SIX, a global data aggregator and operator of exchanges in its native Switzerland, as well as in Spain, has released a flurry of new data products since January, including a suite of ESG tools and two global equities index families that herald a plan to become a one-stop-shop for ETFs.

According to Leslie, the frenetic pace of partnerships, product releases and enhancements this year is just the tip of the iceberg. The Zurich-based, bank-owned organisation has more to come, all built around a trove of data and data capabilities it has built up over more than 90 years of operations.

At heart, it remains a global pricing reference data provider – that’s the “base data” that SIX “is built on”, says Leslie. But the company is putting in place ambitious plans to leverage that core data competency to meet the increasingly complex demands and use cases of financial institutions.

“I believe that the fundamental data set – having really good-quality reference data and pricing data – allows us to create new value-added services and insights to our clients, and that remains the same whether we’re talking about GenAI or good old fashioned master reference,” Leslie tells Data Management Insight from SIX’s offices in London. “Unless you’ve got those basics you can’t really make sensible decisions, let alone produce reliable analytics.”

Expansion Plans

Leslie says SIX sees its USP as the ability to leverage that core data product to create applications for a multiplicity of use cases. Already it is using its fundamental datasets as the backbone of regulatory, corporate actions, tax, sanctions and ESG products for its banking clients.

A slew of recent acquisitions, investments and partnerships have been similarly guided by SIX’s programme of creating services that can tap into its core offering. The purchase of ULTUMUS in 2021 and the deepening of a long-standing association with BITA earlier this year were part of a plan to forge the company’s ETF-servicing business, each deal enhancing SIX’s indexing capabilities.

In ESG too, it has been aggressively striking deals to help burnish a slate of new sustainability offerings. Products unveiled in the past year by ESG product strategy and management head Martina MacPherson all benefit from supply deals struck with vendors including Sustainalytics, MSCI, Inrate and the CDP, as well as new partnerships with companies including Greenomy. Among the ESG products launched recently is an SME assessment tool, which MacPherson said will bring thousands of smaller companies into the ESG data ecosystem, into which banks and investors might otherwise have had no visibility.

Working Data

SIX’s ESG provisions illustrate what Leslie describes as the company’s dedication to making data work for companies.

“Organisations need to figure out how they’re going to incorporate data and how they’re going to make it relevant,” she says. “Well, the only way you can make it relevant is if it’s got something to hook on to, and that’s where you get back to those fundamental data sets.”

Leslie explains that one of the driving forces behind the company’s vigorous expansion plans is the changing demands for data among banks. No longer can any part of the industry rely on end-of-day pricing data, or monthly and quarterly reports. Ditto for risk managers and compliance teams.

The consequence has been a shift in the workloads of the front-, middle- and back-offices. No longer is research the premise of middle-office teams, Leslie offers as an example; the front office needs those insights quicker and so it has made sense for banks to embed data access and functionality within asset managers own analytical workflows.

“Asset managers see that the speed of data is increasing all the time and so the buy side, which was perhaps in the past much more built around end-of-day or less immediate requirements, is moving much more into real-time and intraday needs,” she says. “That requires, therefore, real-time market data, and that is expected by regulators, it’s expected by customers, and its therefore expected by market participants.”

AI Challenge

Jokingly, Leslie likens data operations to raising a child: it needs constant attention and feeding to grow and thrive. The simile is just as true for banks’ data management needs too; they are constantly changing and growing, influenced by internal needs and external innovations. That’s exemplified by the race to integrate artificial intelligence (AI) into processes and workflows.

Recent SIX research found that more than nine out of 10 asset managers expect to be using AI within the next three years and that half already do. Driven by its own clients’ need to understand what AI will mean to them, SIX has begun looking at how it can enhance its products with the various forms of AI available.

It has taken a structured approach to the programme and is looking at where AI can help clients improve efficiency and productivity; examining how it can improve customer experience and support; and, testing how it can be incorporated into products. For the latter, SIX is experimenting with off-the-shelf GenAI technology to identify aberrations in trading patterns within a market abuse solution.

