Electronic trading is like Amazon, or the iPhone, or the internal combustion engine: it’s the story of technology writ large, applied to trading.

Like all technology, electronic trading represents a phase shift in productivity. Just as the personal computer compressed work timelines from days to minutes, electronic trading vastly improves the efficiency of trading workflows. What previously required a phone call with humans on each side can now be done instantly and without human intervention. This elimination of friction in turn unlocks all sorts of otherwise-uneconomical market activity. And in a competitive market, once this paradigm shift occurs, all firms are compelled to get on board to keep up. The automation train only goes in one direction.  

The implications of this transformation are widespread.

For dealers and asset managers, technology becomes a core business requirement, and market share tends to accrue to firms with the most efficient and scalable infrastructure. This tends to lead to consolidation, with less scaled players either acquired by larger firms or competed out of existence. This played out, for example, in equities in the 1990s/2000s, where flow used to diffuse among dozens of smaller dealers, but ended up concentrated primarily among a few large tech-driven liquidity providers.  

Greater efficiency also unlocks new business models. For example, the growth of the SMA (separately managed account) industry in the municipal market over the past decade was fuelled in large part by better technology, which allowed scaled providers to efficiently manage tens of thousands of accounts and millions of individual bond holdings. This in turn allowed SMA providers to lower account minimums, expanding accessibility of the asset class and fuelling AUM growth.

At the market level, electronic trading inevitably leads to a reduction in transaction costs, be it in the form of bid/ask spreads or explicit transactional fees. And as trading gets cheaper, you get more of it, leading to an increase in transaction volumes. This increase is often concentrated in smaller increments, leading to a reduction in average transaction size.

Ultimately, the main beneficiaries of electronic trading are investors, who gain better access to a larger selection of investment products at lower cost.  

How important is data when it comes to increased automated trading? What is the key thing that needs to be considered?  

Data is the lifeblood of any automated trading business. But this should not be surprising, because the same could be said for non-automated trading as well.

When a human is deciding how to make a trading decision, he or she relies on prior experiences and information at hand. Where was the last trade in this instrument? Was there any recent news? Is anything interesting happening in related tickers? How much can I generally charge for a trade in an instrument like this? These questions are answered, in one way or another, by data. The trader probably has a Bloomberg terminal with streaming order book data and a news feed. She also has a database, of sorts, in the form of prior experiences and memories.  

Automated trading systems operate similarly. They synthesise various forms of live and historical data into a series of trading decisions. The difference, of course, is that automated systems can utilise much larger quantities of data at much higher precision, and can apply quantitative techniques to such data near-instantaneously. But the general role of data as an input to decision-making is similar.  

The biggest mistake firms make during the transition to automated trading is simply throwing data away. People have limited processing capacity, so firms used to human-driven workflows are often sloppy about persisting the large quantities of valuable data flowing through their businesses. This failure mode is particularly pernicious because once data is gone, it is often only recoverable in real-time. If you need a year’s worth of training data for a new model, and you’ve thrown your prior data away, guess what? You now have to wait a year until you’ve rebuilt that dataset. Not fun.

What are the most impactful changes AI is making on electronic trading, and markets in a wider sense?

First, some terminology. When people say “AI” nowadays, they’re generally referring to a specific type of technology known as a large language model, or LLM. What’s an LLM? Basically, think: ChatGPT.

LLMs are an important development, to be sure. However, they are just one part of a much broader ecosystem of techniques collectively known as machine learning. Machine learning contains various forms of statistical techniques to understand data. The boundary between machine learning and 9th grade algebra is somewhat fuzzy – for example, is linear regression machine learning? But generally the term is used to refer to more complicated techniques, such as neural networks and random forests.  

I highlight this difference between classical machine learning and LLMs because the impact each has had on electronic trading to this point is quite different.

Classical machine learning techniques have been used in electronic trading for decades. They form the foundational building blocks of many trading algorithms. These techniques appeared first in more liquid asset classes, like equities and futures, but in recent years have proliferated in fixed income as well. For example, since bonds often trade only a few times per day (or less), it can be difficult to estimate the “current” price of a bond. Machine learning techniques such as Kalman filters have been applied to this problem for years.

By contrast, electronic trading use cases for AI/LLMs are in relative infancy. Applying LLMs to trading is less straightforward than for classical machine learning, and the reason is in the name: LLMs are about language, whereas automated trading is about math. ChatGPT can write a pretty convincing rap in the linguistic style of Benjamin Franklin, but it’s not yet great at predicting the price of the next bond trade. Direct applications to trading algorithms are therefore still limited.

