[00:00:00] There's two types of machine learning. There's black box and there's white box. Black box does not spell out and tell you why something was good or bad.

It'll just tell you it's good. It's telling you it's bad. Whitebox, exactly why it was, Xeon was built using whitebox for that reason. When we reject a transaction, we want to tell the business, why did we reject it? So that you can still make that human judgment to say, okay, Xeon was accurate or not accurate, and we can feedback and teach Xeon.

And if you treat Xeon as a new employee that you're onboarding, that you've got to teach and nurture them anyway, this employee is going to get smarter over time. Machine learning crawls huge amounts of data to spot patterns. Within Xeon, there is actually a feature where you can just click one button to find a connection between connected accounts, and that's a great way to pick up bots and fake accounts.

And this means That you can automate a lot of things now. All these manual reviews that these fraud teams spend their time on. That can be done by machine [00:01:00] learning, machine learning will spot the patterns that you're not seeing, and even tell you why. And there are clients that tell us that, yeah, our teams actually pay attention to your white box machine learning because it's telling us what new patterns have emerged, what new data points we should be looking into.

So this is how then we can elevate and help fraud teams and risk teams to spend their time on more important cases or deep dive into things that may not look so straightforward.

Hello, and welcome back to Purpose Driven Fintech Podcast. I am your host, Moni Villares. In today's episode, Amanda Liu, Director of Brand, Product Marketing and Growth at Xeon, shares with us the fundamentals of fraud. We cover why fraud is on the rise, different types of fraud, we cannot prevent nor manage it if we do not understand it well, so this is very important.

Talk about fraud rings, the black box and the white box, that basically the white box allows us to understand why fraud is happening, how [00:02:00] AI and machine learning help us prevent, detect and stop fraud. Fraud and much, much more Amanda and I are aligned in leadership style and what it takes to thrive for us as a FinTech community.

So it's a very fascinating topic. If you enjoy, please remember to subscribe, give it a follow, share with your friends and reach out to me. I will answer all your questions. Let's get into it.

Monica Millares: Hi Amanda. It is an absolute honor to have you in the show. Welcome.

Thank you, Monica. So happy to be here. Thanks for inviting me. Such a pleasure to spend some time and chat with you today.

Thank you. The honor is mine. So we're going to have a conversation about one of the hottest topics in the industry right now. That is fraud. And for prevention, right? But before we go into the topic as such, this podcast is about how can we build better fintechs? How can we [00:03:00] build purpose driven fintechs that have impact to our customers?

So in your opinion, overall, how can we build purpose driven fintechs?

Amanda Lieu: Yeah I think, all the new fintechs lately, all the new startups, they are about addressing real needs understanding what is that actual market gap that they are trying to address. And a lot of the better fintechs or successful startups are great at identifying that and how they go about doing that is that customer research.

And knowing which customer voices to listen to and to elevate. And I think when that's your North star, listening to people's problems, it really helps you get clear in terms of what is the purpose of this product or solution that you're trying to bring to market. But at the same time, I think purposeful fintechs is more than just building a product.

It's about building that working culture where people are empowered to be successful. [00:04:00] And a successful business has the ability to draw in the best like minded talent and foster that sort of culture where these people can bring their best to the game. And I think that's what purposeful fintechs are about.

I totally love it.

Monica Millares: And I want to expand on two topics that you touched. The one is, it's not only customer research. But I liked how you phrased it, that it's like listening to the right people and elevating their voices. Because sometimes we can do research, but it's not really You know, like our audience, our target customer, so that can deviate the findings that we have.

And yes, it's our responsibility to speak on behalf of the customer, e. g. to elevate their voices. I love that. I love the how you phrase that. Thank

Amanda Lieu: you.

Monica Millares: And then the other point that you made was Basically, the working culture, I totally, it's that's one of my biggest kind of, [00:05:00] I'm a big fan of creating an environment where we can be our best selves, that we really have psychological safety, where we can bring like the passion to work rather than just Going to work.

Yeah,

Amanda Lieu: exactly. And I think a lot of that comes into play in terms of how you create and nurture that sort of environment and, most of the best leaders I've worked with. They're very good at removing that ceiling. They know when, where to identify that talent and giving voice to the right people.

And it's not about voice the right people. I guess it's not it's listening to it. More than the voices that aren't always just allowed us in the room. And that's how you create and facilitate that sort of diverse voice. And the ability to inspire that sort of talent so that they seek out their purpose, they seek out their ambition and as leaders, I think it is leaders responsibility to be able to nurture and elevate and [00:06:00] mentor and coach these people to.

