Themes and Trends in B2B Treasury Technology – 2024 Outlook Series with Edward Galvin

Announcer  00:04

Welcome to the Treasury Update Podcast presented by Strategic Treasurer. Your source for interesting treasury news, analysis, and insights in your car, at the gym, or wherever you decide to tune in.

 

Craig Jeffery  00:20

The adoption of new technologies happening at a very accelerated pace, from the early stages of APIs to new formats and the explosive growth of data, the challenges and opportunities are multiplying. What are the most significant technology changes? What are the likely implications of these changes? How do we harness the explosion of data? What must Treasury groups do to ensure they are equipped and staffed properly for this new world. Welcome to the Treasury update podcast. Today’s episode is part of the 2024 Outlook Series, technology, themes and trends in B2B treasury technology. My guest today is Edward Galvin, who’s the Head of B2B Commercial Payment Sales at Visa. Welcome to the podcast, Edward.

 

Edward Galvin  01:03

Good to meet you, Craig, and thank you for having me on the podcast today.

 

Craig Jeffery  01:06

Edward, the first I wanted to get your input on and hear your thoughts on were technology changes and challenges. There’s been a lot of things that have been happening with APIs. We’ve heard the phrase embedded banking, embedded payments ecosystems. What are some of the biggest shifts and changes in tech over the past couple years? How do we think about some of those terms throughout? I’d love to hear your thoughts on that.

 

Edward Galvin  01:32

You hit the nail on the head with those two or three areas you just spoke about. So I think there’s, let me probably take each one individually. There’s one of three or four core areas, as I look at it from the lens of a payment network, and what’s been happening over the past, probably two or three years, and what we see into the future. And so number one is we talk a lot about the consumerization of commercial payments, particularly in Treasury, and there’s coming out of the pandemic. There’s been a major shift towards for for commercial individuals, or Treasury users, or Treasury, Treasury, Treasury people, to have the same experience in their commercial space that they have in the consumer space. So there’s been a push to build products and services for the ecosystem with that, you know, ease of use, with that lens of what I may have as a consumer, the net result is financial institutions, providers in the in the system, in the ecosystem, have had to change how they bring services to the market. So that’s led to increased usage of APIs. It’s led to, to your point, the concept of embedded banking, and it’s also led to proliferation of artificial intelligence as well over the past probably year or so. Let me go into each one in detail, Craig, if that’s okay, and kind of just double click on maybe two or three of those. So So APIs, and we’ve seen from our network. We’ve opened up our network to allow various different partners of ours, be the banks or fintechs or merchants come into the network and use API, use our API suite to generate virtual accounts as an example. So traditionally, in the B2B space, organizations use plastic cards for payments of goods and services. When people are traveling number one or when they’re buying an organization, they now use API infrastructure to generate a virtual account from from the network and pay for goods and services in that manner. There’s been a massive explosion in the number of use cases that we’re now supporting to allow payments for goods and services in the B2B space on virtual account numbers leveraging our API suite. So, big, big, big shift. So that’s number one. Number two, you talked embedded, I think you mentioned embedded banking, embedded finance. And I think we at the network level, Craig, we believe we’ve been doing this for a number of years, right? And, you know, we’ve seen, but we’ve seen more use cases of it, and embedded payments, if you will, as I would call it, is, in our view, is basically meeting the customer where they are right. And instead of providing a payment credential or a payment vehicle to a corporation to pay for goods and services, we are dropping the account number, if you will, into technology or systems that the actual corporate may be using, and embedding the payment, if you will, into existing business flows in an organization which minimizes the impact on the corporate customer and helps, just helps, helps them better, more efficiently manage payments and their treasury organization, Treasury systems in their business today. So I guess wrapping that up massive shift in trend towards consumerization of B2B payments. As we’ve as we’ve exited the pandemic, over the past couple of years, we’ve seen the proliferation of a whole series of new use cases, with the leverage of API technology in particular for. Virtual accounts, then embedding payment credentials into business flows, if you will, in organizations, has also been a major shift in what we’ve seen.

