers the typical market data tick-to-order flow. The main value of this report lies in what is called ‘actionable latency,’ or reaction time. When a UDP frame contains a specific field, such as a price, which triggers an action, the clock starts only when that specific field (i.e. a price) enters the FPGA, not at the beginning of the UDP frame. We measure the time from this point until the TCP order exits the FPGA. With this benchmark, we are showcasing that the latency induced by the handling of 10Gbs Ethernet went from 24.2ns to 13.9ns with the new AMD card, which includes hardened MAC/PCS.”

Exegy claims to be the only capital markets technology provider offering a comprehensive FPGA development framework specifically tailored for ultra-low latency financial applications. Exegy’s nxFramework standardises the development of FPGA-based trading platforms, allowing developers to focus on optimising their core business logic. Exegy’s offering includes reference designs, expertise, and support, facilitating a faster time-to-production for firms developing ultra-low latency trading systems.

The production-proven FPGA development framework provides clients with reference designs to manage a wide range of applications, including pre-trade risk check gateways and tick-to-trade electronic trading platforms. The collaboration with AMD combines innovative hardware with production-tested applications, delivering groundbreaking performance through an off-the-shelf solution that ensures the lowest possible latency.

“There are two main innovations that contribute to this achievement,” says Cousin. “Typically, within an FPGA, there are resources that handle the 10 Gig connectivity. AMD’s innovation is their AMD Alveo UL3524 accelerator card, which involves hard-wiring the logic that deals with the 10 Gig protocol into the ASIC, rather the FPGA, which still has to manage all the network layers above Ethernet. This innovation is a contributing factor to the 49% latency reduction.”

He continues: “Exegy’s innovation lies in creating a UDP stack, TCP stack, and logic that processes the data and sends orders, all with zero latency in the FPGA. There are no clock cycles used for this critical path, achieving the absolute minimum latency as the FPGA processes the data in less than a clock cycle. Our nxFramework includes a full UDP stack for examining UDP traffic and a full TCP stack that supports the complete TCP protocol. For instance, if the exchange requests a TCP fragment to be resent, the TCP stack will resend it. The system is entirely self-contained and operates exclusively in hardware.”

The significant reduction in tick-to-trade execution latency underscores the success of Exegy’s partnership with AMD, which began last year, and demonstrates the company’s ongoing commitment to minimising latency. The collaboration leverages hardware acceleration, FPGA flexibility, and low-latency networking to ensure high performance and determinism. The Exegy team achieved precise testing measurements, reducing jitter to 200 picoseconds—up to 10 times lower than previous benchmarks—thus ensuring the accuracy of the STAC-T0 results. Existing Exegy customers, as part of their subscription, received updates to the IP cores that enabled this latency record.

“The value we demonstrate with this report is that the nxFramework highlights the lowest achievable latency with the FPGA technology currently available in the industry, and we assist our customers in attaining this performance,” says Cousin. “With the addition of support for this AMD card, customers can migrate their code with minimal development time. Customers using our nxFramework solution can purchase this card and migrate their design to systematically achieve the lowest possible latency.”

STAC benchmarks are the industry standard for evaluating solutions that enable high-speed analytics on time-series tick data. The STAC-T0 benchmark, which uses industry-standard hardware, making it fully transparent and reproducible, specifically assesses tick-to-trade network-I/O latency. The previous lowest benchmark speed of 24.2 nanoseconds was also achieved using AMD accelerators.

The post Exegy and AMD Achieve Record-Breaking Tick-to-Trade Latency in STAC-T0 Benchmark appeared first on A-Team.

Considering the use of GenAI, an early audience poll question asked to what extent organisations are committed to GenAI applications. Some 46% said they are testing GenAI apps, 24% are using one or two apps, and 20% are using a number of apps. Nine percent are researching GenAI and 2% say there is nothing in the technology for them.

Value of GenAI applications

A second poll questioned which GenAI applications would be of most value to a delegate’s organisation. In this case, 53% of respondents cited predictive analytics, 39% risk assessment, 39% KYC automation, 28% fraud detection and 19% portfolio management.

The panel shared their own use cases, with one member experimenting with GenAI to produce programming code and creating an internal chat box for data migration, as well as scanning data to surface information that can be categorised, sorted, filtered and summarised to create ‘kind of conversational extracts that can be used.’

