Tibor Gergely, Commerzbank: Building Smarter FX Liquidity in Fragmented Markets

[MUSIC] Welcome to the 360T podcast, a series that features top industry professionals offering unique insights regarding how the FX market is developing around us. [MUSIC] Hello and welcome to the 360T podcast with myself, Galen Stops. And today I'm joined by T-Bawghergaly, head of EFX liquidity at Commerce Bank. T-Bawg, thank you so much for joining us today. Hi, Galen, it's a pleasure joining you on this podcast today. Thank you so much for inviting me and looking forward to this conversation. What I wanted to talk to you about today, T-Bawg, was this intersection we see between technology and liquidity fueled by analytics and data. And I guess what I really want to get into with you is understanding the mechanics and the functioning of a modern EFX desk. Because I don't think that's always fully understood the different components to go into that. To start us off, can you just provide me with a high level overview of the ways in which you leverage market data and analytics to both calibrate and optimize your FX liquidity. And I'll let you take this in whichever direction you want. But I'm thinking, is it different across different client segments? Does it vary by geographies? Is it about distribution channels? I'd be interested just to hear how you think about all of those things. Yeah, you mentioned market data and analytics and EFX trading business can do nothing without understanding these and using them in the best ways. Just to give an idea for our listeners and EFX trading that usually looks up market data. In the spot space, I think we can differentiate spot and swaps. Spot is much more electronic and has been for a while in swaps. It's going in that direction, but much more voice and manual still in some corners of the market. So the way we use market data on the spot side, we listen to a series of different market data sources. And in a nutshell, we build a consensus price that reflects the market in general. So that's one type of market data that's really looking at marketplaces that are projecting effects. We also look at additional sources of market data such as the ADF, the algorithm of data feed that is being worked on at the moment 360T, which is insane and enhanced to you of the market. So we combine these different things. We also look at RFQs, we look at the heat ratios that informs us on the competitiveness of our pricing and we can adjust accordingly in real time. So if I mentioned swaps before, it remains more voice. On the swap side, though, the interesting thing is that you can bring in other types of market data. You can look at futures, you can look at interest rate swaps. We even started parsing some chats to extract from conversation between participants. How does that work? In some instruments that are less liquid work, there's not pain available really that you can listen to, because a lot of the interaction happens via chat. We look at these chats and decipher them, extract the transaction and quoting information from those chats, and put them in a machine-reliable format that we can then use in our price construction, in our risk management. So that's market data and you mentioned analytics. You know, obviously we look at the profitability of the flow and that helps us adjust the pricing that we show to our client. What we've started doing now is really automating that process. So we have to imagine that we have thousands of different price fees, pricing 50-year-up to 100 currency pairs, and dealing with them individually would be very time consuming. So we've automated that. So that's one part of the analysis. The analytics is also automation of tasks that were previously done in a manual fashion. Can you just dive into that a little bit more? You talked about the automation of manual tasks. What it comes to this type of analytics? Can you give some insights on what can and can't be automated? Because this is a conversation that we have with clients on the buy and sell side, which is if this isn't the specific area where you are adding value, then automate that process so you can focus more time and energy on where you are specifically adding value. And you know, there is a lot of small-notional volume, vanilla trades, that people can frankly automate, particularly as you said in spot where the market is a lot more electronic. So I'm kind of curious on your side. What type of things do you think will end themselves well to automation? And what do you think still need more that human touch? So I think it boils down to the amount of data for an analytics system to learn and take decisions that we program in the system. It needs to see enough data. So it's about the sample size. So if you deal with very liquid instruments, where there is immense amount of data available, then that lands itself to automation much more than very liquid assets where a lot of it still happens over voice transactions. Because fundamentally, there are all quotes and bits and offers and trades. It's about the amount of data that's available. Is there ever such thing as too much data? On the one hand, you're sucking in data from all these different sources, some of it's in different formats. And obviously, having that helps you to refine the models, but in a market like FX, where there is so much data flying around, does that become a challenge in of itself, or is it always just more data is better? It's an excellent question. And