Data Readiness and Building Trust for AI in Treasury

Brett Turner
Here we are, Fintech Corner, live here at AFP, the big treasury event. Excited about all the buzz that’s happening here on the show floor and we’re just getting going here. But we’ve got a little special edition here, so I am guest hosting, founder CEO, Brett Turner of Trovata. And we have a special guest, Matt Bramson, who has joined us recently as VP of Sales. So lot to dig in, a lot to talk about. He’s got an awesome background. So first, welcome, Matt. Thank Pleasure be here. And to have you introduce yourself.

Matt Bramson
Yeah, so this is week seven, I believe. So yeah, I’m super excited to be here. Hopefully we have a good discussion around kind of my experiences in market, small companies, large companies. But I can kind of give you like two minutes on who I am and certainly why I joined with that.

Brett Turner
Absolutely. We’re going to dig into your background. All that is going be relevant.

Matt Bramson
At the highest level – I started my career as a pre-sales engineer, did a lot of custom application building, delivered through APIs and flat files to large financial institutions. Worked for FactSet for about eight years. Got the startup bug, joined a company in Chicago called Narrative Science. Very early stage generative AI, which translates structured data into natural language. But we were really trying to solve the information consumer experience there. So our thesis was, at the time, dashboards don’t work, right? There’s a better way to communicate with people but everything was grounded in the data and how you structure it and how you govern it before you can actually deliver insight. So it was kind of act 2, act 3 after the acquisition from Salesforce from Narrative Science, I joined another small company about 100 employees called Manta Data Lineage, and then we were acquired by IBM in 2004, and then was there for about a year and then I joined Trovata shortly a time thereafter so my history is kind of all over the place. It’s pre-sales, it’s sales leadership, there’s an acquisition component to all of this, but everything for me is very much grounded in data and what you do with the data and how you make it meaningful.

Brett Turner
Nice, nice. So I heard data. Yeah, I heard data and I heard data. So a lot of what’s what is really shaping up, you look at AI, so much is changing. I think we’re at just this huge inflection point right now in our industry, in corporate finance, corporate treasury, corporate banking. So I think the question is, whereas so often it’s been about feature function. So why would you know, I didn’t hear like this treasury background. I heard data, data, data. So why is that so relevant? And maybe let’s dig into that.

Matt Bramson
Yeah, so yes, to be clear, I do not have a background in Treasury. And I think everything starts with data. And I’m not necessarily talking about the rows and columns and the ones and zeros. I think everyone can kind of compete at that level, which wasn’t true 20 years ago when I was working for a data provider at FactSet I think we had a lot of unique data assets that we were able to market and sell. We were able to collect data in a way that no one else was able to. Now it’s about access to the data and making sure that it’s readily available to anybody through APIs, more increasingly APIs. But to me, it’s really about what you actually do to the data, how you govern it, how you make it accessible. So once you’ve created a data product that’s usable, you can start sharing it with different types of information consumers. You’ve got to trust the data as well. So that’s one step beyond governance. There’s a lineage component. So like the story of your data, how it started here and how it ended up here and how that impacts the end user. So there’s lots of these different pillars or postures of data readiness that are very common to the enterprise. What I didn’t hear when I was sort of going through the conversations with you very early on is that those concepts were being applied to treasury.

So there is a huge opportunity for treasury to speak the same language as the enterprise and get on not necessarily the same standards, but that common language all in line with these really broad corporate objectives around AI or stable coins or crypto or whatever it is, everything starts with not just the rows and columns, but what you do with the data before you can actually make it usable. So it’s really cool to talk about AI, and I can speak to some experiences that I saw in market with IBM and these prior startups, but it’s really, really exciting to talk about all that stuff. But if you don’t do X, Y, and Z before that, none of that matters. I mean, absolutely none of that matters.

