The main trend we’re observing is the increased demand for market data globally, particularly from international investors wanting access to US and European markets. In the third quarter of this year, Cboe saw 40% of our data sales coming from outside the US and we expect that to continue.  

This demand is being driven by global interest in the US market – investors want access to the outperformance of stocks like the ‘magnificent seven’ – as well as the expansion in retail trading across the globe. In Europe, we recently published our first retail survey with The Options Institute, Cboe’s education arm, and the results suggested a strong interest in exchange-traded equity options but that more education is needed. This could signal a shift of European retail investors from OTC leveraged products like CFDs to exchange-traded derivatives. Both trends are necessitating access to robust and reliable market data.  

Also, we’re seeing notable demand for our European equities data in Asia Pacific, as brokers look to offer a broader range of securities to their customers. Our strong market share in European equities and high levels of market quality makes our data attractive to these firms. 

What are some of the changes impacting how market participants are consuming market data, both in Europe and globally? 

As we look to enhance the distribution of our data globally, it is becoming even more apparent that customers want to consume data as seamlessly and efficiently as possible. One way to achieve that is by offering flexibility in the way customers access data. At Cboe we do that by making our own data available through various delivery mechanisms, including via cloud, helping to ensure lower infrastructure costs for those consuming it. Our North American, European and APAC equities data is available via the cloud, and we’ll be looking to bring on more content to meet the growing demand we’ve seen.  

The other change that will impact consumption in Europe is (finally) the introduction of a consolidated tape for equities. Incumbent European exchanges, through their operation of closing auctions and in the absence of a consolidated tape, enjoy a dominant position in the provision of market data to the institutional community. We believe the introduction of a real-time pre- and post-trade consolidated tape in both the EU and UK will be key to introducing a competitive dynamic in the provision of market data. It’s one of the reasons we launched SimpliCT in conjunction with Aquis Exchange to explore a bid for the CTP.  

Finally, there is also new regulatory technical standards from ESMA on what constitutes “reasonable commercial basis”, the principle by which market data is to be priced by EU exchanges. The final text came out this week and whilst the industry is still analysing what it may mean, it has the potential to change the market dynamic and licensing constructs we’re all familiar with today. All in all, 2025 will be an interesting year in Europe!  

What are some trends you expect to see in 2025 when it comes to market access? 

As with market data, customers are looking for better, globally consistent and more efficient services from their key providers when it comes to market access. Something that we have been really focused on is offering an enhanced access layer architecture for equities and options markets across the globe. 

Cboe has presence in 27 markets across five asset classes and all those markets now sit on one common technology platform (except our Canadian exchange, set to be migrated in 2025). One of the benefits of having a single technology platform is the efficiency and globally consistent experiences it allows us to offer. It creates an ability for us to launch something in one region and then easily replicate it in another. For example, ‘dedicated cores’ allows members and sponsored participants to host their specific logical order entry ports on their own CPU core(s), rather than sharing a core(s), which reduces latency, enhances throughput and improves performance through increased determinism. Dedicated cores is an optional service and Cboe will continue to offer shared access, as some customers will always want that service. 

We rolled this service out in US earlier this year and are now in the process of expanding it to Europe and Australia.  

What areas of the business is at the fore of Cboe Data Vantage’s priorities for 2025 and beyond?  

Cboe’s newly branded Data Vantage division better reflects the broad spectrum of services that were formerly part of our Data and Access Solutions business. Our priority is to continue to meet demand for data, access and analytical services through our three distinct pillars: risk and market analytics, Cboe global indices and market data and access services, along with the newly defined client experience arm, which will help our clients navigate the evolving landscape. 

We see Europe and APAC as key areas of growth for this business. Given that data is a precursor to trading, our focus is to leverage Cboe’s leading position in multiple asset classes around the world to export our data globally and import trading into our markets.  

There are lots of exciting projects on the horizon. One trend we’re leaning into is the desire of participants to consume more data and insights through cloud-based marketplaces rather than file-based delivery. As a result, Cboe offers a range of delivery methods for its historical and derived datasets and recently we made some of that data available within Snowflake to increase access to that data. We’re working with other vendors such as Google and AWS to do the same thing. 

Another significant trend we’ve seen in the US and has the potential to take off in Europe is the rise of defined outcome ETFs, an ETF with a derivative overlay with a defined upside whilst offering downside protection. Our Cboe Global Indices business has been a leader in this space and has developed the capabilities to deliver some interesting indices for our customers and issuers.

