The Treasury Paradigm Shift

Ky: All right. Hello and welcome to today’s webinar on the treasury paradigm shift! This is Ky from Strategic Treasurer. And I’m glad you could join us for the first 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 the chat available by using the chat box icon on your toolbar where you can post comments and questions viewable by all attendees. If you’d like to ask your question to just the presenters, 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 into as many questions as we can. If we can’t get to everybody’s questions, someone from our team will follow up with you. There will also be a couple of polling questions throughout today’s webinar. You will be able to select your response from a list of multiple choices. If you’re viewing on multiple screens today, the poll question might appear on a different screen than the presentation. There’s also an added step in this platform that is different from our past polling questions. You will need to hit the “Submit” button to have your response recorded. Our presenters today are Brett Turner, Founder and CEO at Trovata, and Craig Jeffery, Founder and Managing Partner of Strategic Treasurer. Welcome, Craig and Brett! I will now turn the presentation over to you.

Craig Jeffery: Thank you so much, Ky! And welcome, everyone! It’s good to be on this webinar with you talking about technology. And Brett, it’s good to start off this series with you on the treasury paradigm shift. So welcome!

Brett Turner: Thank you, Craig! Yeah, great to be here with you.

Craig Jeffery: So we have a ton to cover. And Ky gave you a number of really good announcements for what we’re going to do. And she mentioned the chat box. A lot of people are saying “hello” from their location. It looks like about 80% have sent it to just hosts and panelists. Feel free to have content and questions sent to everyone. There’s also the Q&A box if you’d like to be more confidential. So that’s a good way to stay connected during the webinar. But happy to connect via LinkedIn with anyone I’m not connected to. I think Brett probably feels the same way. So there are other ways to stay connected outside of today’s session. But the other way, of course, is to stay connected through our polling questions. And we have three of those, a lot of good information.

But to get things moving along, we’ll look at, “What is our agenda? What topics are we covering?” So we’re gonna look at the treasury technology landscape. What’s changing broadly in technology? And how is that coming home to treasury? What’s changing? Why does it matter? What are others thinking of doing?

We’ll look at modernization. And there’s this constant improvement in technology. But what’s the value of modernizing the tech that you’re using? We may have solved a problem 5 years ago or 15 years ago. Maybe, that’s still working and it’s working well. But what’s the value of modernizing your technology? We wanna introduce some elements of change in the space, in the overall technology space, and in treasury and explore the idea of whether they just represent a minor change or a moderate step change or something that’s more of a paradigm shift that we wanna take advantage of. So that’s gonna be a component of modernization at this particular session as well as part of this series.

Then, we’ll look at the outlook. We’ll look ahead out to a couple of years, out to 5+ years. What is happening? What are your peers experiencing and expecting? How have those expectations changed? Are they using some new technology faster than they planned, slower than planned? Where does this sit? So just knowing where your peers are is an element that we’re going to focus on. So the outlook aspect there.

On the technology stack, a stack is made up of layers. We’re gonna look at two conceptual stacks from the big data cloud-native stack to some of the conceptual ways of looking at the technology. And so how do we build our processes? We build them on top of technology. So we put them on top of a stack. What’s necessary on the layers, and how does that impact what we can do? How fast we can do it? How quickly we can get information? And how does that alter what we’re looking at?

And then, the last two sections, self-evaluation and key takeaways, is a way of looking at this information and seeing, “How does that impact our business?” So self-evaluation is reflecting on your current position or posture and your thinking on this type of technology and how that impacts your business. And then, as we move to the key takeaways and some final thoughts, it’s an extension of that self-evaluation to look at things from a more prescriptive approach. How should we act, and how should we look?

So with that agenda laid out, I’m gonna move to some of the concepts impacting the new landscape. And I’m gonna bring Brett in as well to cover some topics here. As you look at what’s going on here, I’ll just cover a few points.

What’s happened in the landscape? There is a data explosion. There’s more data in your company, more data on the web, more data provided by different data providers. We’re seeing a 40 to 50% compound annual growth rate up. That type of CAGR means doubling every 18 to 24 months of all the data that exists. This is massive, and we’re seeing that. So that creates a challenge and also an opportunity.

And I think anybody who’s been around for a while has seen processing speed increasing, driving down the cost of the activity. Having what’s going on in this, this provides additional opportunities for leveraging tech and how we structure tech. If we look back on the timeline a long time ago, the cost of moving data was a big concern. That’s almost not a concern. We just care about securing data. The ability to move massive quantities of data for almost nothing is an environment today.

And in the past, it was, “Where’s the data? How do we get to it?” It was very hard. And we need to make sure we take advantage of accessing that data and being able to see it.

And there’s another concept about legacy data, old data, getting data that perhaps has been like stale bread to prior-day data, to current data, to real-time data. That’s changing how we think about technology and how we think about treasury tech. So it’s impacting most of our world. I laid a few of those things up. Brett, I know you have a few comments as well here about the change in the treasury tech.

