Matthew Cheung: Hi everybody. Thanks for joining today's Matthew Chung here. I'm CEO of ipushpull. So we're here today to talk about the world's most popular business application. It's been around for 35 odd years. It's got hundreds of millions of users, and hopefully we can talk about things that can help you learn about how you can improve client experience.

Matthew Cheung: How you can be fast to market when launching new products and then how Looking at Excel can actually serve as an entry point into this omni channel delivery which then acts as an on ramp into chats and APIs and lots more. So we're delighted today to be joined by Brad McNee, who's our product manager for TPI CAP.

Matthew Cheung: is also responsible for the world's largest rates, broking desks and platforms. And as you probably know, TPI cap is an inter dealer broker. So they're delivering their data to banks and other institutions. And also Julian Dugat, he looks after fixed income credit and effects for NatWest markets and managing products for cross product sales and covering one of the UK's leading rates desks.

Matthew Cheung: And NatWest markets is the investment banking arm of the NatWest group. And I cover corporates and institutions, so they'll be distributing their prices and quotes out to the buy side or also receiving quotes from brokers like ICAP and there's myself, Matthew Chung. I'm CEO of ipushpull. We're a real time data sharing and workflow automation platform.

Matthew Cheung: So we deliver the right data at the right time to the right place out of the 20 or so integrations that we have, our Excel add in. Still remains one of the most widely used applications and is used by over 70 financial institutions for sharing unstructured and also structured data across pre and post trade workflows.

Matthew Cheung: So, so let's dive in in terms of what we're going to talk about today. So first we're going to talk about why Excel, then move on to how NatWest and TPI CAP are delivering live data. Then we'll talk about Excel and how that crosses over into chat. And then this omni channel data delivery and what that actually means and how it can provide a better client experience.

Matthew Cheung: So let's kick off. Julian, Brad, thanks a lot for joining us today. So, so Julian, to start, could you talk us through why you think offering your data in Excel

Julien Dugat: Hey, Matt. Thanks for having me. So I mean, I guess for us, this is really about we've recently expanded the the number of clients that we cover. In the, the commercial and institutional franchise. So we, we really want to be offering flexibility to our clients. So whatever way they want to use to to connect to us we want to be there basically.

Julien Dugat: So Excel is obviously one of this channel. We, depending on the asset class we have. Our offering is quite diverse. So in effects, we tend to have to offer fixed APIs. And we've got we've got a lot of clients who are actually quite happy to code to our fixed API. So. In the FX space we'd be using I push, pull and excel to distribute things like the, the less true axis.

Julien Dugat: in The rate space we, we use, I push pull to to deliver our axis as well, or live axis. Again, this is just one of many channels that that we use for for this type of data. What is. Quite important to a lot of our clients is the ability to access your data with very little work as in like a no install solution.

Julien Dugat: So the ability to to do this either through web or Excel is actually quite valuable for them because they can really quickly just switch on the stream and the data is coming into their their Excel spreadsheets. And obviously the type of people we interface with as well. So on portfolio managers, people on the execution desk, everybody would have Excel running on their desktop.

Julien Dugat: And we want to actually load some of our data into Excel to actually do some data manipulation, charting these type of things.

Matthew Cheung: And why do you think it's so ubiquitous across every desktop that we see in the financial markets?

Julien Dugat: Why is Excel so ubiquitous, yeah? Yeah.

Julien Dugat: wEll, I think there's definitely a place for Excel.

Julien Dugat: I mean, people have been using it for everything. There's various, a lot of VB code, obviously, being written. So a lot of it will be legacy. But there's definitely a place for Excel as well, just for, for, you know, charting and some sort of data slicing and dicing. But yeah, a lot of people are also using, use it as a pricing engine or way to actually a bridge to other systems as well.

Julien Dugat: So some of our clients use it to to go and sort of collect data, do a bit of data formatting, data manipulation, and then load the data into the, The final system like another management system, for instance.

Matthew Cheung: Cool. Thanks Julian. And Brad, same question to you. Can you talk to me why you think offering TPI CAHPS data in Excel is important?

Matthew Cheung: Yeah, sure.

Bradley McNee: And likewise, thanks for having me here. So from a usability perspective, Excel has kind of remained a bit of a constant in anyone's desktop over Well, definitely the 25 plus years that I've been working and indeed the way in which you're able to expand upon its offering whether that's, you know, from sense of formulas to, to VBA to charting tools as Julian has mentioned, you can, you can really use it as a.

