TRANSCRIPT: Using Excel as part of your digital and platform strategy to deliver live data to clients

[00:00:00] Hi everybody. Um, thanks for joining today. It's Matthew Chung here. I'm CEO of I push Paul. So we are 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, how you can be fast to market when launching new products.

And then. Booking Excel can actually serve as an entry point into this omnichannel delivery, um, which then acts as an OnRamp into chats and APIs and, and lots more. So we're delighted today to be joined by Brad MCNE, who is our product manager for TPI cap. Is also responsible for the world's largest rates, broken 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 Judy dugout. He looks after fixed income, credit and FX for now, west markets [00:01:00] and managing products for cross product sales and covering one of the UK's leading rates, desks and net west markets is the investment banking arm of the net west.

And they cover corporates and institutions. So they'll be distributing their prices and quotes out to the buy side while also receiving quotes from brokers like ICAP and as myself, Matthew Chung, I'm a CEO of, I push Paul. We're a realtime data sharing and workflow automation platform. 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. So let's dive in, in terms of what we're gonna talk about today.

First, we're gonna talk about why Excel then move on to how net [00:02:00] west and TPI cap are delivering live data. Then we'll talk about Excel and how that crosses over into chat, and then this omnichannel data delivery and what that actually means and how it can provide a better client experience. So let's kick.

Um, 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 is important?

Hey Matt, thanks for having me. Um, so I mean, I guess for us, this is really about, uh, we've re recently expanded the, uh, the number of clients that, uh, we. uh, in the, the commercial and, uh, institutional franchise. So we, we really want to be, um, offering, uh, uh, flexibility to our clients. Uh, so whatever way they want to use to, uh, to connect to us, uh, we want to be there basically.

So X Excel is [00:03:00] obviously one of this channel. Um, we, depending on the asset class, uh, we. Our offering is, is quite diverse. So in effects we'll tend to have, uh, to offer fixed APIs. And we've got, um, uh, we've got a lot of clients who are actually quite happy to, uh, to code, to fix API. So in the FX space, we'll be using, uh, IBU and Excel to distribute things like, uh, the, the less true axis, uh, in the rate space, we, we use IBU pool to, uh, uh, to deliver our axis as well or live axis.

Um, again, this is just one of many channels that, uh, that we use for, uh, for this type of data. Um, what is quite important, uh, to a lot of our clients is the ability to access for data with, uh, value to work, uh, as in like a non install solution. So the ability to, [00:04:00] uh, to do this either through web or, uh, Excel is actually quite valuable for them.

Uh, cuz they can really quickly just switch on the stream and the data is coming into their, uh, their Excel spreadsheets. Um, and, and obviously the, the type of people we, uh, interface with as well. So on uh, uh, software managers, uh, people on the execution desk, everybody would've Excel running, uh, on their desktop.

Uh, and we want to actually. some of our data into Excel to actually do some data, manipulation, charting, uh, these type of things. And, and why do you think it's so ubiquitous across every desktop that we see in the financial markets? Why is Excel so ubiquitous? Yeah. Yeah. Um, well, I think there's definitely a place for Excel.

I mean, people have been using it for everything. Uh, There's various, a lot of VP code, obviously being written. [00:05:00] So a lot of it will be legacy, uh, but there's definitely a, a place for Excel as well, just for, um, uh, for, you know, charting and, and some sort of data slicing and dicing. Um, but yeah, a lot of people are also using as a pricing engine, um, or way to actually abridge.

To other systems as well. So some of our clients use it to, uh, to go and, uh, uh, sort of collect data, do a bit of data, formatting, data manipulation, and then load the data into the, the final system, like, uh, another management system, for instance. Cool. Thanks, Julian. Um, and Brad, um, same question to you. Can you talk to me why you think offering TPI caps data in Excel is important?

Yeah, sure. And likewise, thanks for having me here. So, um, from a usability perspective, Excel, um, has kind of remained [00:06:00] a bit of a constant in anyone's desktop over. Definitely the 25 plus years that I've been working and indeed the way in which you're able to, um, expand, um, upon its offering, uh, whether that's, you know, from sense of formulas to, to VBA, to charting tools, as Julian, as, as mentioned, you can, you can really use it as.