Brett Turner
Well, your last startup exits to, and you’ve had a kind of great background of being in startups and then having a couple of successful exits, which is great, scaling companies. It’s not an easy thing to do. But then being at IBM the last couple of years and seeing this whole, you know, AI is just kind of eating everything right now. It’s moving so fast. So if you look at just even in enterprise sales from that perspective, your background, so much has been about feature function. You’re at IBM, all this stuff now happened with AI, they’re talking to really big companies. So maybe dig in like this delineation of like the enterprise sale, so much feature function and now everybody wants AI. And then how can you actually just sell feature function and be able to get AI? I mean, there’s a there’s a cool kind of story of how that kind of was playing out, I think with IBM.

Matt Bramson
Yeah. So the answer is I do think you can, but they’re very point-and-shoot types of use cases, super specific around, you know, maybe an agent for HR. It’s a great example. IBM actually has phenomenal like ask HR bot that they built that they also licensed, but it’s super point and shoot. And you sell it to one type of consumer, supports the enterprise, and HR has objectives to automate to provide better support internally, but very, very use case specific.

Where it becomes really, really challenging is when you build the right data model or foundation to support one or two or 20 or 30 different types of AI use cases. And that was the data practice that I was participating in at IBM for several years. And we drafted a little bit. We certainly, you know, we’re listening to the market in terms of what they needed to do before they could support enterprise use cases across the board, not just these, like I refer to as point and shoot.

I think the big tipping point for us in May of this year, Salesforce, who I previously worked at through my first acquisition, purchased Informatica, which is a data governance tool. It’s a knowledge catalog. But the whole purpose of that is to make data ready for those types of AI use cases that Salesforce wanted to deploy. So the overwhelming feedback that we heard, not just at IBM, but even at Salesforce, was these solutions are great, but our data isn’t ready. Help us in an insurance.

So that’s why you saw an $8 billion transaction with Salesforce to Informatica. So that was sort of, guess, like the tipping point that we were able to leverage and sort of draft off of a little bit at IBM, which is this category creation around data intelligence, which is really data readiness. It’s governing it, it’s trusting it, it’s handling a massive amount of it. There’s so many different components to it. But again, I think from our perspective, like the seat that I sit in, this is really important and the treasury space is this is the common language of the enterprise and I’m really excited for treasury to start to actually use that.

Brett Turner
Yeah, I feel like we’re right on the cusp. I even my background has been in tech and then even in cloud services. We kind of have some commonality there. But doing it as a CFO, so understanding the finance space really, really well, it’s been sort of at the tail end here of this cloud journey. Cloud native technology still isn’t really a thing. There’s a lot of these legacy solutions out there. So we’re kind of in these final innings of digital transformation, you can’t really have digital transformation if digital is essentially means data.

So if you look at now, so much traction has been on feature function and that’s kind of everything that’s been running this industry for the last three decades. And now everybody wants AI. It’s coming top down. Like you need to have an AI strategy. We need efficiency. We need more productivity. We want to move a lot faster. We want lower costs to all those things. So if you’re still trying to win with feature function, sure you might be able to get a couple of steps, but you know, how is that going to really sustain you? I mean, where does that data readiness, if maybe you can only get so far, but if you really don’t have that data quality and the things that you’re mentioning, you’re only going to go so far. So where does kind of that handoff begin and the importance of those elements and why it can truly lead to true digital transformation when everybody’s talking about it, but in a lot of ways as legacy software, you’re not able to really fulfill that. And then why, mean, Trovata sits right at the cusp of this journey now having those features and functionality with full TMS, but now truly having the things that can deliver. I mean, why is that that so key or why, you know, and how you can kind of make that come to life.

