Partnering with IT on Your Digital Transformation

Ky: Hello and welcome to today’s webinar on partnering with IT on your digital transformation! This is Ky from Strategic Treasurer. And I’m glad you could join us for the third webinar in the Digital Transformation Strategy series. Before I introduce today’s speakers, I have just a few quick announcements. The Zoom platform allows for several different ways to interact today. One is a chat available by using the chat box icon on your toolbar that you can post comments or questions viewable by all attendees. If you’d like to ask your question to just the presenter, please use the Q&A icon on the toolbar. This is a full-hour presentation. We encourage you to ask your questions at any time during the presentation, and we will try to get to as many as we can. If we cannot get to all of the questions, someone from our team will follow up with you. There will also be a couple of polling questions throughout today’s webinar that you’ll be able to select a response from a list of multiple choices. If you are viewing on multiple screens today, the poll question might appear on a different screen than the presentation. You will need to hit the “Submit” button to have your response recorded. Our presenters today are Brett Turner, Founder and CEO of Trovata, and Craig Jeffery, Founder and Managing Partner of Strategic Treasurer. Welcome, Craig and Brett! I will turn the presentation over to you.

Craig Jeffery: Thank you, Ky! Welcome, everyone! It’s good to be here. And hello, Brett! I’m glad to do another webinar with you.

Brett Turner: Yeah, absolutely! Thanks for having me, Craig!

Craig Jeffery: Yeah, so for those who have been on the two prior webinars in the series, this marks our third. And for those who are good at counting, it also marks our third. Our first webinar was on the treasury paradigm shift, and Brett was on that one. His chief technology officer was on “Navigating the New Tech Landscape”. And today, the topic is “Partnering with IT on Your Digital Transformation”.

And so here’s the agenda for today that you can see on your screen. Now, we’re gonna be covering these areas. And instead of just flipping lots of slides, we’re gonna be talking at some depth on some of these. So the first area that we’re gonna talk about is visibility. You see that it says the need for information. And this is the concept of “I need to be able to see, and I need to be able to analyze whatever it is I’m doing in treasury”. It could be bank balances, bank transactions. It could be information in your supply chain on the cash conversion cycle. But visibility is a core element and a key driver for much of what we do in treasury.

Then, we’ll look at complexity: what are those challenges that organizations face that make it harder to do our jobs, that impact the view, impact our ability to analyze? So we’ll look at some of those elements of complexity.

Then, we’ll look at the history of IT, connections, and formats. We’ll explore the digital change that’s occurred over time and discuss why that matters in terms of how we look forward and how we… What we’ve done in the past does have a significant influence on how we look forward. And we’ll look at a couple of those areas to tease out those differences.

Then, we’ll move into the drivers of the digital transformation. What is pushing us there from a management perspective, from a requirement standpoint? What makes us have to respond more comprehensively, look at data? How do we respond more rapidly to move to real-time? And a few other of the drivers that take place.

We’ll also look at case studies, a couple of examples of case studies. Primarily, the impact on payments and speed and why that is instructive to us in treasury, in accounts payable, in different areas as we examine how tech can make an impact.

Then, we wrap it up with some key takeaways, some final thoughts about how to think about this. And throughout, there are some polling questions as Ky mentioned. And this is a chance for everyone to engage and see what our thoughts are, what our plans are, and do that rapidly. So we greatly appreciate it when people jump in.

So that’s our topic for discussion today. I’ll start off with the visibility side, and I’ll get you involved at this point, Brett, too. These are some data points from the “Need for Visibility and Information”. This is just a view of what your peers have. Do you have visibility to all of your bank accounts on a daily basis, weekly, or monthly, within a week, etc.? So you can see, the amount of organizations that can see 90 to 100% of their accounts on a daily basis sits at about 70%. That seems to be a key driver for organizations. It’s to have visibility. And there are impediments to that, Brett, a number of impediments. And so I don’t know if you wanna comment on this or the idea of visibility, but it’s pretty interesting that 75% of organizations have visibility to 90% or more of their accounts on a monthly basis. So there’s certainly complexity with international activity there.

Brett Turner: Yeah, like anything, you can’t fix things, you can’t analyze, you can’t do a whole lot unless you can see. So it’s sort of the big obvious. So if you think about that, you have to have the data, you have to be able to have that visibility. And it really is amazing how little visibility there is. But when you really look at… So much as this has been a tech problem, so much then as it has been… Whereas modern tech has changed and we all have experienced it in different areas, but yet it’s sort of slow to adopt mainly with the leaders of innovation really on the banking side that it’s sort of 10 years overdue when you kind of see the advancements of the cloud and a lot of other technologies we get to use and experience in many other aspects. There’s still this pain point. I gotta be able to get better visibility, better transparency, so I can start to advance things more. And I think there are so many resources that just go into even getting this: managing spreadsheets, so many manual efforts, so much cost. There’s a lot of tech debt, so a lot of expensive or cost to be able to just get this. And in today’s day and age, it’s not good enough.

Craig Jeffery: Yeah, that’s challenging. When the financial crisis hit, there was a huge movement towards more visibility. And it seemed like there was a good run of about 8 years where it moved up quickly, fairly quickly, and then it’s been sitting roughly at this area for a while. There was a question about… As we look at this idea of complexity, of balances, how many banks do you have, what currencies are they in, what countries, and you look across the universe of market data, there’s a lot of challenges here to see everything, put it all together, so it makes sense.