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Technology is transforming the industry including buy- and sell-side relationships. On the buy-side, ongoing market fragmentation in trading is forcing a continuous optimisation of sell-side relationships to reach all relevant liquidity pools available and guarantee best execution for their clients. This development is leading to more electronic interaction between buy-side counterparties, which requires the sell-side toward greater specialisation in order to deliver value. Also, AI will enhance this trend and the changes coming could be quite significant or even paradigm shifting.

How can you maintain relationships in a tech driven world to promote transparency, collaboration and market resilience?

Maintaining personal relationships is essential in a tech driven world both to establish a bond of trust with a client and grow that relationship. Real-time responsiveness, 24 hours a day, is most important. And tech tools enable that. But they also promote transparency which is key to trust building. For example, high quality TCA solutions enable the systematic review of the quality of trade executions, and that promotes a continuous conversation/discussion with sell-side counterparties to optimise execution outcomes.

Ideally, tech-driven solutions should also help to optimise and simplify workflows and create a systematic approach that benefits counterparties and achieves the best possible execution outcome.

What sort of technologies are needed/exist to mutually benefit buy- and sell-side participants?

There are a number of useful tools available today. For example: Block-Crossing Network (BCNs) helps connect different counterparts and achieve the best possible price and at the same time minimise overall market impact; improved FIX versions help to exchange as much useful information as possible between different market participants; TCA solutions help achieve trade transparency, best execution controls, and at same time enable, continuous learning from the data created and improve the trading processes.

Technology enables trust building by promoting instant connectivity and transparency. Today, more data is available for all sides to analyse, discuss and optimise execution outcomes.

How do you pick and choose the right tech for your desk?

Our view is that the best way to pick and choose technology is to build it yourself – it ensures that it is built to your exact specifications, as we have done over the years with our own global OMS Bedrock. With the advent of AI that should be more easily done in the future but most firms don’t have that ability now and need to rely on traditional vendors. Engaging with software providers and keeping abreast of new modalities as well as getting client feedback on best in class trading technology is the way to gain knowledge to consider new trading software.

Does increased technology mean the buy-side relies on the traditional sell-side less?

Already electronic execution and direct market access has reduced the reliance on sales traders to source liquidity. AI will likely cause an increase in the use of sophisticated technology where trader’s jobs are supplemented by machines and trades will simply be monitored by human traders. The reliance of traders as we know is likely to reduce over time as one trader will be able to efficiently handle a large number of transactions.

What is the ideal structure for a trading team in today’s world?

A trading team needs to be cohesive across time zones and work together and not have a siloed approach. This is paramount. The global team increasingly needs to work 24 hours as exchanges are likely to be open for longer hours – there is a possibility for exchanges to open 7 days a week!

Although hours of trading per week will likely increase, as trading tools improve, trading decisions can be made by rules-based programs, leading to reduced number of traders involved. Having said that, human traders will still be needed although their focus will be titled towards monitoring.

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We’re very much looking forward to our launch on Monday (9 December) and are definitely optimistic. We have a good mix of clients – both international and German – who are ready to start from day one. 

Once we got approval from regulators on 28 November – who of course look into every detail which takes time when it comes to Q&As etc. – we allowed time for everyone to get prepared. 

The banks and proprietary trading firms who are ready to go have more than 40% of the market share on Xetra today, and we also have some more in the pipeline that are interested and in preparation. 

We will see how it goes on Monday and the first weeks after launch, but we have a good idea of how liquidity in the midpoint book will evolve. As you know we have two order types, the sweep orders and the midpoint orders. Midpoint orders stay in the midpoint book if they are not immediately executed while sweep orders go directly to the lit book in case they don’t get executed in the midpoint book at entry. We actually designed this in a way that makes it a pure upside to use the sweep option compared to a regular order that you would send directly to the lit book: it has no latency disadvantage and it costs you the same.

One step further, if you’re lucky, you can find a price improvement saving half the spread compared to the aggressive execution in the lit book. Therefore, we expect that sweep will be used heavily even if not at all times. It’s an interesting offer where you can use the sweep functionality with no disadvantage at all and then the midpoint orders that will be passively written in the book will not have to wait for long to get executed. 

In terms of the initial launch, we’re also starting with an attractive incentive programme for the midpoint orders to start with, just to ensure maximum efficacy. 

We’ve previously spoken about the idea of an integrated approach to dark trading, why is this important?