On this subject, too, Leslie stresses that SIX can only think about such an evolution because it is confident that it has a solid foundational data offering.

“Our role is to make sure that we’re providing data that is fit for purpose and enables our clients to do business in a competitive way,” she says. “So that will include, as it always has, providing trusted, reliable data that the client knows is fit for purpose and on which they can make decisions. And that’s as true if it’s going to an AI model as if it’s going into a client digital wealth platform or portfolio reporting or risk solution.”

Values Align

Leslie took up her latest role at SIX in 2020 and also is a member of the board for the SIX-owned Grupo BME, Spain’s stock exchange, previously holding roles at LSEG and Thomson Reuters.

She is proud to be part of an organisation whose stakeholders are banks – about 120 of them – and not shareholders “trying to race to hit a quarter result”. She feels a very strong alignment with its values, too.

“It’s an organisation whose purpose is to enable the smooth functioning of the economy and has consistency and trust at the very core,” she says. “When half the world is voting this year, this stuff’s important, and when we’re talking about AI, or we’re talking about market failures then the thing that brings trust and progress is the data that sits behind it. To be a trusted provider in this day-and-age is a critical service.”

The post Building Future Growth Around a Foundational Data Core: SIX’s Marion Leslie 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.”

The post Practicalities of Implementing GenAI in Capital Markets appeared first on A-Team.

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.

The post AI in Capital Markets Summit Tracks Evolution of GenAI and Value Creation appeared first on A-Team.

Advancements in technology and data analytics have led to more detailed, granular, and multi-dimensional TCA, which now considers factors such as order size, market conditions, and timing. Buy-side firms are increasingly using TCA to assess broker performance and optimise trading strategies, integrating real-time data for immediate feedback on trading performance. There is now a greater emphasis on pre-trade, intra-trade, and post-trade analysis, with the growth of custom benchmarks and sophisticated statistical models to better capture trading costs.

TCA is now being more broadly adopted across different asset classes, including fixed income, derivatives, and FX. Machine learning and AI are being incorporated into TCA models for predictive analytics, improved accuracy, and adaptive algorithms. The future of TCA will likely continue to innovate, leveraging new technologies and expanding its application across diverse financial instruments and markets.

TradingTech Insight has compiled a list of the top TCA solutions to consider in 2024. This list is based on a combination of A-Team Group research and entries, along with voting by our readership of TCA solution providers in our recent TradingTech Insight Awards USA and TradingTech Insight Awards Europe.

OneTick

Winner of Best TCA Solution 2024 in both our Trading Tech Insight Awards (Europe) and Trading Tech Insight Awards (US)

OneTick’s Best Execution (BestEx) and Transaction Cost Analysis (TCA) solution offers comprehensive tools for evaluating and optimizing trading performance. It measures execution algorithm performance, breaking down results by market and order characteristics, and checks for spread capture and front-running. The solution compares execution venues, includes venue-specific fees, and provides detailed slippage and spread capture metrics. It supports regulatory reporting (RTS 27/28, 605/606) and offers customizable TCA reports. Users can visualize trends, identify outliers, and analyze client flow toxicity. The hosted research environment and TCA API facilitate market data analytics with pre-configured functions and a powerful Python API. Additionally, pre-trade TCA insights and machine learning capabilities enhance decision-making and model management.

https://info.onetick.com/

Adroit Trading Technologies

Cross-asset TCA is native to Adroit’s buy-side EMS, capturing the entire market context at each step of voice and e-traded orders, from order creation and trade execution to post-trade.  With a single click, users can generate reports to demonstrate best execution and fairness across accounts. Adroit’s pre- and post-trade analysis incorporates disparate data types, including streamed quotes, firm responses to RFQs, evaluated prices, publicly reported trades, and ETF prices. Adroit’s focus is on OTC FICC, across cash and derivatives.

https://www.adroit-tt.com/

big xyt

big xyt’s Open TCA is an “analytics as a service” solution, built on a very powerful and efficient technology stack, and is accessible via web-based front-ends and APIs where derived data can be extracted and additional analysis can be performed. Pre- and post-trade TCA has to manage increasingly complex datasets at previously unmeasurable levels of granularity. This is a challenge for every buy- and sell-side firm.

big xyt harvests, stores and normalises granular data sets across 120 global markets (across equities, ETFs, listed derivatives and FX). With Open TCA, users can interrogate those datasets to estimate clients’ pre-trade costs, benchmark their trading when they executed, and calculate the cost when they did not.