Bradley McNee: It's a really flexible way of pulling data in and manipulating it. Such that you can then also get actionable events from it. From an ICAP perspective really getting data into Excel is is putting is similar actually to what Julian's been saying, is is in some ways the client's preference at 1st point of contact so that they don't have to go through a large or even a small upscale or enterprise wide technology solution to be able to get their data into onto their front end.

Bradley McNee: They can. Install and add in and then run a formula to be able to bring it in and it is just that ease of entry. anD indeed, then the flexibility when the data is in your sheet that helps you to do things like prototyping and really there are now more tools that are being used and more languages that are being used by traders on their desktop.

Bradley McNee: Almost the lowest common denominator is. Formulas within Excel, and then the next level, which is BBA.

Matthew Cheung: And at what level would you see this tactical, easy to use application actually then turn into a strategic application?

Bradley McNee: I say, I think that goes to the point of prototyping. You can prototype within that, and then you can Very easily show someone how you have yourself built and designed it so that it can be handed over to a technology function that can support it more, more widely and spread it across your organization.

Bradley McNee: Indeed, you can even spread functions within Excel across across your organization as well. So but it's that first stepping stone. And so when you have an add in to be able to bring the data into Excel, you've begun that journey. And really, that's the that's the key to us. You might not need a second step on the journey.

Bradley McNee: You might just be serving up the data to a single person or a few persons are able to share it and not need an enterprise wide solution for it. So really, it depends upon the data depends upon the clients and and how much they want to scale the data. In terms of how we from a race perspective, use Excel.

Bradley McNee: Really, it's an, it's an output for our API and the the client has the choice then for on their side, how they would want to be using that API.

Matthew Cheung: Great. We'll dive a little bit more into that in a second, but in terms of the. audience that's listening today. Let's just do a quick poll to understand if Excel is actually already part of their digital offering. So do you, or do you have plans to distribute your live data to any of these digital channels?

Matthew Cheung: So Excel. chat APIs, fix all of the above or anything else. If you're listening to this and you are perhaps a client of one of these services, what channels would you like to receive it in as well? So if you want to respond to that, it should pop up in your screen. And then Steve, if you tell us when we've got enough results and we can, do you want to just cover them?

Julien Dugat: Yeah, sure. So we're getting a... Pretty strong reaction to all of the

Matthew Cheung: above. Excel obviously is popular, not surprisingly. And then probably all of the above is probably the next most popular. Fantastic. Well, we've got the right audience then. Thanks for replying to that poll. So moving on, let's let's kind of go go under the hood a little bit to exactly.

Matthew Cheung: What Julian and Brad are doing with how they're distributing data. Firstly, Julian, can you tell us what type of prices and data are you generating and then why are you then using Excel for that particular distribution method, like when we were talking earlier, you mentioned actually some of it depends on the.

Matthew Cheung: The client, the technical ability of the client, actually the maturity of the market that they're in, because it might not be that electronified, there's a few different angles and variables. What, what, so firstly, what prices and data are you generating? And then why are you choosing to distribute those through Excel?

Matthew Cheung: Yeah, so

Julien Dugat: I think there's probably two main categories, I guess. So one is, some of the data that we are distributing through this channel is is mostly because this is a type of data that is not well supported electronically. So again, as an example, if you look at axes in the fixed income space, so for cash bonds, so this is a really electronic item.

Julien Dugat: So every. Single platform. So multi data platforms or other management system. We basically support receiving this through a fixed message. bUt in FX, it's, it's quite different. So axes are way less of a commodity, I guess. anD it's much less structured. So we actually internally we use Excel and iPushPool basically to distribute this type of data because we have no you know, formal structured way to actually do it.

Julien Dugat: tHe second category is really about Excel as, as a channel in its own right. So we are already distributing our axes, as I was saying in the fixed income space through loads of different channels. So we've got fixed API we send directly to a multi platform, things like Neptune, Bloomberg, TradeWeb, and so on.

Julien Dugat: But we do have demand on the client side to actually get this data directly in Excel. And as I mentioned before reasons can be multiple typically client will actually take this data in Excel and then load it into another system afterwards. So use Excel as a bridge, really. So we also yeah, these are really the two main categories and we, we have

Julien Dugat: quite a few data types that we put on iPushPool. So typically things like prices, axes in, in the rates, credits, and FX space would be so more electronic. Things like like sector axes in rates axes in FX would be less electronic. So they would be getting through iPushPool and not only on Excel, because we also And I think we're going to talk about this later, but we're also doing this on symphony through through bot.

Julien Dugat: So the bot distribution channel we also do it through the the web UI because we do have demand for that. Yeah, so that's the two main reasons for doing it. Unstructured data that we can't easily distribute electronically. And just because of the demand on the client side to actually get the data through this particular channel.