Matt Bramson
From my perspective, everyone knows it, but they might not want to say it, right? You want to jump to the shiny object, which is the AI use case or pick any, I mean, this is Baskin Robbins. You could pick your next use case, your next application down the road. So everyone knows the importance of that, but it’s hard work. I mean, that’s, and it’s not super fun to talk about, but it is, it’s essential. So the first question I would ask almost any organization is just walk me through one project that didn’t work. And why didn’t it work? And 99 % of the time it will be data and creating a data ready product that you can trust, that you can use in those AI or whatever use case it, whatever it might be. So that would be kind of the first piece. The second piece is, again, this is common language. I think when you kind of go up market to the CDO or the CIO, and they understand the importance of this today, trying to launch AI projects as quickly as possible. we have to educate our customer that they need to take like a tiny step back and consider all of these other impacts to actually make those projects super successful. And this isn’t a hard thing to do. It’s not hard and we can explain our posture around all of these things that are super, super important so that we can make them successful in those types of projects. it is an ask for them to take a small step back and consider these other components before we just jump to this future state that everyone has, think in the past, have probably over-promised some of the deliverables associated with it. But those are like, these things are happening now. But to support different types of things in the future, it all comes back to this data readiness foundation.

Brett Turner
Well, if you think you mentioned education, so you get these trends obviously AI is not going anywhere It’s only accelerating but anything that’s new it just gets really buzzy really exciting You got all the sizzle around it and then you get a lot of people who is like I want it I don’t know what it means. I don’t know how to get there I don’t connect the dots maybe talk a little bit about that that education because I think that was a Part of the IBM when you were there. Yeah, there was this whole education circuit. So you’re going around describing and educating and yet and then you know one is there’s there’s a response so describe that response and then the other aspect is like okay now you’re actually going to do things how do you do it

Matt Bramson
So there’s an adage, you don’t get fired if you buy IBM products. That is not true. You actually do and you can. I’ve seen it. But I know, I saw when we were sort of doing the circuit around data intelligence and speaking to the importance of this data readiness foundation.

Brett Turner
You’ve seen it. I’ve seen it. I’m sorry to those who haven’t.

Matt Bramson
and promoting this idea of accessibility and lineage and governance and trust and all of these different pillars, 150 customers globally that I met with, no one disagreed with that approach. Now, some people wanted us to like speed it up a little bit. Okay, that’s all good. We agree with that, but we’ve got this one little problem over here. Can we solve that? Yes, we can. And here’s how we’ll do it. But understand the importance of this landscape before we go into those specifics, because it will only benefit you in the future. That message resonates with everybody.

Because they’ve lived it. I mean, they’ve absolutely lived it.

Brett Turner
And how are you so you think of especially in the enterprise, lots of big corporate departments, big pockets, you’ve got to get different parts of the buyers aligned because it’s not just one often it’s going to touch different buyers, and ultimately to kind of break through on a big enterprise sale. Lik,e how is that even connected to dots with not if you get one group that’s excited about it understands it, that doesn’t you know, how about kind of traversing like you say, does the whole organization some get it some don’t like even what

Matt Bramson
I think anyone that has tried to roll out a data-driven product and has been unsuccessful will get it. Sadly, everyone has. I have, actually. Personally, I’ve tried to use data to make decisions and didn’t do it correctly because the data wasn’t governed properly or it wasn’t accurate. That’s probably on more of a consumer side, but on an enterprise side, these concepts are a little bit more broad.

It doesn’t take the entire organization to buy into this. I think, yes, we do have to kind of win some hearts and minds, particularly when we go into these verticals that haven’t been introduced to these concepts of data readiness. But now we’re speaking the same language across the enterprise. And I think that’s really where we’re trying to start with a lot of this stuff is we’re trying to help you invest in this product and solve near-term problems. But we know that it’s going to ultimately roll up to some sort of broader corporate initiative that incorporate these themes. It’s not just the AI, it’s all this other stuff that happens.

Brett Turner
One thing, how do you connect the dots a little bit? If you think of like in the treasury space, sometimes the treasury space is sort of underappreciated. Sometimes they might feel like they’re on an island a little bit. There are not a lot of people in the org understands what treasury does. So how do you maybe help here? They need AI or they need some of these things. Data is central. Maybe they don’t quite know how to connect them dots themselves. Like how, how do you see helping them kind of get grafted into that strategy or helping them kind of bridge that with the other organizations, probably a few steps ahead of already?