I think it's time to say the big word fragmentation. So the what you see FX market is very fragmented. I've been in this market for a few years. And I remember seeing already at the time when I was a junior quant, looking at this market and thinking surely, this should concern it because there is no reason why it would go more fragmented. And thankfully, I didn't bet on it because it went the other way. We have many more markets today. And it poses many challenges. So to answer specifically your question, is there something like too much data? Well, the challenges that all this fragmentation creates for us is, let's imagine in the spot space, in G10, very highly traded, all these different markets, every market maker, if they want to have a good view of the market, they need to consume liquidity from many, many sources. And the first challenge is that it adds load to our IT infrastructure or tech infrastructure. So more market data sources, it is more servers, more bandwidth consumed, more processing time, more memory. We need to record all of these things for audit reasons or for research reasons. We have to store all these data in its massive. Then even before you get this data, you need to establish all the connectivity with all these participants to gather that data. So that's a lot of setup. And then once you set that up, record the data, then you need the quant effort to look at all these data and combine them and filter them. So all of these who presents real costs to connectivity and data costs also labor time from our quants and technology partners. But it's a fact in this business that any serious market maker needs to have a as exhaustive view as possible of the market. And the only way now is to be connected to many markets. Sticking with the theme of data, how do you measure how valuable data is? Or let me put it to another way. What type of market data is most useful to your trading desk? Is it purely about sucking in real-time market data? Is it about the data that you generate with your clients? Do you lean on third-party data providers? I've heard people say that spot, for example, is more commoditized on a data front. And therefore, data in other instrument types is more valuable. How do you measure value and weigh different types of market data within your organization? Well, for each business purpose, we want to have the best data we can and analyze it in the best way we can. So is create data more important than market data itself? The old self-derived purpose, I think you can do nothing without the good view of the market. So getting market data is crucial. And then if you want to learn from your activity, then you need to be able to analyze your own trades and build the analytics that are adequate to run this analysis. And now I think what's exciting about what's happening in the market, what I see is you've got marketplaces coming up with data products that wasn't the case many years ago. So many years ago, you had your publicly available central-limited order books. You had some ECNs, you can see some market data. The market data you see is what you can trade. And now we see these venues obviously saying, okay, we sitting on a lot of information here that we can package in a product that can be useful to market participants. And they have to package it in a way that is fair for participants. So that's something new that I see. So to come back to your question about the value, obviously this new market data service comes out of cost. So we look at what that data tells us that we cannot see from our own data. I was talking earlier about about RFG use, right? So for the top of the book to know where the market is, you aggregate all these market data sources, but then how do you price bigger sizes? Obviously, it's a function of your risk appetite. It's a function of a particular position, acts that you have in your book. But let's say in a neutral market, where it's always finding the optimal, if you price to, why you don't see flow, if you price to a tight, then you don't make enough money on that flow, right? So how do you find the right price for 10, 20, 50, 100 million? You can look at RFG use, that gives you a hint, tells you if you're competitive at that level, but you can only see your activity. So when someone comes and says, "Ah, I've extracted anonymized information that I see on my platform that can inform me about the level of spreads at higher sizes, and that's additive, and obviously has value for us." So this question I'm particularly interested in as someone who works at a multi-bank trading venue, I want to understand a little bit, how are you currently using real-time market data to adjust your pricing and liquidity distribution across various external platforms that you might use like 360T? Obviously, what we do is all very high frequency, right? So the inputs are all these different market data sources, our own position that fluctuates with the trades that we make. And there is also reading the volatility from the market. So is there a short at this point in time, also knowing when announcements, economic numbers come out that are known, this is really to have an impact from the market, then you adjust your pricing and your hedging accordingly. So you bring in all the market data, you bring in your position, you bring your risk appetite, reading a volatility, and you combine all of these things and try to optimize for your profit for the bank and to solve your franchise. And