I think it’s very important because when we took the decision to enter that segment it’s not an entirely new thing. There are dark pools all over the place but being the reference market (source for reference prices) is unique and allows us to tailor in a way that others simply cannot. 

First of all, we have the real time midpoint prices that other venues also have to use so whenever an external dark pool offers trading in German equities they have to use those prices in order to calculate that midpoint and technically we have those prices without any delay.

This also means there’s no stale pricing, and thus there’s no risk that you have some players in our dark pool that have information advantages over others. This is different from external venues to which a latency arbitrageur could leverage a faster private connection in order to have information on changes in the reference price first transported to that venue before the reference price is even updated there. 

The midpoint book is hosted on the same machine as the lit and incoming order messages are being sequenced strictly across both those books and we can process the sweep order execution in one matcher transaction.

That means in the midpoint book where it might find some immediate execution there and then it goes to the central limit order book. Essentially, it’s only one transaction and only after all those things have happened the next order message is being processed by our matching engine. Therefore, there’s no overtaking. I think that’s compelling.

Can you tell us more about how this is a client-led development?

The idea was born back in Spring 2023 when some of my colleagues came back from a roundtable with some clients and debriefed that midpoint was something we should be looking into.

From there it was basically a joint brainstorming between some clients and us on how we could best leverage our position as reference market and importantly how we could do a complementary offering to others that already exist.

Following that comes finding a release time. We have many ideas and allocate our developer resources carefully at our company that it’s almost like an internal competition as well when it comes to what can be prioritised, but here with clients so involved of course we are focused here. At the end of the day, it’s a business case and when it comes to meeting client needs it’s a back and forth – inspired by an initial idea and then build upon. 

Following the roundtable, we continued bilaterally with those clients we felt were most interested and most committed to providing their insight, really digging into what exactly they wanted from this. 

What are the main technical challenges Deutsche Börse is prioritising when it comes to further enhancing dark trading? 

There were a couple of functionalities and features that we developed, guided by our clients, that we tailored especially for the special needs in midpoint trading. One of the priorities for example is that we have a minimum acceptable quantity (MAQ), something that when we consulted clients was flagged as essential.

Next thing, our clients were very specific on wanting dedicated MIC codes for the regulatory reporting. Essentially all the transactions from our midpoint book are reportable under a dedicated MIC only for this purpose. 

Third, it may seem like a small detail but also an interesting thing when it comes to user friendliness: We’ve learnt that clients, if they use the sweep order, want to do it without even looking at the specific situation or the specific instruments. The result is that on Xetra Midpoint you can use sweep orders even in instruments or at times where the midpoint book is currently not available, without getting an order reject – it will simply be routed to the lit book. 

Another focus is on self-match prevention, as exists in our lit books. Instead of re-using our existing functionality, we learned that actually it’s much more efficient in midpoint trading to use a “cancel passive” logic that allows a trader to switch from bid to ask by simply sending a new order that will automatically delete the older orders marked with the same ID on the other side while the new order is entirely sustained.

And last but not least, the matching algorithm that we use in our midpoint book is different from our central limit order book – optimised to maximise executable volume, reflect individual execution constraints such as MAQs, and checking for potential executions not only when new orders come in, but also if the reference price changes.

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Automation and electronification has brought a number of changes, one of which has been the large increase in volumes. There are various reasons for that – the obvious one being that you can do more with less when you apply computers to a problem like this. Trading desks have got smaller over the years, while volumes have gone up.

Another manifestation is that trading has become more widespread geographically. At one point, if you wanted to trade a German stock, you had to be in Germany and if you wanted to trade a Thai stock, you had to be in Thailand. Today, you can pretty much trade anything, anywhere. The electronification of the market has brought about that change as well, which has allowed money to flow around more broadly. 

The third evolution has been around different trading models. If you go way back, 30 years plus, trading – even on exchanges – was broadly manual. You basically phoned an order through onto the floor of the exchange and people negotiated prices and so on. Since then, central limit order books have come in, around 30 or so years ago. Electronic access to those came with it and we’ve seen evolution of market models ever since, because it’s relatively easy to program in software changes to these types of systems to give you periodic auctions and all these different ways of trading that simply wouldn’t have been possible by hand. 

What are some of the good things that we’ve lost and/or gained in the past three decades?

