Monica Millares: [00:00:00] Hello Norris. It is my honor to have you today in the show with us. Welcome.

Norris Morris: Hey, Monica. Glad to be here. Hi, everyone.

Monica Millares: Thank you. Yes, because we're going to have a very relevant and important conversation today that it's AI and financial services, basically, and all the difficult decisions and.

Questions that we need to think about as we incorporate AI in the industry as such. And I think of many of the players that we have in FinTech, Moniz, you're one of the ones that have been leading, so far when it comes to incorporating AI, not as an experiment, but as a leading proposition. So very looking forward to the conversation.

Excellent.

Norris Morris: Let's do this.

Monica Millares: Perfect. Okay. Before we go into AI, this podcast is about how can we create [00:01:00] better fintechs that have more impact, more purpose driven fintechs. What's your take on how we build more purpose driven fintechs?

Norris Morris: When we look at The beginning of neobanks, for example, so Moniz obviously itself as a neobank very much has been a purpose driven company and when we rewind and look at the phase of neobanks that we are currently observing and their successes.

It was very clear that these fintechs, these neobanks came around because they wanted to, they saw an opportunity where incumbent banks are not maybe doing the best possible job when it comes to customers and the price point and so on. And that opportunity was clearly there. So I think all these fintechs and neobanks came around because they wanted to solve that problem because I think inherently they are all purpose driven companies. And in many ways, I would also like to say that when I look at the evolution of [00:02:00] this industry over the past, let's say five to 10 years, I think, it, it hasn't moved a needle massively. I would like to think that way. So what I can now see is that again, talking about the past at the moment is it's a, when let's say 10 years ago.

In order to interact with your bank, you needed to go to a bank branch, or you needed to call them up. And there was, yes, there were websites, you can log into your online bank using the website, but mobile app based banking didn't really exist. The world was heavily moving towards app based everything, but banking had not caught up.

So I think this tick box has now been done, so people probably, I would say, can't even imagine anymore. Thank you without having that shows balances and enables you to make payments and all this stuff. So that has happened. I think the. Customer centric centricity. And also when [00:03:00] we look at inclusiveness angle and, being purpose driven business, I think this is very much has stick that box.

And again, when we look at the future now, I think we just barely touching the surface. This is this is an industry that is moving, it may seem like quite quickly, but 10 years, is it really quick? I think we have moved the needle, but this is just the beginning because, I would say again, when I'm coming from a neo banking space and I can see clearly.

That's 10 years in. Yes. Let's call it revolution because I guess that's what it is. Right? Revolution has started. It has moved the needle. It has changed the way incumbents are now treating their customers as well, but it's still so early days and AI, which we are going to be talking about today.

Clearly has so much potential here that and again, we're going to talk about this a little bit later, [00:04:00] but I think this is a really for I would like to think this is a benefit. This is for the benefit of customers, but it's a bit of a mixed bag and I have my own views on this wise why these mixed bag, but I think ultimately it is benefiting customers.

I think for the speed from the speed and cost perspective, definitely, but there are negatives as well, for sure.

Monica Millares: Definitely they are. So before we go into the positives and negatives of AI, can you tell us about Moniz? You were definitely one of the pioneers in the new banking industry. Why did you start?

What's your purpose?

Norris Morris: So Moniz, when it started, it started because of really a huge pain point. And again, I had my own personal pain point as a new entrant to the UK. I came from abroad. I couldn't open a simple bank account, which was to me, it was a huge insult. So I [00:05:00] decided to do something about it after I realized that millions, if not tens or hundreds of millions of people are getting also a poor treatment from incumbent.

So, that, that was the driver. I guess and what we as a sort of a retail banking or neobanking brand Achieved I guess is apart from I believe changing the industry alongside other neobanks What we have achieved as our own brand Is that we have really made it much easier for people to access banking services.

And we have brought the cost down dramatically, I think. So that was the noble goal basically is to making banking more easily accessible to remove barriers that are there because of the, some historical, the way things work in a past and so on. So we have removed those. As as much as possible, we have really rethought how everything should work, including customer [00:06:00] onboarding and customer service and all, this.

I think, yeah, specifically on monies. We have today millions of customers across Europe, so it's a truly pan Europe pan European proposition. It is an app based banking service in your pocket, and it's obviously built on incredibly modern, new foundations and technology. And we are going to obviously talk about XYB and our banking platform as well.