Matthew Cheung: Great. Thank you, Julian. And Brad, can you tell firstly just the listeners about how TPI cap is distributing data to clients and then and then maybe touch on as well going further than just this distribution of data. What if one of those clients wants to submit data back to you from Excel? And how does that look like with the access control and kind of regulatory view as well?

Matthew Cheung: Sure.

Bradley McNee: So Our electronic trading offering centers on a an application front end HMO HMO 5 front end that will display the prices to the traders such that they can then put orders on to those prices in markets that are suitable. The examples of that are the interest rate options market or indeed the inflation market, and we will be extending that to other markets over the course of the next few months and quarters for other rates desks.

Bradley McNee: The data then really is, is. Are the prices for the instruments. These tend to be mid market prices. And then where we run matching sessions as well. We make we show that data up on to the front end. For traders to be able to place orders on there, what we look to do with the added is replicate that data that's available in the front end into through the A.

Bradley McNee: P. I. So that people can read it in their tools. Excel being. Great example, as we said, and and where they're then able to read it. They can then compare it to their own prices, their own view of the market, their own positions and be able to make a view of what orders they would like to place back onto our front end.

Bradley McNee: Currently, we don't allow for the capability to send orders back to the platform. And then we're somewhat wary to be able to do so because otherwise we will be Potentially enabling the client, maybe unwittingly to become an algo trading have our algo trading capability and hence have a higher level of regulatory requirements on them.

Bradley McNee: They might not realize that their spreadsheet suddenly becomes, um, a. Really large compliance issue to satisfy the regulatory control requirements that that are needed to operate on such OTF or MTF markets. So if we were to do this, we would do it in full consultation with the clients and indeed probably have some holdover to allow it to The human operated on on on our side to avoid the algo type issues that they may be facing.

Bradley McNee: So 1st, answer your questions. We display prices. For in order to be able to get orders back from the market levels that we're, we're seeing from, from banks.

Matthew Cheung: And what do you both think of this kind of integrated workflow whereby screen space is always at a premium on any trader or salesperson's desk?

Matthew Cheung: Because I've got. You know, only so many physical monitors, and then there's lots of stuff they're trying to squeeze onto that. One of them would be, you know your iCAP screen or one of the offerings from NetWest, for example. How do you think integrated workflow is important? And then being able to then to deliver that into Excel or something that is on that person's desktop?

Bradley McNee: Yeah, so I'll try and take this first. The, the, the workflow that The API to give you, I think, is, enables you the flexibility on your own screen to see, to decide what you want to see. You don't necessarily have to have the applications open if you've got a stream of data coming in to view it in the way in which you want to see it.

Bradley McNee: So and then the workflow around that will hopefully enable you to design something on your site to be able to give you a, Right response mechanism to then choose to interact with someone else's front end on on their on their screen in front of them. So in some ways decouples not quite devalues, but decouples the need to be able to have the screen open.

Bradley McNee: On the desktop at all times, and you can choose when you wish to view it from from my perspective. So I think that the API is it's needed to be able to make those trading decisions more efficient. By enabling comparison more easily on the bank side, but also hopefully it doesn't mean that I'm forcing real estate upon the client.

Bradley McNee: It still remains their option when they want to see it.

Matthew Cheung: Yeah. And Julian, what's your perspective on that? And also on your internal setup, because I know you spent a lot of effort and resource in building a kind of sales trader desktop where stuff does interoperate with each other, with Excel kind of being one component of that alongside a lot of other things.

Matthew Cheung: How is that integrated workflow for you? That's right. So,

Julien Dugat: just. Back, I think to what Brad was saying. So the especially, I guess, in the fixed income space, we don't really have the single data platform. I'm not really the thing anymore. sO getting, you know, a grabbing space on a client's desktop is actually really, really difficult.

Julien Dugat: And it's a tough ask really. So having this this sort of multiple channels, and Excel is one of them, but, you know, using APIs as well. It's sort of giving you this, this flexibility so client can actually decide how they want to actually access your data, where they want to display it and what they want to do with it.

Julien Dugat: So if they want the data in Excel and they want to basically source the data for maybe for multiple dealers and actually display it in in one Excel spreadsheet on one screen, they can do this with, with this offering, um, going back to your, to your second question. Yeah, we've invested quite heavily in in FTC3 and, you know, being a smart desktop to try to make our workflow much more efficient.

Julien Dugat: So we rely a lot on some of our application being context driven. sO some events would push context on our desktop. Another application would react to this. So for instance If an inquiry from a customer comes to us the, the ticket might pop on the trader desktop and would be pushing the instrument as a context to other application on the desktop and other application would then react accordingly.