Starting with the gain, the obvious one is cost. This evolution has certainly helped facilitate dropping commission rates pretty much across the board, particularly in the more agency-style business because again, you could do more with less and new entrants coming in and competitive pressures and the rest of it. Ultimately, trading has become a lot cheaper.

There’s certainly been concerns raised over the years with certain types of trading. I think it’s safe to say that some of the high frequency markets had a bit of a bad reputation, perhaps in the press, for good reasons or bad. It’s certainly caused a lot of changes and people have had to adapt to that. The days when you could simply just put a large order directly on the market and the market would just deal with it, things have changed. You need to be a bit more careful and a bit more considerate about how you interact with the markets.

Of course, the flip side of that is that doing so is much easier because the technology around, and indeed the experience around to interact with the markets, in this new world, is there and is available for a large number of participants at good prices. So I think those things have changed and it’s also safe to say that the electronification of markets and indeed trading in general works best for liquid instruments.

Liquid listed derivatives, liquid shares and so on, they have really ridden the wave of this very effectively. When you get into other asset classes, it’s less obvious that electronification makes a material difference because there’s so much manual processing anyway. There are still advantages, not least of which being that you take away rekeying risk and things like the error rates of trading can come down, and indeed have come down. That’s a big boon as well. But whether you see the same sort of change in volumes and trading styles in some of these instruments or not, that’s yet to be seen. We haven’t seen an awful lot of change in a number of asset classes over the last few years. 

Alternatively, what are some of the bad things we’ve lost and/or gained over the same period?

I don’t know if there’s anything particularly that we’ve lost, however one thing which comes up in conversations every now and again is this slight worry about whether we are losing any skills in the industry. This is a general theme which crops up not just with the electrification of trading, but also with the younger generations coming to the markets in a much more technologically driven environment. Also, with artificial intelligence coming in and being able to take on some of the heavy lifting.

In a way we’re exposing ourselves to a potential risk that we have less experience and knowledge, particularly for dealing with tricky situations on the trading desks. That’s something which I think we as an industry need to make sure we’re very mindful of and act against. Not incidentally by not adopting these technologies or indeed hiring younger people, but by making sure that we have training and we keep the handing down of knowledge going. 

Looking forward, how do you expect the trading landscape to shift in the next 30 years?

We will see in some ways more of the same. There will continue to be evolution and innovation in the markets and people will try new things. AI of course is something everyone needs to keep an eye on as to what various types of AI will allow you to do or enable you to do in the world of trading. Even if it’s just supporting the process in terms of workflow management and pre-trade idea generation, or even if it doesn’t actually make it the trade process itself. We will see more of that coming through as well. It’s also safe to say that newer technology such as blockchain, distributed ledger technology and so on has yet to make a real impact in financial services. We’re probably going to see that becoming more mainstream in the near future, because of the possibilities that provides to simplify a lot of processes.

Beyond that, very hard to tell. I think it’d be very hard to tell 30 years ago where we would have ended up now. People probably predicted fewer traders – with some people even predicting no traders – and that turned out to be completely wrong and a good thing too. I wouldn’t want to say in 30 years’ time we’ll have no traders. We’ll probably see a continuation of what we’ve got today, wherein skill set and the role of traders changes over time – with this probably becoming more technology-based. But we’ll still have traders. We’ll still have trading. There are the larger scale changes that technology will help bring, not least of which being perhaps bringing more cross asset trading together, as the barriers between these asset classes breaks down and technology helps that. Also, with people becoming more adept at managing different types of asset classes as part of their day job. I can see that trend continuing.  

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I think it comes down to offering better products that are in the interest of the end customer.   

In many instances, the way our industry is set up makes it very difficult for customers to actually make money trading certain products. The market has a bloated old infrastructure where lots of different people have to be fed – whether it’s the brokers, the exchanges, the clearing houses, the product issuers, they all need to get paid every year and typically have a vast array of people. But ultimately, when you break all of that down, where’s the rub, how are participants making money and how much value is being added?  

At One Trading what we want is to stop customers getting ripped off because they don’t understand the whole picture. We care about their interests, giving them the confidence and making it fair. In a nutshell transparency - where there’s no hiding it, you can see all the prices and where the liquidity is and who’s trading and see the entire picture.

Are traditional trading practices being affected by the presence of digital assets?