Brett Turner: Yeah! Thanks, Craig! Super excited about this series, this topic, obviously. We’ve really built our business on what’s happening. And part of pioneering and ushering forward this exciting change is what’s taking place. I mean, I share it. Just validating with our own growth as a company, I get to just be a part of this. This is kind of a special innovative startup for me. I’ve spent over 20 years, starting out as a CPA, as a controller for many years managing SEC reporting for Amazon, and then a CFO for about 10 years prior to starting Trovata. All kind of selling into the enterprise, all managing really complex “cash cycles”, lots and lots of forecasts modeling, like many of you, folks, I’ve learned a lot on the treasury side. So a little bit of a treasury outsider from a CFO controller perspective, but always around kind of democratizing data from a financial reporting and analytic standpoint and then, really, working closely with banks through that. And I really had to migrate from my own, as a practitioner standpoint, when I became a CFO looking and experiencing with more cash data to try to get more access to real-time so that we could use that for more cash insight.

So it’s incredibly exciting because when you look at what’s happening, really the rise of modern tech… And a big part of my last startup was in cloud computing, so I had a front-row seat to the whole rise of the cloud with AWS, migrating enterprises to the cloud. And really, in some of these things, you will look at the three there in the middle of really cloud, mobile, big data. All of these things, in some ways, have sort of reinvented a lot of things around tech and kind of taken tech to that next level that we all see. A lot of that is just now finding its way into sort of the final innings of that transformation, digital transformation in financial services. And you’re seeing one of the things that’s really held that back has really been that access to bank data. And now, with APIs, that… “Explosion” is a great word. I mean, that’s happening. It’s incredibly exciting because you have this… You think of high-frequency trading, where getting access to that data has just been game-changing. And it’s all moving into financial services. The banks are doing their job, really getting access to data, and having this baton handoff to the fintech community, to a company like Trovata, to be able to then allow this innovation economy to really take advantage of that.

And so the rise of the APIs is really becoming this gatekeeper of this data explosion that’s now happening from the bank and then treasury. And I think this is gonna continue to be a backbone to really bridge the gap, even with FP&A in accounting as well. And then, but not just APIs, though. It’s not just the API. That’s this incredible dynamic pipe, this new fuel we’ll talk about. But now, taking advantage of that from a more modern tech stack and what that means to be able to really take advantage of that, realize that in a whole new way, and that’s become transforming. So in a world that’s moving faster and faster, we all feel it, it’s about speed, agility, at scale. And then, if you look at that formula, that is what’s driving automation. So you look at all of that ushering in AI and machine learning… It’s those combinations of those things, but also just modern tech that’s really enabling all of the new things that are coming. And they’re coming fast.

Craig Jeffery: I think there are some really good points you made there. I want to ask the question from a CFO perspective. If you were focused on the accounting side at some point, it always seemed like there was this rush to improve the speed to close because that was important. And then, you were going from, “Okay, we’re at 15 days, 10, 8, 2.” Three or two days seems to be a push on the accounting side. Our view is that treasury needed information a lot more regularly. We’re going from prior day to current day to real-time. How have you seen that difference in expectations of turnaround within finance?

Brett Turner: It’s a great question! I’m talking to a lot of controllers now. It is one of the hang-ups to the close process being even more efficient. It is Reconciliation 101. I mean, that’s the other thing. It’s sort of in your CPA toolkit. You still need to reconcile to the penny in terms of a bank-to-books reconciliation, which is different than a treasury reconciliation. But still being able to do that bank rec that has to be done across all your accounts, all your banks, that has been a little bit of a laggard, and it really held the month-end close process. So getting to more of a like a three or five-day close being best practice, and then that kind of starts the cavalcade of other things with the financial reporting on top of that. But you can only get your bank statements so fast. And so that’s been a little bit of a hang-up, I think, in terms of the accounting team even kind of getting that piece of it done. So that’s, again, part of this whole Trovata trove of data. We kind of look at this, the way things are going, sort of this backplane of bank data that not only is gonna automate a lot of the treasury things, but it’s also gonna be conducive to helping the other siloed departments and kind of bring all of those together.

Craig Jeffery: Yeah! And if we continue the discussion on the tech and what’s changing, a couple of thoughts on formats and connections. I got a little picture of that there. 2021. As you look back, and Brett’s going to replay some of the history about connecting information and formats, but this idea of… Data costs were high, now they’re almost nothing. Speeds are massive. There was a one-way push. Now, there are two-way confirmation and validation activities. We used to live in this, I don’t know, delimited format, where it was so expensive to send data. We stripped as much out as we could, and we stuck pipes or commas between records. And the records and the data elements, you knew what they were based on their location. And so it was very limited, and it was very expensive to send it. Now, we can send much richer formats with more data. That means additional processing can be done. And on and on, we’ve gone from file-based transfers, Spartan/delimited files to real-time enriched formats, API connections, and so on. So there’s been this evolution in every aspect of tech, including formats and connectivity types and how those are set. Brett, I know you might have a few comments here before we slide on.

Brett Turner: Yeah! Maybe, the best way to kind of describe it is as a little bit of our own journey on the next slide where you look at, again, a similar timeline. So we’re just moving. What’s been happening is moving out of a file-based world. So you look at this point in time, a payload of data as of this time or during this period is captured in a file. If you’re an elite treasury team, your company maybe is becoming a member of Swift, you’re being able to access that through a multiband gateway with one of the major banks. Maybe, if you don’t have the luxury of going that route, you’re doing some host-to-host connections, you have to get your IT department involved to do that. Or the masses of folks, who even aren’t yet or early on treasury or even for other reasons, are using, downloading CSV files. And then, everybody knows how to use the text-to-column feature. If it was an elevator button, it’d probably be rubbed off because it’s used so heavily in how to do that transforming of your own data essentially in Excel.