Julien Dugat: So maybe one of the application will actually show you the last 20 inquiries for this particular bond, for instance. Um, and it's sort of. It allows you to do things that users normally wouldn't be doing, like the inquiry workflow. yoU know, you get an inquiry, you code back, you execute sometime within 5 10 seconds.

Julien Dugat: There is no way a trader can actually go into a plotter and search for something while this is happening. So, you, this sort of empowers user to get all of this data without really providing an input and give them all this additional intelligence to help them in decision making at point of inquiry in this example.

Julien Dugat: Cool,

Matthew Cheung: and in terms of just going back to the external facing when you're trying to get your data to clients, going to some of the things you just both picked up on, how does actually providing Excel help with the speed of deployment? Because we all know, and. It's it's as gospel that excel is going to be on someone's desktop, right?

Matthew Cheung: So then how how does it help in terms of deployment? And and kind of speed to market when you want to get your data to someone and also touch you I think what brad was talking about on this kind of product development side. It's an easy way to test ideas and products Yeah,

Julien Dugat: 100 so I think In terms of speed of deployment for us, I mean we use the We push our data to web as well.

Julien Dugat: So through I push through so that's it is the fastest market but if somebody is happy to access the data through their web browser, we can just send a link and they will be able to see the data straight away. The next the next fastest, I guess, is to to use Excel. So if there's any data manipulation needed and client do want this in Excel, then we do offer an Excel add in that they can download from our AgileMarket single dealer platform.

Julien Dugat: So it's it's not zero install. There is a bit of work to do to install the add in, but it is very lightweight and we can usually do this really quickly. So obviously this is much quicker than you know, getting the client to build to a fixed API, for instance, which will take weeks or months.

Matthew Cheung: So

Julien Dugat: it, it, it is in terms of the, the sort of the offering you get As Brad was saying, if you want to do any prototyping and start using the data and manipulating it, this is definitely a much, much faster way to do it than any of the the next best, best option, a fixed API or anything like this.

Matthew Cheung: In a way, is it democratizing kind of access to data by having it in Excel? Because there's if I'm if I'm a small hedge fund, for example, and I want to connect to you, I might not have the in house capability or resource to connect to fix like you said. But if I could use Excel as an interface, then to connect into fix with.

Matthew Cheung: Something sitting in the middle, like, like some of the services that we have, does it actually make that the tail of clients that you can service much, much larger and longer?

Julien Dugat: Yeah, and it's it's always been the idea is to be able to to target a lot of clients who don't necessarily have the the appetite or the budget to actually spend time and efforts in, in coding to, to an API.

Julien Dugat: So it is, it's speed, it's cost and it's, it's quite a commitment to go for a, for a fixed API as well. So if you're not quite sure that, you know, maybe you want to interface with a particular dealer it, you sort of need to, to go through the process, I guess, while with having the data in Excel, it's actually, it's almost like a free option.

Julien Dugat: So it's really easy to try it. Anybody can do it. You know, if you actually decide that maybe you don't need the data then, you know, it's very, it's, there's no regrets and basically in this, right?

Matthew Cheung: You got anything to add to that, Brad?

Bradley McNee: Everyone likes a free option. Yeah, but the optionality angle to, to give you the choice of how you want to handle the data is, is I think key.

Bradley McNee: For us, we Our clients are large banks. So within global broking for TPI cap. So here we find more of a problem to be able to get onto their work stack and and their priority queue to be able to necessarily build a fixed connection to to our own API, but you know, it's, it gives them the option for how they wish to proceed.

Bradley McNee: They can do so, um, In a very similar way to Julian's explained through through through the platform. First point through the through Excel at second and then direct to the API third and it's their own pace. They can choose those tools. Excel is a really small first step to do that. And just to echo what Julian said, it's, it's putting it in the hands of traders that can manage this themselves.

Bradley McNee: They are all very proficient at all of the tooling within Excel. And it's the first thing you, you're going to be coached on when you join a desk. And in fact, quite frankly, traders are now getting more proficient rates perspective in, in other analysis type tooling that they could probably quite quickly use some form of Python to be able to connect to an API and, and do that there as well.

Bradley McNee: Excel does is gives you that. ubiquitous tool across across the trading floor for it to be shared and you to learn from that lowest common denominator, as I

Matthew Cheung: mentioned earlier. So it always maintains its relevance anywhere because it's ubiquitous because it's easy to use and actually now with other tooling that's around you can connect Excel to all the heavyweight stuff as well.