Go further. Equally, it's when you allow so many voices to come to the table, you need to enable an environment where they feel okay to share those opinions. And the way you do that is to foster culture where there is resilience. Where people can put their egos aside, where people understand that I might bring a hundred ideas to the table, but maybe only two are applicable, but you need to create that environment and facility where it's okay to brain dumb, collaborate, and then not everything may be accepted, but that's still cool because that's the collaboration and the discussions that we want.

Yes. And I want to add to that

Monica Millares: because you've raised a very important topic. It's not only bringing the ideas to the table. You said Hey, maybe I have 10, but. Only two may be applicable, but even outcome of having this culture and psychological safety is I bring this idea to the table as iteration one.

I don't wait [00:07:00] to go to my boss until it's iteration 10 that I've taken three weeks to think about. It's more like. Hey not only to my boss, but like to the team, the working team, it's a, Hey, I'm thinking about these. And then everybody we may elevate that idea and collaborate on that.

Or just be like, you don't like just parking, put it in the parking lot. But it's this culture where we can bring. Not only we use the word we need to iterate an idea, iterate, iterate the product, but this is more like. Come up with an idea like it can be an idea it's a work in progress and it's okay it doesn't have to be perfect it's okay that it's a an idea and it's not perfect and we'll just Take that as inputs, which is good.

Amanda Lieu: Yeah, I agree. The best teams I've been part of have that sort of diverse perspective, where everybody puts their egos aside, and it's okay to brainstorm, collaborate, iterate, hook on a good idea and then work on it and refine it. [00:08:00] But that also comes about when you have a very clear, shared Northstar goal within the team.

If everybody is focused on okay, we're going to deliver the best customer experience, then it's egos aside. And you're looking at which of these ideas would deliver against that goal, and then you facilitate conversations and narrow that down. Yeah. Beautiful

Monica Millares: summary.

Amanda Lieu: We speak the same language.

Monica Millares: Yes, we do. I'm like, yes we do, but it's a, but we're able to articulate it right? Because then the summary is. To build purpose driven fintech. It's not only about the product. It's about not only about doing your research and speaking with customers, but elevating the voice of customers and the right customers while creating the right environment for our people to basically.

be their best self and bring the ideas to the table so that we can also iterate those ideas and elevate the right ideas, not the egos of people. And with

Amanda Lieu: that [00:09:00] mix, It can go and

Monica Millares: build something

Amanda Lieu: incredible. Yes, exactly. That's

Monica Millares: awesome. So let's get into topic now.

Can you tell us about a little bit of what has been your trajectory, career trajectory so far and what does Sian do?

Amanda Lieu: Yeah I started out in the digital space tech, digital, that was like my passion playground. I pretty much exhausted every angle of it. And I got to a point where I realized it's not just the digital part of things, if you want a business to succeed and do well, there are many other elements of the business that needs to come together.

For example, the core foundations is the brand. What is that narrative that drives everything that we do? What is that positioning of your product or your solution? Where is that angle and edge where everything can be built upon? So I moved to a strategic agency where we worked a lot on that.

And nailing those foundational building [00:10:00] blocks is then what enables campaigns to come to life successfully because it brings that narrative, that positioning into life in different forms, and that's how you create that cohesive strand that ties everything together. So that was my background and I got to a point where, I was curious to see what the startup world was like.

I knew that a lot had to be built, especially if you go in early stage. So I didn't go in with rose tinted glasses. I was ready to get mocking, do whatever it takes. And it's been fun at Xeon. I've been here about two and a half years. And it's fantastic to grow with the business, see how we evolve, how our go to market strategy has changed.

It's very interesting. And about Xeon and its purpose. I always loved the founder story, how Benser and Thomas started out in this. They actually started at a crypto exchange platform and they quickly got attacked by a lot of fraud. And as a small startup at the time, [00:11:00] the solutions in the market were not fit for purpose.

They were either too expensive, too long to implement, but their startup will fold if they did get a solution in place quickly. So they started building their own solution, which quickly became Xeon. So now Xeon Became their business and Xeon helps all online businesses to protect their entire customer journey with frictionless fraud prevention.

We're in the digital world where being frictionless, being real time, being fast is almost synonymous with the digital world and stopping fraud, isn't just about blocking threats. But it's making sure that businesses don't miss out on the genuine opportunities and the genuine customers. So we aim to stop fraud earlier in the customer journey using modern day signals, which is like digital and social media.

Those are our digital footprint data. Combine that with machine learning for speed and accuracy. This is how we can stay on top of fraud. And we built this in a [00:12:00] way where it's adaptable to every business risk because different types of businesses treat and see risk differently, depending on the industry, who they deal with.

The fault prevention has to be adaptable to those nuances.