But this huge paradigm has shifted now where APIs are opening up this floodgate and explosion of data now in financial services and banking, wholesale banking. And it’s been happening on the retail small business and consumer side of the bank where you have aggregators like Plaid and Yodlee. And some of you heard about those. It’s they’ll use the user’s credentials to go in and screen scrape the data. But the banks generally hate that. There’s a lot of tension between that, and it needs to be more secure. And so the banks now are on the wholesale side, which is really… You can think about it like a QuickBooks demark.

If you’re kind of moving off the QuickBooks 20 million in revenue and above, you’re really on the wholesale side of the bank. And so on that side, there really aren’t APIs until now, until recently, and those are being rolled out. And I think that’s allowing this access to data in a whole new way. They’re difficult APIs to connect to. And that’s why it’s hard. We’re still needing our client, needing our IT team to connect to that, but that’s really where we’ve got to start. It is trying to bridge that gap, bridge that access point.

So as an aggregator, one of the things that we do is really ushering that data. Think of Trovata or just the aspects of having a big data platform, application of doing things, but then you still have to get the data, that transport aspect in any system, right? But there’s this whole aspect of where APIs really opened up, and it was three of the main banks, JP Morgan, Wells Fargo, and Bank of America, who were the first three, in February 2018 coincidentally all kind of released around the same time. And those were global first. And we became really the first with Square as one of our early customers to connect to those APIs for the bank. And really, what that’s doing is, it’s just really moving this forward, democratizing all of this data in a way that really is game-changing.

And I think when you kind of look at where we’ve been from this file-based world… I mean, MT940, that file format came out in 1977. And it’s still really prevalent, especially in the US. That’s a primary SWIFT format today that’s utilized. And so what we’re seeing now is this massive shift. It’s almost the equivalent of the rise of mobile or 5G, making this massive sort of telecom leap in terms of communications and messaging. And that is what’s happening, more of this. It’s kind of collapsing down the logistics or the supply chain essentially, where you’ve got this direct access. And the banks know that that’s where they need to… They’re gonna interact with their customers. That’s where everything is gonna happen, all in that intermediary, having the APIs and being able to interact with their customers. Well, it’s now moving into this $3 trillion bank as a service, digital transformation and financial services.

So these APIs are becoming strategic. They’re becoming how they’re gonna interact with their customers. And it’s really opening up the fintech innovation ecosystem for companies like Trovata to be able to kind of connect and deliver and help bridge some of these gaps to be able to take advantage of new services and new things that the banks are not doing or might have a hard time to do or augment what they might already be doing in their online banking portal. But just overall, it’s just driving the transformation. And that’s what we’re seeing now.

Craig Jeffery: I think that at that scale we’ll look at how people are viewing things like the APIs in some more detail. And this idea of… Larger companies always had a way to make things work, whether it was with legacy file-based formats or more modern file-based formats and now APIs. They’ve always had the ability to do that. And this idea of democratizing the access to that data, being able to come much more downstream is exciting for the profession, the growth of technology innovation.

And that brings us to our first poll question. So I know there have been some questions about poll questions in the panel box there. But the first one’s up. It’s about information reporting. Let me explain this to you. So for new connections for information reporting. That means if you’re setting up a new bank, not are you gonna replace an existing setup. But for new connections for information reporting, we would prefer the following method or methods. Secure File Transfer Protocol or host-to-host, that’s the first one. SWIFT in whatever format. An API or portal access to downloads. As Brett had mentioned, the worn-out elevator button if you will. So SFTP or host-to-host, SWIFT, API, portal access to downloads. What is your preference if you have to set up a new institution on connectivity? So go ahead and select those. When you’re done, you can select “Submit” at the bottom. Depending on what version you’re on, it might be the bar, or it might be a “Submit” button on the bottom right. If anybody can’t see that, please type a message in the chat box. Ky, do we have over 100 responses, 150 responses? And so we do. So let’s see, we have… This is the preferred method. Interesting that number one is API for new methods. This, I think, is, Brett, a key indication of the audience that’s on the phone now. APIs are now the preference, with SFTP followed by portal access to downloads, with SWIFT trailing at 23%. Any thoughts on this?

Brett Turner: Yeah, I would imagine there are some folks there in banking or who have experienced it, and they’re getting a taste of it, and they like it. I think, maybe some who haven’t have probably that aspect of, “Hey, it’s something new. What does this mean?” There’s some trepidation there. I think also just because of the cost associated with a lot of these things like you talked about… True, even the elite treasury groups have been able to build out things to kind of make things work really, really well. But it’s also at a tremendous cost. It could be millions of dollars through the significant and long-time implementation of the TMS. And even the costs are kind of maintaining all of that more prior day, or maybe it’s two files a day with intraday kind of piping in the data, but it’s… So that cost is now at a fraction of the cost. So it’s dropping the cost massively. It’s just speeding things up. It’s automating that.

