AI has become a part of our daily lives, with platforms such as ChatGPT being increasingly used by anyone with access to a computer. Looking through the lens of fixed income, a potential new era of precision, efficiency and insight is set to dawn as traditional workflows become paired with the boundless capabilities of AI. Already, the technology has begun to redefine how the industry approaches trading strategies, risk assessment and portfolio management. 

A paradigm shift

“AI’s integration into fixed income trading is not just a mere addition; it’s a paradigm shift,” says Eric Heleine, head of buy-side trading desk at Groupama Asset Management. “By emphasising data integration, real-time analysis, predictive modelling, and advanced computational techniques, AI is setting the stage for a more informed, efficient, and profitable trading future.”

The use of AI can help traders move away from grid based and structured auto-execution rules. Instead allowing them to become more agile and data dependent when it comes to execution strategies for specific orders. 

While AI is currently being used for the automated routing of simpler trades and smaller orders, this can be taken further still. For example, to determine which broker should be used according to an order’s level of difficulty using real-time data including axes, trades, wire time behaviour and related markets.

“The next step would be broker selection: If we balance information leakage against price discovery and only ask a limited set of counterparts, the key question becomes who to ask,” says Eric Boess, global head of trading at Allianz Global Investors. “Experienced traders do all this naturally, but machines are faster in digesting data and turning it into actionable information.”

Real-time analysis in the fast-paced world of trading becomes vital. As new market data sets continue to emerge, AI is able to analyse that data, ensuring that traders are ahead of the curve and able to adjust their strategies alongside everchanging market dynamics. The use of AI allows trades to be executed autonomously while also adapting to market conditions and developing from past trading scenarios. 

“This not only streamlines the trading process but also minimises human errors, leading to more consistent and profitable outcomes,” adds Heleine. “AI’s ability to analyse past trading patterns and forecast future liquidity conditions is invaluable, especially in a market known for its occasional illiquidity. Such predictive insights ensure traders can time their trades optimally, mitigating risks and maximising returns.”

Execution

The role AI plays in fixed income is proving to be more and more impactful, especially in the execution process. AI has the ability to amplify the ways in which traders operate, allowing them to scale their processes and make complex decisions in a more informed way. The technology, which has somewhat evolved from automation in the pre-trade stage, where data is used to create rules for low-touch trading, and is shifting towards more complex high-touch trades. 

“We now have a sea of data, the question is how you use AI to deal with and manage that sea of data in intelligent ways to bring the most important things up to the top and how do you deal with attention in the sea of data,” notes Chris Bruner, chief product officer at Tradeweb.

“To execution, which is more concrete, where traders need to pay the lowest cost and have the best liqudity across a wide swathe of trading, AI is able to lower costs, scale humans and make the process much more efficient so you can do more with less and you can handle lots of market environments. Broadly, it’s going to affect pretty much every part of fixed income – it’s just a matter of how.”

AI is able to assist in decision making processes when determining the timing of a trade, what dealers to use and all the other parameters that go into making a trading decision. These tools are able to optimise the decision that traders are making, but AI is only as good as the data that goes into it. 

“These models are very good at looking at historical information with a level of statistical significance, giving an estimation of what might happen in the future based on all the different parameters that one looks at right now,” says Lisa Schirf, global head of data and Analytics at Tradeweb.

“They’re very good at doing it in a way where humans simply can’t take that much information into account. Liquidity is certainly an area that can be predicted whether it’s for security or overall market.”

Targeting liquidity is an ever-important part of a trader’s role and AI can help assist in this process. However, liquidity is subjective and can mean different things to different people. Historically, metrics have been created that are fairly linear but inherently, liquidity tends to be feature based and dynamic in markets. 

“The latest AI model approaches are really well suited to help humans understand what liquidity conditions are and how they rapidly change, and then use that information to execute within changing markets,” adds Bruner. “There is this inherent non-linear, picking up the patterns and features in large, complex multidimensional data sets, where AI can be really well suited to helping people understand liquidity.”

In fixed income, a large instrument universe with sparse data exists where one may not see much observable liquidity on a certain ISIN. However, when you start to look at a collection of instruments, axes, real quotes or trades, AI is able to provide more observable prices. 

“With some of these machine learning or AI models, you can start to use AI to help you to impute where certain pricing or where liquidity should be, based off a broader set of data,” notes Chris Murphy, chief executive of Ediphy. 