Um, it's a really flexible way of pulling data in and manipulating it, um, such that you can then also get actionable events from it, um, from an ICAP perspective, um, Really getting data into Excel is, um, uh, is putting it is similar actually to what Julian's been saying is, uh, is in some ways the client's preference at, uh, first point of contact so that they don't have to go through a large, um, [00:07:00] or even a small upscale or, uh, enterprise wide technology solution to be able to get their data into, onto their front end.

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

Um, but. Almost the lowest common denominator is formulas within Excel. And then the next level, which is BBA. And, and, and at what level would you see this tactical? Easy to use application actually then turn into a strategic application? Uh, [00:08:00] I see, I think that goes to the, the point of prototyping. So you can prototype within there and then you can.

Very easily show someone how you have yourself built and designed it so that it can be padded over to a, a technology function that can support it more, more widely and spread it across your organization. Uh, indeed you can even spread functions within Excel across, across your organization as well. So, um, but it's that first stepping stone.

And so when you. And add in to be able to bring the data into Excel. You've begun that journey and really that's the, um, that's the key to us. You might not need a second step on the journey. You might just be serving up the data to a, a single person or a, a few persons are able to share it and not need an enterprise wide solution for it.

So, um, [00:09:00] really it, it depends upon. The data depends upon the clients and, um, and how much they want to scale, um, the data, but in terms of how we, um, from a race perspective, use Excel, um, 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.

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

So Excel [00:10:00] chats, APIs. Fix all of the above or, or anything else. Um, if you are 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 wanna respond to that should pop up in your screen. And then Steve, if you tell us when we've got, um, enough results and we can, do you wanna just cover them?

Yeah, sure. So, uh, we're getting a pretty strong reaction to all of the above obviously is not surprisingly. And then probably all of the above is probably the next, most popular. Fantastic. Well, we've got the right audience then. Um, thanks for replying to that poll. Um, so moving on, um, let's, let's kind of go, go onto the hood a little bit to exactly.

What Julian and Brad are doing with how they're distributing data. Um, firstly, Julian, can you tell us, like what type of prices and data [00:11:00] 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 client, the technical ability of the client, actually the maturity of the market that they're in, cuz it might not be that electronified, there's a few different angles and variables. Um, what, what, so firstly, what prices and data are you generating and then why are you choosing to distribute those through Excel?

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

So this is, um, a really electronic, [00:12:00] um, item. So. Uh, single platform. So multid platforms, uh, or auto management system, we basically support, uh, receiving this through, uh, a fixed message. Um, but in effects it's, it's quite different. So actually are way less, um, uh, of a commodity, I guess, uh, and is much less stricted.

So we actively internally, um, we use. Uh, Excel and I push pool basically to distribute this type of data because we have no, uh, you know, formal, structured way to actually do it. Uh, the second category is really about, uh, Excel as, as a, a channel instant, right? So we are already distributing our axis, as I was saying, uh, in the fixed income space through lots of different channels.

So we got fixed API. Uh, we send directly to, uh, platform, things like Neptune, Bloomberg trade web, and so on. , but we [00:13:00] do have demand on the client side to actually get this data directly in Excel. Um, and as I mentioned before, uh, reasons can be multiple. Uh, typically client will actually take this data in Excel and then load it into another system afterwards.

So use Excel as, um, uh, as a bridge, really. Um, so we also, um, yeah, this are the, the two main categories and we, we have, um, um, quite a few data types, uh, that we put . Uh, so typically things like prices, access, uh, in, in the rates credits and FX space, uh, would be so more electronic, uh, things like, uh, like sector access rates, uh, access effects would be less El.

So they will be getting, uh, through IPU pool and not on your Excel. Cause we are [00:14:00] also, and I think we're gonna talk about this later, but we also doing this, uh, on symphony through, uh, through bot, so got bot distribution channel. Uh, we also do it through the, uh, the, the web UI, uh, cuz we do have demand for that.

Um, Yeah, so that, that's the two, two main reason for doing it, uh, unstructured data that, uh, we can't easily distribute it electronically. Uh, and, uh, just because of the, the demands on the client side to actually get the data through this particular channel. Great. Thank you, Julian. And Brad, can you tell firstly, just the listeners about how TPI cap is distributing data to, 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? Sure. So, [00:15:00] um, our electronic trading offering, um, uh, centers on a, um, uh, An application, frontend, HML, uh, HML five frontend that will display the prices to the traders, such that they can then put orders onto 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 two, um, months and quarters, um, for other rates desks, um, the, the data then really is, is other prices for the instruments. These tend to be, uh, mid-market.