Monica Millares: Like that, because then you're saying, Hey, we're customizing this space. Not, customizing. We're building a solution that is customizable to depending on who you are as a business.

Amanda Lieu: Yes, exactly. And businesses do need that. No two banks are the same.

They have different needs, different clients and you have to be a solution that can adapt. Yes.

Monica Millares: So who are your

Amanda Lieu: customers then? We work with a lot of fintechs, so like neobanks, digital banks, payments, money transfers, cross border payments and a lot of like high risk businesses, such as iGaming and Lending.

And we, because we protect the entire customer journey from end to end. It [00:13:00] means we stop fraud at every single touch point. That could be from account creation. To monitoring logins and events and behaviors to protect things like account to account transfers, payment monitoring, and we also offer anti money laundering.

So it goes really well alongside a fraud protection solution. So it's an all in 1 platform that can address these 2 things. And there, that is a pattern that we're seeing in a lot of modern fintechs. Anyway, these risk AML and fraud rules are now being consolidated into one team. So it makes sense to share the data, share the patterns that we're seeing.

And this is how we stop things like fake accounts, account takeovers, payment fraud, and detect fraud or anti money laundering anomalies before they happen. Yes, because then it's

Monica Millares: only one platform instead of segregated against three to four, yeah.

Amanda Lieu: Yeah, exactly. And problems like this translate to [00:14:00] many online businesses.

You any online businesses that has an online presence is exposed to fake accounts, payment fraud, transaction monitoring. And so we are looking to grow into new verticals as well. Things like travel, e commerce. We already have clients in such spaces, but I think it's about making a more concentrated effort to build a presence for such goals.

Monica Millares: Good. Fraud has always existed, right? But then since COVID, it's been on the rise. Now with AI, it is even further on the rise and for 2024, it's one of the key hot topics that's going to be throughout the year. It's like, how do we

Amanda Lieu: prevent fraud?

Monica Millares: So can you talk us through a little bit of the landscape from a fraud perspective?

Why is this happening? Why is fraud so high

monica,_amanda _ jan 6, 2024 001_riverside: lately?

Amanda Lieu: Yeah, I think it's, the evolution of the digital and tech landscape. Tech is advancing. The pace, the speed, the ability to [00:15:00] do things now is so much quicker. And fraud, fraudsters are opportunists, but they are also relentless because they're also a business.

They're trying to make money from this. So they're very creative at exploiting every opportunity possible, and they're more open to using new tech as well. So they're always finding new ways, new new system, new tools to crack the system. And because naturally with our evolution online as well, more and more transactions are taking place online.

There are a lot more real time demands and it's part of the customer expectation that one click, I need to see this happen. One click, my product has got to arrive. So we it's very hard to keep up with such real time demands and that makes it harder to detect and stop all nuances of fraud.

So all the fraud prevention solutions. also have to get better, but businesses out there have to be more open and more agile in adopting some of these modern fraud prevention solutions [00:16:00] that use newer tech to stop the newer tools that fraudsters are using as well.

Monica Millares: Yes, definitely. Anne, you used the word we need to understand the nuances of fraud.

So let's say if I put myself in the shoes of a product team, which I am a product team, but from the, let's say, let's go and build the fintech perspective, we talk about, hey, fraud, we need to prevent fraud, but as a new VPN, let's say, or as a newbie in fintech industry. The world of fraud is so big that basically if we go and say, Hey, think of fraud, they may not understand the complexities of what fraud looks like.

So for us to stop, prevent, minimize fraud, first, we need to understand what do we mean with fraud? So what could be your summary on how can we? Classify or slice the definition of what is fraud in the context of [00:17:00] financial

Amanda Lieu: services. Yeah this is a very relevant topic because internally we're also trying to build that glossary.

There's so many types of frauds, but to be honest, you can categorize all these types of frauds and new fraud attacks into certain parent categories. And because we also look at designing our fraud prevention solution around the customer journey, it's then easy to see, okay, at this touch point, for example, a account creation, what types of fraud tend to happen there, fake account creation, bot attacks, multi accounting.

So this is one way where we can start to see what types of fraud happen at what touch points. And after account creation what happens then the types of fraud that can happen is stolen accounts, you get funny anomaly logins that's one way you can detect that maybe an account has been stolen.

And then you look at behavior and transaction monitoring. [00:18:00] Is this sort of transaction an expected behavior by this customer? Or has this person logged in from a different location on a different device not seen before connected to this account that's trying to transfer this amount of money. So these are some of the fraud types that we detect.