I’ll tell you one quick thing. I’ll be quick on this, but it’s… In the telecom world over the last 10-15 years or 20 years, there’s this term “quality of service”. If you kind of look at the rise of the Internet and all the nodes in terms of as a network, there’s all this quality of service aspect that’s built in the equipment, that AT&T is employing as a part of their network, for instance, or Verizon. And so their software is designed to kind of self-heal and provide a quality of service through that. So when was the last time like us as users getting your email… You had ten emails. You were like, “Well, wait a second! I’d better reconcile the number of emails to see if I’m missing a couple.” It’s like that just never happens because you just know and expect the high quality of service. I don’t have to call AT&T and figure out where I’m missing an email or two. And I think that’s the one key thing that APIs really do. It provides where you can build this quality of service around this piping, these connections so that you get this resilience, more robust, more of an enterprise SLA that you can kind of guarantee around that. And that’s just something that you… Passing files. It’s just hard to be able to get any of that quality of service, and therefore, it can get fairly clunky in terms of file passing.

Craig Jeffery: Yeah, great comments! Thanks, everyone, for taking the poll question! And there are some other instructions to individuals. Like if you don’t see it, it might be that one of your screens is stuck behind some application, depending on how your setup is shown.

But as we continue this discussion about tech and the paradigm shift, what has changed as we look at this movement from heavy overhead expensive setup to the democratization of tech? What looks different? How does that change over time? And so this graph is to show some of those concepts. So in the columns, we have the discipline experts, those who are deeply experienced in particular specialties, to general domain experts who cut across, to power users, to users, to more highly automated activities. And you think about the activities that go on, from setup to making connections to integrating data into our systems for positioning or forecasting, generating accounting entries, etc., to how we manage the upgrade process. All of these things change over time. And they change with the technology that exists.

So for example, we have a green bar that starts near the bottom in terms of how much production rate and volume goes up. So that scale shows that we’re able to scale because we’re leveraging tech. At the same time, how many people and how much time is involved in setting things up, keeping connections rolling, making the process work? We see that declined in terms of time. There’s still some significant effort and expertise required.

But let’s think about some of these concepts. If you look at the upgrade chart, for example, as we move from technology, what did it take to upgrade? Well, we had a new version. Maybe, it’s released every 18 months or 2 years. People will decide, “Can I take advantage of what’s been updated or not? Do we need to do that? We don’t need to do it. It’s a lot of work. We’re busy. We’ll wait for the next upgrade.” And they wait for further upgrades. And then, it’s a major version change. It’s almost like a new implementation. You have to go through the steps. So that changes dramatically. And as you move more towards SAS and more towards web-native applications, the upgrade process becomes transparent. It happens twice a year, three times a year to continually. Those changes are done on a micro-level rather than massive shifts.

If we look at the setup effort, connecting to different institutions for payments or for information, it might be exchanging different keys, setup, and testing, and moving the process to a more streamlined approach, which allows you to eliminate the vast majority of the initial headaches to get things up and running. And we could talk about that some more. But I wanted to give Brett some opportunity to talk about how that shifts, how we think about setting things up, running things, and maintaining them.

Brett Turner: Yeah, absolutely! I mean, I obviously love the curve. And if you see what’s happening there, I mean, in any discipline, there’s the stuff that’s really strategic and then there’s a lot of stuff that’s not. And I think that’s what we’re gonna see and what this is ushering in the combination of APIs plus a true kind of big data modern tech platform and technology to kind of modernize it, to try to drive that to a couple, take that handoff with the API, and then build applications that are gonna automate a lot of those workflows. And that’s what’s happening. So that’s gonna continue to automate more and more. And so I think… If you kind of think of treasury folks, their expertise is gonna be relied on more and more and they’re gonna do more of the strategic things. You don’t hear about that, but I think it’s truly what’s happening. We will live through it.

Having lived through it on the IT side, in the days of cloud with AWS… I mean, early on, there was a lot of the fear of saying, “Well, AWS means that a lot of companies are then gonna fire a lot of their IT departments” or things like that. And it’s like, that never happened. In fact, more IT folks… IT is a bigger profession because all it was, it was sort of repositioning around the things that really mattered. And I think all of us in some ways feel that. There are parts about our job that, whether you’re a CFO or in the accounting department or in treasury that you like, there’s other stuff that’s like mind-numbingly, I’m jabbing a pen in my eye because it’s so manual, right? So those are the things that I think that we’re gonna continue to just drive out of those workflows.

And the big thing here is this. It’s really modern technology and what it means to have more of a componentized true native clouds. So if you’re architected in AWS, or maybe Azure, or Google Cloud, AWS is still ahead of the other two main cloud providers, but if you just know you’re leveraging all of the best, latest, and greatest web services that have essentially been widgetized into all of these microservices and various pieces that you can componentize your entire tech stack… So instead of having something that’s more of installed software or something that’s more monolithic, where you have to actually have… The term “upgrade” means something. That’s a big deal. We’re gonna upgrade. Then, it’s everybody sighs. It means a lot of work. You have to put up some downtime, maybe. Maybe, hopefully, it happens at night. There are all these things that we’ve kind of grown through. Well, that whole meaning of the term “upgrade” is now something that’s dynamic, that’s fluid, that’s happening often. I mean, when you have a modern tech stack, and everything’s built with all these microservices…