Prices. Um, and then where we run matching sessions as well, we make, um, we, we show that data up [00:16:00] onto the front end, um, for traders to be able to place orders on there. What we look to do with the addin is replicate that data that's available in the front end into, through, through the API so that people.

Read it in their tools, Excel being a 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. Currently, we don't, um, Allow for the capability to, uh, send orders back to the platform and then we're somewhat wary to be able to do so because otherwise we will be, eh, potentially enabling the client, maybe unwittingly to become, [00:17:00] um, an algo trading, um, have algo trading capability and hence have a higher level of regulatory requirements.

They might not realize that their spreadsheet suddenly becomes, um, a, um, a really large compliance issue, uh, to, uh, satisfy the regulatory control requirements that, um, that are, that are needed to operate on such OTF or, 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, um, be, uh, human operated on, on, on our side to, um, uh, avoid the, uh, algo type issues that they may be facing. So first answer your questions. We display prices [00:18:00] for in order to be able to get orders. Um, from the market levels that, that we're, we're seeing, um, from, from banks.

And, and what do you both think of this kind of integrated workflow? Um, whereby. Screen space is always at a premium on any trader or salesperson's desks, cuz they'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, uh, your ICAP screen or one of the offerings from that Western, 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?

Yeah. So I'll, I'll try and take this first. Um, the, the, the workflow that. That, um, the APIs give you, [00:19:00] I think, is enables you 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.

So, um, and then the workflow around that will hopefully enable you to design something on your side, to be able to give you a. The right response mechanism to then choose to interact with someone else's front end on, on their, on their, their screen in front of them. So, um, it, in some ways, uh, decouples not quite devalues, but decouples the need to be able to have the screen, uh, open on the desktop at all times.

And you can choose when you wish to view it from fr from my perspective. um, so look that, I think that the API [00:20:00] is, um, is, is needed to be able to make those, uh, trading decisions more efficient, um, by enabling comparison, more easily on the bank side, but also hopefully it, it doesn't mean that I'm, uh, forcing real estate upon the client.

Uh, it, it still remains their option when they want to see. Yeah. And, and Julian, what's your perspective on, on that, and also on your internal setup? Cause I know you spent a lot of effort and resourcing 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.

How is that? Is that integrated workflow for you? That's right. So just back I think to what, um, Brad was saying. The, uh, especially, I guess in the fixed income space, we don't really have [00:21:00] the single data platform are not really the thing anymore. Uh, so getting, you know, a grabbing space on, uh, a client's desktop is actually really, really difficult.

Uh, and it's tough ask really. So having this, uh, this sort of multiple channels, uh, and Excel is, is one of them, but, you know, using APIs as. Um, 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.

Uh, so if they want the, the data in, 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, uh, with, with this, uh, offering, um, uh, going back to your, to your second question. Um, yeah, we've invested, uh, quite heavily in, uh, in FDC three, [00:22:00] um, and in having a, a smart desktop, um, to try to make a workflow, uh, much more efficient.

So we rely a lot on, um, uh, some of our application be being context driven. Um, so some event would push, uh, contact on a desktop. Uh, another application would react to this. Uh, so for instance, uh, if an inquiry, uh, from a customer comes to us, um, 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. So maybe one of the application actually show you the last 20 inquiries for this particular bond, for instance. Um, and, um, um, it, it, it sort of, it allows you to do things [00:23:00] that, uh, a users normally wouldn't be doing like the inquiry workflow. Uh, you know, you get an inquiry, you code back, you execute some time within five, 10, uh, there is no way a trader can actually go into a blotter and search for something where this is happening.

So you, um, this sort of empowers user to get all of this data, uh, without really providing an input, uh, and give them all this additional intelligence, uh, to help them in decision making at point of inquiry in this.

Cool. Um, and, and in terms of just going back to the external facing, when you are, um, trying to get your data to clients, going to some of the things you just both picked up on, how does actually providing any Excel help with the speed of deployment? Cuz we, we all know and it's it's as gospel that Excel's gonna be on someone's desktop.

