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The MoneyPot LIVE: Combating Fraud Through Cross-Sector Collaboration and Shared Intelligence with GBG
In this episode, we dive into the alarming rise of digital identity fraud, which cost the UK finance industry over £1.2 billion in 2022 alone. Our guest, Laura Barrowcliff, Global Head of GBG Trust at GBG, a leading expert in digital identity, shares her insights on how cross-sector collaboration and shared consumer intelligence can transform customer due diligence and help financial organizations fight back against fraudsters.
Laura dispels the misconception that data sharing erodes competitive edge or breaches privacy regulations, explaining the difference between sharing data and sharing intelligence. She discusses GBG Trust Network, a unique data network that combines over 100 million data attributes contributed by a consortium of over 550 businesses across 25 sectors and 80 countries, while ensuring complete data privacy.
Discover how GBG Trust Network's global intelligence footprint and local expertise enable businesses to securely leverage powerful cross-sector consumer insights to detect fraud, onboard more good customers, and pre-empt crime before it happens. Laura also shares her perspective on getting ahead of regulation and influencing policy through action, setting the pace and creating a framework that works for the industry.
Whether you're in the finance industry or any other sector grappling with identity fraud, this episode offers invaluable insights on the power of cross-sector collaboration and shared intelligence in combating this pervasive threat.
The MoneyPot is our podcast from Money20/20. Ian Horne & Rachel Morrissey Co-host
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Hello everyone and welcome to the Money Pot. This is a special episode recorded live from Money 2020, amsterdam 2024. And, as you can tell, I'm energetic. I'm happy the show. We're on day three right now. The weather is mediocre, but the show has been excellent, so I'm in good spirits. I'm joined today by co-host rachel morrissey the ever-present and wonderful rachel morrissey, how are you doing today?
Rachel Morrissey:I'm uh, you know, I just got finished with my, my one on the main stage and now that that pressure is over and my knees have knocked together, I am doing well. I much prefer this main stage.
Ian Horne:It's got a ring there you go. Yeah, I'm bringing stage morrissey, but yeah, no, I kind of.
Rachel Morrissey:I came here, I recorded one yesterday, having come from the main stage, and I I'm bringing stage. Morrissey, it's got a ring to it. There you go. Yeah, I'm bringing stage.
Ian Horne:Morrissey? Yeah, no, I came here. I recorded one yesterday, having come from the main stage, and I think my adrenaline levels were still through the roof. I know my intro to it had energy, at least it felt like it did. I don't know. I'm sure it did Rach. We could go on combating fraud through cross-sector collaboration and shared intelligence. Now that is quite the topic, and we've got Laura Barracliff joining us to talk about it.
Laura Barrowcliff:So, laura, welcome to the Money Pop. Thank you very much. Yeah, thank you Really glad to be here, and similar to you, rachel, I did a panel session yesterday. It's that pressure, isn't it, and you kind of build yourself up and then afterwards you breathe.
Rachel Morrissey:I can relax now. You take a couple of deep breaths, get all that extra oxygen and all this and your adrenaline levels are like through the roof. You come up and you're like ugh.
Ian Horne:Oh, it's mad, isn't it? It's actually mad, and you were moderating, right, Laura? Yes, I was moderating.
Laura Barrowcliff:So I was in a kind of easiest seat. I thought no, moderating is hard. I was just moderating, I think moderating is hardest. I quite enjoyed it. Actually I'm going to take the badge of moderating is hardest.
Rachel Morrissey:I enjoyed it.
Ian Horne:Right, so let's get into fraud.
Rachel Morrissey:Yeah, let's talk about this, let's talk some fraud.
Ian Horne:Okay so fraud, this is a UK one, Rachel, but you'll be fine, it's a familiar theme we.
Rachel Morrissey:Well, fraud is a big, fat, lovely industry into itself, right? Like a $2 trillion industry. Absolutely, criminals are good. They're making a lot of money. It does pay until it doesn't pay.