There’s a question too related to this complexity around visibility. It says, “Where are corporates at with bank and bank account rationalization idea? How do we bring that down?” And I guess what I say is, having surveyed that for over a decade, we see organizations that continue to buy new companies, and it expands their footprint with banks and bank accounts. And so they move into a rationalization project and make good headway, but their natural flow tends to create this expansion over time. And so it has to be an ongoing process, not just an event. But we see this constant effort to reduce it, a constant complexity issue to buy more companies. But Brett, I’d love you to weigh in on any of these items related to complexity or just some thoughts here.

Brett Turner: Yeah, I would say… I mean, the complexities remain. I mean, these complexities have been here 10 years ago, 20 years ago, 30. I mean, all of these complexities have been around for a while. And I think the biggest difference now is that the speed of information… I need to be able to do these things a lot faster. I need to be able to be… We’re drowning in a lot of this complexity because the tools and the ability to work through them haven’t changed a whole lot. Getting all of that data, being able to process all that data, there’s just not a lot of good… As everything sped up, I mean, you kind of look at so many different other areas where modern technology tools natively built in the cloud are providing that speed and agility to be able to… You look at the ad tech business or… There are just so many aspects that happened. Even payments that have in some ways… If you kind of look at most of the fintech ecosystem, it has been largely on payments really trying to go around the bank. So in a lot of ways, we need this information, we need to be able to process this stuff more efficiently, we need to be able to accomplish these tasks in a more automated fashion. And just everyone is sort of scrambling for workarounds or because they just know, they’re just hiring more bodies to do more work. It’s just people have been doing that for the last 10 years.

When you kind of look at the cloud, which does all, a lot of IT ultimately rolls up to the CFO, and you kind of look at that cost reduction because of the cloud. Now, in some ways, it’s been sort of cast overall at G&A, and it’s like, “Okay, we need to minimize G&A because we just expect a lot of these things can be automated.” But in some ways, financial services, treasury, accounting, a lot of these pieces have been left behind. So there’s just this expectation that you’re getting this cost reduction and you’re getting some automation, but there’s just a dearth of tools or means to be able to accomplish that.

So right now, again, it’s table stakes. And COVID was a reminder. Most of us got flat-footed when that occurred, and everybody was looking at dusting off their models, needing information quickly. And from a forecast perspective, that aspect of being able to retire these complex issues that are needed and have to be done but having the bandwidth to be able to be an advisor or be more strategic and guide when needed, that got exposed in a big way with COVID. And everybody’s scrambling. And so I think a lot of people are just saying, “Okay, we have to have upgrades. We have to have the speed of information. We have to be able to automate these workflows.” And I think we’re gonna continue to move through that over the next several years. It’s just like really the digital transformation in IT. We’re actually gonna leverage that, but we’re gonna see this massive digital transformation in financial services and banking and treasury operations.

Craig Jeffery: You said something early on this slide that was interesting to talk about: forecasting in the midst of all that other activity. There’s been a focus, like you said, during COVID to run more models, to run them more quickly. And that’s always been a significant challenge in treasury. It’s long been one of the top areas of focus. People are trying to do it more. And one thing that’s interesting is, it’s viewed as very important. Everyone wants to do it more rapidly. And it’s also one of the things that they would spend more time on if they could. So this, I think, too, is… That’s an element of complexity, adding to the equation, but it’s also tied into some of your comments about, you have to have tech that supports that. That won’t be solved by adding people alone. And well, treasury groups have gradually been adding staff, not individual companies. But on the whole, there’s been a general increase in treasury, which has always been thinly staffed. The solution is not going to be people. That is going to be leveraging tools that amplify and magnify that ability. And we’ve seen that for years. And it will be interesting to see how that plays out.

Now, this brings us to poll question number one. So on your screen, we asked about, “I understand the technical differences between hosted, private cloud, public cloud.” Yes, in a great deal. In other words, you could explain it to someone and they would understand that. Partially, in a limited manner. You have some ideas of clear delineation between those. And then, not really is you’re unsure about what the difference between public cloud, private cloud, and hosted means. So just select the circle. And then, there should be a box to submit it at the bottom. Mine only tells me I can’t vote, so… This is about understanding. We’re gonna go ahead and see those. So yes, in a great deal. So we’ve got 12% – a great deal, partially – 61%, and not really – 27%. Pretty, pretty interesting! Brett, any thoughts on this? As you’ve talked to people, is that clear in your mind?