The way microservices at our architecture works, it’s like… At Trovata, we have hundreds of APIs that are utilized throughout our tech stack, so it’s a little bit more, maybe like, if you’ve seen Big Hero 6, with all the little bots working in harmony together, as opposed to something very monolithic that you’ve got to then make some big change, rebuild, or remodel a room in the house, and that’s gonna take some time before you can move in. And there’s a transition. Like that is really associated more with legacy technology and legacy software. And the whole aspect now of what you can do and build – in that agility and speed at which you can operate, and the rise, and we’ll talk about it in a minute more, of what a truly big data architecture means, why that’s a big deal, why that’s different than a lot of legacy systems that are still built on more relational table-based architectures, why that gives you this traverse across massive amounts of data in milliseconds to be able to retrieve things, and why that’s a big deal. That ushers in machine learning or AI in a way if you get the machines and algorithms to be able to do anomaly detection or looking and hunting through across millions of transactions to potentially find a point of fraud that you’re teaching it, you just simply can’t do that manually.

So those are all the things that couple. APIs, it’s opening this floodgate. The banks are doing their part. They’re opening and releasing the APIs and their data. And now, this handoff can occur. It’s being able to have a true modern tech platform and tech architecture to be able to take advantage of that. And honestly, we’re just scratching the surface. We really haven’t even hit… I would say we’re at least 6 months from hitting a tipping point, but it is coming. The wave is significant. And all of this is gonna be… In 2 or 3 or 4 years, we’ll look back and say, “Oh, yeah! Well, that’s obvious”, just like we do cloud today. But I can tell you living through that, there was a lot of consternation, a lot of like, “What does this mean? How am I gonna have to change some of our current processes?” and things like that. But as everybody’s gone through that and everybody’s migrated, obviously it’s allowed, ushered in so many positive things and positive changes in terms of automation. And it’s not just defense. It’s also offense. The things you can’t do that you simply cannot do in legacy technology today, it opens up the playbook massively.

Craig Jeffery: Yeah, I think you started some of the discussion about, “Why modernize?” Because the playbooks opened. But yeah, maybe you can continue that discussion on this topic.

Brett Turner: Yeah, I think one of the things that this helps change, too, is just in the way. And AWS did this in the world of IT, how IT services are consumed. And it used to be, yeah, lots of procurement processes and RFPs and things like that. And people use that in their toolkit today. But the beauty about modern tech and the way that you can now modernize through that process, it’s… I mean, one is it’s way less expensive than you think. It’s way easier than you think. Once you start to go through it, you’re actually pretty surprised. It sort of enables this crawl-jog-run type of method. You can step in and get into something but with a very low investment of time or money. That’s why we can offer an initial free pilot with connecting to one of your banks like you can’t… We can do that just because it’s a very low cost. The entry for us to be able to deliver it out is very, very low. And so we can offer that up, meaning it’s also making it possible for companies to consume services in that sort of lightweight, more nimble, and more agile fashion as well.

So there’s a whole risk quotient how like a TMS is procured. Let’s do the traditional RFP and kind of go through these “the check of the box” and all the features of functionality and see how it all ranks because the big reason to do that, which… That’s a smart thing to do, obviously, from a decision tree. And you really had to do that in days past because when you were gonna pick up something and go with it, there was gonna be a huge implementation process, a huge investment of money, of time, all these professional services, lots of configuration on and on and on. It was at a huge cost. And so you don’t wanna be wrong. You gotta get it right. And so you’d spend a lot of time going through that.

Well, the beauty about now in terms of consuming something that’s new and modern is you get this more of a try-and-buy concept. You can get something that feels more out of the box. It feels modern, but it’s also really easy to use. And this aspect of kind of time to value where you can actually get in, get started, get some value right away without this traditional implementation process allows you to try it. And if it’s not working, or if it’s not what you want, then you can pull back and try something new. So there’s a sort of notion of, like we use the term “no penalty”. It’s not that if I go down that rabbit hole, and I’m stuck, and I’m just gonna feel compelled where I have to finish that because I can’t go back. I don’t wanna undo all this heavy investment of time and money that I’ve already done. You really don’t have that now in more of a modern tech stack, which is now really modernizing all procurement and the whole buy, that whole risk quotient, mostly in financial, in treasury, in accounting.

A risk aspect is really, “How to assess risk?” And so naturally, there’s a little bit of risk aversion in how to do that buy process or go through that. So I think it’s one of the nice things that really reduces that. You feel like you can kind of test some things out where you’re not massively invested. That concept is something that’s completely changed that paradigm, has it absolutely shifted.

Craig Jeffery: Yeah, a couple of thoughts on some of what you’re saying. The phrase that the Big Bang approach always seems to be fraught with so much risk and so… The other phrase, I guess, is, “You don’t boil the ocean. You wanna break it up into smaller chunks.” And so just extending that down has a positive impact on development.

You said something earlier, too, about what’s gonna happen with IT groups initially. It wasn’t too many years ago where IT groups were very resistant to things in the cloud. Then, they became, “Yeah, we’re accepting the cloud, too. We need to do more in the cloud.” And what’s interesting, too, is the biggest limiter of putting in new technology or initiatives is the gating of IT, the lack of resources in IT, even above priorities of management, which is amazing because if you thought it was gonna go away, it wasn’t. It’s limited there.