All agreed that GenAI produces some low hanging fruit, particularly in operational activities such as KYC automation, but that the technology is too young for many applications, leading firms to build capability internally before unleashing GenAI apps for customers as there is still work to do around issues such as risk integration and ensuring copyright and data protection are not compromised. One speaker said: “There is a lot of experimentation and some research to do before we’re confident that we can use this at scale.” Another added: “There are just not enough skilled people to allow us to push hard, even if we wanted to. There’s a real pinch point in terms of skills here.”

Risks of adopting GenAI

Turning to risk, a third audience poll asked the audience what it considered to be the biggest risk around adopting GenAI. Here data quality was a clear leader, followed by lack of explainability, hallucinations, data privacy and potential misuse. Considering these results, a speaker commented: “We’ve already got existing policies and governance frameworks to manage traditional AI. We should be using those to better effect, perhaps in response to people identifying data quality as one of the key risks.”

The benefits of AI and GenAI include personalisation that can deliver better products to consumers and improve the way in which they interact with technology. From a regulatory perspective, the technologies are focused on reducing financial crime and money laundering, and resulting enforcements against fraudulent activity.

On the downside, the challenges that come with AI technologies are many and include ethical risk and bias, which needs to be addressed and mitigated. One speaker explained: “We have a data science lifecycle. At the beginning of this we have a piece around the ethical risk of problem conception. Throughout the lifecycle stages our data scientists, machine learning engineers and future engineers have access to python libraries so that when they test models, things like bias and fairness are surfaced. We can then see and remediate any issues during the development phase so that by the time models come to validation and risk management we can demonstrate all the good stuff we’ve done.” Which leads us to the need, at least in the short term, for a human element for verification and quality assurance of GenAI models in their infancy.

Getting skills right

Skills were also discussed, with one panel member saying: “We are living in a constantly more complex world, no organisation can claim that all its workforce has the skill set necessary for AI and GenAI, but ultimately I am hopeful that we are going to create more jobs than we are going to destroy, although the shift is not going to be easy.” Another said: “In compliance, we will be able to move people away from being data and document gatherers and assessors of data in a manual way to understand risk models, have a better capability and play a more interesting part.”

Taking a step back and a final look at the potential of GenAI, a speaker concluded: “Figuring out how to make safe products that we can offer to our customers is the only way we have a chance of reaching any sort of utopian conclusion. We must chart the right course for society and for people at work, because we’re all going to be affected by generative AI.”

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TTI: Stephen, can you elaborate on the rationale behind introducing usage-based pricing and risk-free trials in G8? How do these changes help clients better understand the value scaling of your platform and benefit from its flexibility and cost efficiency in developing and deploying trading technologies?

SM: Our aim with the usage-based pricing was to disrupt the traditional pricing model. Our platform accelerates development, allowing applications to be built in days rather than months or years. However, with traditional pricing, it can be challenging for clients to understand how such value scales from an MVP to a full production system. We explored various pricing models and, by reverse engineering our previous pricing for other trading technology solutions, we found that usage-based pricing based on virtual CPUs was the most effective metric. This approach resonates with clients because the need for more CPUs correlates with the complexity, number of users, or volume of transactions, aligning with their perception of the platform’s value. And it follows a tiered consumption model: from 0 to 10 CPUs, it’s $x per CPU; from 10 to 25, it’s $x minus 20%, and so on, so as usage increases, the per-CPU price decreases.

With the risk-free trials, we now offer a trial period with a nominal developer charge, meaning clients only incur costs at runtime, whether in a test or production environment. Our clients appreciate this low-risk, low-cost way to prototype and test new ideas quickly.

It’s also important to note that our platform is cloud-agnostic. Clients can run it on their private virtual machines, on-prem infrastructure, in their private cloud, or on public clouds like Amazon, Google, or Microsoft. Clients value this flexibility, as it allows for a multi-cloud strategy without incurring substantial fixed costs from a single cloud vendor. This also enables them to back up against different cloud providers.

TTI: Can you explain the different categories within the new Genesis Marketplace in G8 and how each category helps expedite the creation of trading and risk management applications in financial markets?

SM: The Marketplace comprises three different categories. The first category includes off-the-shelf solutions, such as the Trade Allocation Manager (TAM), a post-trade allocation confirmation system, and the Automated Quoting System (AQS), a multi-asset class quoting application that supports RFQ business flows between investment firms and their treasury desks or broker-dealers. We are continually expanding these solutions. The second category consists of specific industry vendor integrations, such as Bloomberg TOMS. The third category is what we call components, which perform specific functions commonly found in financial applications.  These are a combination of integration and workflow and include things like alerts, reporting, user management and FIX gateways.