Brett Turner: Yeah, I think some of these are not surprising. Close to 90% – limited and then a lot. Actually, close to a third or a quarter – just not really at all. And I think that that’s largely because we’ve really grown through really a tech revolution in the last 10 years. If you look at what the cloud has done and even what the cloud means, cloud… When really AWS was sort of democratizing, then you sort of had to define, “Okay, it’s a public cloud,” because a lot of people were misusing the term “cloud” and everybody was saying, “Well, we’re the cloud too,” a lot of the incumbent players. But it wasn’t really a cloud. And so we kind of got this term “cloud-washed” in a lot of ways. And just, again, it’s one of these age-old principles in sales that I think we’re all subject to because we all got all of this information upon us: if you can’t convince them, confuse them. And I think that’s essentially what happened really over the last year when people were wondering the difference between these issues and a lot of these bits because when you have something that… Like AWS, they’re democratizing infrastructure to be able to build tools, these modern technology tools in a way that could really shift the balance. And we’ve seen it over the last few years. Major incumbents, their technology is becoming obsolete, and they’re all forced to change. And the rise of certain tech companies has gotten massive, seemingly overnight, if you look at Stripe, if you look at Square and many others. So you look at the speed to be able to do that. So if you look at that, these are some big winners. Well, who are the losers? If there are gonna be losers, of course, you’re gonna get folks who have to really deal with that. And I think that’s when you get a lot of selling through that or kind of maybe a bit confusing that, “No, no, no! We’re a cloud too.” I think you get, which… It really has diluted the message from a tech perspective of what it truly is enabling. But I know we’ll go into that, so… We have more to talk about and unpack that in more detail.

Craig Jeffery: Well, it’s good. And part of the reason I asked that question is I’ve had a lot of conversations with people over the last month or so. And we tend to use the terms SaaS, cloud-native, hosted, and on-premise. And so one of the things that’s confusing is the equivocation of terms. Like you said “cloud”. What is “cloud”? You used the term “cloud-washed”. I won’t use that other than to reference that, but the idea of private cloud, public cloud, software as a service… We sometimes use a description about how software is delivered alongside how the hardware is delivered and how it sits on top. And so I wanted to cover just a few of the ways we see technology and some of the terms.

So we go from on-premise installed. You have software, you buy it, you install it on your servers. You have it on your test dev and production environment. It’s on-premise. It’s in your data center. It’s your software. It’s installed. The company manages it.

If you move over to hosted, it’s like you just have an outsourced data center. In some cases, you just use someone else’s hardware that runs in their data center. And they manage the connections, but you can update the database or the software as you need it. Or sometimes, hosted is, the vendor manages updates to the system, runs the database, he’s responsible for the hardware. And so you’ve outsourced a number of the headaches.

And then, we move over to SaaS and cloud-native. And this is where it can be relatively confusing. Software as a service (or SaaS)… And cloud-native is the term that we use. But private cloud-SaaS is where the vendor manages the software all the time. Multiple tenants are on it. The servers are hosted. The capacity is provided by them. And it’s run on a private cloud, just like the hosted model if you look in the middle. And then, when you look at what is what we refer to as cloud-native, this is public cloud-SaaS as opposed to private cloud-SaaS or SaaS and PaaS, so software as a service and platform as a service. So what does that mean?

So some of the differences are that hardware is running its web-native architecture like Microsoft Azure, Google Cloud, Amazon Web Services. It sits there, and so the software is running on top of the public cloud. And what are the differences in there, in the tech that’s used, that’s running on there? It’s that different tools, the microservices support for… Big data architecture is a component of that. So those are some of the differences between those.

So if you hear us saying SaaS and cloud-native, it’s not perfect terms. But private cloud-SaaS, public cloud-SaaS are some of the terms that make some distinctions between different types of systems and software. And Brett, you’re always talking with a technologist but also from a business perspective. And we’ve had a number of conversations too as we’re going back and forth. And it’s like, “Oh, yeah, we use a term that refers to the software, but we also lump it in with the hardware because we’re using a shorthand.” So cloud-SaaS are… They’re sort of shorthand terms, but they can mean quite different things if we’re not being particular.

Brett Turner: Yeah, and I think what really became a delineation to try to break through that confusion is you hear the term “public cloud” versus “private cloud” because what happened was a lot of the incumbents were saying, “Well, wait a second! We have our solution hosted in our own data center.” And it’s a SaaS product. Because if you think of SaaS, it really came… The two biggest SaaS players emerged as Salesforce and NetSuite. They are two large, prominent players. And they came about in around 2000. 1999, 2000, 2001 was really when that started to take off. And a lot of it was SaaS from a business standpoint, where they could basically package up and make it a lot easier for their customers to consume those services, where they were outsourcing and managing a lot of the IT aspects, so you didn’t have to do that yourself. Then, they could also gather feedback and then be able to use that to upgrade their product roadmap and whatnot.

The biggest thing that happened was… A couple of things. One thing is that Facebook and Google came along. And when they started to have massive scale challenges as they were growing globally to billions of users, I mean, that sort of scale from a database architecture really just broke more of the… You’d look at Oracle being really always the kind of the biggest and most scalable data architecture or database out there. And so when you were starting to see more of these databases breaking under the weight of these new, modern social networking models with the data requirements growing massively, the user requirements growing massively, so the data architecture had to be changed. And so you had Facebook and Google both releasing and reinventing the database essentially and releasing these wide column database architectures and…

And then, you also had this aspect of then folks being able to use some of this open-source tech. That movement started happening a few years prior too. And so then, AWS was getting so big and The Everything Store that we all know all too well in terms of Amazon… Amazon had massive data centers to support its amazon.com and where it was going. Amazon is smart about looking at some of these things and saying, “You know what? We have to invest in a sort of a build to meet the peaks, which is that conventional data center model, and we have all this idle capacity. We could actually just turn this into a business.”

And you had the aspect of virtualization which… VMware came along. And then, you had virtualization, server virtualization, so you could fractionalize, compartmentalize the server capacity essentially.