As a privately owned company with no trading activities, big xyt is an unbiased and objective provider of data analysis. Clients and regulators see independence as an essential ingredient to avoid conflicts of interest or unnecessary leakage of information.

https://big-xyt.com/

Bloomberg

Bloomberg BTCA delivers robust multi-asset transaction cost analysis harnessing Bloomberg’s global market data across a wide range of trading benchmarks. BTCA offers impactful trading insights that help clients create and monitor optimal trading and execution strategies. Using BTCA’s powerful exception-based workflows, traders can efficiently meet a firm’s compliance and execution policies through granular analysis of the entire trade flow life cycle.

https://www.bloomberg.com/

eflow

eflow’s TZBE platform is a highly configurable platform that automates best execution tests, enriches trade data with market data curated from more than 250 sources, and generates highly granular TCA reporting. TZBE also generates valuable commercial insights by highlighting how a firm’s trading strategy can be executed more effectively.

The system automatically ingests data, tests against all core industry benchmarks, and reports on all instrument types and asset classes. Customisable parameters can be refined to mirror specific trading strategies, automatically accounting for variables and reducing false positives. TZBE also includes data archiving and indexing that complies with MiFID II and all other global regulations as standard, ensuring that you are one step ahead of your reporting obligations.

https://eflowglobal.com/

KX

KX accelerates the speed of data and AI-driven business innovation. Time series and vector data management are at the heart of the company’s products, which are independently benchmarked as the fastest on the market. KX’s customers process data at unmatched speed and scale and empower quantitative researchers and data scientists to launch, configure, run, and scale the most important capital markets analytics and AI workloads, such as options pricing, transaction cost analysis, and back-testing

KX technology enables the discovery of richer, actionable insights for faster decision making which drives competitive advantage and transformative growth for our customers.

https://kx.com/solutions/trading-analytics/

LIST

LIST’s Transaction Cost Analysis (TCA) is part of the ION LookOut product suite. ION LookOut TCA is designed to calculate over 80 key performance / cost metrics (KPM) to provide post-trade execution performance analytics to buy-side and sell-side investment firms. The calculated KPMs include execution statistics like participation rates, execution style, spread capture and venues distribution; execution benchmarks like VWAP and implementation shortfall; market status like prices, momenta, ADV, volatility, slippage, and reversions; and implicit costs like delay, spread, market impact, timing, and opportunity. ION LookOut TCA supports pre-configured and customizable reports that can be exported in various formats.

https://www.list-group.com/list-lookout/

Quod Financial

Quod Financial’s TCA stands out as one of the best in the capital markets due to its comprehensive real-time analytics and machine learning capabilities. The platform provides actionable insights, enabling traders to monitor and optimize execution performance instantly. Its unique integration of TCA outputs into OMS/EMS systems allows for immediate adjustments and improved trading strategies. Quod’s TCA offers pre-trade and post-trade analysis, robust benchmarking, and compliance with MiFID II regulations. The platform’s ability to manage big data and provide predictive analytics ensures informed decision-making, enhancing overall trading efficiency and performance. Quod Financial’s TCA features a powerful dashboard for detailed visualization and reporting, making it easier to track market impact, slippage, and hit ratios. Additionally, its AI/ML-driven recommendations for EMS configurations and strategy adjustments further enhance trading outcomes, providing a significant competitive edge in the capital markets.

https://www.quodfinancial.com/tca-best-execution-reporting/

S&P Global

S&P provides an independent TCA tool that provides global empirical performance data to help measure and manage best execution across multiple asset classes. Equity, FX, Fixed Income, CDS. Loans. MMI, Listed Futures and Options as well as OTC derivatives. Our tool combines execution, algorithmic, venue and smart order evaluation analytics to enhance trading-related execution quality management and reporting capabilities. Evolving market practices and global regulations such as MiFID II have increased scrutiny over best execution practice. As the concept of best execution has developed from the best available price at a point in time to a more holistic view of the investment process, the need to measure and manage increasingly complex trades and execution processes has grown significantly.

