S2 - Episode 20: Featurespace, fraud prevention, and the ARIC Risk Hub with David Excell, founder of Featurespace and Andy Su from the University of North Georgia

Featurespace is the inventor of Adaptive Behavioral Analytics and Automated Deep Behavioral Networks technology for fraud and financial crime management. In this episode, David Excell the founder of Featurespace joins cybersecurity student Andy Su from the University of North Georgia. Their conversation explores the financial services industry problems Featurespace helps to solve.

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Speaker 1 0:06

Welcome to the Georgia FinTech academy podcast. The Georgia Vintech 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 give learners the specialized education experiences needed to enter project Tommy

Speaker 2 0:26

Marshall , the executive director of the Georgia FinTech academy. And this is season two episode 20 of the Georgia FinTech academy podcast. It's July 8th, 2021 . I hope everyone had a wonderful July 4th weekend and , uh, spent your time , uh , reading about the FinTech industry. And , uh, I ended up course reading your monthly or sorry, weekly subscription to the Georgia FinTech academy , uh , newsletter, which you can always subscribe to on our website today. I've got , um, two guests with me, Dave XL , the founder of feature space, and Andy SU a I'm currently an intern at visa and a rising senior at the university of north Georgia. Working on a BS in cybersecurity . Welcome to you both. Hey Tommy. It's great to be on. Yeah, thanks for being here. Um, Dave, our listeners love to hear the career stories and I'd say even especially career stories of FinTech founders. So , um, tell us about you, tell us how , um, you got involved with , uh , this exciting and FinTech industry and came to found a feature space. Uh ,

Speaker 3 1:49

Well, thanks for me. So I guess I grew up in Australia, so that's probably where the story started. Um, and then when I went into university at college or sort of my undergraduate degree, I started a five-year course in engineering , um , and information technology, I guess, as, as, as a child, I was always interested in sort of engineering, often breaking things and trying to put them back together and make them work again. So that was my natural sort of , um, passion at that time. Um, and then I guess I always had an entrepreneurial spirit like I , while I was studying and even at high school, I had my own like small consultancy business where I would work with different organizations in doing different types of it type work. So one of those organizations was called , um , farm wide, which was a sponsored out of what was called the national farmers Federation. And that was looking at providing high-speed internet to farmers across Australia, where there was often not like good copper lines to be able to get like broadband or dial up connections at that time. So I was always really interested in that cross section of technology and then how applies, and it makes a difference to people's lives to ultimately make them better. Um, and then while I was doing my final year project at university , um, I was working one of the research schools , um, and there was another sort of entrepreneurial person there. And he , he said to me that if you really want to be taken seriously in business, you need to go and get a PhD. So which I took to heart at that time. Um, but at the moment now I don't necessarily take that , um, fully into consideration, especially because I didn't end up completing mine, but that sort of launched into the next state of , um, I guess my journey to creating features based . So I took that to heart at the time and said, but be nice to experience somewhere outside of Australia and where would be a good place to go and do a PhD. So I guess the two places where going to the U S or going to the, going to the UK, and at that time, I'd already done a five-year undergraduate degree. So doing another five years as a PhD in the U S sounded way too long and going for a three-year option in the UK , um, seemed to be where I put my focus. Um, and then I was really fortunate. So I applied to study at the university of Cambridge , um, and I was fortunate to be able to get some scholarships that would fund , um , my study there. So I landed in the engineering department at the university of Cambridge in what the group there, which was the signal processing and communications group, and really a lot of the foundational research that they did was applying statistics. Um , and now what we call those machine learning to be able to build statistical models, which describe different types of like underlying systems that generate that data. So an interesting, or sort of one of the really other examples when the group was formed was looking at gramophone records and looking at scratches that were carrying those records. And how could you build a model of the music so that you could as bank deeply interpolate across the scratch and sort of editor out of the music. Um, and my, my interest really became, and then I was sort of looking at the aspects of sort of human behavior. So how could we start to teach a machine to have the same intuition that we have as, as a human person? So we can be sitting at a bar or a coffee shop and we can be looking at the surroundings around us, and very quickly as we see people move through is we can understand, like who's a local, who's a tourist who's sitting down for a business meeting. All of that becomes sort of natural observations that we can make as, as sort of our background and context of what's happening in that environment. So the idea was how could we provide that same level of intelligence to a machine, through areas of machine learning. And that's where a lot of my PhD ended up sort of focusing on. And then I guess it came back to a lot more of my sort of entrepreneurial spirit of then looking at well, what were commercial applications of that technology? And that's where really where I founded feature space with my PhD supervisor, professor, bill Fitzgerald. And we just looked at different ways in which that type of technology could then be applied. So we didn't start feature space going. We want to be a financial crime prevention company. It was where it was the best application of that technology. And we ended up landing in this particular space and have never looked back since I love