Right. [00:24:00] So then how, how does it. In terms of deployment and, and kind of speed to market when you want to get your data to someone and also touching, 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. A hundred percent. So I think, um, in terms of speed up deployment for us, I mean, we use the, um, uh, we push our data to, to web as well.

So through I push through, uh, so. It is the fastest to market. Really. If somebody is happy to access the data, uh, through their web browser, we can just send a link and they will be able to see the data straight away. Um, the next, uh, the next fastest, I guess, is to, um, to use Excel. So if there's any data manipulation needed, and client do want this in Excel, then, um, we do an Excel in that.

Uh, they can, uh, download from our agile market single. um, so it's, [00:25:00] uh, it's not zero install. Uh, there is, uh, a bit of work to do, uh, to install the add-in, but it is very lightweight. Uh, and we can usually do this really quickly. So obviously this is much quicker than, um, you know, getting the client to build to a API, for instance, which will take weeks or month.

Um, so it, it, it is, um, in terms of the, the sort of the offering you get, um, as Brad was saying, if you want to do any prototyping and start using the data, uh, and manipulating it, this is definitely a much, much faster way to do it than any of the, uh, the next best, best option fixed APR or, or anything like.

In, in a way, is it democratizing kind of access to, to data by having it in Excel? Because [00:26:00] there's, if I'm, if I'm a small, um, hedge fund, for example, and I want to connect to you, I might not have the in-house capability or resource to connect effects, like you said, but if I could use Excel as an interface then to connect interface, Something sitting in the middle, like, like some of the services that we have to then actually make that the tail of clients that you can service much, much larger and longer.

Yeah. And, and it's, um, it's always been the ideas to be able to, um, uh, to target a lot of clients who don't necessarily have the, uh, the appetite, uh, or the budget to actually spend time and efforts, uh, in, in coding to, to an. Um, so it is it's speed it's cost, um, and it's, it's quite a commitment to go for a, for a fixed API as well.

[00:27:00] So if you are not quite sure that, you know, maybe you want to interface with a particular dealer, um, it, it, you, you sort of need to, to go through the process, I guess, while with having the data in. it's actually, it's almost like a free option, so it's really easy to try it. Um, anybody can do it and you know, if you actually decide that maybe you don't need the data, um, then you know, it it's very, it is, there's no regret spend basically in this, right?

Yep. You got anything to add to that, Brad? Um, everyone likes a free option. Um, yeah, that, but the optionality angle to. To give you the choice of how you want to handle the data is, is I think key, um, for us, we, our, our clients are, are large banks. So, um, within global broker, uh, for TPI caps. So, um, [00:28:00] here we find more of a problem to be able to get onto their work stack and, uh, and their priority queue to be able to.

Uh, necessarily build a, a fixed connection to, uh, to our own API. But, um, you know, it's, it gives them the option for how they wish to proceed. They can do so, um, in a very similar way to Julian to explained through, through, through the platform for first point through the, through Excel at second, and then direct to, to the API third and, and it's their own pace.

They can choose those tools. Excel is a really small first step to, to do that. And it just to echo what Julian said, it's, it's putting it in the hands of traders that can manage this themselves. They are all. Very proficient at all of the [00:29:00] tooling within Excel. You know, it's the first thing you, you are gonna be coached on when you join a desk.

And in fact, quite frankly, traders are now getting more proficient from a rates perspective in, in other, um, analysis type tooling that they could probably quite quickly. Um, some form of Python to be able to connect to an API and, and, and, and do that there as well. What Excel does is gives you that, um, ubiquitous, um, uh, tool across, across the trading floor for it to be shared and, and you to learn from, um, that lowest common denominators I mentioned.

So, so it always maintains its relevance anywhere because it's ubiquitous cuz 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. Yes. Yeah. Yes, precisely. And so, you know, I, [00:30:00] 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. So second, second stepping zone faster. So like, it's just, it will still be the first point from, from my perspective, albeit I'm slightly old school. okay. Old school to new school, then let's move on to chat. Um, yeah, obviously IB chat's 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, you know, lots of places across the financial markets. You've got, you know, the, the old school, Microsoft is obviously release teams and there's lots more going on with that. And then there's ice, some affinitive messenger and slack and lots of other things.