Yes.

Monica Millares: Just expanding on that, because like you've been around for a long time. Have you seen the customer pain points change over the years?

Norris Morris: I would say somewhat, yes, but still, over the past sort of a five to 10 years, I I see that fundamentally we, we still haven't actually done everything that we can.

So it, it is a. Still very much work in progress. And yes, some pain points have been removed. So for example, [00:07:00] again, specifically making access easier. So customer onboarding is now relying more on technology. You don't need to go to a bank branch and all this. So that has become a lot easier, but it's not quite there yet.

So it's still very early days because the regulated industry is hard. It's not easy to change. So I think it's very much a work in progress.

Monica Millares: Awesome. Yeah, that's a very good point because basically we've given, we've had a big leap when it comes to accessibility. So everyone can now just download it, but yeah, but it's still not perfect and it has limitations.

So still a lot to do

Norris Morris: especially country borders are interesting ones. Again we, live in the UK. I live in the UK right now. And the UK is at this fintech bubble where people are taking everything for granted and customers have, Now been [00:08:00] asking even more, even better services, even faster, even cheaper and so on.

But it's not necessarily the same in Europe or, beyond us, for example, and so on. It's still very much lagging behind. So I would like to think that yes, we have. Move the needle more in some countries than others. So there's so much work still to be done. And especially when it comes to cross border banking, it's still a huge mess so it's difficult.

Yes.

Monica Millares: Yes, And definitely, Oh, this is like the perfect product for me, especially now that you say cross border, the segment. Of international people is so underserved, it is just difficult to do your banking. Absolutely. Yeah. Absolutely. But anyways, okay. So moving on to the meaty bitty of the conversation.

So moving on to AI, definitely. AI is here to stay, [00:09:00] it is disrupting the world, but the other side is, Hey, should we regulate AI? There are fears that without AI, without rules, like AI is going to destroy jobs. It's going, there's going to be misinformation, discrimination. What's your take on all the fears around AI?

Norris Morris: I have fears too. So, when I and it's quite scary, basically, when you, when I open my social media in the morning, for example, it's very difficult. It starts to become quite difficult to understand what is true and what is not when you take any of the channels. Really? There's this Facebook, there is X and all these channels, and it's very difficult to understand what is being generated.

It's. On purpose by by somebody who is trying to move things in a, certain way, basically. So images, for example, what do you see images? It's very, [00:10:00] it's becoming very difficult to understand now where images are real or not. If people on the pictures are actually real or have, has somebody not the images in a certain way.

And it's, getting. And this is just the beginning, right? So we are, seeing, again if we go to banking for a second, right? As as we are onboarding new customers to our consumer brands and retail customers are coming through the gates on a daily basis and thousands of them.

Technology is trying to understand whether people whose face we are seeing and voice we are seeing and measuring against our databases, are these people real? Or is AI basically has taken somebody else's face and is playing games with us? Criminals are always ones that have a step ahead, right?

So I would say that this is just the beginning and and this thing is, incredibly difficult to control, but we are still again in the very early days [00:11:00] and the way I see it right now is that, the amount of misinformation is massively on increase the amount of fraud that is criminals using AI in order to draw deep frauds a financial system and, rip off other people basically.

New York. It's on the rise at the moment. So discrimination, as you mentioned, also all this and I see also that if we don't very carefully put rules in place and very, quickly. The chances are that information that comes to us is lower quality. We are seeing this already, so the quality has dropped, information quality.

The you, can't even identify what is real anymore. So most people don't understand that what they may be consuming in media may be absolutely fake and has been produced by. Basically, AI and robots and some people are manipulating [00:12:00] things in the background somewhere. So my fear is real. I'm already seeing this right now in action.

And if this goes on and it goes on, it accelerates very quickly until there is unless there is some rule set in place. I think this thing is going to go. Absolutely crazy.

Monica Millares: Yes, because yeah, I also have those fears. So for example I'm a lot of media and I'm like, Oh my God, like the robot will copy me.

It's so easy because you have so many data points, but it's so many people that are on Instagram, and these concerns you from a fraud perspective, who's going to impersonate who, which then leads me to. When it comes to financial services as such a very specific use case, of course, it's like fraud, it's going to increase another use case that we have when it comes to AI that we see everywhere is improving [00:13:00] efficiency.