So these kind of things all culminated to where AWS then basically built it into a business and pulled these pieces together and said, “Okay, now we’ve got this environment that really started…” They started in 2006. But it really didn’t take hold until… I still remember it because my last start-up, which was a big way of really starting Trovata, was a big segue because of having a front-row seat to the whole digital transformation by AWS and migrating enterprise IT to AWS. And just seeing how they had… When they finally sort of crossed over and kind of hit the masses, I still remember living through this, Morgan Stanley issued their analyst report in May of 2013. And that, to me, is sort of what I refer to as really the tipping point of when everything changed because, at that point, everybody thought, “Okay, now it’s AWS and the public cloud.” We kind of had to use that term to delineate. It is now enterprise-grade AWS. Also, it’s not coincidental that the analyst was coming out because people were getting wind that AWS was about ready to win this massive multi-billion dollar contract for the CIA. So obviously, if you’re serving the CIA, then you’re probably pretty secure. So all those notions about not being secure and not being enterprise-grade just melted away. And that just united really more than just startups. Everybody really adopted the public cloud from Amazon, and they just went faster than everybody. Meanwhile, Azure (it was Microsoft), Google Cloud, they’ve been catching up. But AWS is still way ahead of them. In the early days, it was… Because of what they had sort of democratized and they grew so fast, they went from 2006 starting this, essentially, and now, they’re a 50-billion-in-revenue segment of Amazon. And arguably large, or maybe not arguably, the most profitable. So I think they’re up to about 50 billion in revenue in terms of profits for Amazon. So when you look at that, what happened is the cloud… And I think maybe…

I don’t know if I’m getting too far ahead on the next slide, but really to define that is, really it started to move more to this very rapid iterative architecture. And so one of the things you could argue is the evolution of tech for treasury. But then all of a sudden, now it’s been over the last 8 years or so, 10 years. Now, there’s been this evolution of the cloud because now you’ve got all of these where you… This kind of sums up a lot of what’s happened and maybe the problems and some of the solutions too in treasury, where you’ve got this leapfrogging approach of tech. And now, you kind of get these waves of obsolescence. And the best way to know and to delineate whether or not your architecture, your solution is natively built in the cloud, is… If it was built more than about 8 years ago, then you’re dealing with more of legacy infrastructure. That’s just the fact because you couldn’t build on Amazon using the latest and greatest web services through Amazon or AWS until about that time. And that’s when everything started to take off and then every year, which is making this whole thing speed up massively. It’s because AWS and now Azure are catching up. GCP, Google Cloud, they’re basically iterating on all of this infrastructure to support the innovation that you can now focus and build on. So just like in the treasury, you say, “Hey, let’s automate all these manual tasks so that you can be more strategic, not getting bogged down with some of these operational manual tasks”, in the same way, AWS came along and said, “Hey, wouldn’t you like to not worry about all this IT stuff that is holding you back? We’re gonna take care of that for you. And we’re gonna iterate faster than you could yourself. And we’re gonna make these services extremely cheap.” And then, as long as you manage a thoughtful architecture, you’re now future-proofing your tech stack. And now, you can focus on the things that really matter: how it all stitches together and how you’re going to deploy your services model through that technology. And now, you’re gonna be able to iterate faster than any other model. You simply can’t move with that speed and agility at scale unless you’re cloud-native. And that’s what’s really happened over this massive paradigm shift, but especially now that it’s speeding up because now you have multiple iterations of the evolution of even AWS and now choices with Azure and Google Cloud that’s really making this possible and really separating, becoming really a table stakes game. You just simply can’t do things unless you’re architected in this way. And it’s just becoming a fact. It’s pretty simple.

And it’s really hard for some of the older players to adopt. They can’t just, “Oh, well, let’s move our software into the cloud because… We’ll move it off of our servers or the servers and then just move it into Amazon servers.” Well, that’s not the way it works because being cloud-native means that you’re purposely architecting and building all of the different pieces and services that make up all that infrastructure. It’s really what you have to do from the ground up, which allows you to achieve all of that agility, speed at scale. And then, you just constantly swap out pieces because now all of your tech stack is basically the kind of the best-in-breed of all of these different little services called microservices. And then, you’re actually using APIs to connect all of these pieces and components and infrastructure. And at times, they’re being upgraded, or you can swap them out. You can just do that with ease from an infrastructure standpoint, instead of going through these massive step function migrations and migrating customers. And those are really, really painful, really hard and have a ton of risk when companies have had to evolve over… But now, you don’t have to do that. Now, there are these constant releases, you’re always just getting the latest and greatest if your provider is natively built and architected and built in the cloud.

Craig Jeffery: A couple of things on the history of what’s going on with tech. If you look at the chart you have, on-premises installed all the way from the left to the right, what happened… As we looked at old software, older software on-premises, it might be 2-tier or 3-tier or N-tier architecture where there’s a database layer, there might be a program layer or business process layer and then a user interface. Well, sometimes, maybe, in the beginning, it was that user interface and the process layer might have been all combined. Or maybe, all three layers were combined. And so what’s happened is they started breaking out those layers. It allowed them to move more nimbly and more quickly. And so they’ve broken these things out over time into smaller and smaller pieces all the way to like, Brett was talking about, microservices. Well, they’re smaller components that fit together. And so as we take in more monolithic activities broken into smaller, it allows faster development, easier patches, and changes to leverage what goes on. So those are some of the interesting items.