Speaker 2 6:23

It. That's such a great story. I don't think I've ever asked you where , um , in Australia you grew up. So I

Speaker 3 6:31

Grew up in Canberra, so in the capital city, like halfway between Sydney and Melbourne. Okay,

Speaker 2 6:36

Cool. Fine . Let me see . Um, and , um, let's see. Well, I guess one last question for me on that. When, when did you move, I'm trying to remember now, when did you move from , um, the UK to Atlanta?

Speaker 3 6:53

So it was four years ago on the 1st of July, so it was pretty much my full year anniversary and that expansion out. So it's good timing for the podcast.

Speaker 2 7:01

Yeah. Perfect, welcome. Happy anniversary we should say. Um, well, Andy , um, tell us about you. Um, I , uh, you know, I'd mentioned that you're at university of north Georgia. Uh , just tell us a bit about you and I'm just been always really curious about how you got so , um , interested in, focused on cybersecurity. So yeah , um , that

Speaker 4 7:24

Dates back to when I was around 16 years old in high school, actually , um, when I was 16, well obviously when I was in high school, I didn't know at the time what I wanted to do. So , uh, I would decide to please your engineering, especially know some of them, the camp engineering stuff decided you didn't really like it. So I decided to try something new and recently I got mold in , uh , cyber security or at that time. And it's all , you know, just to try it out, it's called the national cyber warrior academy. And what it does is it teaches the next generation, a group of students and, you know, launching kickstart stone and introducing them to you go cyber career, teaching them basic terminology, you have to hack machines and it was won by design . Really. I've been to a first, so he's a , he's actually my advisor right now. Um, so it was it back . So we met really early on and , uh , my stage, my career and advice and pain, if you guys want to know him. Um, and , uh, he's currently my advisor right now , um, for the rest of my undergrad. And , um, yeah, ever since, ever since I got to that camp, I I've been interested in cybersecurity. I've been interested in the terminologies. I've been interested in , uh, you know, the hacking , especially color hacking. That was the, one of the most interesting parts of being cyber security was being able to mess with the controls that would call . And as I left the camp thinking I wanted to learn more. So that next to you, I'm willing to do three more camps. I think, well , you know, one camp at GSU, one camp or another camp , um, I think , uh, UAH and those were all a cybersecurity camps . So someone's there with stem camps and some of them were technology quite a bit of cyber security in it. So ever since I enrolled in HD camps , uh, in the summer before my senior year of high school, I've only had to make up my mind what I wanted to do a university. So it all starts in high school. So I was exploring different ads signing up for a whole bunch of summer camps, looking at everything. And the cyber security Prague in each camp is always the most critical part . So when I went to university , um, I think , uh , after my senior year, I decided, you know, taking some basic classes, learning to basic technology , to cybersecurity as a professional level, and also in new Orleans, Macrobalance also propelled me to be able to meet new people. I think the most interesting part is the people do that . People have , uh , the people I met at these camps, the people I met in the classes, the people Amanda had at the hackathons , they all just like me do all. I'm motivated, curious. They don't know much about the field at that time. And , um, ever since , uh , I finished my freshman year, I decided I was , I decided I wanted to work for the government. So I had a series of interviews with the NSA when due to interviews, didn't make it, but that's okay since this was questioning you. So I just worked in operations, I Amazon doing supply chain and also doing some basic it tabulation at Amazon. And it's just basically soaking into data, making sure the data does not have any vulnerable code. It was just not an internship. It was just a summer job. And then following that, I enrolled in some cyber security courses in my sophomore year. Uh, and , uh, you know, it took some scripting, took some other classes related to the course. And then I also also got a job offer at an insurance company in context financial , or am I looking at profile ? I was all the details, but like country financial is that the insurance industry. And we work on a lot of InsureTech products and are looking at a low vulnerabilities doing, using a lot of cloud software to do a scanning. And then I think during that year it was COVID you . So, you know , it wasn't much I can do besides or into an online. So , uh , fast forward to my junior year, I finished the rest of my undergrad by including my capstone project, by the end of that , by May, 2021, I finished. And , uh , currently I'm actually the capstone project I did was research based on PowerShell scripting and Hackney computing. I was able to bypass some windows computers at my university to prove the vulnerabilities and they actually got food for the CSC conference, which I'll be attending it. I have to take days off my internship. I attended from July 26 to 2019 Las Vegas. So yeah , that's , uh , that's on the academic side on the industry side. I , uh, as you guys know, I'm currently, I'm an intern at visa. Um , I'm on , I'm on my break right now for my shift, but I'm interning at visa as a associate cyber security engineer. And , uh , what we do is we do a lot of , um , code scanning. We were in a code and vulnerabilities of , um, of , uh , the Risa software. Although if your credit card goes on, please don't blame us. It's probably not our deployment that is causing those vulnerabilities in case you wonder. But yeah , we were , you know , um, vulnerabilities looking over the code and we're currently set to , um , so aquatic where we can broaden Risa security impact and increase awareness and yeah, up to now, I'm , I'm just in this podcast with you and David and , um, we're just, you know , talking about my career path, obviously it's not as long as, or extensive as gauge group path , but it's just , um, uh , basically what you're in a basic , uh , start to work . I'd