it's a constant optimization. So it's all real time, and I think you said it right. These are decisions that are being taken hundreds of times per second or more, and the result or product liquidity that is expressed through the price that we distribute is continuously updated by all the factors that I mentioned. - Tibo, I'm gonna switch gears slightly, and I'm gonna ask you, help me fix the FX market here. We're gonna do some more forward-looking questions for the last segment of this podcast. So whether it's for you specifically or more broadly in the FX market as a whole, what kind of analytic tools do you wish were available or that you could access? And I don't know whether that's AI, whether it's just standardization of data, I'll leave it up to you. You can go anywhere with this. - When you think about liquidity, you think about analyzing, you think, how can I say if liquidity is good or not? How can I say flow is good or not? What are the right metrics? And the level zero of looking at it is like, what's your average bill of respratement you're getting offered to apply? And everyone who's working this market knows how the average bill of respratement is not what you see all the time, it fluctuates. Also, people will show an act. So, you know, it's not the bill of a really that matters like how close you are to the mid-how competitive you are on the side that you're skewing in. And there is also the fact that a client trades, even on firm value, they can miss the quote, someone can hit the quote first. And in a non-firm venue, there is de-acceptance, liquidate provider can reject. So, what you see is not what you get. You're not feeling all the time, there's no certainty, right? You sometimes have to go back in the market and pay a higher price. And then you can also say, okay, but what happens after I trade, does trading with this market maker have market impact? Does that impact myself when I trade with them? And I think everyone has become now all the sophisticated and also in general, the FX participants have become much more data driven and they started looking more in debt. So, they started looking at the bid offer spread, then they started to look at rejection. Now they understand that the aftermath, how market moves after a trade is important. So, everyone is doing this computation separately and everyone will talk about market impact. But no one can really agree, is it 30 seconds? A minute should it be on a trade clock? So, I think if someone could come up with a unified way of looking at the cost of trading that's helpful across the board, that would be quite good for the clients as well because they could have an impartial way of judging across different providers. If you think about it, now take a speak with the makers and then the makers can tell them how good or bad their flow is, right? But this conversation happened one to one. If there was a way to look at the market more in general and thinking about unified metrics, it's not a trivial task because as I said, the quality of liquidity is a multi-dimensional metric. It's not just one number, but if someone can make some progress in that direction, I think he would bring some clarity to the users at the end. - Yeah, I think one of the challenges for the FX market more broadly is it's such a diverse universe of people out there trading FX for so many different reasons that best execution is something that could mean vastly different things to different people across the industry. - It's true, but the other thing that's fascinating about this market is the movie C market with bilateral credit relationships. Everyone's view of the market is different. So for the client, it's important that they create long-standing, sustainable relationship with market makers that can offer a difference. Because I have a view of the market that another company doesn't have. And if I'm very different because of my franchise, I'm very different because of the markets I'm involved in, then I'm gonna offer something complimentary and add it to the liquidity that the client sees. - You talked about everyone becoming more data-driven and you talked about the journey that some people have been going on in terms of what factor and some what data they're looking at. Do you see the growing prevalence and usage of data and analytics? Is it a democratizing force across FX? Or do you view it as more of a winner takes all situation where the person who has the most data or the best data quality, not just quantity? Is able to basically refine their models, win more business, get more data and sort of the flywheel starts? Or do you view it kind of the other way around? Or somewhere in between? - I think it's more democratizing than anything else, but there is a barrier to entry. That's quite high. As I explained earlier, when you were asking about data, is there something like too much data? Well, there's a lot of cost involved in handling all of that. So I think as long as you're ready to pay the entry tickets, then yes, it's there for you to use. It's an investment question. If you want to be seriously in the EFX, you need to invest in data and that's no question ask. - Another forward-looking question. Commerce Bank has always been an early support of 360T's Swaps user network. Don't worry, I'm not gonna ask you to plug our platforms on the podcast, but what I am interested in is 360T's son was designed with the thesis of the Swaps market is going to evolve. It's going to