It’s a very interesting question and you need to look at what traditional is really focused on, which is basically tokenization. Most people like tokenization in large part because it’s an easy thing for people to conceptually get their head around.  But I think that the bigger innovation is going be the perpetual of everything, which allows people to easily go long or short on any asset, whether it is a digital asset, or an equity, a bond or commodity. Once you move to more perpetual markets you solve for a lot of settlement issues, capital efficiency and reduce overall complexity. People are taking note of how innovations in the digital assets space can be translated and learnt from for even more efficient processes. 

We can then have more infrastructure based impacts. For example, CME recently announced that they’re setting up a broker. I think that’s a really interesting development, because in essence it’s a cut and paste crypto model: they’ve clearly assessed ‘if we’ve got the clearing element and we’ve got the trading element, why don’t we own the broker piece as well and compete more directly with their end clients’?  And that’s been proven to be successful in the digital asset world already. They’re repositioning themselves – to some outcry from their customers – but that’s how innovation works. 

How can these two worlds work together for mutual benefit? 

In the traditional finance world you have customer protections through regulation and mass institutional adoption. In the digital asset world there’s huge amounts of product innovation, new retail adoption and market efficiency that has been driven by lack of regulation and controls.   

The line between innovation and control is where I see the two worlds colliding – and where indeed we’ve positioned ourselves. The mutual benefit has to come from driving innovation on the regulatory landscape and also driving innovation in technology and product offerings. 

We have worked with regulators for over three years to build a completely new way of trading, settlement and risk management, that can be appealing for both retail and institutional customers but provide all of the necessary protections. In doing so we have developed cutting edge technology which is 10,000 times more scalable than anything that the traditional world has right now and built simple products where you can go long or short anything.  There are going to be winners and losers across the board in terms of who is leveraging those things most effectively and actually bringing the two sides together. Unregulated venues will increasingly disappear and regulated traditional venues will innovate more on products and structures. We are in the consolidation phase.  

What will be the biggest trend over the next 12 months when it comes to digital assets [digital asset exchanges]? 

A big topic right now is Trump’s putting Bitcoin back in the world again and so we’re probably going to be seeing a lot more global treasury being allocated which is interesting. That’s one trend that I expect to be dominating global news, certainly the first six months of the new President’s office. 

That’s one piece and then of course is the world of perpetuals where everything is coming to fruition – that’s the other big one.

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Outside of the increased trading volumes, which were expected in certain asset classes, from an electronic trading perspective, there was a notable uptick in the use of FX algos—especially market-tracking algos. This is perhaps not a surprise, but it does show the progression from limit orders to more dynamic algorithmic execution during risk events. What particularly stood out for me was the significant increase in basket trading. The basket execution tool, that we call StratX, likely suited these market conditions given the ability to react quickly during market events and simultaneously execute a basket of market-tracking or limit-based liquidity-seeking strategies containing multiple sizes and currency pairs. 

To put that in context, if a Trump victory and a Republican sweep were perhaps foreseen, by creating a basket in advance that reflects the desired positioning, you would have it all ready to go as and when needed. During the campaign, with the policy proposals that were put forward, the associated potential tariffs and fiscal outlook, the FX strategy could look to express broad USD strength versus CNH, high-beta Eurobloc, and commodity FX. In addition to that is the single-line ‘basket order’, which may have provided the ability to execute a single limit order at mid. 

To what extent do you think these trends may become more common place beyond the elections? 

The basket trading observed demonstrates how workflow efficiencies that enable market participants to trade at scale can be just as important as execution and pricing competitiveness, especially in volatile markets. I believe that these execution tools, as well as other tools, will become more widely used, not only in stress events but also during normal times when their use perhaps fulfils a desired execution outcome. In the current rate environment, we’ve seen this during monetary policy decision points and any associated volatility. 

The increased use of FX algos reflects the growing level of comfort with algorithmic execution, but it also signifies a step change in the development, customisation, and sophistication of the algos, as well as the associated tools. As trading insights, analytics, and TCA develop in tandem, the performance of the algos and those associated e-trading tools can then be assessed, whether it’s pre-, at- or post-trade, which then validates or helps to shape algo choice and further enhancement. Additionally, when looking at broader asset classes, algos are being employed and developed elsewhere, so it will be interesting to see how that shapes up. 

How could a potential regime shift impact the trading landscape over time?   

We know that policy initiatives have a meaningful impact on how market participants interact and trade. One doesn’t have to look back all the way to Dodd-Frank to see how regulatory requirements have shaped trading behaviour and technological developments. We’ve certainly seen a significant number of regulatory proposals and final rules in the past few years. Thinking about this election and what lies ahead, personnel at the regulatory agencies will have a significant impact on the policy agenda. Over time, we will be monitoring any changes in senior staff at agencies like the SEC and the CFTC and assessing the impact these changes may have on rulemaking dynamics. 