Matt Bramson
I think the first piece is not getting them away from the idea that it is just about rows and columns. That’s table stakes. And I think a lot of people don’t understand that there’s a step beyond that and it may be a step beyond that and a step beyond that to make it ready and accessible. So I think really just trying to get it, the concepts in a place where it’s similar to the way they’re thinking about it now, but one step further in a way that they haven’t really appreciated what a vendor can actually do. Protect that data to make it ready, to make it accurate to support these use cases down the line. So there’s it’s a small shift away from just you know bits and bytes and ones and zeros to OK what do we what do we actually do with it to make it to make it valuable. And I think you’re right and Treasury is sort of a corporate treasure to me is a new is a new space and I’m hearing that all the time I haven’t I haven’t heard of that concept or we get a little bit of pushback that that’s all great but you just have a trap door to solve like my forecasting issues?

And that’s okay like we can absolutely do that, but again the theme is empowering them with that language that other parts of the organization are using to help them get The the software procure. I mean, that’s that’s really what it is. So And that’s a differentiator not just the messaging but our product does this. I mean it absolutely does

Brett Turner
Because I think that’s what it sounded like. You’re kind of, you’re on the circuit. You’re meeting with some 150 Fortune 500 companies talking about this AI strategy and what they need to do, data readiness, what all this means, unpacking all that. And it seemed like you had said this is one thing that really resonated with in our conversation and you joining Toronto. Why it’s so relevant is that it worked in part because it actually connected with people. It resonated. They’re saying, Yes. Okay. I get it. I understand now. I need that. Let’s move forward. But then everything’s kind of falling flat.

Matt Bramson
I didn’t want to go. But Brett, but yes, I mean, think there’s, there’s one…

Brett Turner
And I don’t even say that necessarily as a knock. Just saying, I think that’s just hard in the enterprise right now. The space that’s very, everybody’s dealing with this. You have solutions if you’ve been in the market for 20, 30 years. And these are the incumbents. These are the giants of our space, enterprise software. It takes a long time to build that kind of critical mass. And now, however, the nimbleness and agility to be able to leverage your core data, to be able to do these AI centric things. So part of it now is like, okay, that delivery path. So not saying maybe it can’t be done, but it’s, let’s just say it’s a lot harder. kind of where does that start to fall flat and then come back and say, you know, obviously being able to back up and be then move quickly.

Matt Bramson
Yeah, well, I think, you know, IBM is sort of a unique example that they’re way ahead of some things like quantum. But there are some other things that they’re still catching up with, right? Cloud, even SaaS. I mean, they very much promote this hybrid model. In the example that you provided, yes, the message absolutely resonated. But I don’t know if the market was ready to like believe us. Yeah. And we had, you know, the whole host of ways to show them and try to convince them. But it really came down to a single page.

Right. So when I talk about all those different components, those all lived in a different environment. You had different logins, now they’re, you know, I’m sure a lot of work has been done to integrate them. And when they do, will be a really powerful solution. The difference in Trovata is it is single pane. Everything is there. We can speak to all of these things, to support again, a current use case, but build, but really build for the future. So, yes, people believe the message. They believe it. What they had some doubts about or something we had to prove was how all these products actually worked together with one another to support these enterprise use cases.

Brett Turner
So what are you most excited about? In some ways, you see like how relevant like this data-centric story is. You have a lot of storytelling to kind of provide and back that up and here’s a new space that really doesn’t, I mean again, once AI, once where things are going, but yet doesn’t maybe quite know how to get there. Intuitively, I think they understand that data is critical.

Cloud native technology is critical if you’re going to do anything AI or any level of velocity, and you want to do something next month and not, you know, next decade. And I think that’s partly what you see. I mean, even here at AFP, a lot of companies have been entrenched in the space for 30 years and haven’t changed their strategy, you know, since, you know, the eighties, right? So we have a very different strategy. We have all those pieces. So what gives you maybe the confidence and maybe the excitement about being able to exploit that and really take advantage of how we can be a part of this transformation?