Payment fraud is still common. Stolen cards, card fraud, that still continues on in the digital world. E commerce is prone to those. Charged backs because of the stolen cards. Because of friendly fraud, people buying something and they want to refund it after, and money laundering is hot topic now as well with a lot of financial crime going on.

Yeah. Hopefully that explains a little bit in terms of what we see. Yeah. It

Monica Millares: Explains the depth of the word fraud. Yeah. Because it is a lot. It's not just Oh, transaction fraud. No, it's like [00:19:00] across the customer

Amanda Lieu: journey. Yeah, exactly. I was going to say, and sometimes if you don't have a good, robust solution in place, you wouldn't even realize that fraud threat exists.

There are some businesses where there's a lot of hidden bot accounts in their system that they're not aware And then when you have a certain promotional campaign that comes to life, suddenly all these bots come alive make the most of that promotion that you're running and suddenly your system is all swamped.

So it's a, really interesting space. There's so much to detect and catch around fraud and being aware of the kinds of threats that do exist. And yeah, if you don't have something good in place, you don't know what you don't know. Exactly. Can you then

Monica Millares: expand on how big is this? Because we see it all over.

I was going to say all over the [00:20:00] news, but all over LinkedIn feeds. It's like fraud, It's on the rise. It's on the rise. Can you quantify like how big is this fraud?

Amanda Lieu: Yeah. There's several reports, a lot of different parties do research into this yearly. For example, JP Morgan had an annual Payment fraud survey where they were they were seeing on the digital side, a lot of card related fraud that rose by 10 percent over 2022.

And the recent most famous one is PSR's APP Fraud Performance Report. Authorized push payment fraud accounts for 40 percent of fraud losses over 2022 in the UK. That's massive. Can you expand

Monica Millares: on that? A P fraud. It's account push

Amanda Lieu: payment. Push payment. Yeah. So that's for example if you aren't aware and you're transferring money to account that you think is legit when it's actually not, and that's such a [00:21:00] common fraud that happens right now because there's not a lot of good measures to detect that sort of scam.

Great. And then the owners goes on, is it government to create that awareness or is it on the businesses? To create education. So that's another interesting topic that we can unpack, but I the main thing around fraud is that fraud scales as a business grows. And a lot of businesses maybe sometimes are short sighted, not thinking about the long term because if fraud is costing you, for example, 1 percent right now.

As you scale bigger, that 1 percent can mean a lot to your bottom line. And as you grow bigger as a business, you also start to draw in more attention. And suddenly you can appear on the radar of fraudsters and they see you as an opportunity. So that's the other topic that I feel businesses should be more aware of as well around fraud.

Monica Millares: So can you expand on that? Because as a business, I'm sure we, they don't [00:22:00] have all the awareness and There's quote unquote mistakes that we make, right? What are the common mistakes or oversights that we make when it comes to fraud?

Amanda Lieu: Yeah I do feel like, businesses sometimes do underestimate that total cost of fraud.

Like I say, some people think that, okay, it's just the resources that I need to hire into my fraud and risk team. And they see, okay, maybe fraud is only a small percentage of my current bottom line, but the total cost of fraud is. The resources you've got to hire, the tools, the different tools to stop fraud at different touch points that you've got to combine together to make sure you've got a robust protection all around.

And the fact that the cost of fraud compounds as they grow, as the business grows, that small percentage means a lot. And sometimes with short sighted planning, you don't foresee that if you put a robust solution right now, that is the thing that would enable your business to scale bigger without exposing [00:23:00] yourself to bigger threats later on.

You see a lot of traditional banks where, they've built a solution to this point where it's very hard to rip certain parts of it out. Cause suddenly there's so many dependencies and if that specific tech. It's no longer fit for purpose in today's world. If it doesn't detect some of the new tools and new patterns that we're seeing in fraud, it's not easy to replace that one thing.

You've got to engineer the entire solution. So sometimes that sort of robust planning and scoping from the start can help to prevent and just give businesses that foresight of what to anticipate when your business scales. Definitely, and you've used

Monica Millares: the word detect, basically, like a few times in the past few minutes.

So I want to move the conversation more towards Xeon as such, that it's basically a solution and then, One of the things that caught my attention as I was going through the website, it's and [00:24:00] probably you are the mastermind behind this because it's like the positioning and the story and the branding.

So it is, you say , how do you stop fraud if you can't see it? Then it's followed by detect fraud rings and unnoticeable bot attacks with AI and machine learning.

Amanda Lieu: Can you expand on that? Yeah. Yes, I wrote that and it's actually one of my favorites because, yeah, when I first joined SEON what I really loved about it was our machine learning tech there are a lot of machine learning solutions out there.