The caveat is that all of this is changing rapidly. I anticipate more direct applications to trading strategies over time.

And widening the aperture a bit, AI is beginning to have the same impact in trading as in every other industry: as a major productivity enhancer. For example, copilot-style tooling is increasing the throughput of the software developers who write the code behind trading algorithms. I expect this form of impact to grow significantly over time.

Looking ahead to the rest of 2025, what industry developments/market structure changes are you most conscious of?  

The main theme that comes to mind is: we’re so much closer to the beginning of this journey than the end.  

We’ve come a long way, to be sure. In investment-grade credit, for example, electronic trading has grown from less than 10% to north of 50% market share over the past decade. High-yield credit is around 25%, and on a similar trend line.  

But this is just the start. There are many fixed income markets where electronification is just getting started. Municipal bonds, mortgage specified pools, loans, and others are still voice-dominated markets, with electronic volumes below 20%. Will these markets follow the precise path of credit or equities? No. But the direction of travel is clear.

And electronification of trading volumes is just the first step. When execution is cheap and instant, it unlocks forms of market activity that would be otherwise infeasible. For example, in credit we’ve seen the rise of portfolio trading, where hundreds or thousands of bonds are traded simultaneously as a single package. This kind of workflow could not exist without automation. I expect we will continue to see new forms of market activity like this, built on the back of electronic trading workflows. For example, OpenYield (in which, disclosure: my employer, TD Bank, is an investor) is building innovative trading protocols to create a more equity-like experience for fixed income investors.

I am also watching areas of the market which have not yet garnered as much attention. For example, electronic trading is mostly discussed in the context of secondary markets, but not as much in relation to primary markets. The process of debt issuance hasn’t changed much in 25 years. Timelines are long, processes are manual, and underwriting fees haven’t budged. These conditions are ideal for the emergence of a more automated solution. I would not be surprised to see a push into this space in the coming years.

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Aviad Axelrod was named head of fixed income and equities (FIEQ) product for EMEA at BNY within the Global Markets Trading business. He most recently served in an algorithmic trading and execution services role at Stifel Financial. London-based Axelrod will report to both John Goodheart, global head of FIEQ product and Bianca Gould, head of fixed income and equities EMEA at BNY. His experience spans over two decades, working at firms including ITG Virtu, Pi-Finance, and Stifel in roles related to electronic algo trading, business development, and market structure.  

TD Securities appointed Rob Fallon as director of sales trading, based in Dublin. Fallon joined the firm from Deutsche Numis, where he spent the last two years, most recently serving as director of sales trading. Prior to his role at Deutsche Numis, Fallon spent over two decades at Goodbody, also based in Dublin. While at Goodbody, he most recently served as a senior sales trader covering Irish and UK SMID stocks. Earlier in his career, Fallon held a money market derivatives operations role at Deutsche Bank.

Broadridge appointed Stephen Wilkes senior vice president, head of international buy-side sales, based in London. As part of the role, Wilkes will be responsible for the firm’s sales efforts across EMEA and APAC, focusing on the asset management and asset servicing communities. Earlier in his career, Wilkes spent nearly 13 years at Deutsche Bank in a variety of sales-related roles. Before joining Deutsche Bank, Wilkes spent six years at JP Morgan, most recently serving as executive director, futures and options and OTC clearing sales. Before this, he worked as vice president at the bank for four and a half years.

The Association for Financial Markets in Europe (AFME) appointed April Day head of capital markets. Day was promoted to the role, following 12 years at AFME, where she has previously served as head of equities. As part of the role, she oversaw equity capital markets (ECM), trading and post-trade activities. She also brings extensive experience in investment banking and capital markets to the new role. Earlier in her career, Day held senior roles at Dresdner Kleinwort, as well as serving as director of equity sales at Panmure Gordon.

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Fallon joins the firm from Deutsche Numis, where he spent the last two years, most recently serving as director of sales trading.

Institutional broker Numis was acquired by Deutsche Bank in 2023, as part of its Global Hausbank strategy aimed at “unlocking deeper engagement with corporates in the UK”.

Read more: Deutsche Bank completes acquisition of Numis

Prior to his role at Deutsche Numis, Fallon spent over two decades at Goodbody, also based in Dublin.