Speaker 2 12:14

Say it's a tremendous start. Um, and I , I was also just wanting to mention you, you've been , um, uh , an active participant in our Georgia FinTech academy program. Um, and we've , uh, I was, it's just always been great to have you particularly involved in all our, you know, our weekly student events, because I've appreciated your perspective and you've asked great questions of all these exacts we've had come in. And , um, your passion around cybersecurity , uh, has certainly , uh , come through in meaningful ways. You know what, I think one thing I just, when I, when I talked to you, Andy, that I just get excited about are just the, the amount of just, I think, possibilities and opportunities you're going to have before you , um, as you continue to move forward. I think I just wa I saw an article earlier this week in the wall street journal, noting that there are right now 500,000 cybersecurity job openings in the United States of America. It's like mind boggling on my off by 300,000.

Speaker 4 13:25

It is more jobs than professionals available. Yeah. It's

Speaker 2 13:28

Really something that's really something. Um, well, great. It's great to have you here . Thanks for sharing that. Um, so

Speaker 4 13:36

I want to add something , uh , regarding Debbie academy. I think I , I kinda missed that part, but yeah. Um, the Julia FinTech academy, I started getting interested in it since spring 2020, since COVID has actually, I would say one good point about COVID is that it actually saved me a lot of time on commute and, you know, going back and forth. So what the excessive time I have, I've been getting a lot of emails from the Levita . I was annoyed at photos . I was like, okay, let me I'll find the opening it up. So I opened up the whole email, looked into the meeting. So you Thomas and , uh , all these wonderful people that do their thing, FinTech academy. And I started attending these meetings. That's when I was going to attend these meetings, these career fairs showing up. And , uh , I think , uh , one side of, I did not mention this meeting was I also have an interest in the financial side. I think I bought a buy up before about vibing hood . I was also doing some investing on the side, doing day trading as well, learning the basic sets , um , obviously lost money, but like, you know, don't get too emotional over that. So the jewelry centric academy also broadened my perspective, I think, into the financial side of things, because , uh , during the cybersecurity curriculum at UNG has taught a lot, but it needs to expand a little bit within the financial , uh, financial sectors, because I think one to have common , most common reasons people attack other people's wants because they obviously want financial and economic gain . So the Judah FinTech academy, I think gave me some insight into those perspectives, how companies are operating, how companies have run your businesses and also how companies invest in cyber security . So it was actually, it was actually bridged the gap between the technology and financial side of things. So in my world is allowing me to [inaudible] in between. And, you know, since it's called FinTech, it's kind of like a hybrid between a financial technology sector . And I think it gave me the opportunity to learn more about blockchain and cryptocurrency and a lot of the ramifications of FinTech as a whole.

