Fintech Talks: Money20/20 Europe | Reshmi Suresh & Nabil Manji: AI, Stablecoins & the Future of Payments

Speaker A: The Georgia FinTech Academy podcasts are available on itunes and Spotify. To obtain additional information about the Georgia Fintech Academy, please visit our website at Georgia fintechacademy.org hello everyone. Welcome back to another Fintech Talks. It's your host, Laura Gibson Lamoth here at Money 2020 in Europe in Amsterdam. Really excited to have the conversation with you both today. Appreciate your time. Can you just first introduce yourselves and your role in what you do?

Speaker B: Yeah. Hi guys, I am Reshmi. I lead agentic commerce at uh, worldpay

Speaker C: now Global Payments and my name is Nabeel. I lead enterprise growth and partnerships also

Speaker A: at worldpay now Global Payments tying back to Atlanta. The presence there is strong and we have a lot of folks that are uh, supporting and working with Global Payments. For you guys here, I know you were speaking and there's a lot of collaboration and conversations you're having. What are you hearing and what are some of the themes that you guys are taking away from this year's event?

Speaker B: Yeah, love coming to these events. You get to see so many new companies and what everyone's focused on. I think the two or three themes that I'm hearing from this year's conference is one, agentic commerce and agentic AI. Generally there are so many unique use cases of AI that has a lot of promise in optimizing how we do various process over the next year or two. Lots of startups, so that's been super interesting. The second one is stablecoins and that infrastructure. There's a lot of conversation happening around how can that help optimize money movement and how can we make that better? I don't know. Nabil, what do you think?

Speaker C: Stablecoins and AI. I feel like you can't go to a payments conference in 2026 without um, both of those things being front and center. Other than that, I think a lot of discussion around payment performance, which is interesting. People talking about authorization rates, lower friction, better authentication. So that, that's been interesting and then related to but slightly different than stablecoins is just more efficient money movement, like better use of real time rails around the world now that those systems are more prevalent. A lot of talk about real time payments in the US which are now starting to take off. So yeah, really interesting.

Speaker A: Yeah, question around the uh, stablecoin piece, I guess carrying that theme forward and I love how you guys are connecting. One is enabling or helping facilitate the other. But from a stablecoin perspective, how do you see fintechs start to adopt that capability? I saw there's several announcements that happened from 2020 and partnerships and people are just announcing new news. But what does that mean from a fintech perspective to, to be able to adopt?

Speaker C: Yeah, it depends on your business a little bit. So I think the killer use case right now seems to be cross border payments, particularly in certain currency corridors where traditional rails are slow or companies don't want to pre position liquidity, they don't want too much exposure to that currency or whatnot. So that seems to be where a lot of the growth is that uh, cross border payments use case. What I'm more excited about is actually like the internal treasury and liquidity management side of it. A lot of fintechs, particularly those that are operating in multiple geographies and currencies, we need to move money around the world constantly and it's hard to do that when again there's not connectivity between those different currency systems and payment systems. And so stablecoins has been acting as a nice kind of connectivity layer to allow companies to again uh, position cash more effectively and things like that. So I think that space is going to be really interesting to watch over the next year or two.

Speaker A: Oh yeah, I think about like settlement and you know, batch processing and like

Speaker C: that's even a whole separate thing. I mean yeah, most of the large scale payments they're all batch based. Right. But I think we're slowly moving towards a world where it can become potentially transaction based. So for example the card networks are looking at how do you do things like transaction by transaction clearing rather than batch based clearing and then how do you translate that into more frequent settlements and things like that.

Speaker A: So well and then thinking about AI like what is, what is exciting, what excites you? I saw your profile on LinkedIn, I did a little bit of research and your journey coming into worldpay now Google Payments. What, what kind of keeps you motivated and excited about what AI is doing now in the industry?