While at Goodbody, he most recently served as a senior sales trader covering Irish and UK SMID stocks.

Earlier in his career, Fallon held a money market derivatives operations role at Deutsche Bank.

Read more: TD Securities names new head of European cash equities

“[I’m] delighted to announce I [will] join TD Securities, Dublin as a director of sales trading, joining Carl Hayes and his [sales trading] team as we expand the TD equity franchise across Europe […] I thoroughly enjoyed my time at Numis and very much looking forward to the next chapter at TD Securities,” said Fallon in a social media announcement.

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The watchdog also charged the bank with “failing to supervise” the head of its US Treasuries trading desk who allegedly made “hundreds” of illegal trades over that period.

The firm was ordered to pay $6.5 million to the SEC, $6 million to FINRA to resolve ‘related charges’, and entered into a deferred prosecution agreement with the US Department of Justice and agreed to pay a total sanction of more than $15 million.

Mark Cave, associate director in the SEC’s division of enforcement, said: “Manipulative and deceptive trading undermines the integrity of our markets. Broker-dealers and other firms cannot ignore their employees’ manipulative conduct and must take meaningful steps to detect and prevent it. Today’s action results from our continuing commitment to combating illicit trading.” 

Specifically, a former TD Securities trader was found to have spoofed the US Treasury cash securities market through entering orders with no intention of executing to obtain more favourable execution prices on other orders which were taking place simultaneously which he did intend to execute. 

After these intended orders were filled (profiting TD Securities) the trader in question allegedly then cancelled the other orders.

The SEC has ruled that the firm “lacked adequate controls and that it failed to take reasonable steps to scrutinise the trader after receiving warnings of his potentially irregular trading activity”. 

Read more: JP Morgan hit with record $920 million penalty after admitting eight-year spoofing scheme 

Following the findings, TD Securities has consented to the entry of the SEC’s order finding that it violated an antifraud provision of the federal securities laws as well as having failed to reasonably supervise the trader in question.

The SEC confirmed that it had received assistance from the Fraud Section of the DOJ’s criminal division and FINRA throughout the investigation.

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Morgan Stanley appointed Pankaj Dhake as a new electronic sales trader, based in Mumbai. Dhake joins Morgan Stanley from CLSA, where he spent nearly seven years, most recently as an electronic sales trader. This followed a stint as an associate at CLSA – a position he held for nearly two years. Prior to joining CLSA, Dhake was a senior quantitative researcher at WorldQuant. Elsewhere in his career, Dhake served as a global equity derivatives trader at UBS.

Eric Kohler was appointed to Kepler Cheuvreux’s high touch trading team based in New York. Most recently Kohler worked as an international equity trader at Citi for more than three and a half years having previously served as a commodities sales and trading analyst at the firm. He has also served stints at both Morgan Stanley and UBS Wealth Management. In the role, he is set to help the firm grow its execution footprint and expertise across North America – a key strategic base for Kepler Cheuvreux.

Jamie Crank was named group executive technology and data at the Australian stock exchange, ASX. Prior to this appointment, he was general manager in the trading and markets division, and before that general manager of information and connectivity services for ASX.  He will officially begin his role on 9 September. According to ASX the appointment followed “an extensive external and internal search process”. Sydney-based Crank has worked in the industry across various exchanges for two decades. He has previously served at Chi-X Australia and the London Stock Exchange.

Crédit Agricole appointed Ryan Jones vice president, Latin American (LatAm) RFX trader, based in New York. Jones joins Crédit Agricole from Natixis Corporate and Investment Banking where he spent nearly three years, most recently as vice president, LatAm FX trader. Prior to that, Jones held the same position as an associate. Before joining Crédit Agricole, Jones spent three years at Standard Chartered Bank – also based in New York – most recently as a LatAm RFX trader.

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Specifically, TD is set to enhance and further innovate banking experiences for clients through adding Google Cloud services to its portfolio of technology solutions.

The move follows a previous collaboration between the parties which saw TD Securities’ Chicago-based subsidiary TD Securities Automated Trading (TSAT) use Google Cloud’s Kubernetes Engine (GKE) capabilities in a bid to keep up with market developments.

Dan Bosman, senior vice president and chief information officer at TD Securities and treasury and balance sheet management (TBSM), explained: “Google Cloud’s features are very well-suited to our business and provide a secure and scalable infrastructure that can support compute-intensive quantitative analysis, with an elevated developer experience.