When you use our platform, you have access to all three categories within the Marketplace. We are heavily investing in expanding the Marketplace so developers can utilise these components, with only a nominal developer fee, and pay based on CPU usage. We see this as a significant disruption to the traditional buy versus build paradigm.

TTI: How do your strategic partnerships with major financial institutions like Bank of America, BNY Mellon, and Citi influence the development direction of the Genesis platform? Can you elaborate on their role in shaping your product offerings and training initiatives?

SM: They play a crucial role. We have a strategic investor forum with these partners every six weeks, where they help guide our platform roadmap based on feedback from all our clients. We gather extensive input from clients about the functionalities and solutions they are building, or would like us to build within the platform, giving us a comprehensive understanding of their needs.

Accessibility and ease of use are major priorities for our partners because they want to get large groups of developers on Genesis.  So we’ve focused heavily on our training program, the Genesis Academy. Initially, we were doing a lot of the development work for our clients ourselves, but this has now shifted significantly. Our investors provided invaluable feedback on training materials, documentation, certification programmes, and what we call developer enablement and evangelism. They also wanted the ability to scale through their systems integrators and consulting partners, so we’ve collaborated with these parties to enable them to use the platform effectively.

A lot of the feedback revolves around the tools they want to see in the platform product roadmap, as each partner has different requirements. For instance, BNY Mellon, the largest custodian in the world, is using the platform to drive new business innovation. Citi and Bank of America are exploring how the platform can support new consortium opportunities or innovate around existing consortia.

Regarding tooling, we’ve recently released Genesis Create, a web-based tool that allows users to create new applications in minutes, and Genesis View, which enables rapid UI development by converting screenshots into UI code, using generative AI. It’s immensely valuable to have strategic investors who are deeply invested in our technology roadmap.

TTI: G8 includes enhancements in desktop interoperability and improved FDC3 support. How do these enhancements facilitate better integration and communication between different trading systems and platforms, and what role do open APIs play in this process?

There’s a lot happening around desktop interoperability, and interoperability in general. All our UI components are FDC3-ready out of the box. We are completely vendor-agnostic, working seamlessly with platforms such as OpenFin and interop.io on the desktop interoperability side, where we continue to expand our FDC3 capabilities. And with Genesis Create, you can enable FDC3 for your UI components from the outset.

We’ve always maintained an open approach, with open APIs from the beginning. On the server side, our technology integrates with various vendor systems such as Murex, Calypso, Fidessa, TT, ION, SS&C, Bloomberg, and Symphony. Whether it’s server-side data integration or technical APIs like REST and MQ, we ensure quick data transfer. Additionally, we support industry-specific protocols such as FIX and SWIFT, maintaining openness and flexibility across our platform.

TTI: What impact have the free trials and training had on client adoption, and how are consulting partners contributing to this new approach?

SM: We’ve received excellent feedback from our current clients, many of whom previously used our managed applications or products. They’ve expressed that they always wanted to use the platform, and now, with no real barriers to entry, they can. They can start using it for free, get comprehensive training, and access the Marketplace. They are only charged at runtime, once they see the value in a test or production environment. We’ve also engaged with new clients who had heard about us but hadn’t interacted with us before. They now understand how to engage with us, and clients who weren’t platform users but had specific solutions built by us can now see how scalable and user-friendly our technology is, thanks to the tooling and extensive training materials we provide. The pricing model also makes sense to them.

We also collaborate closely with consulting partners, who find this proposition very appealing. Previously, they focused solely on the professional services aspect, but now they can also participate in revenue shares by introducing new clients and implementing solutions for them. This approach encourages the entire industry to think differently about the buy versus build dilemma, or what we now call ‘buy to build’. This model allows clients to enjoy the benefits of both buying a solution and having the flexibility to build on it. This concept has really resonated with our client base.

TTI: To wrap up, where do you see the most significant opportunities for software innovation in the financial markets industry, and how does Genesis help firms address their innovation backlogs?

SM: There are several areas, but I’ll highlight two key ones. Firstly, there’s a significant focus on replacing spreadsheets and end-user computing systems. This process can be very complex because it’s not just about the spreadsheets themselves but also the workflows and how these spreadsheets are communicated within an organisation. These systems often have numerous integrations, with data being uploaded and downloaded between different systems. We see a lot of work in this area.

Another critical area is vendor consolidation. We frequently get asked if we can replace a specific vendor. However, rather than simply ripping and replacing existing systems, we excel at what we call ‘vendor scaffolding’. This approach involves integrating our technology on top of, next to, below, or around existing vendor technologies. It enables clients to start innovating quickly around their current technology stacks. Additionally, this method allows for the clean-up and optimisation of the existing vendor technology implementation. Vendor scaffolding is a significant use case because it enables clients to innovate rapidly without the substantial risk of replacing entire systems.