And I’ll give you an example outside of treasury, but… We do a lot of research, we put out surveys, and we manage data and analysis. And we needed a data lake. Well, we actually provisioned a blob, which is… For the scale that we were using, the blob worked just as fine. We provisioned it in Azure Blob in like less than five minutes. And when you think about what you’d have to do with hardware to get that set up, it’s like you got to buy it, source it, plug it in, install the database, put in new security, do everything else. This was click, select some options, provision it, and then create the API link from the business intelligence tool, and then start running our apps. And what would normally take months was a few clicks. Well, I had to enter a credit card too for the company to make that work. But just think about the time and speed of doing that. It’s just very different. But let’s shift.

I think this one, we probably covered a fair bit on here. These are the in-house servers. You have to have redundancy. If you have peaks, you go like, “Oh, we need bigger servers.” And I remember arguing with people, companies, IT groups. They were trying to get treasury to buy three huge servers they didn’t need because they needed to run some other app on it. And so you’ve got this. You have to have people who can support the servers, huge data warehouses, all the way to… You’ve got the Ashers of the World, the Amazon Web Services. Now, it can be completely scalable. And this history of IT shifts slowly from the in-house servers to hosted and SaaS. And now, all of the new focus is on SaaS and cloud-native. It’s not on hosted and in-house servers. That’s not an area of focus nowadays. But this is part of the shift. Yeah.

Brett Turner: Yeah, I was just gonna say a couple of really, maybe, salient examples. If you kind of look at companies like Salesforce and NetSuite, when they came about around 2000, they couldn’t really build natively in AWS because it didn’t exist, and so… But those are huge companies. And with massive amounts of investments, they could start to make changes. And because they were already so big on their own data centers, they were able to adopt, certainly, some of those services themselves to, at least, kind of keep up, making it very relevant in the space. But then, a lot of companies that just weren’t that size have really, in some ways, struggled. And you were kind of then contending with having to, essentially, rebuild from scratch, which you’re never gonna do because you also have to have all the people and expertise from a software development perspective to know how to build in that new environment. So I think if you kind of look at the history of those companies…

Workday is another one. When they came onto the scene, really when was the last time somebody built a new ERP system? Almost, never, right? So because it’s so hard. But the big thing for them is they came out with more in-memory computing. And so part of what they were doing is they would store all the data… Instead of in a relational database architecture, they would store more in memory, which would allow a speed for retrieval. That would be really, really fast. For a big scalable system, that was game-changing. But the problem is, it has a compromise. So even Workday, that’s… If you go and deploy Workday, it’s gonna cost you a lot of money. Huge implementations are really expensive. So you’ll get some of the benefits of that speed but at still an extensive cost because it’s not cloud-native. You’re not able to get some of those, whether it’s in memory or other database architectures, and kind of combine them in a way, where it’s sort of… The British term “horses for courses”, right? You want the right horse running the right race. So when you kind of put those pieces together in a way that is tackling different… There are different problems. Workhorse, you’d want super-fast so that you’re caching and indexing or still deploying a relational database architecture more for certain things, not everything combined. So all of those things that you can do, you can start just piecing it all together, breaking up some of the challenges, and then just rebuilding that in a way that meets all the needs for scaling and speed, velocity, all of that at scale.

Craig Jeffery: Yeah, so one of them is the history of IT. Another is connections. Many, many years ago, the cost to transfer data was astronomical. And if you had a… And the speed was slow, and there was a lot of noise. It was analog, which… Some of you may not even know what that means, right? It’s not sent digitally. And so certain sized files couldn’t be sent over phone lines. They’d have to have a dedicated circuit. Some companies would even transmit tapes, physical tapes, deliver them manually to load at the bank to make that happen. That was the worst part of file-based.

Now, the speed of transfers improved. You don’t necessarily have to have a dedicated circuit one into another. But this is file-based. It’s the whole we’ve got encrypted, we’ve got the keys on both sides. We moved to APIs, where the connection is essentially instant. It’s not a multi-step process. It’s an always-on.

And the formats at the same time have moved from fixed through delimited to save on space and transmission to extensible like XML, for example, where the data comes with its own schema that says, “Hey, here’s a payment amount. I tell you what I am. I can describe myself, and the systems can use that.” And that’s been a huge change with requirements from PSD-2, requiring banks to support APIs, to a really rapid growth of APIs. And I know you’re quite a fan of APIs, Brett. I thought you might wanna comment here, too.

Brett Turner: Yeah, I mean, there are these segues of why I’m getting super excited about the opportunity. Coming off of my last startup, I mentioned a company called 2nd Watch, the first premier consulting partner of AWS. So all of that IT stuff we just talked about was very… I had a front-row seat to all of that, but then… So part of it is a tech problem, that all of that is just finding its way into the space now. Like your example is great because I’m kind of finding how easy it is to provision services in the cloud. That’s been going on for a while, but it’s just finding its way now. So that discovery is exciting, but it’s also long overdue.