Ian Horne:You just absolutely USA'd us there by saying trillion, because I was going to say digital identity fraud costs the UK finance industry over $1.2 billion in 2022 alone. And now we feel really small, fry.
Rachel Morrissey:No, no, no. Globally, it's trillion, it's globally, but it's a global problem as well.
Laura Barrowcliff:So you know we uh, we've put a uk figure in there, but actually gbg is a global company, so we see this across the board. You know, in the us, um, massive, um synthetic identity problems in australia for massive problem with scams actually less of a problem with synthetic IDs but more of a problem with scams and data breaches. So fraud is absolutely a global problem and it's not, you know, country specific. It is a problem absolutely in the UK and something we need to solve, but it's a problem everywhere.
Rachel Morrissey:Yeah, I mean, I've been. I was looking at this last year because we did the fraud summit and you guys have done a summit here that deals with a lot of the issues around fraud, and one of the things that came very clear to me is that fraud is a business and the fraudsters take it very like. They treat it just like it's a business.
Laura Barrowcliff:They're professional criminals. Absolutely, it's industrialized, so you can still get your opportunistic fraudsters, you know you still get people just trying to chance it, but it's a business in itself and actually that is increasingly worse. As you know, technology advances, um, you know they could, they can essentially do it in volume, at scale. You know, essentially it is absolutely a business in itself.
Rachel Morrissey:You're making it sound great all the things we would celebrate if it were a pro if it's like at scale, they can do it in volume if it wasn't illegal.
Laura Barrowcliff:It's a great business we'll do hyper personalized fraud 2020.
Ian Horne:This is the fraud part it's a great business.
Laura Barrowcliff:That's it. We'll do hyper-personalized fraud at Fraud 2020. This is the fraud part. It's been a pleasure Seriously.
Ian Horne:Anyway, digital identity fraud is massive. Oh yeah, obviously, laura, you're here to talk about it. You're an expert in it. What are the current trends that you're seeing in this? I'm still talking about it like it's a really cool thing. Oh yeah.
Laura Barrowcliff:What people doing? What should we worry about? I mean, as we said, it's, it's um absolutely increasing at scale, um, you know, ai, I think, gets a lot of bad press and and ai does increase the risk of fraud. You know, we've all seen videos of deep fakes this year. We've all seen um deep fakes going into the various elections, going on um, which is scary. But also ai is an opportunity, I think, from a fraud detection perspective and we can get into that maybe a bit later on. But in terms of some of the trends, I think synthetic ID is absolutely an issue and we see actually an identity stolen every 22 seconds at the moment is something we look at also, which is pretty scary, isn't it? Every 22 seconds.
Rachel Morrissey:Three a minute, yeah, as we're speaking here, but you know, identities are being stolen. 90 identities will be stolen as we have this podcast.
Laura Barrowcliff:Yeah, good maths, good maths I'm glad you did that. But actually about 85% of synthetic identity goes undetected. So if you think about that from a business perspective, but also from a consumer perspective as well, um, you know, it's actually really really scary in that. Um, you know, we've got some statistics of how often identities are stolen, but actually a lot of that goes undetected. So there's a lot of unknown, for that is happening as well you.
Rachel Morrissey:You know it's interesting. Yesterday we were having a podcast with a guy from the London Stock Exchange and we were talking about reusable digital identities and one of the things that was clear we mentioned Adhar, because Adhar was sort of this revolution in digital identity and he said within the first year there were over I think he said like 200,000 false digital identities created in AdHart. So like, yes, it was and yes, it did, but there was also this loophole or this kind of gap where things got created that are not real but act real yeah.
Rachel Morrissey:And I thought that makes this problem. You're like, okay, we thought we had solved something here and now we've got a new problem. It's whack-a-mole you know, it's really.