Matthew Cheung: Yes,

Bradley McNee: yes, precisely. And so, you know, I can't see a time when, um, it will not be that first stepping stone. Although maybe others will still get to the second, second, second second stepping zone faster. So, like, it's just, it will still be the first point from my perspective, albeit I'm slightly old school.

Matthew Cheung: Okay, old school to new school then. Let's move on to chat. You know, obviously IB chat has been around for a very, very long time. And like Excel is ubiquitous in the front office on sales and trading desk. But chat has really come onto its own kind of post pandemic. You've got symphony that now is being used in lots of places across the financial markets.

Matthew Cheung: You've got, you know, the, the old school, Microsoft has obviously released teams and there's lots more going on with that. And then there's ice and repetitive messenger and slack and lots of other things. So chat is always going to be a part of this industry because of the nature of negotiations and things that we do.

Matthew Cheung: But what do you, both see as the future of chat workflows in this industry. I know, Julian, you love chatbots and chat and you've invested very heavily in it. And Brad, you've got some big ideas from what you want to tackle as well. What type of projects are you both looking at at the moment?

Matthew Cheung: Should I go first?

Julien Dugat: So, yeah, as you said, so we are we are heavy users of IvyChat, obviously, and Symfony. We, we have as an example, we've got an execution box in the rates and credit space, um, that is sort of augmenting the, the sales client workflow. So it provides indicative prices and, and really assists the, the, the sales people through the execution workflow, um, the, the sort of, and we do have.

Julien Dugat: Quite a lot of bots in Symfony there is there's obviously a life cycle to sort of build bot features release them and that can be quite lengthy sometimes, even if Symfony is actually, you know, pretty open platform and it's pretty easy to do that in Symfony. So more recently. We've been using the the, the I push pull features the, the bottom demand feature which has allowed us to really quickly respond to, to client demand and an internal demand from from our salespeople and traders.

Julien Dugat: So when somebody wants a very specific function on a box, we, we don't have to go to or it team to actually build that. A lot of it can just be set up in the In the web, you are very easily. So somebody like myself can actually go and and send set this up within, you know, 5 10 minutes. So, as an example, one of our client asked us to to get access in a in a very specific format.

Julien Dugat: So they were after a very Specific set of axes. So for a specific set of countries and materials and they wanted this to be output in Excel on symphony by just typing a command. Yeah. So just calling the bot and typing a three, four words command. And then that should give them the accepting.

Julien Dugat: So because we've got all these data in a push already building the, we could build this within. 30 minutes. Let's say that was pretty much done. So we can be really responsive for things that are actually, you know, might sound quite basic but the ability to get a specific, you know, filtered set of data.

Julien Dugat: in A very specific format, whether that is outputting your table in Symphony or whether it's just outputting this, you know, in an Excel spreadsheet is actually quite powerful for us. So, at the moment, we do offer this service on Symphony and it's used quite heavily by by our internal salespeople and by a few clients.

Julien Dugat: A lot of our clients are on IB Chat. So ideally what we want to do going forward is is provide something very similar on IP, uh, as and when IP start opening up a bit more to to chatbots. Because, yeah, that would be really looking at a user base. That would be extremely powerful.

Matthew Cheung: Yeah, absolutely.

Matthew Cheung: anD Brad, what's what's your thoughts on chats based kind of projects?

Bradley McNee: So we're now in the cycle for planning next year. And indeed these these are on the horizon from a race perspective comes down to prioritization of what we're looking to do for the resource we have available, but what more widely across TPI cap in other other assets are in global broking.

Bradley McNee: We're using chat to be able to make the the full life cycle of, order entry to trade matching to trade confirmation more efficient and really we start that for from back to front. We started to be able to deliver what is the end message to the client for what has has traded and and just looking at the whole workflow of, What an I.

Bradley McNee: B. I. D. B. or a venue executes for clients. We're always looking to make that more efficient. And so from a race perspective efficiency and speed to trader is going to be key. So there is other market infrastructure that we need to get that into. They don't just want to see it in the chat.

Bradley McNee: They want to receive the risk. Yeah.

Bradley McNee: In through STP reports and, you know, other confirmation services, such as market wire or indeed things like Bloomberg, VConn and and such like, but some of the steps are to be able to make more efficient to automate that chat rather than have people type it. And yeah, so that that I see is.

Bradley McNee: It's part of the journey that rates will be going on that other assets within TPI cap have already gone down the root hole. So yeah, it's just making the overall process more efficient.

Matthew Cheung: And in terms of the kind of the overlap between Excel and chat. So how, how we kind of see it from my perspective, this kind of workflow is probably split into like three different buckets.