The biggest problem, though, is that even if you have great tech, if you can’t get the data… And now, we also find that there are really two pieces to this. So if you can’t really get the data, then you’re kind of only left with half of the piece. And I think that’s what happened. It was, once seeing that the banks are gonna open up, seeing what was happening on the retail core of the bank where you have screen scrapers and these data aggregation providers like Plaid, and that was really spurring a lot of this fintech innovation on the retail core of the bank, small business and consumer, it just… You couldn’t do that. That model was never gonna work, and it couldn’t really work in wholesale banking.

And so the big excitement for me is that it was not an “if”, but it was a “when”: when our banks get a chance to kind of roll out APIs, a true API, in a bank-friendly way. Here is the way the bank wants to provide data to their customers or to a fintech provider like Trovata on behalf of their customers. And so now, when they rolled that out, honestly, that just became an enormous watershed event because getting file-based statements through SWIFT is very inefficient. If you kind of look at the history of telecom and being able to get your data, there’s so much innovation that’s happened in the carrier or the telcos to be able to make sure there’s a resiliency in the network, basically, for your use of the Internet to access things or to have data flow back and forth. And that was another startup that I was a part of called WorldWide Packets, and it was the last kind of… It was in Carrier Ethernet. We got one of the last kind of true telecom exits back in 2008. But a lot of that too… We had things called deep packet inspection, where the telecom gear is basically looking at the data that’s flowing through, they’re inspecting it, and they know where to route it, or if there needs to be some healing in the network where they can kind of take… If there’s packet loss, they can package that together, make sure that the other piece of the data that’s missing moves along and ultimately gets there. I think that aspect has just been completely missing when you’re just dealing with picking up a file on a secured server, moving that file through the Internet or through VPN or some sort of secure tunnel, and getting that on the other side. And that’s why I believe that that’s really a big part of why treasury reconciliation really exists.

Reconciliation, it’s not like… The accountants would talk about it as CPA1. CPA101 is the bank rec, but treasury reconciliation is… If you think about it, a lot of it is just, “Do I have all my data? Do I have all my transactions? I have to do a recap. Opening. I put all my transactions and activity into these cohorts that I can manage and see. And if I need to dig in, I can do that. And does that tie out to the ending balance and then across all of my bank accounts to all my banks?” That’s a difficult thing to do. But APIs are really enabling all of that to be automated. So if you look at it, it’s a big part of what we’ve done.

We’ll get to case studies in a little bit, but what we’ve done with Square: 18 banks globally, over 15 million transactions, and building and automating the reconciliation. So when the data arrives, we’ll tell you if we have a hole in accounting to know whether there’s a problem or not. But all of that is automated into gathering the data through it because now with an API, you can automate picking up all of that data or catching it and now processing and transforming it, normalizing it, all of that data, so it’s fully managed, centralized, all normalized in a centralized way that’s fully managed for the user. And all of that is a big part of what we do because why should you ever wanna get into the weeds and have to do all of that? Reconciliation has a lot of other values. So let’s focus on those. But just the aspect of, “Do I have all my data?”, that’s something that clearly needs to be automated and that’s something that we’ve accomplished and done because of the APIs.

And now, as a global leader in API connectivity with banks, in wholesale banking, we’re only speeding up. And that is just another way where we can free up treasury teams and operations teams, so they don’t have to get bogged down in some of these things. Telecom solved it. If you look at moving to SWIFT or to fiber or more advanced networking with SWIFT teams depending on the file, SWIFT is sort of like the US Postal Service of managing and sending and receiving files. I’m sorry, but it’s very antiquated, and you just will never be able to get, I mean… And I’m not saying… The US Postal Service still has a place. Amazon uses US PS for delivering packages on Sundays. So it’s still always gonna have a place because there are so many banks. But if you look at the breadth and depth of the main banks, that’s where you can drive automation. So if that gets you 80-90% and you’re kind of relegating the file-based to some of the, over time, I think those will get automated over time, but maybe that’s the long tail, then still you’ve achieved a ton of automation through all that. And that’s a big part of APIs and why it’s so transformative.

So my last little point too is that, “Sorry! What does this analogous do?” A big part is even if you have… Again, we’ve talked about that first part of it. You have to have more of a cloud-native architecture on the tech side to be able to take advantage of a dynamic pipe now that’s the API because if you can’t, it’s sort of like if you think of having a cabin in the woods. There’s no running water, no modern plumbing in the house, and it’s a two-story house. And you have to get buckets of water down to the creek and up to the house. So the APIs are like bringing a water main from the creek to your front steps. And now, you don’t have to get the buckets out of the creek, right? The water main is right at your doorstep, but you’re still not gonna be able to run a dishwasher, you’re still not gonna be able to wash your clothes in the washing machine. You’re not gonna be able to take a shower in your upstairs bathroom. And that’s just because the house doesn’t have modern plumbing. You need to be able to get the water from the water main up into those areas where you can really make that useful. And so I think that it’s a two-part two-pronged issue: API’s dynamic pipe, opening the doors for a lot of things, and, then, now a modern tech, that modern infrastructure to be able to take advantage of it. And those two combined are being able to deliver those. Those two combined really allow you to then just blow the doors off and really futureproof where you wanna go, automate a lot of this manual stuff. But then now, it opens up a lot of the things where you can go and bring this and innovate in a whole new way.