Speaker B: Yeah, I'll say two things. One is related to what Nabil said on stablecoin use cases and tying it back together. There's a third use case that I'm super excited about which is machine to machine payments or programmatic payments. For example, let's say you are doing some research and you've got a $10 budget as a student and you need to call or use certain assets like read an article, get a research paper, but you don't want to subscribe to all of those things. Wouldn't it be nice if we had a way to let's say pay 10 cents to read an article once and a small amount of money to spend and have your AI agent go and uh, negotiate those with these companies out there. Right. So the easiest way I suppose to make that happen from a commercial perspective is like stablecoin infrastructure, something like that. Because traditional money rails are not necessarily built for very, very small transactions. So that's an interesting use case. But thinking agentic commerce wise, I think what I'm excited about is the cognitive load going away so humans can then focus on the value of the commerce. Right. For example, I don't want to think about scheduling a plumber and paying for it. I just want my water in my house to work well. So if an AI agent could schedule those things on a regular basis and manage the commerce side of things, then I don't have to worry about it. Uh, or I don't want to have to search through hundreds of things to figure out what my 13 year old niece would like because I've not been 13 for a long time. So if he can do that research for me and suggest some options like here are ah, all what all the 13 year olds are like liking these days and which one do you want to pick? Based on my budget it's doing a lot of the thinking for me and I can focus on the fun things and not the payments, not the research. And that's what I'm excited about to help humans with the cognitive load to free up our time to then do other things that we like more.

Speaker A: I mean speaking of cognitive load, I have a lot of it this week and I've been using AI for efficiencies. When you hear all of that, do you think risk, do you think things that you have to overcome operationally to, to really consider that journey to, to get to that?

Speaker C: Yeah, I think it depends what you're using it for. Right. I think in something like product discovery, right. It's fairly low risk in the sense that the humans doing the review of what the AI research, uh, is producing and then ultimately making the decision on what product or service to buy. I think where the risk comes into it, particularly in financial services, is if you start automating certain things like fully using agents or AI, you have to have a very high degree of confidence that it's going to do what you expect it to do. So I think that's what I'm hearing from policymakers and regulators and other folks in the industry is the capabilities are amazing. But how do you clearly say to the regulator or say to your customer that what's Going on in the back end with agent is what you expect it to do. So everyone uses that term hallucination. Hallucination is not maybe that risky when you're looking at what plumber to hire or what product to buy for your 13 year old niece. But it's super risky if you're doing automated customer onboarding or like investigating fraud or transaction monitoring or something. Right. So you gotta think about what it's actually being used for. And the risk profile is quite different.

Speaker A: Well, and what I'm hearing from you also is like not everything justifies throwing AI at it. So there's certain processes and obviously there's an assessment naturally that has to happen. Balancing customer friction, risk, whatever other areas that are operational efficiencies as well and cost savings, uh, on top of that. And how are you guys currently using AI and advancing some of the conversations that you're talking about, especially from cognitive load perspective. I'm interested to see maybe operationally and internally what you guys are offering your clients today and that roadmap of what you're planning to offer strategically in the future.

Speaker B: Yeah, we have three broad uses of AI within the company or applications. One is agent E commerce, which is like helping our merchants accept payments from an AI in a trusted way. Our own products. So we've got optimization products, we've got fraud products, various other things that we offer our consumers, customers and merchants. And how do we make those products better with AI, can we identify fraud in a faster way, in a more dynamic way? Can we figure out better ways to optimize so authorizations rates go up for our merchants? Right. So using AI for that purpose is the second use case and the third use case is internal. So productivity improvements. So I know we use a lot of AI tool for coding. We use it for like cdd, customer due diligence, anti money laundering, onboarding, all of those use cases that you can think of where something is done repeatedly by humans and it's easy to perhaps delegate to an agent because you know what's expected and it's not like a complex decision making involved in there. Those are the things that we're looking at. But what I will say is like when you do move trillions of dollars, there's a responsibility to make sure that that's done well. So you can't afford to make mistakes. It's like whoops, like four or uh, five hours we went down. Right. We can't do that. It is also done in a fair bit of controlled and observed way. We have got an AI Governance, et cetera. Just because like when you're moving people's money, you have to be very careful in how you do it.

Speaker A: That's a good point. And thinking about what you mentioned earlier from a Treasury perspective and thinking about moving a trillion dollars, which I wish I had, in my bank account.