 

Craig Jeffery  05:10

You had indicated that it’s this idea of APIs, it’s meeting the customer where they are, and so this embedding reduces the friction, right? Takes the the impact out of the process. It makes it makes the payment almost invisible or less visible, less a point of friction. It’s, I’m doing some activity. It becomes part of the process, as opposed to a completely separate activity that seems to be occurring, I think, like you said, on the consumer side, and that’s expected on the business side now it’s becoming increasingly the expectation.

 

Edward Galvin  05:45

Very much so, very much so. And I underscore your language on just reducing the friction in payments. Another use case, or an example of that, is a business traveler, or a traveler in an organization who may want to make a makes one or two trips a year. Now, traditionally, they may have been issued with a corporate card, plastic for for those two, for the for the trip, right? But in in this new world, you know, it’s possible to generate a virtual account leveraging an API for that traveler provision it to their handheld or their mobile device for that trip, and it’s the one and done. And once the trip is done, they have reconciled, they can reconcile their transactions and they’re done, as opposed to that cardholder, if you will, having a plastic that they may use twice a year. Just another example of how that kind of comes together in today’s environment, Craig.

 

Craig Jeffery  06:36

That’s a good use case now. Edward, as you look at this idea of Visa certainly wants to be able to leverage APIs to allow for this insertion or embedding into the various payment processes. And so there’s a there’s probably a huge curve of companies that are leading in that companies that are very far behind this idea of tech debt. You know, people have old tech sometimes that wouldn’t necessarily support APIs, and not everything can be shifted over instantly to the the new way of doing business. It’s going to happen over quickly, but over, you know, quickly isn’t measured in few months. Any thoughts on the the tech debt. And you know, as companies need to convert. How do you how do you encourage them to move more quickly to this new embedded way of doing business?

 

Edward Galvin  07:31

Yeah, I will say, you know, so we work primarily with financial institutions, merchants, fintechs, and we’ve been starting to work with some large corporates as well. And in my business and the B2B side organizations want to, want to move from from many to many to less, many to few, right? So we’ve seen today, many corporations. We were many entities we work with. They have multiple technology platforms, and they’re trying to reduce the the tech stacks of the tech platforms, the number of tech platforms, they have to less through that process. There’s an opportunity for them to work with, let’s say newer technologies. They need to get there. It’s a shift, right? And they need to move beyond multiple platforms servicing multiple customers to fewer platforms serving more customers. So one more easy way to support that is, you know, instead of coming to a an entity, be it a FinTech or in a financial institution, but another platform to support that, we come with the APIs, so they leverage their existing technology to punch into us with with API infrastructure and, yeah, like, some are not ready, but like, you know, I think they they recognize that they need to get that on their roadmap and and kind of move into into the current way of operating, of the current paradigm, because their customers want it, they will find that, you know, they can provision services to their customers if they do not have them, you know, let’s say a relevant tech stack and how they’re going to market as well.

 

Craig Jeffery  08:58

Yeah, thanks shifting from APIs and some of the tech changes to another area of technology, artificial intelligence and machine learning. We’ve we’re multiple months where multiple months on from where chatgpt, all of a sudden started getting talked about a lot. There’s Bard, Microsoft has copilot. You embed it on your desktop. These systems are being used for real work right now, the pilot certainly, but also for real work in some instances, I’d love to hear some of your thoughts on where do you see this being used now, and what’s coming soon in the area of payments? Will this cause disruption? Just good things. How is it being used? How do we need to think about this from a staffing, structure, payment standpoint? So the use of AI and machine learning?

 