Laura Barrowcliff:You know, absolutely. You know reusable identity makes it easier for the consumer. You can own your own identity, all of that but fraudsters just find a new way of stealing identity credentials. You know so. It's absolutely not a you know, I know this is a bit of a bingo phrase, but absolutely not a silver bullet in terms of the digital identity piece. Actually, what you need is intelligence around fraud on top of the digital identity piece as well, because it's forever changing. It's real time. Fraud is real time, so you need to time, so you can't just stick with an identity and then expect that to stay the same. It's absolutely happening.
Rachel Morrissey:Well, I'm just glad you said it, because I really needed to fill out that bingo card.
Ian Horne:Yeah, but with an identity as well we're seeing people put everything in one place and that almost sounds kind of scary, because if someone can steal one thing they can notionally access everything. Obviously, some of the biggest sessions we've had at the show this year have been about the Open Wallet Foundation or about the EUDI. Like what do these initiatives need to get right? Like what are the big concerns here?
Laura Barrowcliff:Yeah, they need to get right the kind of multilayered approach to this, because digital identity is not a thing in itself. It needs to go hand in hand with fraud prevention as well. So it's around adding multiple layers of intelligence, I would say, is that we work with 20,000 customers across the globe and we say don't just look at this with a one-size-fits-all approach and don't just take one single solution to do this. Actually, you need to add multiple layers to to your digital identity and your forward um prevention, um technology. So it's um adding multiple layers in it's. It's actually sharing and collaboration.
Laura Barrowcliff:You know we talked uh in the subject heading around um collaboration, actually a lot of um, especially in the finance sector. I would say a lot of people are scared of sharing data with other companies and and quite rightly so, in in terms of from a privacy perspective. You know, I think everybody's worried about oh, what can I do with this data? What can't I do? But actually, if we're sharing intelligence rather than data, you can really learn from each other, you know, of how to detect that fraud and how to prevent fraud.
Rachel Morrissey:You know, that's interesting because I sort of understand why they are reticent to share data. I mean, first of all, there's been a. I mean I'm still in the dark ages. The UK is a little bit ahead with the open banking laws that they have and the way that they have data sharing according to customer wants. We're approaching it. But the thing that I find interesting about that is, you know, there's a fight about who owns the data and even within banks there's silos of data where they don't share with each other, and some of that is a compliance right. So there's a thing. So sharing intelligence versus data is a very interesting juxtaposition. So how would you define intelligence versus data is a very interesting juxtaposition. So how would you define intelligence versus data?
Laura Barrowcliff:Really, it's about looking at the insight that you can gain off the data. So, for example, we provide customers back with a trust score. So we would give a transaction a score based on all of the data that we see in the background, but we don't share that data back with the individual or the customer. It's really about sharing the score and it's around sharing some of the behaviours that we've seen with that data. So that's what we would say is intelligence or insight, rather than sharing data back in the clear. So what we're really looking at is how that data behaves within our identity network.
Laura Barrowcliff:So we're looking at do we see any anomalies there? Do we see any combinations of data that don't look quite right or that do look right actually to identify good customers as well, and we apply a score to that so we can say, yeah, this looks like a pretty good customer or actually, no, you might want to take another look at this customer or you might want to actually prevent them. And one piece actually around the the intelligence as well is using that before you even onboard customers, so where, if you think about um as a consumer, you're going through that process of um getting on board with a bank or opening a new account somewhere. You really have to go, go through many loops and hoops to get through that from a from an identity perspective, and that can cause a lot of friction for good consumers. But actually if you do some of this preemptive intelligence at the front door, you're not necessarily then adding that friction to the process of getting customers on board.
Laura Barrowcliff:So, it's better from a consumer perspective as well.
Ian Horne:I want to jump in on something that Rachel can introduce just there. Um, which is of that collaboration piece and rachel's right, people understandably don't share data, but when you're having conversations with people, what reasons do they actually give you and do you think there is an effective workaround to that where you can get people to be, you know, drop their guard and and share data proactively?