Two years ago, AI wasn't this big thing. It is now. And everybody's we have to buy something with AI because that was automated, but two years ago already, Xeon has already developed something quite robust and. There's two types of machine learning, there's black box and there's white box.

Black box does not spell out and tell you why something was good or bad. It'll just tell you it's good, it'll tell you it's bad. White box tells you exactly why. It was, SEON was built using [00:25:00] white box for that reason. When we reject a transaction, we want to tell the business, why did we reject it? So that you can still make that human judgment to say, okay, SEON was accurate or not accurate, and we can feedback and teach SEON And if you treat SEON as a new employee that you're onboarding, that you got to teach and nurture them anyway, this employee is going to get smarter over time. Machine learning, crawls, huge amounts of data to spot patterns within SEON There is actually a feature where you can just click one button to find a connection between connected accounts.

And that's a great way to pick up bots and fake accounts. And this means that you can automate a lot of things now. All these manual reviews that these fraud teams spend their time on, that can be done by machine learning. Machine learning will spot the patterns that you're not seeing.

And it even tell you why. And there are clients that tell us that, yeah, our teams actually pay attention to your white box machine learning because it's telling us what new patterns have emerged, [00:26:00] what new data points we should be looking into. So this is how then we can elevate and help fraud teams and risk teams to spend their time on more important cases or deep dive into things that may not look so straightforward.

Okay,

Monica Millares: I want to expand on the beginning of the conversation. We said to create purpose around fintechs. We also need to think about colleagues, right? And bringing the best out of people. And as we introduce more AI tools in the workplace, machine learning, and you just gave a beautiful example. Then there is this universal fear that AI is going to replace our jobs.

There is another stream of thought that it's hey, we'll be hybrid intelligence where we continue to do our jobs but better because then we have basically tools that allow us to do better analysis in this case. And you just touched on that, that it was like, Hey, the [00:27:00] specific use case is all the manual monitoring that we are currently doing.

It could be done with machine learning and AI solutions. What is like, how is the solution impacting? Codex, like members of staff in product teams in fintechs. Is it received as a threat or is it received as a hybrid intelligence type of solution? Yeah.

Amanda Lieu: A lot of clients actually appreciate that Xeon can remove their time doing some of these manual reviews.

So AI is good in that sense in that it does help you process a lot of data sets a lot quicker. And and honestly speaking, I think machine learning isn't quite there yet. We, lean on machine learning because it helps us. Do a job more efficiently, but human intelligence is something that's not replaceable [00:28:00] quickly.

A lot of current solutions in place, especially even in the FinTech world, some of the more advanced FinTechs, they're still looking for good talent. Hiring talent is still difficult because, that sort of human judgment, human insights are things that are not replicable by machine learning and AI at the moment.

Yeah, I love that

Monica Millares: because it's it pacifies the fears that sometimes they are fears, right? It's the unrooted fear of the uncertain future, but it's a no, actually, I do believe that well, unless something goes really wrong, we

Amanda Lieu: And if you don't learn to adopt that tech, fraudsters will. So that's a very good point.

Monica Millares: Yes. Which leads me to a very, good point. Coming back to very specific use cases that fraudsters will use these technology and any other emerging technologies to become better. That's why we need to become better as well in [00:29:00] learning these technologies. So at the beginning at some point in the conversation, we said, Hey, the definition of fraud, what do we mean with fraud?

And we said, there's multiple use cases. One of those use cases is in the onboarding flow, right? That it's like, Hey, we need to do identify your identity. But then if we start layering the complexity behind financial services, it's not only The types of fraud that we have in onboarding and fake and identity as such identifying your, who you are, but it's also fake identities with leaked data.

So that now it's like it's both, right? It's like somebody stole data and then we have all these fake identities. Can you expand on how does that look like in a, FinTech, let's say, and how does Xeon help identify these types of fraud? [00:30:00]

Amanda Lieu: Yeah, good fraud and risk teams always tell you that fraud isn't just looking at one data point or one data set.

The best fraud teams look at as many data sets as possible to find that combination of what are the right smart insights to pay attention to. So although you can have leaked data, people can steal your password to an account. But they're not going to have access to all your other accounts. So how we combine this tech then is you can use things like device fingerprinting and dual location.

We might see that, okay, now suddenly you're logging in from a different location than expected. You're logging in from a device I've never seen before associated to your account. And maybe it's telling me that you're logging in from Italy. Where your social media accounts is normally saying that you're based somewhere in Asia and with that sort of login event and behavioral monitoring, you start to spot these different anomalies.

So it's not [00:31:00] just using that one thing to stop fake identities. It's the ability to combine all the different data sets that we can collect so that you can make that smart decision. And be able to pick up such patterns quickly. Yes.