“The optimal right now is man and machine working together in tandem. We’re going to see an acceleration of people deploying machine learning algorithms to assist in that process. All of these models are only as good as the data they’re trained on. Because traditionally in fixed income, there has been a paucity of real high-quality data that you can rely on, you need to be a little bit more careful about whether the model is sitting on top of weak foundations.”

The importance of data

In fixed income, a growing number of machine learning techniques are required to help aggregate and make sense of the very broad and quite disparate set of data which exists in fixed income markets. 

What AI enables is the ability to aggregate – in real-time – data sets and to make predictions about where a bond is likely to trade and how much liquidity there is likely to be in the marketplace. AI is able to produce signals which can help inform decision points for traders, with data essentially being a vital part of the decision-making process in the execution workflow.

“What we’re able to do with AI is feed into the model a very, very broad set of data points – including data points that may not be about the specific bond that we’re trying to solve for,” says Gareth Coltman, global head of trading automation at MarketAxess. 

“The machine learning model can then iterate and select which of those data features are the most reliable signals of liquidity when they’re tested against the market. What we’re seeing today is very broad adoption of these machine learning tools, and that’s because their ability to predict reliably and consistently is really benefiting the traders that are using them.”

The role of passive inflows and ETFs

The evolution of the fixed income ETF space has brought more automated market makers into the space, due to the ETF market based around equity market structure. This has seen fixed income markets translate more of their activity in the ETF market into the single lane market, allowing the ability to stream firm pricing on single names and respond to RFQs in a more automated fashion. 

“It’s really raising the bar for all of the dealers out there to say look, if you’re not able to algorithmically price a certain part of the credit market then you’re not going to be fast enough to be able to respond to RFQ inquiries,” adds Murphy. “Someone else is going to respond quicker, with a more accurate price and your market share is going to be eroded. Via an indirect mechanism, the growth in the ETF market and growth in passive is actually changing the rules of the game and raising the table stakes for you to be in the flow credit space.”

Managing high levels of flow

In terms of helping larger firms manage flow, AI can be extremely useful in detecting outliers by monitoring previous history of how traders approach their accounts including when certain inflows come in and how much is traded. If something were to go wrong in the execution process, AI is able to notify traders that something is not right and can help stop that specific trade from executing. 

“AI is essential for this problem domain because it’s difficult to capture all possible outliers using simple rules, but AI can even spot complex outliers in seemingly conforming individual data units that collectively represent an outlier,” notes Miles Kumaresan, founder and chief executive of Wavelabs. 

However, Kumaresan re-emphasises the need for AI to be based on accurate, useful data. 

“A neural network is just a sophisticated statistical engine. Its magic comes from its ability to identify levels of abstract relationships between a set of inputs and the associated target dataset. AI’s performance is not so much defined by the large amount of data it uses, but about learning from the representative dataset. Finding the representative dataset is a challenging task and is essential for the AI’s prediction accuracy, and to avoid unwanted biases and surprises.”

For firms managing large flows, automation solutions are essential to help desks execute low touch flow. AI is able to assist traders when assessing whether resources need to go into a specific trade and whether it is something that a human trader needs to see. However, it is important that appropriate barriers are set to make sure traders are able to catch everything that needs human intervention. 

“You don’t want to have situations where a trade that needed manual attention has gone through for automation because the rules are too simplistic. You also don’t maximise your opportunities for automation using that type of rigid, parameter-based approach,” adds Coltman. 

“AI can be used to make a better, more finely tuned decision about what needs to end up with a human trader, and that really is going to allow you to maximise how much benefit you are getting from automation and able to tweak that efficiency to the maximum possible level.”

The evolving role of the trader

As with any new introduction and evolution to the trading desk, things have to adapt. AI has the potential to elevate the trading process, reduce the amount time spent on trades that could be automated and also help traders make more informed trading decisions. However, the role of the human trader remains vital, as AI has not reached a point where trading flows do not require managing and monitoring. 

Financial markets, as we see repeatedly, are very complex. Traders and market practitioners still hold an edge by being able to provide a real view on context. Although the role of the trader is shifting, AI is far from being a human replacement. 

AI requires a high degree of care when implemented. However, the benefits that AI can provide to fixed income markets should be taken into account when developing new trading strategies. 

“This shift doesn’t diminish the importance of traders but redirects their expertise,” notes Heleine. “For complex execution or bundle multi-asset execution, the trader will be equipped with richer insights and predictions. This empowers traders to make more informed decisions, rapidly respond to market shifts, and identify opportunities or threats that might have previously gone unnoticed. As AI constantly evolves, traders must continuously update their knowledge to effectively harness the latest technological advancements in the market.”