Speaker 2 15:24

Yeah, no . And , uh , you bring up a really good point about this intersection of financial services as an industry and cybersecurity . It's probably a good segue just to talk some more about feature space. Um, Dave, let me just come back to you and , um, you know, tell us just kind of unpack feature space for us. I mean, it's just really kind of remarkable , um, capability that, that you created and , um, and that you brought to the industry. Uh , tell us more about that and some of the details. Yeah.

Speaker 3 15:55

So I guess the , the centralized , um, product that we have a feature space is what we call , uh , Erik brisk Cub . So it's effectively a platform or a set of software that we provide to financial institutions like banks and credit card , um, credit unions, but also to payment processes like , um , well pay or FIS and TSS that enables them to be able to analyze transactions . So payments and , um, cut credit or debit or prepaid type transactions, but also , um, applications for new financial services , um, products. And so that , I guess one of the fundamental underpinnings of the software is applying machine learning to be able to identify , um, financial risks . So looking at both attempts of fraudsters to be able to commit fraud, but also looking at financial crime and potentially money laundering activity that's taking place within , um , the financial ecosystem. And one of the key differentiators for what we do at feature space is a lot of , um , fraud solutions look at historic patterns of fraud that's taken place in the past. And they're effectively looking to re identify that same pattern, which has taken place, and we effectively swap or reverse that on its head. And we started to say, well, we've got so many good consumers, like 99.9% of all customers are good customers that we want to keep and continue to do business with, but how about we learn their behavior and learn their profiles and make sure that we're operating in the boundaries that are labeled those customers to do what they want to do without the increased friction that you can see from a fraud or security simulation . And I often think back to when we had corner stores and you'd go in and you'd actually get to know the person behind the counter, and they would know you as a customer, right ? How do we translate that into a fraud and security product? And so we, we build that model of being able to understand what each individual customer or consumer looks like, where they like to spend when they like to log on to their online banking and then effectively look for anomalies and changes against that, which allow us to identify new types of fraud and risks. So we are able to identify when is there a significant behavioral change to say, we think that Tustin is potentially at risk. Do we need to start to increase some friction to be able to validate or authenticate that customer to really make sure it's them who's transacting.

Speaker 2 18:26

I think about , um, like there's, there's nothing more annoying and hopefully everybody's maybe experienced this, but only once or twice, but you're , you're somewhere. I guess the typical stories are I'm somewhere, I'm somewhere. I'm not normally, but I'm about to make a significant kind of payment. Um, I present a payment instrument, I guess, typically a credit or debit card and the merchant, either the restaurant or the airline or the, you know, whatever they decline it, but come back to the table and they're like, I'm sorry, Mr. Marlboro . But , uh, we, you see your , your transactions not clearing. And , um, of course I'm good for it. I've got the money in the bank, I've got the I'm in good standing with my credit card company. Um, but , um, th the , the transaction has been declined and it's just, it's, it's a ho and I'm angry. I am super angry and I'm not really angry at the merchant. I'm angry at my card issuing bank, or whoever has put that instrument in my hand. And , uh, and I know , um , you know, having many of these bankers and card issuers as in payment processors, as clients in my consulting work and, you know, knowing people in this industry, they , um, they are not happy about this circumstance either. They're like, I did not want to be making some of my best customers angry or any of my customers angry for that matter , um, in , uh , my efforts to control fraud and financial crime. Um, and I think , uh, and then, then I kind of think of interspecies feature space, enter Eric it's ending and what the, the industry, I guess, for the students, I'll say this, this whole , that whole circumstance. So Tommy's angry because the , the payments gotten declined, that's called a false positive. Um, that means that , um, the, there has been an incorrect analysis of the transaction to what Dave was saying earlier, likely using one of these older antiquated ways of , uh, analyzing the , uh, the risk on the transaction. Um, and they they've made a mistake. They've, they've decided to decline a transaction. That is, that is definitely coming from a customer that is in good standing and is not looking to commit any kind of a problem. And now they've made the , uh , they've made the customer angry , um, and efforts to, to control that risk. So that's that false positive . So, so I , I know, like when I, when I first , um, heard some of your customers, Dave talking about, you know, why they'd taken on feature space, they were like, Tommy , you don't understand. They're like, they're like cutting the number of false positives by like massive numbers. I mean, it's, it's almost like couldn't even believe their eyes , um , when they were talking to him about this. But , um, so I guess, do I, do I have this right? Am I kind of , am I telling this story the right way, Dave?