So chat is always gonna be a part of this industry because [00:31:00] of the nature of negotiations and things that we do. But what do you. Um, both see as the future of chat workflows in this industry, I know Julian, you love chat bots and chat and, and you've invested very heavily in it. And, and Brad, you've got some big ideas from what you wanna tackle as well.

What type of projects are you both looking at at the moment?

Go first. And so, yeah, as you said, so we are, um, We, we had the users of, uh, uh, IB chat obviously, and, uh, symphony, um, we, we have, uh, as an example, we've got, uh, uh, an execution bot in, uh, the rates and credit space, um, that is sort of augmenting the, the sales client workflow. Um, so it, it provides indicative prices, uh, and, and really [00:32:00] assist, uh, the, the, the.

People through the execution workflow, um, the, the, the sort of, and we do have quite a lot of bots and symphony. Um, there is, uh, there's obviously a life cycle, uh, sort of build bot features, uh, released then, uh, and that can be quite lengthy sometimes even if symphony is actually, you know, pretty open platform.

And it's pretty easy to do that in symphony. Um, so. More recently we've been, um, using the, uh, the, the IBU cool features, uh, the, the bottom demand feature, uh, which has allowed us to really quickly, uh, respond to, to client demand, uh, and, and internal demand from a, from all salespeople and traders. Um, so when somebody wants a very specific function on the.

we, we don't have to go to, uh, our it team to actually build [00:33:00] that. Uh, a lot of it can just be set up in the, uh, in the web UI, uh, very easily. So somebody like myself can actually go and, uh, uh, and send, set this up within, you know, five, 10 minutes. So as an example, uh, one of our client asked us to, um, uh, to get access, uh, in a, in a very specific format.

So they were after, uh, a. Specific set of axis. So for a specific set of countries and materialities, uh, and they wanted these to be output in Excel, uh, on symphony, uh, by just typing a command. Yeah. So just calling the bot and typing a three, four works command, and then that should give them the Excel thing.

So, because we've got all this data, uh, in Abu, uh, building the, we could build this within. 30 minutes. I'd say that was pretty much done. So we can be really responsive, uh, for things that [00:34:00] actually, you know, might sound quite basic. Uh, but the ability to get a specific, you know, filtered set of data, um, in a very specific format, whether that is outputting your table in symphony or whether it's, uh, just outputting this in a, in an exercise spread.

um, it's actually quite powerful for us. So at the moment we do offer this service, uh, on symphony and it it's used quite heavily by, uh, by our internal sales people and by a few cl clients, um, a lot of our clients are on IB chat. So, uh, ideally what we want to do going forward is, uh, is provide something very similar on.

uh, as, and when IB start opening up a bit more to, uh, to chatbots.

cause yeah, that would be really looking at a user base. Uh, [00:35:00] that would be extremely powerful. Yeah, absolutely. And, and Brad, what's, what's your thoughts on chat based kind of projects? Uh, so, uh, we're now in cycle for planning next year. Um, and indeed these, these are on, um, the horizon from a rates perspective.

um, comes down to prioritization of, of what we're looking to do for the results we have available, but why more widely across CPI cap in other da other assets in global bro, we're using chat to be able to make the, um, the full life cycle of, um, Order, uh, entry to, uh, trade matching to trade confirmation, um, more efficient.

And really, we start that from, from back to front. We, we started to, to be able to deliver what is the, the end message to the client for, for what has, [00:36:00] has traded and, and just looking at the, the whole workflow of, um, What an IB IDB or a venue, uh, executes, uh, for clients. Um, you know, we, we're always looking to make that more efficient.

And so from a race perspective that, um, efficiency and speed to trader is, is gonna be key. So, um, there. These other market infrastructure that we need to get that into. They don't just want to see it in a chat. They want to receive the, the risk, um, in, through STP reports and, and, you know, other certain confirmation services such as market wire, but, um, or indeed things like Bloomberg and, um, and such like, but look, some of the steps are to be able to, um, make more efficient.

So. That chat rather than [00:37:00] have people type it. And, um, yeah, so that, that I see as, as part of the journey that rates will be going on that other assets within TPI cap have already got gone down the route of, so yeah, it's just making the overall process more efficient. And in terms of the, the, kind of the overlap then between Excel and chat.