Under a Trump administration, there are a few ways that previously finalised rules can be unwound, delayed, or amended. Set against this backdrop, we expect a less active regulatory environment. Policy priorities for the new administration may focus on initiatives that support innovation and the use of emerging technologies like digital assets and artificial intelligence. That said, it is too early to make any predictions, and we’re tracking what this change in administration could mean across a number of market structural rules. 

Are there any particular final rules you’re keeping a look out for that could affect trading? 

Absolutely. I’ll mention just a few that we’ll be examining these through the lens of what the new administration could mean for likelihood of finalisation, timing, and impact. 

First up, it will be of particular interest to see the outcome of litigation on the SEC ‘definition of a dealer’ final rule. Given the effective date of this rule in Q2 2025, should the rule stand, this does not leave a huge amount of time for any impacted market participants to prepare, compounded by the US Treasury cash clearing requirement at end of 2025.   

There is considerable industry preparation underway for the US Treasury central clearing requirements. The repo clearing component, for example, impacts a vast number of market participants. This final rule is significant given the potential impact on pricing, liquidity, and trading activity in both the cash and repo markets.  

With the advancement of trading technology in mind, an SEC proposal, which looks to change the definition of an ‘exchange’ and apply Regulation ATS to Treasury platforms previously exempt from this regulation, had been in the frame for finalisation. Market participants have been keenly tracking this due to considerations for execution management systems and emergent technology, which seek to introduce efficiencies in operational workflows. 

And last but not least, we are of course keeping an eye on any revision to the Basel III Endgame and GSIB Surcharge proposals from the US agencies because of the broad reaching and significant impact the original proposals would have on market liquidity and capital markets. 

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There has been a shift in the size and scale in the types of managers that we’re talking to. My new favourite saying is that I don’t think this is a recessionary product any longer, but rather a future state. The way that people are thinking about it has changed dramatically over the last couple of years and a lot of that is driven through how customisable the product is through the whole life cycle of trading. Obviously, execution is a key piece of it, but just looking at all the different parts and how that can come under one commission rate is completely different. We did a survey on about 300 global asset managers and one of the main themes that came out of that was around outsourcing. Around 30% of them said that they would look at outsourcing trading, which demonstrates how much momentum there is in this space. It’s driving that capital light variable cost operating model that you can no longer ignore.

The other really key area for us as a product has been fixed income. We’ve seen a 98% growth in the last three years in our fixed income space and we actually launched a fixed income desk from Sydney in September. That is bolstering the 24/6 offering that we have around that asset class. It helps to have people on the ground that can help support firms based in the UK or in the US from that perspective. Another factor that’s key and won’t be that much of a surprise is the trading technology and infrastructure itself. It’s critical that you remain on top of that and it’s really expensive. If you can leverage somebody else’s expertise and infrastructure from that perspective it is instant cost saving.

What is driving these trends on the client side?

A lot of it goes back to pressure on managers. Everyone knows that there are costs and performance pressures, but it comes down to where can you gain operational efficiencies, regulatory reporting help or instant access to new products – whether it’s a different asset class or region. Co-sourcing in particular has been a big theme this year. The expense of setting up in a new market for a new product is high, you’ve got to get through a hiring process and everyone knows that that alone can take months. We’ve seen quite a few clients diversify into different asset classes over the last 12-18 months with interest rates changing and things like that. There’s also access to liquidity which is becoming more and more difficult. We’ve now got more than 500 different brokers for equities and fixed income.

T+1 was also a really big driver for us – we’ve seen quite a few managers who were looking to solve for different positions around that. Northern Trust has got offices in Chicago, New York, London and Sydney covering different asset classes and from that side of it, you’ve got the security. To some extent we’ve seen quite a lot of managers look at us for BCP purposes. They’ll have a line open and they have the infrastructure there but if something was disastrously to go wrong, whether it’s on a regional basis or macro or something internal they’ve got us as a backup.

What is driving change in the outsourced trading provider landscape?

We’ve noticed quite a lot of M&A activity. The underlying aim of that is achieving scalability of growth, access to liquidity, the governance structure, and basically whole product. The industry is really viewing outsourced trading as a high quality product now and with that comes a really high standard, high expectations of what you can deliver. Execution is key but it’s the scalability, the operational efficiencies, the support around regulatory reporting, the data analytics, the number of broker and venues that you can get to, and the advanced technology that’s wrapped around it.