Kind of all the back office, all the customer service, like all those processes, they will be disrupted. What's your opinion? On which other use cases will we have when it comes to not efficiency when it comes to processes, but more from a product design perspective and how we deliver better design better products for customers as such.

Norris Morris: To, to me, I think one word is hyper personalization, which which has been my dream for many years right now, and before AI really became became something that is in the news and I, really, again when, I started building monies, my dream was to make sure that a bank or a banking service is able to see each customer.

As a human being not an, account, but a human being who has history, who is living [00:14:00] in a certain country, who has a certain set of documents and that system the bank should be able to take information that it has from the customer. And understand it properly without putting people in a, basically a box where the computer says no, because that person's data doesn't tick certain boxes.

In a hyper personalized way the bank of the future without manual human involvement, which is obviously time consuming and it's not really reducing efficiencies, but, or increasing efficiencies, but it's increasing, cost instead. So I think the dream was that, aI will, come to help, will able to understand customer's personal circumstances and not just onboarding but also when it comes to credit.

So credit is the next big frontier in my view, where again, when you look at UK specific [00:15:00] market, right? So you go to, a bank, you go online and you apply and what your bank is doing is doing a credit reference check. And what is a credit reference check? So basically credit reference check is all your bill payments on time or not are in a register.

So they are getting pools and then the bank is applying their own little sort of a gold dust or magic dust on top and the decision is then born. But what if you are coming from abroad and you don't have any history in the UK? Maybe you have been in the country for a couple of months and you need. To buy let's say you are you're a driver.

You need to work and get to get a car sorted basically. So you're outside the system. So my dream basically is to make sure that the data is portable and this hyper. Personalized the way the information can be brought from abroad, [00:16:00] let's say AI or technology is able to sort, take relevant pieces of information and not only relying on quite generic cost, credit score data that is in the UK.

And right now I'm seeing that innovation is happening in this space, but it's a very, slow process. And my big dream basically is that hyper personalization and AI is able to finally make this a much better experience for people and like significantly beyond just offering customers better prices or based on that.

So I'm talking about some things that really move the needle, right?

Monica Millares: Awesome. I'm with you with hyper personalization, exactly. Because that's what we need right now. But the thing that caught my attention the most was you used the word the bank of the future and like coming from someone who's like a pioneer building fintech [00:17:00] buying one of the biggest one in, in, in in Europe.

So it seems like we're even seeing the evolution with you as a founder and kind of visionary that you were like, Hey, let's start new banking. Banking is broken. We're fixing it. And now we're like, Oh, this disruptor came in, AI. And it's even you're even disrupting yourself and you're thinking, saying, now let's build the bank of the future.

The bank of the future looks like that. So we stop even talking about AI because AI is just a tool. It's a technology. We start thinking about like the bank of the future. I love that as a concept. Within this conversation. Yeah, I was like, yeah, that is super cool.

Norris Morris: We, are, indeed with X, Y, B and platform technology.

We are disrupting Moniz, which also has been around for quite a few years now, right? So we are disrupting ourselves. Yeah.

Monica Millares: Definitely. And before we go into X, Y, B, that I'm very happy that you brought it up. [00:18:00] Just like to follow, just to bring all the listeners, our fellow FinTechers, just to bring all the FinTechers on board in the journey with us.

We have identified. Let's say several use cases for the use of AI, whether that is fraud is going to continue to go up. How do we stop it? Whether that's let's improve efficiency across all the bank operations, or how do we build better propositions and service for customers? Then the challenge is the leadership team, mid management, senior management, ex co's, boards, like all of the leadership team, then they have to go through this process of saying, who, what are we going to do now with AI?

How we're going to incorporate that in our ways of working, in our DNA, in our design as a proposition, as a company, as such, it's a very difficult question because none of these banks nor [00:19:00] fintechs have those. Capabilities in house, because this is a new capability for everyone. What's your view?

What's your view slash what did you do in Moniz to think through this journey? Like, how do you think about it as a leadership team?

Norris Morris: Frankly it's been, again if I rewind a little bit and I earlier had talked about my dream of hyper-personalization and this was, I didn't even know if I'm able to apply AI there, but I think our journey recently has massively accelerated with XYB and and now servicing other banks and financial services companies and so on.