Matthew Cheung: One. where it's Excel based workflow with some semi structured data and that spreadsheet might be emailed backwards and forwards or attached to a chat. Another might be in the chat itself where people are typing, you know, manually typing prices, entering prices and people responding. And then, and then the last one where those two things overlap, where you, you might attach a spreadsheet and you type something into the chat at the same time alongside it.

Matthew Cheung: So, One of the things that we're we're launching very, very soon is actually we just integrated symphony chat into Excel so you can have the chat embedded into Microsoft Excel. So it's side by side. So again, you've got that kind of integrated workflow deploying it onto things that are already on the desk.

Matthew Cheung: But how do you see Excel and chat evolving together? Because I think like we've already said, there's always a there's always a place for Excel. Thank you. In the short, medium, maybe long term because of the nature of the flexibility of what you can do with it. And because you now have chat is so much more open, you obviously it was led by Symfony initially.

Matthew Cheung: And then everyone else started following suit, including now Bloomberg, where you can start. being able to push data into a chat and pull it back out again, do things with it, manipulate it connect it into different systems and so on. Where do you see Excel and chat kind of going forward together in the future?

Matthew Cheung: And it might depend on different markets as well, because I think Julian touched on earlier, in some markets that are not electronified, stuff is still done on Excel. So it has to kind of live in that space. But as the, maybe it's a broader question of electronification in markets as well. You know, and where does Excel and chat sit on all those journeys?

Matthew Cheung: And is it an on-ramp? Is it a springboard? You know, how, how does that work?

Julien Dugat: So,

Bradley McNee: go ahead Julian.

Julien Dugat: I was gonna say we are in terms of workflow, so we would tend to favor chats at the moment. So we, we all workflows would, would run or be facilitated on, on chat. We don't really do workflows in Excel today. I can see the. The advantage of doing this, the benefits of doing this but it's not really something we've explored.

Julien Dugat: So yeah, for us, it really is at the moment, Excel is really a way to surface the data. We don't really get anything back. So it's really a one way, a one way thing we push to Excel. We don't really Very pulled back from it. Anything that is like an interaction with with clients for instance is done through chat, so potentially through bots and other assisted tool for workflows.

Julien Dugat: But yeah, not in Excel.

Bradley McNee: Yeah, so I think this, this does go to the point of how given even to the point of given desk or different assets will electronify their product from, um, an IDB perspective I, I sometimes went to the term electronification because it's all around efficiency. And how we can make the process more efficient is often through making the tasks, uh, more digitally accessible.

Bradley McNee: And so here, I just say that I, I, I think that there's always a place for the human in. The fixed income or rates market, and that actually, when we, my fear is that you, you make it not too automated, but you might put too much onus on a computer making decision and might over automate it and maybe over execute in things that from a race perspective are always.

Bradley McNee: Executed in large size. So I think the rates market, from my perspective, will start off and, uh, the journey through electronification and see how far we can push it, not get to that place where. The execution is always a bot against bot inside inside a chat. It would still be sort of human managed and the efficiencies of of the of the output can can be automated.

Bradley McNee: But the actual decision making itself. Is is on the whole still needed to have a lot of human guidance over it. So, so I'm not sure if I necessarily ask the question, but I would just say that our in integration with chat over Excel. We'll always be with the trader in mind and to try and make their, their life as, as as easy as easy as possible.

Bradley McNee: Really?

Matthew Cheung: Yep. Yeah, going back to that client experience point, the trade is your client and you want to make it easy for them. And if it's easy for them, then they might give you more business ultimately.

Bradley McNee: Yes. To a degree, that, I mean, yeah, that's, that's right. That's a, it's a good modus operandi.

Matthew Cheung: And, and I suppose the, with everything then moving towards being more API driven, it makes you're both product managers in, in your respective organizations, but now that things become more API driven, how much easier does that make your life?

Bradley McNee: I'll, I'll start with this time. It makes it a lot easier to be able to see what's going on. So, so I can. I can tell now not so much in a, in a surveillance type way, but I, but I can now, now monitor progress of, of the desks in, in a lot in from the thanks you have of my own office, but also just to be, be able to.

Bradley McNee: Rather than have to go and ask someone an opinion, it's it's now a lot more based on actual data rather than opinion. So I think that that's the big, uh, the big change from. My perspective is maybe as a as a product manager is that is that now we can, we can actually inquire that with the data directly,

Matthew Cheung: I think so. That's not Julia.

Julien Dugat: I'm not sure we're seeing more things going through API's now. I mean, I suppose it depends on the asset class, but I would say in race and credit, things are more and more going towards electronic platforms whether it's. You know, people using an actual UI or using like rules based execution engine or, you know, some of the tools basically provided by the platform and must be connecting the OMS through API.