Monica Millares: Which brings me to a comment for all the product managers listening to this.

So when the fraud team may ask you, Hey, we need to incorporate a data field in the, in, in, the system, let's say in the fraud system. It makes a massive difference into the fraud model and ability to identify data. So on your mind, you may be like, Oh, it's just one field. Oh, it's not the highest priority against all the competing priorities.

But actually in reality, based on what you said, it's if we want to. Understand fraudulent behavior is better even having one extra piece of data to different three different [00:32:00] data points make a massive difference. Once we aggregate them. Because then we start like

Amanda Lieu: connecting all the dots in a better way.

Yes, exactly. For example connected accounts, device fingerprinting can probably detect that, okay, all these accounts are connected because maybe they're connected from the same device. Equally patterns that you wouldn't even think of, like battery is plugged in and charging at a hundred percent.

If you think about bot farms, they're all definitely plugged in and charging a hundred percent. So sometimes, a data point that you think, Oh, might not mean anything, but when you aggregate it and you start machine learning starts to point out what are the commonalities between all these data sets you're seeing, this is where the patterns come out.

Monica Millares: That is so interesting. I've never thought about. But yeah, sometimes my phone is charged and maybe at a hundred and I'm still like texting in there, like random things that we did as humans.

Amanda Lieu: Yeah. What I mean, and as you said, sometimes you think this data point, I might not need it, but it might come into play [00:33:00] in a bigger aggregated picture.

That's the

Monica Millares: key in a bigger aggregated picture. As an individual data point may not, as an individual data point in a customer, it may not. But the moment that you aggregate it, then you're like, Ooh, we start seeing the patterns.

Amanda Lieu: Yes, exactly. Beautiful. So

Monica Millares: then to expand on one of the hot topics when it comes to fraud as such is transaction monitoring.

There's many transaction monitoring tools out there, but the challenge is that transaction monitoring is post factor. Okay. It's monetary, right? So what can we do as an industry to move the needle less? To move the needle away from transaction monitoring and more towards fraud transaction prevention as such.

Amanda Lieu: Yeah. That's a good point and [00:34:00] that's how and why Xeon is built the way we are because we want to stop fraud early in a customer journey and you can't help it. Sometimes things will slip through. So that's why transaction monitoring is so important, but if we can filter out all that junk from even allowing it.

From entering your ecosystem, say, if you think about a digital bank, they go into new markets and what sort of new markets you go for, they go for on the bank markets because that's where the opportunities are and they spend a lot to create signups and create all that awareness, but what if all the signups are just fake accounts?

Neither do you as a business want to onboard all these fake accounts. If SEO can stop all that from the start, you will have less junk in your ecosystem, less potential threats that happen further down the journey. Ability to stop fraud quicker with cheaper data. You don't have to KYC every single sign up.

You can use our alternative data using [00:35:00] modern signals because everybody's got digital footprint. You can use such signals to identify legit customers, genuine customers, and at least block out bots from signing up to your account. So that's one way we can reduce one type of fraud. Yeah. And

Monica Millares: this phrase that you use now, digital signals, it's exciting because then like we have more data and we can prevent fraud, but if I put myself.

As a customer, I'm like, Ooh, that's scary. You have my digital footprint, it's so it's so basically banks are genuinely, they genuinely know a lot about us and our habits and our personalities and all of this is covered under the privacy policy that we all blindly agree. Yeah,

Amanda Lieu: but it's scary.

The thing is, although Xeon uses these digital signals, we only use open source data, so we're not invading your privacy. So [00:36:00] a lot of your profile settings, we respect that. It's only things that people choose to post publicly online. Any probably available data that we can get. That's what we use.

So we're not invading that sort of GDPR protection or any privacy compliance, regulatory requirements. And I think when you look at on the bank markets, say a pack Lata, a lot of that population may not always have in depth credit history. So for some of these businesses, if you don't have a credit bureau, what can you do so that they can lower their risk in onboarding the right kinds of customers?

They need alternative data sources. Without having to KYC because that's expensive. So Sion offers such businesses that option and it is the new way forward because you look a lot at these digital citizens, a lot of these under banked or high growth economy markets, they just don't have that traditional trail because everybody lives online now, your email, your phone is literally your passport.

And [00:37:00] what data you openly share publicly like that is down to you as the consumer as well.

Monica Millares: That's a very good one clarification point that it's not like you have all my data, but it's just like alternative sources of public information that I choose to share online. So it's not like you're invading my privacy and know everything about me.

Amanda Lieu: Yeah.

Monica Millares: Then I like this use case that it's coming back to purpose driven fintech and creating more impact. That is, I like the use case of pay for the underbanked, for customers who underbanked or unbanked, customers who may not have a credit history and we still need to include them in the financial system.