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LCH Group appointed Corentine Poilvet-Clédière as chief executive of the firm’s Paris-based European central counterparty LCH SA. Poilvet-Clédière will assume the role on 1 October, subject to regulatory approvals. She will replace Christophe Hémon, who confirmed he would be stepping down as chief executive of LCH SA on 1 October – when Poilvet-Clédière assumes the role – after nearly two decades in office. Poilvet-Clédière brings over 15 years’ experience in financial markets to the role. She currently serves as head of RepoClear and collateral management at LCH SA. Before that, Poilvet-Clédière was global head of regulatory strategy at LSEG.

Sonal Rashmi has joined equity trading business Instinet in an execution sales role, following seven and a half years at Goldman Sachs. In this new role, she will focus on EMEA clients trading globally – specifically quant clients, The TRADE understands. She was most recently vice president at the investment bank, responsible for the algorithmic trading performances of key clients, as well as undertaking strategic analysis. During her tenure at Goldman Sachs, London-based Rashmi also previously worked as an associate and an analyst. Prior to this, she was a group strategy analyst at HSBC, working across technology strategy, innovation, and blockchain.

Allianz Global Investors appointed Kayvan Vahid as head of equity Europe core and value. Vahid joined AllianzGI from UBS Asset Management where he served in a variety of roles over the last 20 years. Most recently, Vahid served as deputy head of global value equity and head of European mid cap equities, where he held responsibility for managing a range of institutional and retail funds across global, European and UK equity mandates. Prior to that, he served as a portfolio manager for European small and mid-caps as well as a European equities research analyst. As part of the role, Vahid will help strengthen and expand the firm’s capabilities in the fundamentally-managed European core and value space.

Both Barclays and JP Morgan made new appointments within their equities trading and sales teams. Doug Polera was appointed as an equity sales trader at Barclays, joining from Credit Suisse where he spent the last 18 years. While at Credit Suisse, Polera most recently served as director of equity sales trading. Prior to that, he was vice president of international equity trading at the firm.

Elsewhere, Louis Barré was appointed equity derivatives trader at JP Morgan, joining from Barclays where he held the same role. Previously in his career, Barré also served as an equity derivatives trader at Societe Generale Corporate and Investment Banking (SGCIB) as well as Mosaic Finance. Before joining Mosaic Finance, he served as a front office trading assistant for derivative listed products at SGCIB.

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Most recently, Vahid served as deputy head of global value equity and head of European mid cap equities, where he held responsibility for managing a range of institutional and retail funds across global, European and UK equity mandates.

Prior to that, he served as a portfolio manager for European small and mid-caps as well as a European equities research analyst.

Based in London, Vahid will report to Jörg De Vries-Hippen, head of investments equity Europe. As part of the role, Vahid will help strengthen and expand the firm’s capabilities in the fundamentally-managed European core and value space.

“The addition of Kayvan to the team will further strengthen our capabilities in European core and value investing, an area we know is of key importance to our clients,” said De Vries-Hippen.

Vahid’s appointment follows a string of recent hires within AllianzGI’s equities team including Giles Money as chief information officer, global sustainability/SRI equity team, as well as the promotion of Rajnish Kumar to the newly created role of head of investment technology and AI, investment platform.

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Eric Boess

How do you feel changing market structure and price formation in equities is impacting institutional investors?

This is a classic question that’s asked at every TradeTech conference, and it brings up the key question: what actually has happened since last year? To be frank, there hasn’t been an awful lot of change. There have been no major developments in terms of consolidation on the exchange side, or in terms of market participants. If anything, fragmentation is probably still an issue, and Brexit has added to the complexity. But these have had limited impact because both the UK and Europe are currently redefining their frameworks. I think that will have an impact at a later point in time, but I don’t see a fundamental change in how we trade now versus last year.

Are we seeing retail investment growth in Europe?

We focus entirely on institutional investment, but we’ve seen a lot of news coming out to suggest that people are trying to adjust to growing retail involvement and participation. Maybe it is access that is improving, rather than volumes growing. I don’t think retail flow is as important in Europe as it is in the US, where it is significantly bigger. It’s also quite difficult to define retail flow and market size in Europe as there are not many really good sources of information.

 Do you expect consolidation in Europe to continue and what impact does it have on the markets and the trading desk?

Asset management consolidation is what we’re waiting for, and it has proved to be notoriously slow, as it has on the banking side. I wouldn’t expect any significant developments or market impact from consolidation in the near-term. Trading platforms, liquidity providers, venues – that might be a different story, but right now we don’t expect any major acquisitions there either.