Julien Dugat: But, yeah, generally, I don't think, yeah, in the rate space, we've been seeing more flows coming through actual like execution APIs. So in effects, I would say probably yes, that's true. And yeah, but back to what Brad was saying, it's basically making giving you more transparency of the data. That's for sure.

Julien Dugat: But yeah, in rates, I don't think, I don't think we're there. And I think it's, it's just a slightly different model, I guess.

Matthew Cheung: Yep, so voice and chat still still dominating in the asset class. So, so we've we've touched upon Excel, we've touched upon chat and spoken about APIs as well. So that then gets you into this omni channel approach, whereby you can connect to high push pull in this case.

Matthew Cheung: And you can distribute to all of those things, plus a bunch of other stuff as well. It'd be good to understand from the audience that are listening as well, if we do another poll, you know, as a bank or a broker or a data service or any other data producer, you know, what's your view on building and maintaining all of these different integrations in order to make your data available to clients or wherever.

Matthew Cheung: They want it. So will, will you service an omnichannel distribution strategy for your digital platform or out to your clients? You know, are you looking to, to buy in and partner with companies that are out there? Are you looking to build it yourself? Are you looking to buy, to build that would be using like a no-code platform or do you not think omnichannel distribution is important and you are quite happy just to stick with the channels you're already using?

Matthew Cheung: And it's Steve, if you can pick up the results of that.

Julien Dugat: Yeah, so just give it a couple seconds longer for people to respond. At the moment,

Matthew Cheung: buy and buy to build are probably the favorite responses so far. Yeah, those two. Great. And I suppose Brad and Julian, it's just in terms of, you know, you've probably both been in the markets, you know, 20 plus years like myself.

Matthew Cheung: How have you seen that shift between, you know, build or from building things in house with your own resource actually now to working with FinTechs or vendors or people externally to help you deliver things? And also, how does it help now you have standards like FinOS and FTC3 and people playing nicely with open source and so on?

Matthew Cheung: How have you seen that shift? Why did you both choose to partner with iPushPool rather than build it yourself?

Bradley McNee: So there's quite a lot to cover there, but if I kick off, so I mean, I think there's been a general trend from my time here working financial markets to move from build towards a more blended solution, and that then oscillates around how much you are building yourself versus you're buying, you basically make all of those decisions through your technology teams as to what's the most cost effective.

Bradley McNee: But also you make those decisions quite as well. Sometimes what's the fastest market? So from to to answer the last question, though, for so engaging by push pull what we really got was that fast, faster to market commodity that was an Excel API in this case. And then that product could be supported where it gave us what is more cost effective way to be able to support without needing the in house specialist.

Bradley McNee: So, um, so, yeah, that, that, that's kind of it. But you take each each challenge, each problem on its own merit. And so you have to make those, those calls very pragmatically as, as how you rather than necessarily be in one camp, nor the other. But so what I'm seeing now is that blend of buy some stuff, build some stuff yourself.

Bradley McNee: anD it can depend upon whether that is your, your, your key strength, whether that is your own IP that you have to mount, that you want to retain. And, and so, yeah, you kind of have to make those judgment calls in partnership with your own your own technology, technology organization.

Julien Dugat: Yeah, completely agree with that. Yeah. So it's for us, it's very similar. So it's, it's a good mix today, certainly. The reason we chose iPushPool we usually look at you know, how differentiating basically is this piece of technology how quickly can we get it to market if we build it ourselves, how much is it going to cost us to actually maintain it, so build it and maintain it, um, versus just having somebody dedicated to actually doing this and keeping it updated and So certainly for this, this sort of omni channel approach.

Julien Dugat: So making updates are basically available through excel through API through web interfaces on symphony. wE, we took the decision to actually go without push on this basis because we could get a product to market really quickly and we didn't think we could actually build it and support it for less than the license cost.

Julien Dugat: On the second half of your questions in terms of you know, Finos, FDC3, and how it, how it helps.

Matthew Cheung: So, it does

Julien Dugat: help a lot to have these standards. And when you want to to do a project and work with other vendors or clients, the fact that you've got such standards to leverage. So we know that on our desktop, we basically use FDC3.

Julien Dugat: We know that a lot of our customers and vendors are on the same technology stack. So you can actually when you're talking about some of our application talking, for instance, with a UI that the client is running on the desktop for the OMS, for instance, that is now possible because everything is running on the DC3, for instance.

Julien Dugat: So. I think it's still there's still quite a lot of work to do there. It's definitely going in the right direction. But yeah, it's going to take a few more years, um, to really, you know, have this widespread and, and, and make, make releasing products much more efficient. Are we getting there?