Where the competitive landscape side of it is growing it’s great because it’s giving more optionality to everyone, it’s validating what we’ve been doing for a really long time now. If you’re active or passive and you’re looking at it from a fully outsourcing perspective or from a co-sourcing perspective, we see it as the future and it’s going to become a really imperative part of your operating model regardless of who it is. There are too many pros now for it to be ignored.

What would you say to those who remain anti-outsourced trading?

We always talk about the journey. It’s got to be the right time. There are going to be certain trigger points, whether that’s a new member on your C-Suite or additional cost pressures or access to liquidity or a new asset class or market. There are so many individual trigger points that happen at all of these firms at different times. This is becoming increasingly difficult to ignore and avoid. The route that we take is it’s a partnership for us -it’s not about taking jobs.

We have some clients who were still doing the trading themselves and their response has been ‘I can go back to doing what I’m meant to be doing, which is picking stocks, not deciding how to trade them’. That helps bolster their infrastructure too. We’re at a really exciting point in the life cycle of outsource trading, there’s massive momentum around it. You can’t ignore it, but also don’t be afraid of it. It’s not about putting people out of work, it’s about creating opportunity.

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It is an interesting question because there is a broad spectrum of approaches across organisations. It fluctuates between those organisations that are leaning in and are on the front foot and those that are watching carefully and are engaged but they have not yet put all of their chips on the table. There are also organisations that are unsure of how to start and how to enable themselves and I think there’s a humility that comes with that. 

There is an interesting dynamic within AI where it is accessible to all of us, but challenging to implement within financial services. As much as there are some really exciting things that we can do with AI, in financial services we have a lot of regulation and compliance that we need to think about.

Culture within firms is also a significant factor. AI is not one team’s problem to solve, you have to get a community really working together for a truly holistic approach. 

We are starting to see a change in terms of the demands of the end users and in their actual way of working, which is impacting the character of these previously very tightly defined personas. I think that is going to have a really interesting effect in financial services.

How feasible is AI use when it comes to trading?

One of my rules with AI is that if you have to explain it and you have to repeat it, maybe don’t use it. The problem with AI is that it is a probabilistic model so if you ask the same question twice, you’re potentially going to get a different response.

That of course doesn’t mean it’s not valuable, but it means that you have to think very carefully about which use case you are solving for. So, when it comes to traders, this is really fascinating because it comes down to trust – if a trader was like a magic box and every time you shook it came out with a different answer, would you trust it?

Traders are essentially accountable, so the idea that people are going to use AI and potentially get different outcomes that they can’t fully explain in these high-risk tasks seems implausible.

Furthermore, the idea that regulators are ever going to get comfortable with AI giving the best answer only “most of the time” is highly unlikely. For that reason, I think traders are going to be around for a while.

What is meant in practice when the industry says we must adopt AI in a responsible way?

When it comes to responsible AI, the key is trust. One has to delve into what it actually means to be responsible – essentially, if you’re using AI enabled processes, can you trust it and what does it mean to trust something?

One aspect is knowing where the data has come from, another is checking for biases and establishing the ethics of models, and another is choosing the right model for the right task and taking responsibility for that selection.

At the end of the day, we are now responsible for products that are AI enabled, so a big part of that responsibility is reinforcing it, through a secondary model and maybe a tertiary model. In the event that something catastrophic happens, we must have that ability to say, ‘not a problem, we have a back-up, we’re going to switch to something else that is more suitable and continue to uphold the status quo’.

How important is that holistic approach to AI?

What’s important to note – aside from teams coming together to approach this at the same time – is the fact that AI came from outside of financial services and is now being imported into financial services. We are seeing examples in other regulated industries of how people are implementing AI which has the potential to be hugely transportable and relevant when we think about financial services.

I believe that this is going to have a dramatic effect on the way that financial services operate because in the past we’ve seen financial services very much segregated from everything else and tightly defined. That is now starting to change, and we are starting to see cross industry collaboration. 

Interestingly, we are not only focused on the research and investment in AI within financial services. As a community, we are beginning to see the potential relevance of AI investment within other industries. A part of this is greater mobility of  talent from non-finance industries, bringing relevant new perspectives and skills.