Speaker 3 21:22

No, exactly. And that's generally ultimately how we're judged is how do we reduce that friction from a genuine customer and take that situation away, where especially if you're impacted and then your trust of that brand and that card starts to go away and that your loyalty to that , um, starts to disappear. So it's not necessarily about the impact of just stopping that single transaction, but the ongoing relationship that you'll have , um , with that, that brand and that institution. And ultimately, that's a lot of the business case for us. It's about how do we either stop or , um , increase the amount of fraud that's taking place. And then at the same time, making sure that that friction is an introduced in, into the journey ,

Speaker 2 22:06

Um, the Eric risk club risk hub, which is a R I C hub, what is a R I C stand for? So it's one of those

Speaker 3 22:18

Like fantastic acronyms that describe what we do. So it stands for , um, adaptive. So where the models are constantly adapting to the type of transactions and fraud that are taking place , um, it's real time. So , um, many of our customers use our technology to make a decision on a payment that's in flight. So if you're using , um , your credit card at like a target or a Kroger, it could be our software, which is making a decision on whether or not that transaction should be processed. Um, and then it's about the individual. So we're not looking at group behavior or looking at the behavior across a customer base. We're looking at individual consumers and credit cards and , and learning how they interact and then ultimately looking for change. So we're looking at when does it behavior change from what we've seen historically taking place as being a lot of the really good information that we use to identify when something's suspicious or is taking place that we need to sort of step in and hopefully apply the friction at the right time to stop the transaction when it truly is. So

Speaker 2 23:27

I've got adaptive real time , individual change. Um , so I want to ask you one thing about real-time and I want to get your reaction to this, Andy. So , um, and this is one thing that I still have a hard time getting my mind around with the feature space solution and what the Eric risk hub offers is the real-time piece, because it's happening really, really, really fast. Right. Um, cause like, Dave, my understanding is that the risk of is intercepting the, the transaction in that like authorization state, which is milliseconds and then making a determination on, you know , whether to slow things down or not , um, in that very, very, very, very narrow window of time. Um, can you talk more about that? And like, I don't, I still like, how do you do this? It's just amazing to me.

Speaker 3 24:27

Um, so I guess it's a lot of very clever software engineers that we've got back , um, in Cambridge that are sort of continuing to refine and build that software. So a lot of it is also then about the efficient use of the data. So for a lot of machine learning systems, it's how do I get the most data that I can and how do I use that to be able to make a decision that's coming through? And usually one of the hardest things in making a fast decision is building through that, that context of sort of what, what are the last five, what are the last 50 transactions that that customer has made? And it's almost accessing that information is the thing that can be the slowest, because you need to go with, reach out into all the databases, pull it back. So for us it's how do we make that data accessible very quickly so that we can look at the new transaction and say, how does it make sense in terms of what we've seen historically that customer do? So we spend a lot of time sort of optimizing that process. And then when we look at sort of a lot of our deployments, as they're running across large infrastructures of , um, like , um, uh , clusters of, of resource to be held to make those decisions really efficiently,

Speaker 2 25:39

Andy, I wanted to kind of bring you into this and just get your reaction to that kind of that. So is this occasion or this functionality just don't based on your perspective and what you've been learning , um, in your , uh, in your studies.

Speaker 4 25:57

Yeah, I was , um, thinking about what , um, they, they would just say about , um, you know, the thought on prevention and I was thinking of , I do have a question for the baby. So I was thinking in what ways have , um, implementation or any updates to the security of the company increased friction in fraud prevention or decreased it? Because I know security can also be a very heavy, a very heavy asset that can also decrease, decrease a decrease convenience, but like sometimes you have to give up convenience in order to make sure you won't say so. I just want to, I was just wondering in what ways has the implementation of security , uh, created or reduced friction and fraud prevention?