Our TCA platform meets the rigorous performance verification needs of execution providers’ trading customers. Our solution allows for actionable insight to enhance and synchronize trading related execution quality and delivers trading intelligence valued by trading desks. Our service provides the metrics necessary to streamline performance-based order routing and help with optimal trade strategy selection. In addition, toxic liquidity and front-running surveillance tools accurately differentiate the performance of alternative execution channels as well as being able to fulfil an extensive compliance and regulatory use case. Using best in class benchmark data sets in asset class where price visibility is challenging, S&P also provides proprietary pre trade models as well as deep and wide peer data sets to provide context on trading activity.

https://www.spglobal.com/marketintelligence/en/mi/products/transaction-cost-analysis.html

Spacetime

Spacetime’s TradeFabric platform is a trade intelligence and insights platform designed to augment trader decision making throughout the trade lifecycle. It goes beyond traditional TCA services with a highly visual interface for flexible in-depth analysis, and real-time adaptive analytics for pre and in-trade insights that provide context and situational awareness of where and when traders need it most.

Sell side desks can maintain coverage levels more efficiently and respond quickly to potential issues and opportunities on client orders, while Buy Side desks can restore information flows, liquidity sourcing, and alerting they often lose when working an order themselves.

https://www.spacetime.io/

Trading Technologies

Trading Technologies places a strong emphasis on TCA across its platform from the newly acquired Abel Noser suite of multi-asset TCA products to the dynamic implementation of TCA into the TT Premium Order Type algo process managed by TT’s Quantitative Trading Solutions (QTS) unit. TCA is not only available for TT clients post-trade but employed to improve/optimize the algo suite as part of its comprehensive data science ingredient in the product’s design and application.

TT’s Abel Noser Solutions is the leading global provider of TCA solutions. Its secure universe of trade data and analysis helps hundreds of client firms achieve best execution/measure trading performance/evaluate strategies/compare costs/identify performance improvements in equities, fixed income, options, FX and futures. The Trade-Zoom post-trade multi-asset solution allows clients to benefit from sophisticated analytics as well as customizable reports and benchmarking against the largest universe of annualized market and trade data.

https://www.tradingtechnologies.com/
https://www.abelnoser.com/

TS Imagine

TS Imagine’s TCA empowers customers to optimise liquidity and make timely, accurate trading decisions with complete visibility into execution performance across all counterparties and venues. Users can tailor analytics using over 25 benchmarks, 50 market data venues, and various visualisation tools, enabling teams to make informed decisions regarding broker and algorithm selection, timing, and strategy. This leads to reduced costs and maximised opportunities through in-depth, data-driven performance insights. Customers can also rely on TS Imagine’s team of data scientists and analysts to manage their data, allowing them to focus on generating alpha and maximising returns.

https://tsimagine.com/data/transaction-cost-analytics/

The post The Top 12 Transaction Cost Analysis (TCA) Solutions in 2024 appeared first on A-Team.

The collaboration aims to integrate OTC cash equities trades into Cboe Clear Europe’s cleared environment, enabling them to be netted against on-exchange transactions for settlement purposes. This initiative is expected to provide clients with significant efficiency gains and the benefits of an established risk management counterparty.

A key component of this initiative is the development of a proof of concept linking DTCC CTM’s tri-party trade matching workflow with Cboe Clear Europe. This will allow Prime Brokers to access a golden copy of transaction details once a match is achieved between a Hedge Fund and an Executing Broker via DTCC’s CTM service. Upon tri-party match confirmation, CTM will automatically forward matched trades to the CCP, enhancing netting and clearing benefits for clients.