But that brings us to, “What are your peers on this webinar doing? What are they thinking? How has this changed?” Now, and so as you look at this chart, I wanna look at a couple of items here. There are APIs, the third one from the top, AI. That’s two examples. So you can see the dashed line showing expectations of growth within 2 years, which is the blue bar if you can see colors. And then, the orange bar would be, “Will use within 5 years.” So when we look at some of these items, what’s currently in use, almost 40% were using some type of API within their group with another 40% expecting to use it within 5 years. The same thing with AI. Using AI went from 15% currently to another 32% expecting to use it within 2 years.

I wanna say something about our surveys. Usually, when people say, “We plan to spend heavily. We plan to make these changes,” their eyes are bigger than their stomachs. More people are expecting to do things than they actually do, so it’s some percentage of. What we’ve seen with AI and the use of APIs is we’ve seen on some of the other surveys that there’s an expectation of uptake within a couple of years. We have seen more than 2 years worth of expected uptake occur in the past year. I think that’s dramatic because that’s over performing or over adopting, particularly with the use of APIs and AI. So I think that’s really interesting that this is really… It’s been a significant interest, but the actual application of it has been greater, which tends to be different from much of the expectations. Brett, any comments on that before we move forward?

Brett Turner: Yeah! You also look at the blue bar. What folks are still anticipating is AI and machine learning. And that’s the biggest: 32% of the blue bar, right? And I think that it’s making its way. And again, in other modern applications, in other industries, it’s not really finding its way here. And again, I think the big barrier is just you have to have a modern tech stack to be able to do these kinds of things. Otherwise, it’s just talk. And I see that was kind of some of my foray into surveying a lot of kind of what’s out there today in treasury. And it’s just there’s a lot of 20-year-old plus systems at best, many 30 years old. If you don’t have modern architecture, trying to do machine learning, AI, from somebody out there to kind of educate a buyer, if they’re saying they can do that and it’s something that’s more than maybe 10 years old, then I would highly be skeptical. You really need to drill down because I would say, “No chance!”

Craig Jeffery: Right, that brings us to poll question number two. It should appear on your screen. It should say “speed” at some point. Identify your next year’s expectations, 2022, for speed with treasury information. So pick one. Monthly or weekly speed is adequate. This is for treasury data. Prior day is sufficient or is needed. The third option is current-day information at several times during the day can work for us. And real-time data holds more value for us. So we wanna see where people’s expectations of speeds are at this point. So fill that in, hit the “Submit” line, row, or button, whichever you see. If you don’t see it on your screen, hold down Alt-Tab until you see the polling question appear. And while you’re doing that, and after you’ve completed that, for those who are interested in seeing the results of the poll questions from today’s webinar, if we get, let’s just say, 60 people to type the word “poll” in response to everyone… A lot of people are sending it just to the panelists, the word “poll”, but send it to everyone, so we can see it. Then, we’ll send all the poll results to everyone who’s attending. So we will need to get 62 to do that. That shows us that there’s an interest. I know a lot of you guys like data as well. So shall we go from there? But let’s go ahead and show that up and see where we are. Brett, you’re gonna like this because almost 40% see that real-time data holds value. I don’t know if that’s a bias for those who are attending this webinar because of the topic in the series, but monthly or weekly is adequate, a very small number of companies. Prior day works for… Now, that’s almost a third. And then, we’re at 71%, multiple times during the day or real-time holding value. Any quick comments on that? Because I know we gotta push on to a couple more.

Brett Turner: Yeah! No, I love it. I think one is I would say, maybe there are certain things that you have to have. But who doesn’t want something in real-time? Look, maybe a quick story. One of our first customers, besides Square I mentioned… But one was Sonos, the speaker company, and they were kind of accustomed to getting information on a prior day. And they said, “Yeah, at a minimum, we need that. We like the promise of real-time.” And so when we first got them connected, and this is the early days, this is like maybe customer two or three with JPMorgan with APIs, we could get real-time. It was almost a little of initial vertigo relative to their current workloads because they were used to prior-day. But all of a sudden, data’s coming in real-time. And that initially was hard to adjust, and they were like, “We’re gonna have to change our workflows that year to accommodate this.” And so and then, I almost like stepped in, and I was like (I was almost apologetic), “Yeah, I’m sorry, it’s coming in too fast basically. We could actually slow it down and kind of sync it up with some of your other banks, so it’s all kind of on a common denominator.” And they were like, “No! Are you crazy? We want real-time. We’ll adjust.” And so that notion of willing to adjust because, hey, real-time is really gonna open up a lot of doors, it was really, really cool.

Craig Jeffery: Great! Let’s pull not quite as current data as our poll, but from a survey. I’ll do a quick couple of comments on the left side. So we have the importance of APIs. Two-thirds believe it’s important that their TMS or the treasury system allows APIs for connectivity. And almost three-quarters thought it was extremely or very important for their banks to support it. This, I think, is becoming foundational. But you can see that on the tech side. Brett, if you looked at this a couple of years ago, I think those numbers would be less by a lot. What about you?