Edward Galvin  09:49

Yeah, it’s very relevant. And I am a user of Copilot myself, so I’ve been training myself, if you will, to learn how to use it every day. So and it’s making them. A major impact on how efficient I am as a as an individual in the organization. So let me start with, there’s a few areas, and I think first and foremost is fraud, right? You know, people think about payments. There’s always a concern about fraud. And like, fraud detection is a massive area where, or is an area where AI in particular can provide a massive amount of incremental support. I mean, Gen AI can be trained on normal transactions and data patterns and generate alerts when it observes anomalies or deviations. So I think as a as a first use case, I would say, primarily fraud detection, right somewhere where, where AI can certainly be leveraged in our ecosystem and space, risk modeling. Credit scoring is another area in risk modeling, genii can generate some data sets for robust model training without really exposing sensitive customer information. We’ve been looking at how we how we can leverage Gen AI with risk modeling andor credit scoring. The final area, in my view, where Gen AI can just provide incremental value, if you will, is in just in analytics and working with the customer, right? So a lot of what we do in the B2B space in particular is help an organization understand how they can be more efficient with their payments, right, and how they’re managing their payments, payment, payments across their B2B suite, as Treasury services, you know, with with machine learning and Gen AI, there’s an ability to look at large data sets and make some intelligent recommendations on that data set, on how a you know, how an organization may be processing their accounts payable file, you Know, but learning how they can process more efficiently as they go into the future, and then that may to the points earlier on. May tie back into leveraging API for virtual accounts, or maybe embedding certain payments into payment credentials and certain payment flows. So I guess your question, Craig, there are probably three areas where I see just immediate applicability of Gen AI, in particular, as we think about, you know, the payments ecosystem and the B2B payments ecosystem, fraud detection, risk modeling, and then, you know, just say, customer analytics for for efficient, efficient payment models, or efficient payment modes, I think is just right for adding value with Gen AI.

 

Craig Jeffery  12:20

And a lot of those are in play now. Are there, are there any other areas that you think may come online, you know, in a year or two, using AI and machine learning, besides expanding and filling out these areas?

 

Edward Galvin  12:34

Maybe think of software development, product development, certainly, maybe some area that where gnai might lean into again, it’s early days, but I think there may be two incremental areas that Gen AI I will support software developers and product developers when they’re looking at new product codes and new products setups, if you will, as they’re developing those products and solutions. Just the perspective, yeah. I mean, who knows? I mean, it’s changed rapidly Craig in the past nine months, year. I wish had a crystal ball for the next 12. Would be great.

 

Craig Jeffery  13:08

Well, yeah, when it was interesting, when it first came out, I was like, we’re using it for fraud detection, because of the strength of detecting deviations or any anomalies. And then it was like, well, it helps with detecting patterns, so forecasting, and then, you know, the ability to do more analytics. And so it seems like more opportunities are being discovered as we go, as we move forward and gain, gain understanding. The third area that I wanted to ask you about how to do with, you know, data and processes. The background, of course, is that the sheer amount of data that’s being generated now doubles every two years. You know, 40 to 45% increase in all data of all of humanity, you know, is doubling every two years. And this is probably the challenge, right, getting your arms around all of this data as it expands, analyzing it and it certainly requires, probably better analytics. But how do you see the potential and power of data and the insights or analytics that comes from this, and how are companies going to handle this? You know, maybe you address this broadly, but I’d also like to hear how you think about this in the in the payment domain. And you know, how does that impact other things like finance or working capital?

 

Edward Galvin  14:31

Yeah. So firstly, I think we said the ecosystem in general is under, under utilizing the power of data today, right? There is so much data out there. I think we have. We can certainly do a lot more with what we already have. And I always use the language like Make, make data work for you, right? And you know what we do and try and do with all our customers is, you know, lean into what we’re seeing in the data. To make intelligent decisions about how to manage the business as we go into the future. And let me give you some practical examples here. You know we have the benefit of our network of looking across our let’s say all our B2B issuing business and can deduce what areas or what verticals or what payment categories, if you will, are on the rise or have opportunity. And then we can bring benchmarks back to each of our individual partners and help them understand where they are relative to benchmarks. That adds a lot of value to some of our partners and customers as they think about where they should be focusing relative to what we see across across the network. Right? So that’s bad ads that helps them make the data work for them. So that’s number one. Second point I want to make is the data then helps our customers build their business, but it also helps them add value to their customers, and it helps them, and it helps them add value on how they should products they should build to support what their individual customer needs are. Mean, yes, it’s incredibly powerful. There’s a lot of data out there, but I think harnessing it and providing it back in an intelligent, meaningful way to our customers is what our focus is. And I think what the ecosystem is basically trying to do in general. I think the other thing here is, to your question, it’s how to make payments intelligent. What is the best mode of when a buyer should pay a supplier, you know, based on, you know, the their their working capital mix today, what should that payment vehicle be? Should it be on a card? Should it be? Should they be doing a wire, whatever that may be as an example, should it be on a virtual account? Right that, you know, having all that data helps the business make better, more effective decisioning, intelligent decisions around, you know, around their payment mix, to help them work, figure through, you know, their working capital mixes at any point in time.