Val Wotton, Managing Director and General Manager, DTCC Institutional Trade Processing, commented: “We are pleased to be working with Cboe Clear Europe on this important initiative to bring greater post-trade efficiencies to the industry as the global markets look to accelerate to a T+1 settlement cycle. Cboe Clear Europe’s extensive venue coverage combined with CTM’s large client base will deliver increased operational efficiency and netting opportunities across European trading venues. DTCC remains committed to bringing greater post-trade automation to increase efficiencies for global financial markets as they work toward implementing accelerated settlement.”

Vikesh Patel, President, Cboe Clear Europe, added: “We are excited to be the first CCP to connect to DTCC’s CTM tri-party matching workflow. This joint solution enables us to bring greater efficiencies to our clients, helping to optimise their current post-trade workflows and operational processes as the global financial markets look to accelerate settlement cycles.”

The new workflow aims to reduce operational and settlement risks and post-trade friction, particularly as markets prepare for accelerated settlement. Expected benefits include decreased post-trade processing times, reduced risks and settlement costs, and lower capital requirements when transitioning from OTC to CCP settlement, potentially leading to fewer trade fails and defaults.

DTCC’s CTM, a central matching service for cross-border and domestic transactions across various asset classes, is utilised by over 6,000 clients in more than 80 countries to streamline workflows. Cboe Clear Europe, the most connected CCP in Europe, provides clearing services to 46 trading venues and is authorised to clear a wide range of equity-related contracts.

Subject to regulatory approvals, the initial phase of linking DTCC’s CTM to Cboe Clear Europe’s CCP is projected to go live in Q2 2025.

The post DTCC and Cboe Clear Europe Collaborate to Enhance Post-Trade Workflow for OTC Cash Equities appeared first on A-Team.

The awards were presented during a celebratory drinks reception after the close of A-Team Group’s TradingTech Briefing in New York City on 6 June 2024.

This year’s awards included more than 40 categories ranging from Best Matching Engine for Cryptocurrency Trading Venues to Best High Performance Network Services, Best Equities Trading Solution, Best Machine-Readable News Supplier, Best AI Solution for Trading, Best Trade Reporting Solution, Best Overall Market Data Provider, Best Specialist Market Data Consultancy and more.

An editor’s recognition award for USA Trading Technology Industry Professional of the Year was presented to Steve Schiff, Vice President, Index Technology at Nasdaq.

Andrew Delaney, President and Chief Content Officer at A-Team Group, said: “Congratulations to the award winners and thank you to all the vendors that entered A-Team Group’s TradingTech Insight Awards USA 2024, to our TradingTech Insight community that voted for its preferred solutions, and to our independent, expert advisory board that worked in collaboration with our editorial team to select this year’s winners.”

A complete list of winners and their solutions can be found in the TradingTech Insight Awards – USA 2024 report.

You can find out more about A-Team Group awards, which also cover RegTech, Data Management and ESG here.

The post A-Team Group Announces Winners of TradingTech Insight Awards USA 2024 appeared first on A-Team.

Meritsoft’s TTEM platform monitors the entire trade lifecycle, providing near real-time updates on trade matching and settlement statuses. This allows users to identify and address at-risk trades promptly, ensuring they meet the new shortened settlement deadlines and avoid the costs associated with failed settlements.

Taskize, utilised by over 600 financial firms globally, offers a secure workspace for resolving trade queries. The integration enables TTEM users to initiate settlement queries directly within the TTEM interface. This action creates a secure workspace in Taskize, known as a Bubble, connecting users with the appropriate counterparties to resolve issues swiftly. Moreover, the integration leverages TTEM’s AI capabilities to automate the creation of Taskize Bubbles. By analysing historical trade data and current trade statuses, the system can initiate queries automatically, enhancing operational efficiency and reducing the likelihood of trade failures.

Speaking with TradingTech Insight, Daniel Carpenter, CEO of Meritsoft, explains the significance of the integration: “In the T+1 environment, firms need to resolve issues as they arise. If the issues are internal, that’s straightforward. But once you need to communicate with an external counterparty, how do you resolve the issue effectively? Traditionally, this would involve PDFs, phone calls, emails, and similar methods. Nowadays, instant messaging is more common, which is fine, but it raises questions about the audit trail and how to capture a comprehensive view of communications.”