Laura Barrowcliff:yeah, absolutely. So some of the um, the kind of pushback that you might get, is like from a privacy perspective, I think people are worried about what they can and can't do in terms of sharing their customers' data. The other piece, and also from a consumer perspective, you worry obviously about sharing your data, but most of our data is out there anyway. As we talked about, that, fraud is an industry. Most of our data is out there anyway. As we talked about, that, fraud is an industry. Most of our data is available on the dark web. So actually it's about making sure that you're working with somebody who has gone through all of the kind of privacy processes which you know.
Laura Barrowcliff:We're absolutely, really stringent from a privacy perspective. So making sure the solution you're using is privacy by design. So making sure the solution you're using is privacy by design and that can really help alleviate some of those the reasons that people give around sharing data for privacy reasons, also competitive reasons as well. So, for example, we have some customers that don't necessarily want to share their bad customer you know, their bad customers with with their competitors because they're like actually we want them to get the bad customers. So if they get them, we don't. Yeah, yeah.
Rachel Morrissey:So there is a bit of that kind of a little bit like I don't have to outrun the bear, I only have to outrun you.
Laura Barrowcliff:Yeah, yeah but but everybody's trying to solve the fraud problem, so it's like come on, guys, you know um, grow up and share.
Rachel Morrissey:Well, from a consumer perspective, I mean, obviously it's hard to say, but maybe we're a little bit more sophisticated consumers now because we have so much knowledge about this. We talk about privacy and and it's just sort of ephemeral at this point, Like I mean, some of us are like oh, they have everything just to prove the damn cookies, and who gives?
Rachel Morrissey:a crap, I mean at this point you sort of feel like you're out there, and I'm not sure that's always a good thing. There is something about wanting to pull back on that that I understand.
Rachel Morrissey:But what I think is funny about the competitive one is they would really all benefit from sharing, because if you're talking about preventing onboarding a bad customer or a fraudulent customer right, it's not a really not a real customer Then if you are sharing the insights and you're sharing the data that's feeding that insights and you're seeing patterns at a greater point, then you're preventing it for you too. Like there's a lot more sensibility around sharing, but I think that I think collaboration is hard when you are in a competitive environment.
Laura Barrowcliff:Oh yeah, yeah, but I think people are adopting that even more so now. So if I just give you an example, actually we've seen um a guy that we lovingly refer to as mr c in our network um who has so lovingly?
Laura Barrowcliff:referred to as mr c. So over the last 12 months we've been tracking this guy and we've seen him apply um over 5 000 times now to multiple organizations 23 different organizations that are in our network um that mr c is trying to defraud. So we've then been able to tell some of our customers of those 23 different organizations of like look, this guy is is attacking you. He's also attacking companies over here um. Again, we never, never give the names of the different organizations that are using the network, but it's like actually we can see this across different sectors. So we've talked about the finance sector here, but Mr C is targeting gambling companies, he's targeting retailers, he's targeting financial services companies. So, like you say, it's really about it's going to benefit them as well as you, others in in in the network as well, if they just share some of that intelligence.
Laura Barrowcliff:And actually the funny thing, as you mentioned, rachel, is within organizations data is siloed, but we have many customers who have bought, you know, they've acquired other organizations, so they've actually got multiple brands under their banner and again they're using different processes. They're keeping their own data to themselves, but we can see mr c across these different brands. So you know that I think people are really starting to adopt this approach now and can see the the sensible approach around. You know collaborating and sharing some insight, and I now want to mr c comic strip I want to see the adventures of Mr C the fraudster.
Rachel Morrissey:And also he sounds really energetic.
Ian Horne:Yeah, who's?
Rachel Morrissey:got time.
Laura Barrowcliff:Who's got time to do that? Yeah, this guy's legit.
Rachel Morrissey:He's going on one of our summits. I'm talking to him this week, seriously.
Ian Horne:One thing I actually want to look at here is obviously collaborating is how we can get stronger as an industry to protect against fraud. But what competitive advantages do we have over fraudsters? Because you say they're sophisticated every time we create something new, they create a new approach. Yeah, ai, ai is great. All of a sudden, ai is good for fraud. Yeah, biometrics are cool. All of a sudden, we find ways to do deep fakes and so on. So, like, do we literally just have first mover advantage, or is there some other thing that we've got going for us?