Craig Jeffery: Yeah, and if you’re only bathing once a week, maybe it’s okay to go down to the stream. Just a couple of points on this because we covered… A fair bit of this was this idea of “How do we align the needs between IT and treasury or IT and finance?” and this idea of “What is IT trying to do? What is treasury trying to do?” And we have this movement from relational databases to data lakes and big architectures, structured and unstructured, right?, as opposed to matrices or relational databases and tables. Treasury wants to look and examine, explore information, and do analysis, and operate more nimbly and quickly. So too does IT. It wasn’t too long ago where IT was focused on, “Everything has to be done in-house. We need to control it all, too. We need to make sure that our users can respond quickly.” And so on the bottom line, we have “Build strategic, buy tactical,” but you still have to run it in-house to… Now, there’s a democratization of treasury technology where more firms can get it to… There’s this idea of there is microservices interoperability but also user-controlled analysis, self-service models where the users are more empowered. So that’s like the full era of the continuation on the democratization side. Brett, any quick comments before we move to our next poll question?

Brett Turner: Yeah, I think that there’s just such a massive shift. And I think even on big data architectures, again, natively built in the cloud, you can actually… It’s not just one database over another, but you’re able to put together different database technologies together in a way that, again, allows you to kind of get the best of both worlds or solve lots of these problems in unique ways. And I think all of that is more of a modern cloud service that allows you to be able to do that and achieve this. But you have to have a big data architecture to be able to get there.

Craig Jeffery: Yeah, great! So that brings us to our next poll question. So that’ll be popped up on the screen. So our view of IT is… If you’re in IT, click the first circle. IT is a key ally. IT in our group has different priorities. IT is a frequent blocker of what we need to do. I don’t know or have an opinion. I guess we could have said, “I’m worried about IT reading my response.” I might be negative about IT, but I won’t do that or even say that. But go ahead and fill that out. And then, Brett, after we’d look at that, I’d like to move on to the development and time to value discussion, which builds nicely on what’s been said before. But let’s go ahead and see what this looks like. And if we get 40 people typing the word “poll” in the chat box to everyone… Don’t just send it to speakers. If we get the word “poll”, we’ll send out the responses from these and all our poll questions today. IT is a key ally. This is really, really good news. 62%. If you looked at this five years ago, I don’t think it’d be anywhere close to that. IT is a frequent blocker. 7%. We have different priorities. Very, very interesting to see how this is playing out. This is really good progress. I think that’s the idea of, “There are needs. The needs can become aligned.” And that’s really the key part of today’s session. But I’ll let you comment on that as we move to the next section, which is on rapid development, time to value.

And I’ll just set this up really briefly because we talked about a couple of things. You’ve used the terms “at size”, “at scale”, “the agile development”. And we see that by a couple of factors. One, we compress things down to smaller components. In this idea of virtualization, we are not restricted to, “I have a physical box. If I need scale, I’ve got to physically move something there.” Virtually, we can expand it. Like I was saying, we provisioned a data lake with a few clicks in about five minutes. And we were able to tap into all these servers without the overhead. This is really a component of, “There’s time to value and speed and agility at scale.” And in one of the conversations we’ve had, it’s like, “Select any two of the above”. And the answer is, “No, we don’t want just two. We want all of them.” But your comments, Brett?

Brett Turner: Yeah, I think one of the things that’s… And it’s encouraging. In some ways, it’s not surprising on the poll question, 62%, where… I think we are in the final innings of the migration to the cloud. As I mentioned also, AWS is at 50 billion in revenue, and what was a… There still was a $1 trillion digital transformation in IT, and we always talked about a journey. It’s gonna take time. And I think financial services, banking, insurance, these are huge systems to be able to contend with. How do you really migrate a lot of these things into the cloud to be able to get there? And I think we’re just starting to now kind of get there, unbundle that.

So when you kind of look at that 62%, I would say, “If you wanna modernize IT, whereas there might have been some friction and they’re holding you back a little bit, those tables are turned.” We’ve seen it with customers, big customers, where IT gets on the call and they’re actually pushing the treasury team to like, “Yes, this is something modern.” I mean, if you kind of look at it, there haven’t been really any modern technology solutions that have hit the market from a TMS perspective in over 20 years. So that’s just crazy. So there’s just a dearth of innovation. So when you kind of look at…

If you wanna bring this question up to IT, they will thank you for it because they’re looking to try to make upgrades because this is the kind of stuff they wanna support. They don’t wanna support a lot of these monolithic systems that sit there. If you kind of look at overall, this… Again, we’ve kind of talked about it, about that rapid development, time to value. When you put these great new pieces together, dynamic APIs from the bank directly, you can now start to consume banking services from the bank directly. The banks are a big part of driving the innovation. So we can say as much as we want about the banks over the last 10 years, but they’re driving that innovation, they’re making APIs, they all have strategies around their APIs. That’s a big part of now kind of the $3-trillion bank as a service opportunity that’s happening. And that’s why they’re part of that innovation. They’re opening up with open banking and with APIs. And that is allowing with a modern tech stack to be able to… If there’s something new from the bank, you as a user get that really, really quickly. If you’re in a legacy solution, it’s gonna take you a long time to get that benefit. But because of that agility, because you can rapidly develop, and maybe we’ll get into the case studies, but that’s a big part of like doing these massive projects or squares, building a really high-performance bank data lake, what we call a treasury cloud, building out new things. We built that in six months, new things like transforming payments that connect directly to bank APIs, so you can use the rails, the bank rails directly. We built that in four months. They’re now live. So the iteration of being able to… That time to value to you as customers is something that we pride ourselves on and really any modern tech solution prides itself on to be able to drive that.