Brett Turner: Obviously, I’m really pleased to see these percentages high. But yeah, from the experience of kind of going through the progression, when we got started… And we’ve been in the market for two years. We were kind of doubling quarter over quarter. So the demand has been massive, and we’ve grown a lot. But even prior to that, before we even made those connections to the banks, the API connections, going back a year prior to that, there was still a lot explaining to a lot of folks in banking what an API was. And I remember talking about, “Well, here’s what an API is,” to a gateway team at a major bank. And then, they were all kind of listening, “Oh, that all sounds really cool. What is that?” But to see where we’ve come and how quickly that has come, I mean, that’s also just a validation of the pent-up demand. The comfort or familiarity with modern tech and other aspects, maybe nonfinancial services, or banking, or treasury, now it’s here. It’s like the acceptance rate is very, very fast. It’s really getting that exponential springboard because it’s a long time coming and everybody has been waiting for it and now it’s here. And so people wanna action on it.

Craig Jeffery: Yeah, great! And I’ll just let everyone’s eyes glance on the right-hand side, and then you can make your estimates of how this will change. These show the top product development priorities for corporates this year, one through six. And I think it’s not too much of a challenge to think some of these are going to move up, others might move down, but they’re all important.

But just for the sake of time, we’re gonna move to the modern tech stack and two views of this. The left-hand side from the bottom, data, connectivity, systems, and what we used to refer to as reporting and analytics, which we’re consolidating to analytics, is the conceptual stack. What is your data? Where is it? What format is it? How do I connect from one system to another, internal and external? What systems are used to support that? How do I do this analysis, whether it’s related to risk, visibility, etc.?

The stack on the right is the modern cloud, cloud-native stack. There are transport layers (How do I move data around, get access to it? Where do I store it, get it ready for use?), some of the application layers where I’m either analyzing or interacting with the data. This provides the basis for all of what we do. We’re sitting on top of this, making decisions, protecting the corporation’s assets, planning for the future. The modern tech stack is necessary to add value over time, decrease the time to value. There are a few things on the bottom that get into some more detail. And, Brett, I’ll let you take that piece if you would highlight a few of those items.

Brett Turner: Yeah, absolutely! I think that a lot of folks just concentrate on modernizing the UI. Like this is how I’m working with the software. My integration or my use of it is through the UI. And that’s true. But all the pieces are kind of behind that that makes that work. And if those aren’t modern, then no matter how pretty or… There might be some features through the UI. But to be able to kind of get these iterative changes and progression and growth, you want your tech stack to be just as dynamic as the API itself. What’s so exciting about the API… And like JPMorgan, for instance, is on v3 of their API. Bank of America on additional versions as well. So these are getting upgraded. More data is coming through, richer metadata. And it’s all in response to customers asking for certain things. So you have a dynamic fuel type that’s coming in. It’s very new. You can’t just plug it into a conventional vehicle. It’s a different kind of fuel. So to be able to take advantage of it, you have to have these other layers or these other pieces that are also very agile and built more componentized.

The only way to do that is if you’re not managing that infrastructure yourself. I mean, the way to do that over the last 10 years, it’s all been ceded to the big cloud providers like AWS, Azure, or Google Cloud. And so if you’re really not natively architected in there, when you need to make a change, you don’t have to twist the wrench or do any of that, like all of that plumbing or all of those pieces. You’re using all of these microservices or things you can swap out because they’re componentized. If AWS releases a new feature that makes something faster, I can plug that in and I’m gonna get the benefit of that instantly.

And all the UI end-users from that poll are referring to that time to value, meaning, “How quickly?” If you get something, a piece of data, through the API, how quickly are you, as a user, going to actually experience it through the UI? Because that’s how you’re gonna utilize the application. It’s in the application layer, right? So well, if you’re not architected more natively in a cloud with a lot of those kinds of componentized APIs, microservices… They’re really driving the entire tech stack. And it’s gonna take a long time. You’re gonna be on this upgrade… Well, it’ll be in the next 6-month release cycle or… Well, that’s in the fall of 2022. That whole paradigm is all kind of legacy. A modern tech stack is where you’re doing constantly releases, where we release… Every week or every two weeks, there are new things coming, new advances, more streamlining. Some of it is under the hood just to make everything run faster. But you will kind of see, other things are very visible, that there’s a new feature that will pop up and will educate folks. And it’s all in response to having this dynamic community-based feedback loop from our customers. We’re talking to our customers. We want them to challenge us. What do you want? What are you looking for? What are we not doing that you need? And that feedback loop comes through. All of those things get fostered when you have this kind of tech architecture. And so having that, again, time to value, like it’s coming, but when do I actually get to benefit it or benefit from that? And you want that to be very, very fast. If it’s more than a couple of weeks, or if you have to wait for a long time, then there’s a problem with really the underlying tech and a lot of the plumbing.

Craig Jeffery: Yeah, so as we continue that discussion, we’re gonna… This series covers some more of the technology elements here. So I’m just gonna make a comment or two on this and move on. I’m promising that we’ll go into some of the details and explanation in some more detail on a future webinar. But on the left-hand side, you see some of the functionality that people look for in treasury and financial systems. You’ve got big data architecture in the middle. And to have a great user experience about some of the things that Brett was talking about, there’s a number of these required. Plumbing structure activities, that’s necessary. So everything from rapid retrieval requires dynamic indexing, storage, being able to do natural language search as opposed to a query export. All of these items feed into what we come to expect with the tools that we use personally, whether it’s social media or how we bank or get the right share to how we can leverage items in finance. We have a lot more we could say on that, but I’m just mindful of time.