Matt Bramson
So it’s easy for me to just come in here and say, well, I heard this at IBM or, you I did this in my first startup or, I got a pre-sales background. I can sort of think around the edges over here. That’s great. And that’s like a, that’s like a Matt strategy. That’s not a, you know, a go-to-market approach yet where that becomes like a complete flywheel is when our customers say, and our prospective customers say, yes, I believe that. And that’s exactly what I’m looking for. Thank you for bringing that up and helping me understand that before I go and do this. And that’s, that’s happening today. So that’s why I don’t like lose a lot of sleep over this strategy because our customers are reinforcing it every single day in our conversations. And to be fair, I think some customers might not be ready for this. And that’s that’s OK. Yeah, that’s completely fine. Exactly. And when they are, we’ll be very, you very top of mind for us.

Brett Turner
There’s an adoption curve.

Matt Bramson
But other things that excite me being here is great. And I think, you know, I’m starting to learn a little bit more about kind of the industry here and there is a gap. There was a gap between treasury. Like you said, there’s a lot of people that understand what they do. Maybe they’re underappreciated a gap between all of that value that they’re adding and maybe the finance office or other parts of the organization. So you can think of them as two soup cans. You know, our job is to basically like pull the string. Yep. So they become one or by God, like give them some walkie talkies or something. I mean, something to just improve the channel of communication between the two groups. Cause that’s where I think the magic happens is when, I don’t have to ask our marketing person what’s going on. It’s completely self-service. I get answers and insights immediately and software empowers that. It’s the soup cans was probably the worst analogy in terms of technology, but that’s where I think like the magic happens is when different parts of the organization are all just working together with the most common strategic initiative, which is we’ve got to launch this project. We’ve got to trust our data to do this.

Brett Turner
That’s it. So maybe a little personal anecdote because I know, you know, you’re, coming to the show, maybe a little blurry eye, cause you’re talking about that this morning. You went through a, you just moving into a new house. We’ve all moved. If you’ve done that before, you know that that’s a grueling experience. That was this weekend and, and you leave, I’m sure you, it’s all boxes at home. So I’m sure there is a, you know, I was asking you, like your muscles feel a little sore.

You could probably give a shout out to your moving company.

Matt Bramson
Shout out to my beautiful wife, who’s handling all of it. But yeah, it’s a war zone. Yeah, yeah.

Brett Turner
Do any personal like anecdotes of what you felt? You’re moving in boxes and saying, hey, this is just like moving the enterprise into…

Matt Bramson
There’s something there too, but I think the other way I was thinking about we used to service who was it was really good It’s an app, you know, you can download it’s called Dolly, you can pre book a mover to come, you type in all the things you want them to move.

Brett Turner
They’re not a sponsor.

Matt Bramson
Sorry, yeah, there’s no free ads.

But you know that analogy is there. The input is only as good as the output. Like the moving experience is going to only be as good as all of the stuff that you provide them with first, which is accuracy around your data, what it is you want to move. Otherwise, they show up with a crossover SUV and you’ve got a couch. And so that’s what happened. And so you’ve got to work backwards and unwind that. But yeah, it’s been good.

Yeah, we’re excited to put some stuff away and really focus on the next step, which is enjoying the house. Awesome.

Brett Turner
Well, hey, thanks for being on show and super excited to kind of where you can really lead and take us in terms of our sales journey and all of that. So how this resonates with our customer, being able to tell these stories; we’re trying to get the word out. I think even already just, you know, connecting with some of our customers, seeing how that’s already started to kind of take place and how so many customers are already leaning in knowing that they need help. They want to help get there and we can we can do that.

So, yeah, thanks for being on the show.

Matt Bramson
Thank you for having me.