So how, how we kind of see it from our push pulls perspective, does the kind workflows probably split into like three different buckets, 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. Another might be in the chat itself where people are typing, you know, manually typing prices, entering prices and people responding.

Um, 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. So. One of the things that, that we're [00:38:00] we're launching very, very soon is actually we just integrated symphony chat into Excel. Um, so you can have the chat embedded into Microsoft Excel.

So that's side by side. So again, you've got that kind of integrated workflow deploying it onto things that are already on the desk. But how do you see Excel and chat evolving together? Cause I, I think like we've already said there's always a, um, there's always a place for Excel 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 symphony initially, and then everyone else started following suit, including now Bloomberg, where you can start, um, being able to push data into a chat and pull it back out again, do things with it, manipulate it, um, connect it into different systems and so on.

Where do you see Excel and chat kind of going forward together in the future? And it might depend on different markets [00:39:00] as well. Cause 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, and 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? And is it an on-ramp, is it a springboard? You know, how, how does that.

So go ahead, Julian. I was gonna say we are, um, in terms of workflow, so we would tend to favor, uh, chats at the moment. Um, so we, we all workflows would, would run or be facilitated on, on chat. Uh, we don't really do workflows in Excel today. Uh, I can see. The, the advantage of, of doing this, the benefits of doing this.

Um, but it's not really something we've, we've explored. Um, [00:40:00] so yeah, for us, it really is at the moment, Excel is really a way to surface our data. Um, we don't really get anything back, so it's really one way or one way, think we push to Excel. We don't. Very pulled back from it. Uh, anything that is, um, like an interaction, uh, with, um, with clients, for instance, uh, is done, uh, food chat.

So potentially through bots, um, and other assisted tool for workflows. Uh, but yeah, not in Excel.

Yeah. So I, I think this, this does go to the point of, um, how, uh, given, um, even to the point given desks or different assets, uh, will electronify their product from, um, an IDB perspective. Um, I, I sometimes went the, the term electronification because it's, it's all around. And [00:41:00] how we can make the process more efficient is often, um, through making, uh, the tasks, uh, more, uh, digitally, uh, accessible.

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

Executed in large size. So, um, I think the rates market from [00:42:00] my perspective will start off, um, and, uh, the, the journey through electronification and, and see how far we can push it. But not get to that, um, place where the, the execution is always a bot against bot inside, inside a chat. It, it would still be sort of human managed and the efficiencies of, um, of the, um, of the output can, can be automated.

But, uh, the actual decision making itself. Is is on the whole, uh, still needed to, to have a lot of human guidance over it. Um, and so, so I, I'm not sure if I necessarily asked the question, but I, I would just say that our in integration with chat over Excel, um, will always be with the trader in mind. [00:43:00] And to try and make their, their life as, as, um, as easy, um, as easy as possible.

Um, really. Yep. And, you know, going back to that client experience point trader is your client and you wanna make it easy for them. And if it's easy for them, then they might give you more business, ultimately. Yes. Yeah. To, to a degree that, I mean, yeah. That's that's right. That's a, it's a good motor, Andy . Um, and, and I suppose the, with everything then moving towards being more API driven, it makes your both product managers.

Um, in, in your respective organizations, but now that things become more API driven, how much easier does that make your life?

Um, I'll, I'll start with the time. Um, it, it makes it a lot easier to be able to see what's going on. [00:44:00] 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, uh, progress of, of the desks in, in a lot, um, in, um, from the thanks sheet of, of, you know, of, of my office, but also just to be, be able to, um, uh, yeah, rather than have to go and ask someone an.

It's it's now, uh, a lot more, um, based on, um, actual data rather than opinion. So, um, I think that that's the big, uh, the big, uh, change from my perspective as maybe as a, uh, as a product manager. Is that, is it now we can, we can actually, um, inquire that, uh, about with the data directly.[00:45:00]

Anything, so add to that, Julia. Um, yeah, I'm not sure. We, we are seeing more things going through APIs now. I mean, I suppose it depends on the asset class, but, um, I would say in race and credit things are more and more going towards electronic platforms. Uh, whether it's, you know, people using an actual UI, uh, using like rules based execution engine or, you know, some of the tools basically provide the both platform and must be connecting the OMS through API.