Laura Barrowcliff:yeah, no, I think it's. It is about um, it's about finding those holes within the processes. I think it's it's. You may never get ahead of fraudsters, but I think being able to again, you know, work together across different organizations and across different sectors, to to identify um, because some, some fraudsters will be stupid as well, so to identify some of the things that you know they're doing wrong. Or to identify um, because some, some fraudsters will be stupid as well, so to identify some of the things that you know they're doing wrong. Or to identify some of the holes in their processes, and just trying to get ahead of them, really. But um, but yeah, it's, it's a cat and mouse game.
Rachel Morrissey:I even think there's actually an aphorism right there. I think nothing, uh, is makes it so easy to catch a criminal. Is them being stupid? Yeah, I love that, but that's so. So, as you're talking about barriers to collaboration, what are you finding when people do collaborate? Like what are you finding them finding for themselves?
Laura Barrowcliff:Yeah. So I think they're really surprised in the results that they see. Yeah, it's. It's like we do some um studies on our customers data and show them some results and they're like we didn't even know we had this, this problem. You know we we found some um, some results from. You know we might analyze a month's worth of data and find in one of our customers' cases we found over 6,000 records that were suspicious for them to then go on and investigate within a month. So they're really surprised at some of those results.
Laura Barrowcliff:And what we see as well is actually again highlighting some of the holes that they have in their processes. So, for example, companies are using one-time passcodes, thinking that they are, you know, taking a box, a security box, and actually that's secure, but actually we see fraudsters really intercepting those one-time passcodes straight away. And we deployed a new rule recently within our network and within four hours we saw multiple matches to these disposable mobile numbers that people go on and register online and just use for one-time passcodes. Again, we were able to highlight that to some of our customers and they're like, whoa, we didn't really know we had this issue. So I think that's the positive piece that our customers are seeing is actually the benefit of, of that collaboration um, so it's really seen in in the results that's terrifying.
Rachel Morrissey:I'm sorry, I just. I just realized how many times on my phone I get a one-time answer like oh god okay, yeah, I guess for businesses.
Ian Horne:What are the main vulnerabilities?
Rachel Morrissey:that people have right now because I feel like this.
Ian Horne:Let's say it constantly evolves. As you say, individual people within a company could be a weak point. It could be human behavior. That's a problem. It could be something else. But what are the biggest risks that we've got, that perhaps are new, that people aren't savvy to?
Laura Barrowcliff:I think it is around the um, because I think businesses have tended to concentrate on what they need to do for regulatory reasons or for, you know, to tick the compliance box at that onboarding stage of the customer journey. But actually they're really vulnerable at that onboarding stage. So I think it's thinking about how do you block that at the front door, you know, how do you really put that in place to preempt the crime that's going to happen further down the line? So I think that, that's, you know, maybe, some of the vulnerabilities. And then, as we've talked about, there are obviously new technologies, there's AI, there's generative AI that you have to worry about. But I just think it's really making sure, from the business's perspective, that they're working with a vendor who is keeping on top of some of those fraud complexities that are arising.
Rachel Morrissey:That makes me laugh in a way, because it's we're working with this juxtaposition right. One thing, they're being very pressured to make onboarding more frictionless, and then, on the other side, that is where they are most vulnerable.
Laura Barrowcliff:Yeah.
Ian Horne:Right.
Rachel Morrissey:And those two things are in conflict, because a little friction might decrease the vulnerability Definitely.
Laura Barrowcliff:Yeah.
Rachel Morrissey:And so how do you? What do you think the balance is? What would you tell your customers about the balance?
Laura Barrowcliff:it's a really tricky balance, actually, because you have so, for example, we speak to fraud and compliance teams and they're saying we need to put friction in this process, we need to make sure we send them down this route and do some knowledge-based authentication, and all of that. Bicycle wheels oh yeah, I'm kidding.