Solutions like Xeon allow us to have other data points that basically give us an innovative way to verify this customer and say, hey, it's trustworthy customer versus a fraudulent customer. And then based on those data [00:38:00] points, saying coming into the party, coming into the financial system. Yeah, services for you.

Amanda Lieu: Yeah, exactly. That a lot of fintechs are trying to enable financial inclusion. But when you go to a market where maybe someone cannot provide that traditional trail, but they have an autonomous trail, it makes sense for a modern business to look at modern data points.

Monica Millares: Definitely. So if we go back at the beginning and we say, hey, culture and people, part of building a fintech or a robust financial service ecosystem is about, like we said at the beginning, it's about having the right talent in the right environment.

Having innovative mindsets and also resilience. Resilience is very important. And in this case, we're talking about fraud that in, what's the right word? In preconceived ideas of people's categories of people, you say, Hey, [00:39:00] someone in marketing, they may be all extremely creative. Then someone in fraud, they may be more analytical, less creative.

How do you think we can bring a creative culture of innovation? Where we have AI, we have machine learning, we have fraud, we have traditional innovative brains and we bring them all together. How?

What's,

the secret sauce to create that culture that allows for innovation?

Amanda Lieu: Yeah. Unfortunately I don't think there's a secret sauce.

I think it's just shifting mindsets that we see people for who they are, we've got to give voice to them voices that aren't always loudest in the room. Everybody brings a different perspective. In the same sense that for example, if you think about writers and authors, an aspiring writer or author might go there's loads of authors and books out there, where is there space for me?

But we meet so many different people in our social life, work life. Nobody's ever the same. [00:40:00] Everybody brings that fresh perspective. And that is simply the lens that we need to apply. If we're looking and seeking perspective on ideas and innovation, see people for who they are and seek out those voices that aren't always loudest in the room.

Give them a platform to voice it, create an environment and a culture where it's okay to brain dump because we'll riff each other, riff off each other to refine the idea towards a shared North goal. And I think that's how we achieve it.

Monica Millares: I like that way of thinking because we're not saying hey, we need to create an innovative culture where we're open minded or opposite, like we need to create a culture where, to scale culture we need a set of best practices and ways of working, but on the contrary, this is a, just to your point, this is a different perspective where we're saying we need to accept people for who they are,

Amanda Lieu: Basically, give

Monica Millares: space to have different perspectives, elevate the voices that normally [00:41:00] couldn't be so loud in a group of loud people, and then basically elevate each other's ideas, brainstorm and elevate each other's ideas.

It's not a my idea against yours. It's a, generally we listen to different perspectives. We focus on the idea rather than on the who is saying that or the ego or the title or something.

Amanda Lieu: Exactly. And you see this in companies that grow so big, sometimes it's just management voices, but this is how that disconnect happens.

Cause they're not talking to the people on the ground, the people who are seeing the day to day, and it's actually those voices. That would help everybody have a more informed perspective on what the problem is. And it is interesting when you go around the company, even at Xeon sometimes we face a problem.

If I speak to a different team who would be seeing it from a different perspective, they will offer me a different way of looking at things. So it's always important to [00:42:00] see people for who they are, not their function, not whatever their title is, because everyone brings a unique perspective. Yes,

Monica Millares: and to build on that, I'm like, and to build on that, we're practicing the, we're practicing what we're saying, and to build on that, I think it's a, you started talking basically about the power of diverse thought.

As much as I love FinTech as an industry, and we've had tons of progress, and we have, let's say, two women here talking, there's still a ton that needs to be done in the industry when it comes to diversity, not only diversity of gender, but diversity of backgrounds, diversity of social classes, diversity of many things.

So what are your thoughts on what are the practical actions that we can take as an industry? To improve diversity in the

Amanda Lieu: industry. Yeah, I think it's stuff like what you're doing, podcasts that get more voices out there more channels and more vehicles for people to share stories and share voices [00:43:00] so that it becomes the norm.

I know it's difficult in the tech space cause it's very dominated by men, but there are women in there. It's not, we're not as rare as it used to be. And it's just elevating these stories and insight sharing and that would make it feel a lot more normal. And the best things are always formed of different perspectives.

Monica Millares: Definitely. I totally agree, but actually one of the reasons why I started the podcast was exactly because of that, so that this podcast did not start as a fintech podcast, it was a COVID project.

And part of that kind of journey was I wanted to showcase more women who had a professional life that it's cause I have this hypothesis that if you are a woman under 50, it is quite likely that your mother was not an executive in a bank, for example. Hence we did not have that role model, but then the, quote unquote girls, [00:44:00] the next generation 20, 22, 25.