He continues: “Our integration with Taskize addresses this. From a bank’s perspective, you don’t need to leave the Meritsoft system. The system will automatically identify a trade at risk of failing to settle and, through our integration with Taskize, the necessary information is sent to the counterparty, regardless of the system or communication channel they use. When the counterparty responds, their reply comes directly back into our system, so the user remains within one system on the screen. By integrating the existing capabilities of TTEM in forecasting, predictive analysis, AI, and tracking, with Taskize, it now allows our clients to resolve issues through their routing mechanism, streamlining the entire process. You don’t need to know what systems all these different counterparts are using, because Taskize takes care of all of that for you. That’s the purpose behind it.”

Kishan Bharwad, Head of Product at Taskize, elaborates on the integration’s benefits. “The integration with Meritsoft allows clients to consolidate and manage exceptions in one place. When the user clicks on an exception within Meritsoft’s TTEM exception management dashboard, it brings up a Taskize resolution window right next to the exception. This means users can start resolving the issue with their counterparties immediately using our unique prioritisation technology, our Smart Directory, and the integrations we’ve built with various communication channels. This setup is particularly exciting as it empowers users to identify and resolve problems almost simultaneously.”

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Iosif Itkin, co-CEO and co-founder at Exactpro, explains why and how the company’s award-winning initiative was developed and the benefits it can deliver.

A-Team: Please tell us about Exactpro and the types of capital markets clients the company works with.

Iosif: Exactpro serves various types of exchanges, post-trade, payment, market surveillance systems, as well as technology vendors. Although each of them is unique, our clients are committed to the same goal – providing compliant low-latency services to their end users and customers, and maintaining uninterrupted operations in an environment of ongoing change.

A-Team: What challenges are your clients facing at the moment?

Iosif: Capital markets firms face regulatory pressures and the need to optimise operational costs, modernise legacy systems and digitise and automate manual processes – the list goes on. Be it a specification change in a trading or payment protocol, expansion to a new asset class, or adjustment of risk management algorithms, it all trickles down to software or hardware changes that can potentially disrupt existing processes and leave infrastructure vulnerable to defects. It’s easy to imagine how many of these technical changes go into, let’s say, a platform migration.

Some software defects are relatively easy to detect, while others can stay dormant for months or years until triggered by a rare combination of conditions.

A-Team: How does Exactpro help customers address these challenges?

Iosif: As an independent software testing services provider, we put objectivity first, and objectivity comes from being informed about all aspects of the system. Due to our comprehensive approach, the extent and depth of our quality assessment goes well beyond supervisory, business or any other requirements. It allows us to obtain extensive knowledge of and control over the system we test, and stress it with multitudes of controlled outages, helping to pinpoint any vulnerabilities.

Since early 2023, our approach has been enhanced with machine learning (ML) and artificial intelligence (AI) techniques. They assist our human testers and significantly optimise their work in cognitively demanding tasks throughout the software testing process. Similarly to our clients, we continuously improve our methodology to provide services in a more efficient and transparent way.

A-Team: More specifically, please tell us why and how Exactpro developed its award-winning AI testing training course.

Iosif: Being a technology vendor that supports financial market infrastructure (FMI) transformations gives us the foresight and advantage to align our practices with the highest standards. In addition, we have long been committed to regularly sharing expertise well beyond our firm. Growing our own AI capabilities and seeing AI technology leapfrogging its way to industry adoption, we realised that we are uniquely positioned to help formalise and standardise skills assessment for technology professionals in this new context.

In early 2024, our Certified Tester-AI Testing (CT-AI) training curriculum for individual and corporate clients received accreditation from ISTQB, a global software testing certification body. This followed in the footsteps of the ISTQB-accredited Certified Tester Foundation Level training course that the Exactpro team taught to a global audience in a remote format from 2022 to 2023.