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Historically, the technology and processes to support manual data reconciliations have been very much geared towards addressing challenges around sharing the data, looking at the data and then using very linear technologies over the top. But a series of trades doesn’t simply add up to a position. It’s a very simple statement, but an important one.

This is compounded by a couple factors -the increase in transaction volumes and more complex assets being transacted. This is leading to frequent errors (due to different systems and non-linear processes) resulting in a costly mess of point-to-point reconciliations and mistakes.

We really need a very different approach than the one that exists now. One long-term solution to this is tokenisation and digitisation, where everyone is looking at the same record. But even then, that’s not enough on its own. The optimum state is having the ability to make a summation of those records by using non-linear enabled technologies which can be aligned to clear business processes.

How can new data management technologies help reduce operating costs?

It’s important to note how new data management technologies can not only reduce operating costs, but also reduce risk. This means individuals can be granted permission to access only the specific data they need therefore ensuring compliance with market data licensing and regulatory obligations while being authorised to perform the right action. Therefore, creating a safer environment: people can then see the bits of the puzzle they need for their specific role, without necessarily seeing all of it.

Again, the issue with the push towards tokenisation and digitisation, means a lot of the public blockchains have access to everything. So that’s not quite the right solution. It’s about finding the balance which reduces duplication, synchronisation issues, translation problems, and breaks, while maintaining the controls required for financial services.

What is the key driver behind the push for real-time data sharing?

It’s largely driven by the increased sophistication of the ultimate capital allocators. If you look at sovereign wealth funds and pension funds, as a macro trend, they’re starting to insource more of their own risk management. In order to do that, they need to look at the same data.

So, they’re starting to ask their managers and their custodians and administrators for data that’s at the same time point. When quick decisions are necessary, relying on data that’s 90 days old here, 30 days old there, or even just a few days outdated can hinder the process. The goal is to have all relevant information in real time to enable better, more informed decisions on a macro level. We’ve seen that trend an awful lot more where the end capital owners are becoming much more sophisticated in their approach.

What are the main pressure points for asset managers when it comes to their operating models?

There’s a change in the asset mix with the end allocators wanting both public and private assets. There is also a change in the demand for data with asset managers wanting all their data in real-time. For allocators, fee compression is a significant concern. As more machine learning, AI, and automation are introduced, they may ask, “Why should I pay 1.5% or 2% in fees when I could be paying just 0.5%?” Additionally, with interest rates staying relatively high, investors may question, “Why take on risk to earn 7% when I can get 5% or 6% from government bonds – and avoid paying you a 2% fee?”

This combination of factors has created a perfect storm: capital flight from traditional managers, pressure to lower fees when they do secure capital, and an increased demand for complex asset mixes. All of this contributes to a significant challenge for the profitability of asset managers.

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At a high level, I think that most teams are pretty excited about the prospects of AI and the opportunities that it presents. Certainly we see very good usage among our teams. Despite this, there are certain concerns, understandably, and hallucination is certainly a topic that people are aware of. But at the end of the day, before trust comes education. It’s about helping folks understand where these models can add value right now and where they can’t.    

A lot of the wariness also comes because AI models are known not to be good at certain tasks and this taints opinion when it comes to others. For example, AI models are not good at math – that’s just not what they’re trained to do. The key is to educate [our] internal users and explain that they shouldn’t get spooked because, when it comes to the analytical path, the potential is there.   

How is AI already having a positive effect on trading processes? 

The traditional ChatGPT system, similar to our design internally, is focused on quick questions and quick answers. It aims to save people 20 to 30 minutes, on average. The deep research system we are working on allows one to rigorously research complex questions for results that can potentially save people 3 to 5 days.

AI has the ability to unlock a lot of productivity for investment professionals, allowing those within capital markets to discover and digest information even faster than they were previously able to do.

You could either be the fastest or you can be best, and we all want to do both but there are a lot of factors to consider.

How are firms across the industry adapting their teams to be more AI-focused?

In the future, our firm, and others, will want every team to effectively be an AI enabled team. At this point in time, however, what is of most benefit to organisations is to take a centralised approach. We have a team that is dedicated to AI as a centre of innovation – with technical expertise, doing research and building tools, but as importantly, looking for opportunities within the firm.   

A lot of my role and the role of my team is connecting the dots and finding commonalities across teams at Balyasny. If something is working really well in one team or one vertical, it then becomes about translating that. It’s never a direct translation but taking the lessons about what’s working well somewhere and then adopting it somewhere else allows us to achieve more scale within the firm.

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