Speaker 3 26:41

So I guess often where like our ultimate is to, I guess, reduce the friction when it's not required, because that always impacts the customer journey , um, and what they're doing. But I think there's a really interesting story with one of the customers that we started working with in the UK. Um, and they, they were , uh , an online merchant. So they were essentially allowing transactions to take place online and something that's predominantly in the UK that we may, and we'll see the rollout of it in the U S is a technology called 3d secure. So that's where you're looking to authenticate the customer prior to an like a card authorization actually taking place. So it's a step where after you've entered your credit card details in that online form, it will come back to come back with , uh, entering in a secondary password or a one-time , um, code that's sent by SMS. And so that's used to try to authenticate to say, well, we've got the car details, but do we actually know as the right person that's entering that data? And one of the things that we started to do with our organization was , well, when we started to know and trust the customers , we go, well, we don't need to authenticate them because we trust them. So we can sort of bypass that friction into the journey. But we had sort of through that process there , the safety mechanism of seeing that authentication, made those customers feel secure in the transaction that was taking place. So as we started to reduce the friction and not needing to do that prompt all the time, there was some feedback from customers that were feeling like they weren't as secure in that transaction when that security , um, prompt was started to be reduced from their journey. So there's always an interesting trade off , especially when you're teaching consumers about a specific way in which they can authenticate or make a transaction in the payment . Like

Speaker 4 28:33

That sounds very interesting, you know , I'm currently processing it. So why are you talking about our customers there ? I also had a question that popped into my head. So , um, especially with COVID moving everything online and increasing new cyber attacks, those zero day attacks and stuff. Uh , so I was thinking of with all these new attacks coming , uh, here and there , um, and everybody working from home and, and experiencing different issues. How have you adopted strategies to mitigate , um, unwise customer behavior change in case a customer kind of like , uh, acts against the intended decision? How have you adopted strategies to mitigate those behaviors?

Speaker 3 29:09

So I guess we had , um, and we've got a report that we can , um , share as well that we published with TCIs where we looked at , um, how our score changed during the onset of the lockdowns around , um, COVID and I guess, going back to the original sort of the acronym, Eric , the first bit about adaptive is that we were able to show through that process within a week of all the lockdowns taking place, the model that had effectively recovered and relearn all of the new behavior of the consumers to be effective as it was before. So it got back to the same level of detection of fraud by looking at that massive shift that we saw from by card-present transactions to card, not present transactions, the shift away from restaurants to groceries, all of those types of things were taken into to fact to be able to make that , um, sort of adjustment in terms of the behavior that was taking place. And I think in terms of when we're looking at like training, the models is you always need to look at the data quality that's coming in and not always saying well , when I do see a transaction, which is marked as fraudulent, it's not always guaranteed that that's a hundred percent true. So a good example is potentially looking at something like first party fraud, where it's actually really the consumer, which is making the transaction, they're just dispute. They potentially claiming that it didn't arrive when it did. So you need to sort of factor those types of things into , so of say, how do I get more and more confidence that a particular attack truly is fraudulent versus it could be the consumer that's being fraudulent rather than the, like the card details or the password being compromised , um , in the same way.

Speaker 4 30:50

So , so interesting. And , uh , I think , uh , speaking of , um, fraudulence and false positives, oh, we're going to people on your team, have you guys also looked into strategies to have , um , engineers check over false positives to verify them all , and also have you guys considered automating those false positives and trying to get verified them because we can only do it on our team . So I think that was a little bit related at all to what we do.