“Google Cloud’s capabilities have helped us grow TDSAT’s trading volumes and portfolio size, and optimally serve our global clients. Additionally, the Google Cloud team has been truly collaborative, providing the resources we needed to help our technology integration process be as seamless as possible.”

Read more: Fireside Friday with… Google’s Rohit Bhat

The partnership will also allow TD to benefit from Google Cloud’s engineering support, including access to Google’s global network of engineers in order to optimise product use in a highly regulated environment.

Matt Renner, president, global field organisation, for Google Cloud, said: “Our multi-year strategic relationship with TD will leverage the power of Google Cloud’s secure cloud infrastructure and world class engineering talent with the goal of driving new levels of agility, customer-centricity, and engineering innovation to more easily adapt and respond to the changing needs of TD customers.”

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LCH SwapAgent’s member count has now grown to 44, spanning 12 countries, which have holistically registered over $5.9 trillion in notional at LCH SwapAgent in 2023 – with average daily volume (ADV) up 78% year-on-year.

“Welcoming TD Securities as LCH SwapAgent’s first Canadian bank member is a significant milestone, and we look forward to working with them as we continue to receive interest from users in North America,” said Nathan Ondyak, head of SwapAgent, LCH.

“The continued growth of SwapAgent is testament to the processing, margining and settlement benefits that our members derive from the service.”

LCH SwapAgent’s services claim to bring improved standardisation, efficiency and simplicity to the bilateral derivatives market.

Last year, SwagAgent added KfW to its service, having successfully processed the first transport currency trades between KfW and counterparties Bank of America, Commerzbank, Danske Bank and Santander.

Read more: LCH SwapAgent processes first trades for KfW

“We are delighted to be the first Canadian bank member of LCH SwapAgent,” said Jason Cope, executive managing director and head of global fixed income at TD Securities.

“By using the service, we believe our clients will benefit from its robust capabilities and potential reduction in costs and risks associated with the bilateral derivatives market.”

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Using Tradefeedr’s unified data API, clients of TD Securities will be able to access and analyse all their trading data, increasing transparency and engagement for all parties.

Trading data from TD Securities will flow to the Tradefeedr platform automatically making TCA, client analysis, comparisons and benchmarking more consistent.

Using Tradefeedr will also allow TD Securities to have a data dialogue with its buy-side clients, with all parties using the same analytical tools for review meetings or algo analysis.  

“We are delighted to welcome TD Securities as our newest Liquidity Provider,” said Balraj Bassi, co-founder and chief executive of Tradefeedr.

“Connecting to the world’s leading financial institutions allows us to capture, standardise and analyse more trading data, which delivers new insights and better decision making for all.”

Earlier this year, FlexTrade integrated Tradefeedr’s FX pre-trade forecast data into its multi-asset platform, FlexTRADER EMS, to deliver enhanced data-driven workflows.

The new offering is available for FlexTrade’s buy-side clients and will help improve transparency and enhance trade decision-making.

Tradefeedr’s data analytics network now includes 21 liquidity providers, 50 major buy-side firms and 10 trading platforms.

“Tradefeedr allows us to conduct TCA and standardise our client reporting using trusted independent analytics,” said Ellie Griffiths, global head of eFX sales at TD Securities. 

“In addition, we are now able to deepen relationships with clients by identifying growth opportunities, using data to increase engagement.”

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Rabobank and TD Securities have become the 23rd and 24th dealers to join the fixed income network for axe indications, Neptune.

The network provides a venue for investors to sift through bond axes and inventory data from bank counterparts and allows a more targeted approach to executing large size orders in fixed income.

It already has 21 dealers live and providing axe information in real-time, with the 22nd bank expected to go live in August this year.

In May, Bank of America Merrill Lynch joined the network, following other investment banks like Citi, Jefferies, Nomura and Deutsche Bank.

Grant Wilson, CEO at Neptune Networks, explained the addition of Rabobank and TD Securities now indicates the maturity of the platform.

“Both banks are important counterparties in their areas of the market and will further satisfy buy-side client demand for the highest-quality data in the bond market to satisfy pre and post trade needs including managing liquidity risk,” he said.

Neptune’s network provides axe data on more than 30,000 securitise with over $140 billion in gross notional across 20 denominations, which is generated from over 30,000 pre-trade axe indications daily. 

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