Um,

but yeah, generally I don't think, yeah, in the rate space we've been seeing more flaws coming through, uh, actual like execution APIs. So in effects, I would say probably, yes, that's true.

And yeah. Back to what Brad was saying. Yeah. It it's basically [00:46:00] making, uh, giving you more transparency of the data that's for sure. Um, but yeah, in rates, I don't think, I don't think we are there and I think it's, it's just a slightly different model, I guess. . Yep. So voice and chat still, still dominating in, in that 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 omnichannel approach whereby you can connect to, I push, pull in this case and you can distribute to all of those things, plus a bunch of other stuff as well. Um, 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. They want it. So we'll, we'll use service, anomaly channel distribution [00:47:00] 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, so that'll be using like a no code platform or do you not think omnichannel distribution is important and you're quite happy just to stick with, um, the channels you're already using. And it's Steve, if you can pick up the results of that.

Yeah. So just give it a couple seconds longer for people to respond at the moment by and by to build are probably the favorite responses so far. Yeah. These two. Great. Um, and, and I suppose Brad and Julian, it just in terms of. yeah, you, you're probably both into markets, you know, 20 plus years like myself.

How have you seen that shift between, you know, build or from building [00:48:00] things in house with your own resource actually now to working with fintechs or vendors or, or people externally to help you deliver things and, and, and also how does it help now? You have standards like and FTC three and, and people playing nicely with open source and so on.

How, how have you seen that shift? Um, and why, why did you both choose. Partner with I Paul rather than build it yourself.

So, uh, it's quite a lot to cover there, but if I kick off, so, um, I mean, I, I think there's been a general trend from my time here, here, uh, working financial markets to move from, build towards a more blended. So. That, um, then oscillates around how much you are building yourself versus you are buying, you basically make all of those decisions, um, through your, uh, technology [00:49:00] teams as to what's the most cost effective.

Um, but also you make those decisions quite, um, clear as well. Sometimes it's, what's the fastest to market. So, um, from. To answer the, the last question though, for so en engaging by push pull. What we really got was that fast, fast to market, um, uh, commodity that was, uh, an Excel API in this case. Um, and, uh, then that product could be supported where it gave us what is, um, a more cost effective way to be able to support.

Without needing the in-house specialists. So, um, so yeah, that, that, that's kind of it, but you, you take each, uh, each challenge each problem, um, on its own [00:50:00] merit. And so you have to make those, those calls, um, very pragmatically as, as how you, rather than necessarily being one camp nor the. Um, so what I'm seeing now is that blend of buy some stuff and build some stuff yourself, um, and it can depend upon whether that is your, your, your key strength, whether that is your own IP, that you have to man, that you want to retain.

Um, and, and so, yeah, you kind of have to make. Judgment calls in partnership with your own, um, your own techno technology, um, organization.

Yeah. Completely agree with that. So it's, um, for us it's very similar, so it's it's good bit. Um, today certainly, um, the reason we, we chose [00:51:00] IBU pool, uh, we usually look at, uh, you know, how differentiating basically is, is this piece of technology. Um, how quickly can we get it to market ourselves? How much is gonna cost us, start to maintain it.

So build it and maintain it, um, versus just having somebody dedicated to actually doing this and keeping it updated. Um, and for, so certainly for, um, this, this sort of omnichannel approach, so making your data basically available through Excel. Through API through web interfaces on symphony. Um, we, we took the decision to actually go without push, uh, on these basis, uh, cause we could get a product to market really quickly.

Uh, and we didn't think we could actually, uh, build it and support it for less than the license cost. Um, on the second half of your questions in terms of, um, uh, you know, pH at DC [00:52:00] three and how. How it helps. So it does help a lot to have these standards. Um, and when you want to, uh, to do a project and work with, uh, uh, other vendors, uh, or clients, the fact that, uh, you've got such standards to leverage, uh, so we know that Arnold desktop, we basically use FDC three.

We know that a lot of our customers, uh, and, uh, vendors. On the same technology stack. So you can actually, uh, when you're talking about summer of application, talking for instance with, um, uh, a UI that the client is running on the desktop for their RMS, for instance, that is now possible, uh, because everything is running on the DC three, for instance.