increasingly electronefy and this will require additional tools and functionalities to basically replicate some of the ways that people are trading now in an electronic environment. What are the big opportunities that you see from your perspective and your side of the market in the FX swap market as it electronefies? We love innovation and yes, we were one of the early borders of 360T's son. We see a big benefit in it in that it reduces the lot of manual overhead. To the clients, it really brings more price transparency and lower cost. Coming back to democratization that you mentioned earlier, I think it levels the playing field more because it allows more smaller participants to compete and improve on pricing. It's a firm venue, so when it brings to the client is certainty of execution that was maybe less present in other ways of transacting in the past. For us as a market maker in the Swaps, it allows us to efficiently show an axe when we have a position and we want to invite flow on one side and that results in a better price for the client. Now, the challenge is that you need to manage credit, for example, and pricing blips because when you are continuously pricing, you cannot afford having mistakes and blips. So it becomes much more visible. So I think it brings a lot of transparency. It brings a lot of value to the client in terms of certainty of execution and better pricing, but also it exposes the DLP, that they need to be really good at making sure that everything works correctly. Otherwise, it would be very visible very quickly. - Why in your opinion has so much of the FX Swaps market been slower to electron by versus something like Spot? Obviously there is the credit component, but when you look at the BIS, the Bank for International Settlements numbers over the last five, 10, 15 years, Swaps growth has been incredible. this is now a market that numbers in the trillions of no-sional volume every day. You would think that the potential savings and productivity boosts and efficiency that could be gained from even just electronically finding a small part of that market would be a big driver for banks and their franchises. - We were one of the first banks to stream outside of London hours on the site. And that came after we started in London. So you can see that this is sort of a progressive approach as we are building the toolkit to respond to this new flow. I think the direction of travel is electronicallyification and we embrace it. Now it's a progressive one. It's a big matrix of products. And what we think will happen is that the most liquid part of it is already well-electronified and will spread progressively into other parts of the matrix. But at the end of the day, it will benefit the client. - And then last question that maybe we'll touch on a few things that we've talked about here. From your perspective, how does a modern market making firm like Commerce Bank expand their footprint? These things we've talked about, the data, the analytics, the connectivity, how do you think about expanding and growing your FX business in today's FX market? - It has a lot to do with marketing as well and outreach and network. And it has to do as well with the competitiveness of our products. So it's two parts, right? You need to have a good solid competitive pricing. You need to find also selling points in a very commoditized market that trades in the most fundable products. So finding the specifics, you're good in some currency pairs. Because you have a specific franchise in some countries. For example, we have one book for Spiderman for Swaps. So that allows us to net positions between Asia and Europe, for example. So we can show competitive scan deprises in Swaps in Asia time. That wouldn't be possible if we had silo desks by trading center. And the technology and quant arms raise to be on top of that. And everyone wants to be the best at pricing FX. So that's a continuous improvement on that side. And then there is reaching out to the right liquidity consumers, understanding their pain points, understanding what they expect from the liquidity providers. And the most sophisticated clients now, I even come to conversation that I think I never would have heard before, some very sophisticated liquidity taker, they sometimes refrain to take liquidity if it's gonna hurt the LP liquidity provider. Which is something that I didn't hear many years ago. I think the consumers of liquidity now, they understand that they want to develop long-standing sustainable relationships with their liquidity provider partners. Because they understand that maintaining relationship with so many people and heading to maybe cycle through some because the performance is not good. It's very time consuming. So consumers understand that it's better to share information, talk to each other, look at data together, to find an optimum where it's a mutually beneficial trading relationship for the liquidity consumer and for the liquidity provider. Because at the end of the day, if you add up all the costs, that's what makes most economical sense. -Tibleth, that was really interesting. Thank you so much for your time and insights. We really appreciate it. -Thank you, Galan. I'm a pleasure chatting with you about these fascinating topics today. -And to our listeners, please do join us again next time. [MUSIC PLAYING] -Thank you for listening to the 360T podcast. Check the 360T website to catch up on past episodes and find new listings. [MUSIC PLAYING]