A-Team: What are the client benefits of taking the AI Testing course and, more broadly, how could the course benefit the wider industry?

Iosif: To ensure resiliency in the capital markets ecosystem, the industry needs solid guidance on efficient quality evaluation. The course provides a much-needed benchmark for the professional competence needed to operate ML and AI systems and assess their quality. The curriculum offers an extensive theoretical part and practical skills needed to comprehend, create, train and test intelligent systems. It also provides guidance on building AI and ML capabilities to facilitate the testing of complex infrastructures.

Our hope is that, with this educational initiative, the industry is one step closer to levelling the playing field and standardising the now disparate use of AI and ML techniques. The initiative should catalyse a transformative shift in terms of how quality and resilience are ensured in finance and beyond.

A-Team: Please run through a short case study of Exactpro’s award-winning professional development initiative.

Iosif: Use cases for taking the course vary, but it aims to serve:

• Those looking to learn the basics of AI systems and their quality assessment
• Specialists already using AI and needing to increase their level of confidence or organise their knowledge base and, of course, those planning to take the official ISTQB Certified Tester AI Testing certification for academic, professional or other purposes.

From the very first video session, participants – either individually or as part of organised groups – will start to get a structured in-depth view of:

• The types of AI and the unique quality characteristics of AI-based systems including flexibility, adaptability, transparency, interpretability and explainability
• Data handling and model training for ML
• Methods, oracles, performance metrics, acceptance criteria and test environments for testing AI systems, including neural networks
• Integrating AI into software testing.

In as little as 44 class hours, or in self-paced mode depending on preference, participants will get an exhaustive and critical view of AI and ML systems and a toolkit for responsible implementation and testing of their strategic initiatives.

Anticipating the needs of our audience, the course makes the ISTQB syllabus come to life. The course is highly visual and interactive, it aims to facilitate comprehension, accommodate various types of learners, and support them on their journey to taking the official ISTQB CT-AI exam, should they choose to do so.

A-Team: How will you develop the AI testing training course over the next year?

Iosif: We don’t plan to introduce changes to the curriculum in the coming year as we don’t expect changes to the official ISTQB CT-AI syllabus that our program already covers exhaustively. However, we will rely on the feedback from our first participants to further develop the variety and delivery of our supplementary materials and practice workshops.

We hope to see the course shape more and more skilled professionals and innovators equipped with the tools to responsibly drive ML and AI technology forward, for the good of their firms and across industries.

A-Team: Finally, what does winning A-Team Group’s 2024 innovation award for Most Innovative Professional Development Initiative mean to Exactpro?

Iosif: Promoting professional excellence has been a strategic direction for our delivery centres and the global Exactpro Group for a long time. Winning the award helps us reinforce Exactpro’s position as a technology and thought leader in our space. The team and I truly appreciate such high recognition of our work.

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This year’s platinum award winner is Regnology for its Most Innovative Regulatory Reporting Solution. Gold award winners include Interop.io, Quod Financial, S&P Global Market Intelligence, and SmartStream Technologies, with plenty more entrants picking up silver awards.

The Innovation Awards 2024 included over 40 categories across A-Team Group’s Data Management Insight, TradingTech Insight, RegTech Insight and ESG Insight news channels. They ranged from Most Innovative Smart Trader Desktops and Workflows to Most Innovative Data Standards Initiative, Most Innovative ESG Data Solution, Most Innovative AI in Regulatory Compliance Initiative, Most Innovative Data-Driven Transformation Project, Most Innovative Financial Technology Executive, Most Innovative Professional Development Initiative, and more.

A complete list of winners and their solutions can be found in the Innovation Awards 2024 report.

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The new capabilities, which build on the company’s foundational secure communication platform, help streamline the post-trade process. Symphony Innovate featured demonstrations of each followed by a Q&A session with early adopters from Citi, UBS, Wells Fargo, and JP Morgan. 