Speaker 3 31:15

Yeah. So typically a lot of financial institutions will have fraud operations teams and that that's, that's what they'll do is they'll be looking at those , um, false positives and there'll be often, it will be the customer phoning up going, why did my transaction get blocked? It was really me. So that's where we get a lot of that data that comes back. And again, being adaptive is that information feed straight back into the platform. So it continues to learn from that information effectively in real time, sort of updating the statistics and being able to react and respond to those new data elements that we're able to process. Yeah ,

Speaker 2 31:50

I think what's also just worth mentioning is that , um, as, as Eric, I mean, we've been talking a lot about card present card, not present payments, but , um, my sense to our guests just observing it feature space and how you've evolved the company. Um, Dave, you got Eric kind of continuing getting continuing to evolve to point at different use cases, whether it's, and in money laundering, the merchant acquiring side of fraud, like we got , um, you know, these, a lot of these players that are looking to add new merchants as, as the, as their acquirers. And that has often been a kind of heavily manual, slow , um, risk born process. That's been getting more and more and more automated. Um, I noticed you'd added a gaming as a, as a folk is an kind of area to that. Eric can address. Um, can you just kind of just talk briefly about how that , um, how you've continued to expand , um, where Eric can , um, can help add value? Definitely.

Speaker 3 32:53

And I guess I always liked to solve new problems. So we're always looking at different ways in which we can apply the technology. And so it's really like in areas where we can build a profile and understanding that consumer behavior and looking at different ways in which that can be applied. So, and also part of the mission that we have at feature space is to look at like financial crime across the world, and ultimately to look to risk score , uh , every transaction in the world so that we can provide that protection to the financial industry. And so it's looking at well, where are all the different places where decisions get made about those transactions? So often that example that you had earlier, tell me about the transaction being blocked is it may not be the card issue. It could be someone upstream of that transaction. So it could be the merchant or the merchant acquirer, which is also running their own fraud strategies and making a determination that they don't want to process the transaction because there's potentially fraud at that , that point. And also fraudsters operate all over the place. So sometimes there may be fraudsters that are registering and creating new merchants to be able to process stolen credit card data through that. And I could think another really interesting aspect is the , um, I guess the real-time payments ecosystem, which is continuing to build out. Um, we've seen that be very successful in the UK. Um , looking at Zelle here in the U S and , um, then as the fed now is looking at their new RTP platform, those create really new, interesting areas of being able to apply , um, the article . Yeah, that's a great

Speaker 2 34:28

Point. In fact, we had , um, the clearing house came in and spent , uh , did a session with students , um, uh, back in January. And , um, it was a good intro to that just as a Mac on a massive emerging area payments real-time payments , um, in , uh, and how that , um, is, is taking greater shape, the adoption's improving. Um, and , uh , but I could definitely see how there'd be a lot of new opportunities to , um, to address , um, from a future state standpoint. Um, well, these conversations always go faster than I would like. Um, we're , we're starting to near the end of our time. And , uh, as our listeners know, we like to end cap with , uh , just a FinTech news. That's caught our collective attention in the last week. Um, so Dave, I'll let you start any kind of news items that , uh, you'd like to bring to the listeners attention. Yeah. There were

Speaker 3 35:27

A few that I was really sort of excited about looking at investment or , um , there's been made in some of the emerging markets into creating new fintechs, like especially unfair money in Nigeria is they're effectively similar to the Eric risk hub , but for a financial hub of looking to provide different financial services in Nigeria and also India where they've expanded into. So I think looking at providing digital banking services to those consumers that don't have access to banking technologies is really exciting and looking forward to see how they continue to expand. And I think in the article that I read is they brought 150 open positions at the moment. So definitely something that the high growth rate , um , for that organization.

Speaker 2 36:12

Yeah. I'm , I'm glad you brought that up. That, that just that whole FinTech ecosystem in Nigeria has been exciting to watch. We, and we have a lot of , um, first-generation Nigerian , uh , students that have been bobbing getting involved with FinTech academy and they've really helped kind of edgy . They educated me a lot , um, on the space and we've been starting to pay a bit more attention , um, to particularly , um, that part of Africa and how things were evolving. Um, so , um, you know, thanks for bringing that up, Andy . Um , how about you?