 

Craig Jeffery  17:05

So intelligent payments, that’s that’s excellent. The last area that I wanted to dive in as a topic area had to do with this longer look, not just looking out the next year, maybe even the next two years, but over five to 10 years, with Treasury technology, with payment technology. What should we expect to see, you know, over this longer time domain,

 

Edward Galvin  17:28

So I guess to the future, and what we’re seeing, I guess, or hearing, in market. And let me step back a minute. We we’ve just commissioned a, what we classify as a working capital index, right? And we, Visa, went out, we interviewed seven to 800 treasurers across public class size, grow, corporates globally. And that gave us access to a lot of data and analysis on, you know, what’s going on out there right now, in the in working capital in particular, as we think about treasurers organizations, we’re certainly in interesting times. We’re in high rates environment, but like working capital is a key priority, a top priority for all these organizations, and how they manage it into the future is key and critical. But we’ve seen, and we’ve worked with some external parties on this, there’s going to be a change in what we see is a change in the in the payment mix, if you will, right? So while there’s a lot of payments today on on check and ACH, we’re seeing clearly there’s too much check in the system, right? So we think about working capital and treasury, we’re seeing a movement away from from check. We saw some of that particular during the pandemic, and ACH and other modes to more intelligent payments. And that may be, you know, some of that is on cards, some of those on virtual accounts. Some of that is on embedded payments within organizations, or intelligent payment flows within companies, or new commercial money movements, tools or services that are that are being built out as well. So as we think about treasury and payments, one of the big shift that’s going on out there right now is just the shift, shift in that payment continuum, right? And that’s driving, that’s driving new technology is driving new new modalities within treasury and how people are paying, being paid and and want to be paid as they go into the future here. So that’s one of the kind of the main themes and trends, I guess I I’m seeing at this point, Craig, when I think of the Treasury organization, so and just maybe just a step back, and some of the drivers, if you will, as we think about working capital and treasury, number one, optimization, digitization, right? Talked about that at the outset. Number two, AI is having an impact, right? AI is going to make, is certainly going to add a whole new decisioning factor around Treasurers and how they work, embedded finance, you know, the demand for working capital. And then finally, I think the just like global money movement, is changing as well, right? We’ve new players, and we’re actually involved here too, but in providing global networks to support moving money from Kansas City to Tokyo as an example, you know. So there’s new technology supporting treasurer’s needs around the world, and how they want to move money, be paid and pay their suppliers as well.

 

Craig Jeffery  20:09

Is this working capital index? Is this report available? Is that something you put in the show notes?

 

Edward Galvin  20:14

Well, certainly, yeah, yeah, the working capital is available, and I can give you a link to it, and there’s calculators, and what we’ve, yeah, we’ve also, we also, again, to my language earlier on, on making data work for you. We have a working capital calculator to be built as part of this, to provide data points to back to the corporate on you know how to best calculate the working capital. We also look at some different lens from different regions, because what’s relevant for a treasurer in one region may not be relevant for a treasurer in another region, you know. So there’s different cuts on the on the data and what it means regionally, as opposed to just, just a single, single global study.

 

Craig Jeffery  20:53

Sure, like terms can vary significantly from one country or jurisdiction from another, and I like it so working capital impact the whole smart money, how that’s changing over time. And really be interested to see how long it takes for the major changes to shift, to move more rapidly, to less and less checks and less of the more legacy systems, to more and more of the more intelligent payment processes that that’ll be really interesting to see how that unfolds.

 

Edward Galvin  21:24

Yeah. I mean, I would say cards, embedded payments, intelligent, automated invoice payments. Yeah, we will still see ACH and RTP and traditional cross border, but there, there will be and there are developments of new global money movement services as well that are providing more intelligent payments in the B2B space.

 

Craig Jeffery  21:46

Thank you so much for your time.

 

Edward Galvin  21:48

Thank you, Craig. It’s great to be part of this today, and thank you for having me on.

 

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