Rachel Morrissey:I hate the bicycle wheels. I'm like I don't know, I can't even see it anymore.
Laura Barrowcliff:So yeah, the kind of you know from that perspective. But then you see the marketing team saying hang on a minute, we need to get more customers on board, we need to.
Ian Horne:Or the customer experience team saying we need to make this customer journey really seamless we want it to be, you know, biometric led and all of that.
Laura Barrowcliff:So it's really difficult to get that balance, um, but I would say, you know, back to that kind of multi-layered approach is, if you have to do, for example, document verification and a selfie at the beginning, that is quite a lot of friction for a customer to experience. It's just making sure you're you're balancing that risk with what you're actually, um, you know, going to lose if you don't do that. So I think it's making sure you um add, um the the things that you need to do from a regulatory perspective, but also add that intelligence that we've talked about at the beginning so you can do that kind of seamless stuff in the background without putting too much friction into the customer journey the selfie thing seems almost like a generational one.
Rachel Morrissey:Like you're asking me to do a selfie, I would be like I don't want to do a selfie, but if you're asking gen c to do something, they're like I do one every five minutes why, not like I wouldn't have any any friction there for them. And I almost wonder about that being a generational friction.
Laura Barrowcliff:Oh yeah, well, you think about, like I think about my mom and dad, for example. You know they would find that really difficult to do. A… Do you get a duck face or not, sorry. So you know it is thinking about what works and you know the inclusion side of things as well, making sure you know your processes can be led by, you know, people with disabilities or people that are not used to doing that kind of technology process as well. So I think it's making sure you're plugging in again those multi-layered, you know insights at the beginning of that onboarding stage to make that as seamless as possible. It's also good to prioritize your good customers using that insight as well. So actually, if you see that this is a really good customer, we've been able to collaborate and see from other sectors and from other companies that actually they use their data really well, their identity score is really well, that they're really trusted, then you don't have to put that friction in the process. So it's just thinking about.
Rachel Morrissey:That's interesting, the idea that the collaboration could actually feed one another's information about how to onboard so that you can decide who gets a little more friction and who doesn't. Oh yeah that's it. That's a really personalized UX. Actually.
Laura Barrowcliff:It's thinking about good customers and bad customers. You know it's not just about stopping the fraudsters. It's thinking about good customers and bad customers. You know, it's not just about stopping the fraudsters. It's actually thinking about your good customers. Why should good customers lose out because you're trying to stop the fraudsters?
Ian Horne:Yeah, but how can you spot a bad customer? Because obviously you know Mr C is not even trying anymore to hide what he's doing.
Laura Barrowcliff:You know all day, every day, he is frauding and he frauds hard and that's great and he's having a good time. But yeah.
Ian Horne:Is there a way to spot someone early, before they've done their like 900th fraud?
Laura Barrowcliff:yeah, yeah, oh, absolutely. So it's looking for um and and that's. You know, we see these behaviors time and time again within the network, so we're experts in being able to identify this. So you can see it before it gets to the 900th time. You know we can see this a few times in.
Laura Barrowcliff:So it's looking at the um, the velocity of the transaction. So it's looking at the velocity of the transaction. So it's looking at the amount of time somebody is trying to come through. It's looking at anomalies within the data. So our lovely Mr C very often changes around his full name and his middle name, for example, or just changes his date of birth slightly. So it's looking for those anomalies within the data and looking for things like so using data, like mobile numbers that usually people would only have one or two or three of, maybe um, you know that then link different data types together. So it's using those data types to then link it to an address or link it to a name that you then see switching around within the network. So it's spotting some of those behaviors.
Ian Horne:Essentially that that don't look quite right yeah, and, and I guess we're seeing the evolution of technology here. We keep talking about, you know, hyper personalization. We keep talking about seamless transactions all that kind of stuff.