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Glimpse Markets founder and chief executive officer, Paul O’Brien, confirmed in a post on social media that Allianz has signed up to the data sharing platform, as it prepares to go live in the coming months.

Allianz follows Paris-based Groupama Asset Management, which was the first buy-side organisation to join the network last month. O’Brien told The TRADE that three asset managers in total have so far agreed to use the data pooling service to date.  

“We’re thrilled to have Allianz Global Investors join the Glimpse data sharing network,” O’Brien added. “This is another big step in the right direction and further validation of our business model. It’s exciting to see the buy-side rallying around this idea and coming together to tackle the longstanding issue of post-trade data for corporate bonds.”

Outlining plans for the start-up in August, O’Brien said that more than 20 asset managers were going through legal review processes to become part of the corporate bond data pooling network.

Glimpse Markets is looking to provide traders in Europe with a consolidated tape for credit markets, which has been long-sought by bond traders in Europe. The platform is free for use with a ‘give to get’ model to incentivise the buy-side to share their trading data. The platform is expected to launch by the end of this year.

“Ultimately, this is data that buy-side traders don’t currently have access to and it’s in high demand because the composite pricing which many rely on today is merely an estimate of where the market is,” O’Brien told The TRADE at the time.

O’Brien is a veteran fixed income product manager, most recently working at the London Stock Exchange Group’s bond trading platform MTS as head of buy-side solutions and fixed income electronic trading. He has also spent time during his career building out platforms for Algomi and Etrading Software.

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ThinkFolio will provide Allianz with enhanced decision support, portfolio modelling and trade generation. The platform will be leveraged as a managed service hosted on the Amazon Web Services (AWS) cloud.

As part of the service delivery, IHS Markit will manage all thinkFolio upgrades and real-time feeds, as well as, executing its overnight data loads and start-of-day processes.

“The functionality and customization capabilities that thinkFolio offers are complementary to our unified investment process, and thinkFolio’s ability to handle all instruments within the fixed income asset class is important in helping our diverse range of strategies meet the expectations of our clients,” said global head of fixed income at Allianz Global Investors, Franck Dixmier.

Allianz added in a statement that its fixed income team, which manages €193 billion in assets, had in recent years moved to expand its capabilities and evolve to become a more integrated and global business model.

“As asset managers face an increasingly competitive market and challenging operating margins, IHS Markit is well-positioned to provide the technology solutions and services required to enable Allianz Global Investors to scale efficiently including accessing new markets, deploying new cross asset investment strategies, and growing assets in private and public markets without disruption,” Keith Viverito, MD for EMEA sales for financial services solutions at IHS Markit, commented.

Markus Lohmann, global head of IT at Allianz, also described the thinkFolio platform as a cornerstone to this evolution that would allow the company to unlock its target workflows.

“We have a long-standing and productive relationship with IHS Markit, including our use of their enterprise data management (EDM) solution, and look forward to partnering with their senior team to execute on this operating vision,” added Lohmann.

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Not-for-profit trading consortium Plato Partnership has bolstered its network with the addition of three major asset management firms and two leading broker-dealer firms.

Allianz Global Investors, Schroders and T.Rowe Price, as well as Credit Suisse and Exane BNP Paribas, have joined as members of the partnership. The new members will all help the Plato mission of improving market structure and achieving greater efficiency in Europe’s equities markets.

“We have always prioritised the development of improved trade execution as well as identifying new sources of liquidity from a diverse list of participants,” said Jeremy Ellis, head of European equity trading, T.Rowe Price.

“We are confident that the forum for market collaboration enabled by Plato and its partners will bolster and boost our own processes while allowing us to contribute positively to discussions in the wider marketplace.”

Plato’s growing list of other leading buy-side firms include Invesco, Janus Henderson, Legal & General Investment Management, BlackRock, Fidelity Investments, Union Investment and Balllie Gifford. Its sell-side members also include Citi, Deutsche Bank, Goldman Sachs and JP Morgan.

The addition of the new members follows a series of initiatives by Plato last year to offer new services and improve trade execution. These include the launch of a transaction cost analysis (TCA) platform from US-based BableFish Analytics, which will also act as Plato’s preferred partner for buy- and sell-side venue and routing analytics. Plato also teamed up with BMLL Technologies to launch Platometrics, a free market quality data tool.

“Their participation in helping us realise our vision for improved market practices across Europe marks a huge milestone for Plato,” added Mike Bellaro, CEO, Plato Partnership. “We will now take the momentum built in 2019 through into this year, as we continue to work towards a better marketplace for all participants and end investors alike.”