TTI: Thank you, Stephen

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Opening the summit and introduced by A-Team president and chief content officer Andrew Delaney, Edward J. Achter from the office of applied AI at HSBC set the scene for the day, noting the need to build AI and GenAI products that are responsible and ethical and can be scaled, and describing the importance of educating and engaging the workforce to ensure solutions are used effectively and ethically.

In more detail, the keynote speaker explained the explosion of interest in AI and GenAI following the release of ChatGPT and a change in conversation at financial institutions. He also warned of risks inherent to the technology including fairness and bias, data privacy, and the deliberate spread of false information. To mitigate risk and create value, Achter emphasised the need to get your data house in order and, perhaps a long time in the asking, pay attention to data leaders as data is the lifeblood of AI and GenAI applications.

Also important to consider are regulatory requirements around AI and GenAI, addressing the carbon emission costs of using LLMs, and perhaps most importantly, writing a clear company policy that can be shared with all stakeholders. Demonstrating the benefits of AI and GenAI products can turn scepticism into an understanding of benefits, including productivity gains that can be measured, and change negative perspectives into positive approaches to doing more with the technology.

Ultimately, a skilled workforce, educated customers, technology used in the right context of conduct, and confidence across the organisation will result in value creation.

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TT Trade Surveillance, powered by TT’s proprietary SCORE machine learning algorithm, expands the company’s surveillance capabilities across multiple asset classes, including equities, options, FX, and fixed income. The company plans to start upgrading all users of its existing trade surveillance platforms, TT Score and Compliance Plus, to the new TT Trade Surveillance system, which includes 47 new configurable models to detect manipulative trading activities, in the second half or 2024.

“TT Score, a futures and options surveillance platform based on machine learning, is a product that TT has offered for several years. Last summer we acquired Abel Noser, which also has an equities surveillance platform called Compliance Plus,” says Ted Morgan, Trading Technologies EVP Managing Director, Compliance, in conversation with TradingTech Insight. “Over the past year, we have been combining the best features of these two platforms, addressing any gaps, and developing TT Trade Surveillance, our new platform due to be launched on 1st July, which will offer comprehensive multi-asset class trade surveillance, covering not only equities, futures, and options, but also other instruments such as foreign exchange and fixed income. It will also feature enhanced case management capabilities, extended graphing and charting, and will include all necessary market data for comprehensive surveillance. Assembling that across multiple asset classes has not been a small project, so this is a big step forward for us.”

Included in the new TT Trade Surveillance platform will be front-end functionality that allow users to adjust settings and thresholds that pertain to particular models so that they can be run on any subset of data they want to filter, such as defining parameters differently for specific countries or distinguishing between retail and institutional flow.

TT Futures TCA, the company’s new comprehensive transaction cost analysis tool that also builds on TT’s August 2023 acquisition of Abel Noser, leverages an extensive repository of anonymised, microsecond-level futures market and trade data to provide extensive metrics and measures for detailed post-trade analysis, aiming to fill the gap in TCA tools tailored for futures trading.

“Abel Noser were pioneers in transaction cost analysis (TCA), primarily in the equities markets, but increasingly expanding into FX, futures, and fixed income,” says Peter Weiler, TT’s EVP Managing Director, Data & Analytics, and Abel Noser CEO. “The merger with TT brings significantly enhanced market data. We now have large, anonymised sample sets of trading data that we can compare against that market data. We have also expanded our metrics beyond traditional equities benchmarks like VWAP and implementation shortfall, to include those critical in the futures market, such as quote data, depth of book, sweep orders, and so on. With this integration, we’ve also improved our front end’s functionality with additional analytics, enhanced charting capabilities, and executive summary reports.”

The new TT Futures TCA capability allows users to select from a variety of customisable reports to analyse and enhance their trading strategies while assessing the effectiveness of their trading counterparties. This capability is available now and will be integrated into the TT platform as a front-end widget in early 2025. The customised analytics will be accessible to clients based on their desired metrics, breadth, and level of granularity.

“The front-end widget will display all trade data and measured data in one place, providing comprehensive transaction cost analysis across asset classes, even if you don’t trade exclusively through Trading Technologies,” says Weiler. “This integration will bring together cash equities with options, options on futures, buy/writes, strangles, straddles, and more.”

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