And one last thing: to be able to do that but at a low cost. So again, we talked about like, you can do some of these things, but you’re gonna have to throw a lot of money at it, a lot of server horsepower or overweight on certain areas to get there. But to be able to do all of these things and still be able to do it within your cost of operations as a provider, it’s just a fraction of what it is versus a legacy provider. That’s also the big game-changing value to be able to drive that really out of the box in ways, so you could just eliminate what’s been that typical implementation, which nobody likes.

Craig Jeffery: So I’m gonna just speed a couple of things along. On the drivers’ side, we’ve covered most of these about what drives digital transformation, expectations, needs in IT, requirements for speed and efficiency in treasury, other areas. And then, I wanted to give you an opportunity to talk on maybe General Atlantic. You gave us a bit of a view on the case study with General Atlantic. We have a couple of more things to go. So I don’t know if you can give us a thumbnail overview of a particular example with General Atlantic, and I… Yeah.

Brett Turner: Yeah! I think our big approach out of the gate is we wanted to be able to really democratize now with APIs coming online from the bank, democratize all this data and really help with our opening slide: visibility, transparency, a lot of the basics that a lot of people are still struggling with, so cash positioning, cash flow analysis, bring cash forecasting to the table. So these are just core basics that everybody needs, everybody should have them. And so we wanted to make that accessible to everyone. As we’ve now…

Bigger companies, who need that too and are using Trovata, they’re starting to ask us, “Well, what about this? And what about this?” More media parts of traditional TMS. And so we’ve been leaning into that. So one of those is on the payment side. We’ve kind of intentionally held off payments for quite some time, knowing that’s a very saturated ecosystem. But all of that exists really outside the bank. And we wanted to do something that was… With the banks now releasing payment APIs, we wanted to do something directly with the bank. So we’re not a payment provider. The bank is a payment provider. But we’re gonna build a great user experience, your signature authority and matrix, and all your workflow approval, and all of that in a modern way, using your mobile phone to be able to approve, using biometrics. All these things that should be in more of a modern workflow experience, we wanted to do that. But then, all of that instructions and handling to go and send to the bank and really initiate… But the bank is initiating those payments. We’re just becoming a bridge in facilitating that. And so that’s what we’ve done.

In large part, that’s what we’ve done with General Atlantic. That was their big request because they’re sending out 25,000 wires a year. They’re one of the largest private equity companies in the world. And because they’re having to use their current TMS, a lot of these just need to be account-to-account transfers. But instead, their TMS isn’t set up to do that. So they have to send them out as wires, which really brings about a lot of added cost. And there’s just not that same experience to be able to do things differently that can improve that whole process. And having less tracking, all those kinds of things that we’re helping to improve and bring to bear now through a better user experience.

And then, we talked a little bit about Square. So all that’s kind of… We’re leaning into these bigger problems now. And we’re able to adopt and drive and deliver in a fraction of the time it takes traditionally to build that because of the way we’re architected.

Craig Jeffery: Yeah, great! Thanks for going over a couple of those case studies just to bring some of those points into specific examples. The last polling question is up. IT has the following activities underway. This is a “Select all that apply”. It’s either underway, or they’re live. And I think we still need about 14 poll responses. But we’ll leave the poll up. We’re gonna slide to the next slide as well and just wrap it up. And then, we’re coming to the end of our time. So please complete any of those items there. But I think the key takeaways is that expectations, requirements for expandability require different thinking, leveraging new tech in different ways. And so the expectations have changed in treasury. The IT focus has changed. And in many ways, they’ve become a line that provides the opportunity for digital transformation and transformation of treasury along with transformation through IT. Brett, any final comments?

Brett Turner: No, I mean, I… Hopefully, this has been really informative, I think, just kind of getting this understanding of all these pieces and maybe the perception around some of these things. But hopefully, kind of these two new pieces are coming together now, and people will understand a little bit the Xs and Os of… Okay, now they can ask a basic question around architecture or technology in a way that maybe they didn’t feel comfortable before. So hopefully, that’s been helpful to everybody.

Craig Jeffery: Great! We’ll show the results of the poll in the next webinar. It’s on October 20, “Evaluating Tech Solution Sets”. You can see the responses on the screen. And we actually do not have enough “poll” comments to send that out. So if we get a few more, we’ll be over the threshold. So if we look at these items, it’s really interesting. Moving or moved ERP to the cloud. That’s a real big issue. Huge. SAP, Oracle. That’s a massive set of movements. So we’ll send that information out. And I’ll turn it over to Ky as there are elements to connect for the next webinar. Brett, thanks for talking with me on this topic today and, everyone, thanks for joining us to discuss tech and digital transformation!

Brett Turner: Thank you!

Ky: Thank you, everyone, for joining us today! The CTP credits, the webinar slides, and a recording of today’s webinar will be sent to you within five business days. We hope you’ll join us for the fourth and final part of this webinar series “Evaluating Tech Solution Sets”, which will be held on October 20 at 2 pm Eastern. The registration link is in the chat box. Thank you for joining us today!