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Utermann has been CEO of Allianz Global Investors since March 2016, having first joined the institution in 2002 as global CIO for equities. He will be replaced as CEO by global head of distribution, and 20-year Allianz Global Investors veteran, Tobias Pross.

Deborah Zurkow, global head of alternatives at Allianz Global Investors, will also replace Utermann as global head of investments. She has been with the firm since 2012, building out its infrastructure debt capabilities and overseeing growth of the alternative investments platform.

“Leaving Allianz Global Investors will not be easy,” Utermann commented on his departure. “Having had the opportunity to work alongside so many talented and engaging people, to develop and lead a strong team and to build a respected global investment business, is a source of great pride. It is therefore comforting to be able to pass on the leadership of the firm to Tobias and Deborah, both of whom have the energy, insight and values to develop further Allianz Global Investors’ offering and reputation.”

Allianz Global Investors said that the leadership changes are due to take effect on 1 January 2020, although Utermann will remain available to the leadership team on an advisory basis for the first six months of next year.

“[Utermann] hands over the leadership of the firm to individuals who are well placed to make the best of the options available to Allianz Global Investors to continue to serve clients well in a period of change within the industry. I wish Andreas well and look forward to working more closely with Tobias and Deborah from 2020,” Jackie Hunt, member of the Allianz board of management with responsibility for asset management, concluded.

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PFaroe from RiskFirst delivers analytical and reporting capabilities to defined benefit (DB) pension plans in the US market and will allow AllianzGI to further enhance its asset allocation expertise, fueling optimized strategy outcomes for clients.

“The adoption of PFaroe’s analytics will support our next phase of fixed income growth in the US by bringing the US LDI strategy down market into the advisor-led space,” said Andy Wilmot, head of US Financial Institutions Group (FIG).

The tool will be used by Wilmot’s group and AllianzGI’s liability-driven investment (LDI) team.

RiskFirst said its tool will provide more integrated asset-liability solutions and incorporate their own capital market assumptions into their analysis, enabling more effective, informed risk management decision making for defined benefit pension clients, and helping to propel LDI business growth.

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“The use of electronic platforms, while it is driven by the need to maintain productivity, frees up time for traders to do their actual day-to-day job, which is communicating with PMs, communicating what the street has in terms of information back to the PMs and vice-versa,” he said.

“For me, electronic trading is not only about efficiency in trading, that’s obviously one of the driving forces, but making traders an even more active part of the investment strategy that we are running.”

Boess detailed that as AGI has an exclusively active management strategy and works on a decentralised desk with PMs spread out across multiple locations, making the process of offering new products and greater flexibility is “paramount”, which can be achieved through greater use of electronic trading systems.

“Throwing more money or more people at the problem is not an option anymore, which is why being a little bit more electronic and scalable is something that is inevitable,” he said.

The proliferation of electronic platforms, such as all-to-all trading, in the fixed income market may have increased the number of players in the space and eased access to liquidity for some, it also means that firms such as AGI must be far more nimble and quicker the react to new developments.

“All-to-all adds a new favour to it but I don’t think it changes anything structurally, in the way that traders and PMs communicate,” he said. “What it does do is allow traders to get any axe not just from a dealer…so, more potential axes feeding into the system. That obviously requires us, as traders, to bit a little bit more nimble when it comes to reacting on those axes.

“That’s where technology can help, but it’s not just about speed of communication, it’s also about quality of communication.”

AGI went live with an automated execution system at the start of the year and Boess stated that the firm has seen “no surprises” in the time since, but did not put too much emphasis on the execution side.

“If you look at our equity business, which, at first glance looks like it could all be automated…we barely auto execution in equities, so in a way, fixed income has bypassed equities already,” Boess stated. “Some of the features that fixed income platforms build around what you can do with auto execution often cross the line to algorithmic trading, so the set of parameters we are using is much harsher than in most equity algorithms and I think that has great potential for the future.”

While the introduction of MiFID II this year may have brought about impactful changes to certain markets, Boess said that this impact was not as pronounced in fixed income, where changes in the market were “kicked off by regulation and the marketplace just picked them up and utilised them, making them grow in terms of what we are seeing in growth and platforms.”

However, Boess did express frustration with European regulators that have yet to make meaningful decisions on the issue of data consolidation, in particular the continued lack of a consolidated tape for fixed income data, which has resulted in a “reports in RTS28, which are pretty much useless, because no-one can read them.”

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