And we’ll push on to our final poll question. We’ll put that up, and it’s about tech. Big data and cloud-native treasury means to me the following. Something I need to learn more about. We’ve got that you’re pro or you’re against it or there are doubts around some of that. But just click what makes sense for you, any or all of those that make sense, and go ahead and hit “Submit”. And Ky, I don’t know if we’ve had our 60 responses on the poll side or not. I saw some come through the Q&A side and some come from others. So I don’t know if we hit our level. Yes, it looks like we did hit our level of 60 come through, which is good. There are some questions about certain banks supporting APIs, and I think it was mentioned that some of the trillion-dollar banks, they do support APIs. Some of those are required through some legislation even. All right! So on the tech side, let’s go ahead and pop those up. We’ve got a bit of a sprint here. Really interesting! It’s a great opportunity. A quarter. Concepts and technology that is will shift the treasury’s paradigm. I guess if you came to a webinar, that makes sense.

We’re gonna move off of this because we have a fair bit to cover as we move into the end. But what does treasury need to do? And then, what are some of those final thoughts? I guess I’ll just say a couple of things here. All of these questions center on, “How does this technology change with data, with processing, with cloud-native technology? How does that change your thinking? How should that influence your plans and your approach?” And so we’ve laid out a few things here. I just want to put that into your mindset. You have to be adapting to what’s going on. How dramatically do you need to do that and what’s essential is what I wanted to leave you with on this particular slide, that perspective. And then, I turn it over to Brett to get us going on some final thoughts here for the application of these.

Brett Turner: Yeah. Oh, sorry! In terms of just… That was my cue. I missed it.

Craig Jeffery: Oh, sorry! Sorry! Yeah, I was really short with what I was saying. It’s just because of time. Sorry!

Brett Turner: Yeah! No worries! Sorry, Craig! So yeah, I think when you kind of look at summarizing these things… I mean, the poll is great because it’s like, “I wanna learn more,” and I believe it’s gonna happen. I mean, if the 42 and 49, you’ve got 91%, right? Which is fantastic.

I could kind of tell one thing about big data. Craig, if you maybe back up like two slides. I promise I’ll be quick because I know we don’t have a lot of time. But that whole kind of “learn more”, maybe this will help some folks of that 42%. A lot of people don’t really understand like, “What does big data even mean?” And I think one of the things, just like layman’s vernacular of kind of what this means… Maybe, I’m dating myself because I have a fair amount of gray hair. But if you’re gonna go find a book in a library and you go to the Dewey Decimal System and get the library card catalog, I mean, a relational database, which typically will look at like massive scale even with Oracle, it’s finding stuff that’s down rows, down columns, find that cell, just like it would be in a giant Excel spreadsheet. You’re having to go through the aspects of traversing that in that linear fashion, down, across, etc., to find that data point. A little bit like it. If you’re gonna go find the book, you’ve gotta walk on the right floor, down the right aisle, up the right shelf, over on the shelf, grab the book, and you’ve got the book. Big data, though, with now modern indexing is basically like having millions of librarians virtually all in front of you. And they basically all have the book that you’re looking for. And when you say, “Hey, I want that book,” whoever has it steps forward and says, “Here you go.” That’s the kind of that speed and pre-indexing of all that data gets you because now you can do things on that without having to spend so much of the horsepower, the compute capacity that’s needed to really drive the wagons to go get that book on the shelf. You already have it. Now, you can do things with it. And that’s that throughput, that fast retrieval. Those are the kind of things that big data ushers in. And it’s really because Facebook and Google, as they rise with them, the amount of users and data, they really broke the largest database Oracle out there. And they had to reinvent really the data structure. And that’s where really the rise of big data. And that’s what a modern tech stack is really gonna deploy. So I think that’s the key APIs, of course.

So you have to have the right tech, the API. You’re getting that hand off the bank that’s so key because, again, it’s just… You might have a Ferrari, but if you don’t have gas, you’re not gonna be able to drive it. That’s a great sports car. Your modern tech is gonna allow you to do things with it. And now, having the right architecture is so key about that tech. So scrutinize that, make sure that’s all in in terms of your buy decision and really look for something that’s more modern and question if it’s not. Now, all of these things are here, and they’re now, they’re ready. It’s up to everybody to be willing to kind of step in. It’s a lot easier than you think. It’s a lot less expensive than you think to kind of step in and make that first step forward. And I promise you you’ll be excited and you’ll be a part of the journey going forward.

Craig Jeffery: And I think a lot of people are using APIs, so they’re… Everyone’s tasting it to some extent. Thank you so much, Brett! Those who are on, there are more in the series. Here are the next three. And if you register for part two… I think you can click on the section on the screen, register for part two, or you can register from the link that’s sent out. Brett, thank you so much for talking through these things today! And everyone in the audience, thanks for listening and responding to the polling questions and for your investment of time today!

Brett Turner: Thanks for having me! Thanks, everybody!

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 part two of this webinar series. “Navigating the New Tech Landscape” will be held on August 18th at 2 pm Eastern. The registration link is in the chat box. We’ll stay online for a few more minutes if you have any questions or comments. But again, thank you for joining us today!