Speaker 4 36:47

Uh, I think I've mentioned , um , a lot of things happening between the two, two countries. I won't discuss too much now, but it has been impacting on the stock . So the stocks I've been taking a hit, especially companies with strong investments , um, in China has been taking. Yeah , I do want to mention , um, yeah, a lot of things going on within my company. So as we're dealing with some of my former companies, your Amazon, have you guys heard a transition , um, and investor confidence in that company has been , uh , has remained pretty steady though. Um, uh , especially with visa scanning gives a crown to your Andy Jassy new CEO of Amazon. And , um, yeah. Also know a lot of, a lot of things they've been doing , uh , in , uh , over the past , uh , basketball weeks. They approached us to AMC, which , um, yeah , I think, I think, I think the approach was AMC . I don't know . Is it, or is it a different movie studio? Yeah . Yeah. Amazon protester . I think a movie studio. I'm not sure it's AMC or if it's a ,

Speaker 3 37:44

Um , with the , um, the bond series, which was the crown jewel of that , uh, at that maybe studio

Speaker 4 37:49

That's right. And I know for sure that their sales last quarter, we had a surge to 44% , um, yeah, a lot of prophets out chip Watson . Uh , you can't miss it . You're actually expected to make, you know, I think 40% of the e-comm sales by the end of this year, a lot of , um , a lot of things going on with big tech and a B-cells is focused on blistering growth of these folks . Cause , uh , I think in the past, when I worked at Amazon in 2019, there are 14 new shift principles and you just add it to a plump. And , um, I think right now there are focused is more on corporate responsibility after , um , Bezos the POC or has focused on listening. And speaking of that , um , yeah , at visa , we also focused on now we'll focus on expanding the reason across the world. And recently you've guys have heard, we've been partnering with the genome, jd.com, large e-commerce giant in China. So like Amazon, eBay , China , um , we've been pointing to Goldman Sachs and we've been trying to introduce new products who we'll do the Risa that's . So you're a lot of things going on in our organization and this has impacted the yeah. Go on.

Speaker 2 38:55

No, I'm glad you brought that up. We , I think we mentioned in last week's show that visa had announced they were going to acquire a tank in , um, Europe, which is , uh , I guess in my simple mind it's plaid, but it's in Europe. Uh , so I guess I'm very curious to see how that goes. I mean, obviously visa attempted to acquire plat and then the deal blew up after like, I don't know , almost a year , um, the , uh, department of , um , trade wouldn't, you know, wouldn't approve the deal. So , um , I'm curious to see how that comes about. Um, I guess from my side back on FinTech, just to two kind of key items, one is that , um, Ys , uh , successfully completed their IPO yesterday , um, at a round at 10, 12, $12 billion valuation , um, wise I know as TransferWise , it was, they changed their name, kind of like we were right before the IPO. I still, it still catches me by surprise when I see it, but like kind of a legendary FinTech company, decade old, just really tremendous success story out of the UK has expanded globally, just really a tremendous accomplishment for that team. Um, and then , uh , a crowd favorite at the Georgia FinTech academy and most of the students anyway, Robin hood , um, they , uh, announced in the past week that they will do their initial public offering. Soon. The date hasn't been set , um, there, this has been anticipated. They had to , um, kind of clear some regulatory fines before they could , um, they could successfully , um, list , um, and they took care of, I think it was one of the largest fines in the history of FINRA. Uh , they, Robin hood had to pay. So they have that, you know, I guess go on for him . Maybe I don't, I'm not a huge fan of Robin hood. I know [inaudible]

Speaker 4 40:48

Is fine in FinTech history. I still think it's Alibaba, the 2 billion fine. Yeah .

Speaker 2 40:54

And , uh, there was , uh, just to add onto the federal fine. Um, the , uh , Robin hood got fined again and they just paid that I think $10 million fine yesterday that was crypto related. It had to deal with how they'd handled some of the crypto transactions on their platform. But , um, I guess the other, the last interesting thing on Robin hood, and this is very unusual is they reserved 35% of the shares that will be listed for Robin hood customers, which means that, you know, Robin hood customers will get an allocation that they can buy at the, whatever the IPO list price is, which is , um, kind of a reward in some ways, I suppose, for existing customers, but I'm unusual move in in that regard. So, but that'll be exciting to watch and see how that unfolds. Well , um , Dave, Andy, just thanks so much for doing this really appreciate you having you on the podcast this week. You are always welcome at the Georgia FinTech academy. Um, hope to see you both , uh , again soon and just thanks for all your contributions. Thanks.

Speaker 1 42:01

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