Exception management 

The first solution was developed with DTCC, which has integrated Symphony into its Central Trade Matching user interface (CTM UI). This new functionality enables post-trade operations users to collaborate with their counterparties directly from the CTM UI. The CTM display now features an icon for trades indicating a settlement exception, which when clicked offers instant access to a Symphony chat room with the counterparty that’s pre-populated with trade data and exception details. These details will include Unique Trade Identifiers (UTI) in an upcoming release.  

Non-CTM users also benefit as they will see the conversation in their Symphony desktop or mobile application. Where firms have integrated Symphony into their case management tools, the conversation will appear there also. Symphony’s goal is to be able to link to any exception management tool. 

Symphony and DTCC began working on this integration over two years ago. The solution has been operating in pilot mode with broker-dealers and buy-side firms, with positive feedback from the buy side in particular.  

To address concerns among larger brokerage firms, about the possibility of being inundated with chat messages, Symphony developed a communications bridge into case management tools, which it also showcased at Symphony Innovate. 

Case Management Interoperability 

Many of the larger broker-dealers have made significant investments in integrating email into case management tools such as Salesforce to trap, monitor, and prioritise communications from internal and external groups. These firms tend not to use the CTM UI for exception resolution.  

With the communications bridge, when a chat message arrives, a pre-populated case is automatically opened and assigned to the correct recipient. The recipient can resolve the case or escalate as necessary to internal and external groups. The client is automatically copied on these actions. This functionality ensures the correct people are fully informed on the status of the exception with no rekeying of data or context switching, all from a single point. 

Operations Directory 

The third solution showcased at Symphony Innovate was the Symphony Ops Directory, introduced in early 2023 in response to requests from SIFMA members. It allows firms to digitise and share their operations taxonomies both internally and externally with other participants, moving them away from manually maintained spreadsheets and SharePoint sites. One of the early adopters requested an additional feature be added that would escalate a new chat if there had been no activity or response within a specified period to ensure optimal client experience.  

With the move to T+1, it will be important to get the right people involved in exception resolution as quickly as possible. When a new chat gets created, the escalation bot automatically joins the chat and waits for the designated period before escalation. The bot then uses the Ops Directory hierarchy to identify who the chat should be escalated to, vertically up through management and/or horizontally across the post-trade organization. It understands ‘presence’ – whether the recipient is online – and can use a follow-the-sun model. 

Early Adopter Experiences 

Citi, Wells Fargo, UBS, and JP Morgan are all global enterprises with hundreds of post-trade operations teams spread across multiple geographies, each covering different products and markets. There may be seven or more equity derivatives teams each covering the same product from different locations. This can make it difficult for clients and internal operations staff to navigate the organisation and find the right person to deal with a specific issue.  

As one presenter put it, “In many cases, finding the right person (internally) can take longer than resolving the exception.” 

In other cases, a Client Representative as a single point of contact can become a bottleneck for resolving time-critical issues. The Ops directory facilitates peer-to-peer communication between counterparty SMEs facilitating faster resolution time, eliminating the bottleneck while keeping client service reps informed. 

For most of the firms, the initial step has been setting up the internal taxonomy. The next steps will focus on additional post-trade processes to minimize human intervention and reduce or eliminate email traffic. 

In preparing for T+1, reducing the time to connect the right people to near zero is critical, particularly for firms covering US markets from other geographies. 

Countdown to T+1 

As May 28 approaches, the innovations showcased at Symphony Innovate 2024, particularly the collaboration between Symphony and DTCC, offer practical solutions for accelerating the exception management process and the window of opportunity for firms still struggling to meet the DTCC target rate of 90% SDA by the 9:00 pm ET cut-off, is rapidly running out. 

The DTCC pilot has received positive feedback from broker-dealers and buy-side firms. Concerns raised by the larger broker-dealers over possible increased chat traffic have been addressed through the creation of a communications bridge between Symphony and case management systems. The result is a shortened exception resolution time with a significant reduction in email traffic and improved client service. The Ops Directory plays a pivotal role in enabling enhanced post-trade workflows. 

As DTCC notes in its latest commentary on T+1 readiness firms unable to make T+1 deadlines run the risk of reputational damage and additional costs due to trade fails or the additional cost of settling trades via delivery orders. 

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