So I think it's still, uh, there's still lot of work to do there. Uh, it's definitely going the right direction. Um, But yeah, it's gonna take, uh, a few [00:53:00] more years, um, to really, you know, have this widespread and, and, and make, make releasing products much more efficient. Probably getting there. Good to hear. Um, 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. Um, and you can also provide the ability to share data in the applications, depending, even on. The technical ability is of the client all the way through to what the maturity is of the particular market.

Um, so the omnichannel approach is always like an evolving goal. Cause all it's always gonna, uh, new things are gonna be added to it as time goes on. But Excel is actually the easy point of entry for all the stuff we just [00:54:00] discussed, you know, around it being very easy to deploy it's quicks and faster market.

You know, it's on a trader's desktop. People know how to use it. But having a controlled, an access controlled kind of audited permission environment to use Excel is really useful. Um, and actually Excel becoming an interface. So it's super lightweight and it can that through Excel, connecting to something like our service, it can actually connect into a particular steer screen or a particular fixed engine or whatever it might be.

And you've 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 FTC three compliant, having extension apps in symphony, having something connecting into Bloomberg. 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.

Um, I was gonna finish off and unless you can sum up in 30 seconds, both of you in terms of improving client [00:55:00] experience. Just before we move to Q and a, in terms of improving client experience, what keeps you up at night? You know, what, what, what are you thinking about and what keeps you up at night that you think there's something can always be a little bit better?

Uh, so for me, just, just going back to, uh, what we were talking about before already, it's, um, it's, it's us having the, the right offering. So being able to deliver a product. 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 are there. We can actually meet them on this channel.

Um, so this is, this is really what we are investing on. Now it's reaching out to more clients with more products through more channels. Great. Yeah. So for, for me at the moment, it really is making sure that all the foundational layers to what we are doing [00:56:00] are, are 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, um, uh, robust, stable, and, um, able to be, um, Yeah, supported, uh, for the client in, uh, and ourselves in the long term. Um, but as it happens, I sleep very well. So, uh, I don't, I don't, I don't get up, uh, halfway through the night.

Well, that's always good to hear. Um, okay. Brad, Julian, thank you so much for sharing your knowledge and insights today. Um, so to wrap up, we've got a few minutes left for any questions. Um, Steve, are there any questions on the audience? Um, yeah, conscious, we've only got a couple of minutes left, so there's probably one question that probably would nicely finish off.

Um, what, uh, both Julian and Brad were just saying, which [00:57:00] is around, how does delivering live data to your clients give you competitive advantage or does it give you competitive advantage?

Yeah. So for, from a, from a TPI cap 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 that I think is, is what trading is all about from our perspective to help.

Banks manage their risk. So, um, so yes, it, it is allowing people to see our prices is its vital and, and this is a, a channel to, to enable that. [00:58:00] Yeah. I mean, for us, so time data in, in Excel, um, is it giving us company advantage? Yes. Um, just again, going back to the exam example of, uh, access. Um, so for, for client consuming this through an API on platform, they can see this in real time for clients who want to see this in Excel, typically how it, it used to work and it works is, uh, you would, uh, receive a spreadsheet, uh, from, uh, one of his sons person.

Obviously when you open the spreadsheet, the axis are already sta uh, they're not. Uh, if we use, uh, well, IKU pull in, in this example, we can actually stream our access directly into Excel. So when you look at your spreadsheet, you know, that the, a data you seen there is actually up to date. So if you then go and reach out to a sense person, uh, about a particular act, you [00:59:00] know, it's not gonna be still and you would be able to execute, execute on that.

So, yeah, definitely competitive advantage. Okay, thanks guys. Um, we're we're coming up to turn of hour now, so we'll so we'll wrap up. So, but thanks again for everyone that's listening. Uh, thanks for sticking around for the whole session. I hope you've learned something new. Thank you, Brad. And thank you, Julian.

And if you wanna learn more about Excel, there's a ebook which you can access, um, inside this platform. Uh, you can also get it from the website and if you've got any questions for Brad or Julian, you know, I'm, I'm sure they'll be happy for you to reach out. And also if you wanna learn more about I push Paul and how you can deliver live data in some of these channels, then do give us a shout.