Many of them, especially in emerging markets, there's still this view that by 27, you need to be married with kids, right? So it's we cannot change that perspective overnight if they don't see other role models doing different things. So this idea of putting diverse leaders and examples of what is possible in front of other people, I think it's super

Amanda Lieu: important.

Yeah. And as a woman, you can still have kids in a career. I know many women like that it's becoming more of the norm now. And I think those things do happen. We just need to get those stories out. Definitely.

Monica Millares: Perfect. So it's been an absolute pleasure having you in the show as we are getting closer towards the end.

I have two more questions for you. You are a marketing professional. Personal [00:45:00] branding is part of marketing as well. So we get a lot, I'm talking about women. Like we get a lot of questions on, Hey, how do I build my personal brand? And there's all the practical things in the, how to build a personal brand.

But there's a key question that I see coming up again and again, that is the, as you build your personal brand, you should be. Asking yourself the what is your superpower and the how I can have a silly question of what's your superpower. As a marketing professional, but basically you're an expert in these how did you recommend women or anyone in the industry as they think through this question?

How should they frame that in their minds to then communicate that? Yeah,

Amanda Lieu: This is a funny one. So what, makes us unique? I think each of us have some kind of inkling in terms of what we bring to the table. It's one reinforcing the confidence around that, and two is the funny one I was [00:46:00] saying is get the external perspective.

It's the same as positioning a product or solution. I can apply the internal lens in terms of what I think this is from an internal company view, or I can ask my customers and hear from them. What do you think of this? So in the same sense when you have an inkling, you're like, okay, I think that's my superpower, but ask your close friends, ask your close network.

What do they like about you? What do they value from you the most? And you might be surprised in terms of the things that people will tell you, what your partner would tell you, what some of your close friends would tell you, because that close network around us offers us that perspective. And it helps to validate certain things that you already know, but it also gives you that different perspective where sometimes we miss it about ourselves because women can be hard on ourselves.

We're very critical. And sometimes it's important to build that channel where you have that support network to tap into and hear from other people because they [00:47:00] reinforce some of the things you might miss out and they highlight to you how critical you can be about yourself. And I think that's how I would go about it.

Have confidence in what you know makes you unique. Poll your closest friends and network around you and hear from them, because they will validate and support some of the things you do. And they will highlight some of your superpowers as well.

Monica Millares: Definitely. I think that's a beautiful framework to, to wrap up that diversity conversation.

So if

Amanda Lieu: people want to know

Monica Millares: more about

Amanda Lieu: you and Sion, where can we find you? I'm on LinkedIn. I think that's the best place to connect one on one. I love conversations. I love networking and meeting other people in the space. Equally for people trying to discover where to go in their marketing career, happy to explore and chat.

And for SEON, we're going to build more content, more voice as well on LinkedIn and on our website. Next year is a exciting year as we produce more thought leadership stuff that we can't wait to share. So yeah, come follow [00:48:00] us on LinkedIn.

Monica Millares: Definitely, we'll add all the links in the show notes.

So before we go, there's this question that I love asking everyone. If there was, if there is one thing that you would change in FinTech. If there's one thing that you could change in the industry that can make the lives of customers, colleagues, and shareholders better, what

Amanda Lieu: could that be? I think this aligns with your podcast because I think for fintech startups, it is finding that balance between profit and purpose.

Profit keeps your books in the green, but it's purpose that would really drive you to deliver impactful solutions and build lasting cultures. If you look at the biggest fintechs that we always remember, what were the two things they achieved? The ability to generate income, to sustain the business, to go far, but the kind of culture that they've created as well.

And those are the things that leave those lasting stories. Definitely,

Monica Millares: [00:49:00] because then the culture is also what your people need to be resilient while feeling appreciated. To then continuing the journey, right? I think that is not built by a founder. It's by a founder and all the team, otherwise it doesn't go far.

And then the culture gives the outcome of that culture is what we build for our customers, whether it's B2B or B2C, but it's like the experience end to end, whether that is in the app, web. Phone chat, wherever the touch point it may be, it's the passion and commitment of our people is reflected in customer experience.

Amanda Lieu: Yes, a hundred percent.

Monica Millares: Beautiful. Amanda, it's been amazing having you in the show. Thank you very much

Amanda Lieu: for your time and your insights. Thank you, Monica. I've been a fantastic conversation. I love the topics and things that you've raised and brought to the table. Yeah, thank you. It's been really, interesting.

Monica Millares: Thank you. Ciao, ciao, everyone. See you next week. [00:50:00] Bye.