Matthew Cheung: Good to hear.

Matthew Cheung: So. We'll start to wrap up and then take some questions. So, so this, just to kind of summarize the, the omnichannel approach means you can, you can actually cover more clients because you can cover more channels and you can also provide the ability to share data in the applications, depending even on what the technical ability is of the client, all the way through to what the maturity is of the particular market.

Matthew Cheung: So the omni channel approach is always like an evolving goal because it's always going to new things going to be added to it as time goes on. But Excel is actually the easy point of entry for all the stuff we just discussed, you know, around it being very easy to deploy. It's quick and fast to market.

Matthew Cheung: You know, it's on a trader's desktop. People know how to use it. But having a controlled and access controlled kind of audited permission environment to use Excel. Is really useful. I'm actually Excel becoming an interface. So it's super lightweight and it can that through Excel connecting to something like our service.

Matthew Cheung: It can actually connect into a particular dealer screen or particular fix engine or whatever it might be. And you got that one connection and also gives you the on ramp. Starting from Excel, a lot of the time, the on ramp inter chat APIs being FTC3 compliant, having extension apps in Symfony, having something connecting into Bloomberg.

Matthew Cheung: So everyone does always want to improve their client's experience, and it can be done in a variety of ways, and ultimately helping to make processes more efficient. 30 seconds, both of you, in terms of improving client experience. It's before we move to Q& A. In terms of improving client experience, what keeps you up at night?

Matthew Cheung: What are you thinking about? What keeps you up at night that you think there's something that can always be a little bit better?

Julien Dugat: So for me, just going back to what we were talking about before, Eddie, it's it's us having the right offering. So being able to deliver a product through as many channels as we can. So, when clients come and engage with us, And want to deal with us in a certain channel. We're there. We can actually meet them on this channel so this is this is really what we're investing on now It's reaching out to more clients with more products through more channels

Bradley McNee: Yeah, so for me at the moment, it really is making sure that all the foundational layers to what we're doing are All right, so it's less about actually what's being exposed to the client at the front end. It's more about making sure that our, that the robustness of the venue that we're operating is robust, stable and able to be, yeah, supported for the client and ourselves in the long term. But as it happens, I sleep very well. So I don't, I don't, I don't get up halfway

Matthew Cheung: through the night. Well, that's always good to hear. Okay, Bryce, Julian, thank you so much for sharing your knowledge and insights today. So to wrap up, we've got a few minutes left for any questions.

Matthew Cheung: Steve, are there any questions from the audience? Yeah, conscious, we've only

Julien Dugat: got a couple of minutes left. So there's probably one question that.

Matthew Cheung: probably would nicely finish off what

Julien Dugat: both Julian and Brad were just saying, which is around how does delivering live data to your clients give you competitive advantage or does it give you competitive advantage?

Julien Dugat: Yeah. So from from a TPI

Bradley McNee: perspective, it, it does give us a competitive advantage such that they can see our prices and be able to act upon them. And with specific. Reference to excel. We can do it in an environment where they can compare to their own prices. And it's that comparison of of of market levels that enable someone to make a decision to act upon it.

Bradley McNee: I think is what trading is all about from our perspective to help banks manage their risk. So so, yes, it is allowing people to see our prices is it's vital. And this is a. A channel to to enable that.

Julien Dugat: Yeah, I mean for us some real time data in excel is it giving us competitive advantage? Yes, so just again going back to the example example of axis so for For client consuming this Through an api on platform.

Julien Dugat: They can see this in real time for clients who want to see this in excel Typically how it used to work and how it works is you would receive a spreadsheet from one of your salesperson. Obviously, when you open the spreadsheet, the axes are already still they're not updating. If we use well, I push put in, in, in this example, we can actually stream our axes directly into Excel.

Julien Dugat: So when you look at your spreadsheet, you know that the axe data you're seeing there is actually up to date. So if you then. Go and reach out to a sense person about a particular acts, you know, it's not going to be stale and you will be able to execute on that. So, yeah, definitely competitive advantage for us.

Matthew Cheung: Thanks guys. We're coming up to the turn of the hour now, so we'll wrap up. Thanks again for everyone that's listening. Thanks for sticking around for the whole session. I hope you learned something new. Thank you, Brad. And thank you, Julian. And if you want to learn more about Excel, there's an ebook which you can access inside this platform.

Matthew Cheung: You can also get it from the website. And if you've got any questions for Brad or Julian, I'm sure they'll be happy for you to reach out. And also if you want to learn more about iPushPull and how you can deliver live data in some of these channels, then do give us a shout.