Speaker C: Managing liquidity for a global payments company at that scale is complicated. Right. We've got thousands of bank accounts and hundreds of currencies in lots of different geographies across different products and services. And so like the number of variables and the complication of that web is like, yeah, quite immense. But I think to Rashmi's point, like, a lot of that money movement falls in a kind of regulated perimeter. Right. And so when we look at AI in Treasury or finance, I think it's quite interesting a lot of companies are finding it quite effective for like, forecasting as an example. So like, you know, taking some of the guesswork out or, you know, doing it maybe more efficiently or more quickly than a human can, but then the actual money movement is still being done by a human. Because with any sort of money moving at that scale, there's very strict workflows around who needs to approve what, what needs to get documented, all that sort of stuff. So I today haven't heard many companies where that, that are using AI or agents to actually move the money itself, like initiate the transaction. But a lot of them are using it to speed up processes like forecasting, which are in and around that workflow.

Speaker A: You know, I, the first thought was regulation. There's just so much of it. You get state regulation, like individual states, uh, regulation. You have things like obviously the genius act, developing the states. I'm, I'm hearing so much here and to be honest, so much of my career was focused seeing what's happening abroad and leveraging that as learnings and insights into the future possibilities of what could come and influence the work that I'm doing. Uh, but from your perspective, how do you control maintaining all of that and that balancing act of regulation and innovation, uh, in a very vast mixed footprint, geography of influences, a big team of

Speaker C: people with a lot of knowledge. Look like any large financial services company, right. Is going to have hundreds or thousands of people across legal and compliance. And for good reason. Right. Uh, you know, financial services is up there with health care and transportation or, you know, some of the other industries where trust is everything. And so that trust often comes through regulation, you know, implicit backing from the government that, you know, if this company is licensed. Mhm.

Speaker A: Mm.

Speaker C: That implies a Degree of trust. Right. But you need to earn that. And earning that takes work and work means people and technology.

Speaker A: Oh, that's so true. You know we're at time and I just wanted to ask I guess one wrap up question obviously with me and my role focus on future fintech, uh, workforce for the industry. What recommendations or insights or guidance do you guys have for this next generation, ooh, experiment.

Speaker B: That's what I'd say. Download whichever AI tool sounds good to you and start typing, ask it a question because no one will know whether it's a stupid question or not. So like ask a question of how do I start coding, how do I build a website and maybe prompt it to be like, I know nothing about this, what tools do I need? Walk me, like walk me through this as I'm 5 year old or whatever it is and start from there because if you don't, the barrier becomes higher and higher and the cost of experimentation, at least right now, compute is given for free or like close to free for a lot of people. Take advantage of it and like try out as much as you can and that'll help you be better positioned to go into a professional role in the space.

Speaker C: I love that.

Speaker A: Thank you. What about you?

Speaker C: Yeah, you gotta have the AI, uh competency, that's for sure. The other thing I'd say is don't forget the human elements. You know what's interesting is, you know today if you want to, if you're a business and you want to go buy payment services or fraud and authentication services or foreign exchange services or whatever. Yeah, you got a lot of options.

Speaker A: Yeah.

Speaker C: But in the day people uh, are buying from people.

Speaker A: That's true.

Speaker C: And I think AI with all the productivity enhancements, particularly in like the engineering space, there's going to be even more options going forward. Right. Like it's, it's going to become the, the marginal cost of creating a new technology product is going down.

Speaker A: Yeah, right, yeah.

Speaker C: So there's going to be more options and with big purchases that are critical infrastructure material to your business, I think the human element is going to continue to be really important. So invest in the relationships, build your network.

Speaker A: I love that. My advice, I love it because we, you amplify the message we always try to give the uh, students and you know, the network matters. Being uh, curious and you know, getting your hands on. We have a tech fluent, a now growing, increasingly AI fluent generation that's already testing and learning and building.

Speaker C: That's table stakes.

Speaker A: It is, it really is. Oh yeah. I feel encouraged and motivated by our conversation. I really appreciate you guys, your time today. And for those listening in, you know, keep tuned with fintech talks. You'll have more from us, uh, coming up here soon as we wrap up. Money 2020 Europe, 2026. Thank you.

Speaker C: Thank you.

Speaker A: Welcome to the Georgia Fintech Academy podcast. The Georgia Fintech Academy is a collaboration between Georgia's fintech industry and the University System of Georgia. This talent development initiative addresses a massive demand for fintech professionals and gives learners the specialized education experiences needed to enter the fintech sector.