Ian Horne:Um, and it makes me think which customer you know market we're going for. Obviously, the new kind of propositions we have. I think when you look at, uh, embedded finance, open banking, all that stuff, I see the mass market opportunities. All this technology we're seeing on fraud does that create a mass market vulnerability? All this kind of AI tools that we've got now, does it mean that more people can be defrauded more quickly?
Laura Barrowcliff:It does, but it's also, as I said at the beginning, it's also an opportunity. So it's an opportunity for the financial services industry. It's an opportunity for people like GBG, so there's obviously other suppliers out there that provide for prevention and identity verification. We use AI to be able to tackle those fraudsters as well, so it's an opportunity as well as a threat.
Ian Horne:Right, I want Rachel to get the last question, but I'm going to ask one first, which is I'm sorry, I can't lose this concept of fraud 2020. I'm thinking of alternative careers for myself. I think fraud 2020 could be the one.
Laura Barrowcliff:Mr H, I just exactly, exactly, I can do that, six or 7,000 a day.
Rachel Morrissey:maybe it could be your side hustle.
Laura Barrowcliff:It could be and no one ever needs to know.
Ian Horne:But you know if I'm if I'm booking the content agenda for fraud 2020,. I want to get some tips. What topics am I booking?
Laura Barrowcliff:um, you're booking ai. I know it sounds uh kind of obvious but it's so cliche. Um, I think it's um looking at um, you know how. You know reusable identity is an interesting one as well. It it's like how you know how some of the what look like those solutions to reusable identity actually are, you know, have some of the holes, as you mentioned before, rachel. I think it's maybe regional and country differences as well is an interesting one Great.
Ian Horne:every nation gets a stand.
Laura Barrowcliff:Every nation gets a stand. You know, I can see all the flags now in for 2020. But it's thinking about again learning from other countries of what they're seeing, because there's different problems within different countries, different data availability, different regulations, et cetera. So I think maybe they would be some of the topics Love that.
Rachel Morrissey:I just realized that it would be a really interesting cultural study to just look at what fraud is popular where.
Ian Horne:Actually, I'd be fascinated.
Rachel Morrissey:It would be fascinating just to look at all the geographies and say what fraud is working within what cultures.
Laura Barrowcliff:I mean.
Rachel Morrissey:I'm not sure we should collect that, because if we form the fraudsters, oh go, do that there. That's a good idea, but it would be really interesting to know what you're more vulnerable to because of the cultures that you're raised in.
Laura Barrowcliff:Yeah, absolutely, and it depends. You know, like I said, data availability varies. So, for example, we see in the Middle East that people don't celebrate their birthdays. They usually put it as the first of the month. So you know, that's again a vulnerability that companies who operate in the middle east really need to think about, because something that we see is quite unique it's not unique in the middle east, so it's like thinking about other ways to then find that uniqueness.
Rachel Morrissey:You know nobody they don't have. Everybody shares a birthday. Like there's so many shared birthdays, that would never have occurred to me. Yeah, I'm way too western, oh, oh my. God, I'm just dumb American, that is. I just fell right into that.
Ian Horne:Okay, it's all right, I'm a British person who's been mispronouncing everyone's name for the last week. It's all good, but yeah, I see that Again we'll talk about with the selfies and Gen Z and then you know, has segmentation, let's not go there because we don't have time.
Rachel Morrissey:No, it would be fun, I would love to, but yeah, yeah well, we're gonna have to like hire you as a consultant. I think we will.
Ian Horne:So, yeah, yeah, we'll wrap it up, but this has been the money pot. I better not say the wrong one it has been the money pot. It's been really good fun live again from amsterdam. It's been a pleasure having, uh, the live audience with us, that's. That's given me some energy. I've really enjoyed that. Laura, it's been fantastic having you on thank you, appreciate it rachel ethic as always.
Ian Horne:What a co-host oh thank you and of course, of course thank you to all of our fintech nerds listening in again. This is the money pot. Goodbye for now.