And when I back at our own retail banking experience for. We have seen that we have been using AI for actually. A while now, and maybe even not something we have, certain things we haven't built [00:20:00] ourselves, but the tools that we are using, including customer support tools, for example, so our agents who are using specific tools in order to talk to the customer, talk to our customers and so on those companies who would develop those tools have already implemented AI within those tools.

So we have been actually using those tools and AI for years. But in terms of a specific intent on our board level or our company's board level, it needs to actually come from I think you have to have a specific use case. Does it make sense to just to do a tick box? Because yes, AI is cool right now.

Everybody's talking about it, but does it really make sense to, does it really make sense to deploy capital and use your scarce resources in order to do something just for tick box? I'm sure there are companies out there who are doing this, right? Not to. Fall off the train, basically, and so on.

But from our perspective, and also what we did with Google, for example, we announced a partnership [00:21:00] recently between Google and Google Cloud and XYB is to basically make sure that there are specific use cases where our collaboration and partnership and work we do together is able to give our bank partners and also, for example, Moniz.

Specific tools to fight fraud, for example, right? So I can give you a use case, which I think will be very beneficial for any, bank or any financial services company really that let's say fraud. Let's say there is a payment that has been flagged by internal systems as a fraudulent transaction or something like that, then at some point not all companies have completely automated everything.

And frankly, it's not even possible because, for regulatory reasons, it always has to be a human element as well. But let's say something is stopped and either in order to deal with those stopped payments [00:22:00] or some fraud alerts. Quickly and efficiently it would be quite useful if the person who is dealing with this matter, if this person has as much information in as clean format as possible in on a single screen, so you don't have to log into specific systems, many systems and read thousands of codes of a log or something to make a decisions, for example, right on a simple production.

We're talking about, fully populated and AI driven sort of a office tool where an agent can very quickly grasp. What is the the background of this? What is the customer looking like? What is the normal for this customer? So it's everything nice and neat. So you can immediately.

Look at the screen, you make a decision in 30 seconds, 1 minute, because AI has filtered everything and put it in a nice and neat and clean format, for example, and that it makes things easier. Financial crime and [00:23:00] tackling financial crime and being able to understand what is false positive.

Or not. I think this acceleration, the speed and it decreases the cost. And of course, the amount of people you have to pay and have a payroll on a payroll and so on. I think that's very, powerful. And we are starting to deploy this.

Monica Millares: Yes. I like that thinking because it's like you say, there's two, two sides to this coin.

One side says, Hey, let's experiment, do AI experimentation. Just so that we get used to it. And then what you're telling us, it's, let's think of a very specific use case that if I step back a little bit to take, let's say a framework from what you said, it's a, let's take the use case for a challenge that we actually currently have, for example, for our KYC, like the operations team as such may have all these challenges.

And see how is it that we can accelerate [00:24:00] impact with the use of AI. And it may be that we don't start by us building AI here, because in this case, this is the part of the vertical in the industry that has the most advancements with other players in the industry using AI. So it's like, how do we partner with our partners to make the most out of AI to incorporate in.

Our current processes ops rather than go and try to become an AI company when we are a financial services company.

Norris Morris: Yeah, exactly. So it's a concept. You have to search social market and you can understand what is, possible to buy them and what you need to do. And again, when we talk about X, Y, B, and how it serves the world's banks and gives them technology to replace some legacy infrastructure and, the cores and so on, this is exactly what we're effectively doing.

Instead of trying to build everything and put [00:25:00] a huge amount of resources that take. Years to deploy and by the time they deploy, they already are behind the curve, right? So that's where we are doing it for the banks basically. So we are partnering with huge companies like Google, for example and many others to, to take that worry away and make sure that our technology is as good as it can be and on, on top of the curve, basically.

Monica Millares: Yes. And let me step back a little bit here because probably people fintechers know monies as a neobank for like consumer neobank as such, but actually back in May you launched XYB that it's an end to end cordless banking platform. And you have a very bold statement that it's we believe that it could revolutionize the banking industry.

Can you expand what is XYB? And expand on that statement. Why can it [00:26:00] revolutionize? Financial services.

Norris Morris: Yeah, of course. Of course. So again there is a little bit of a history. So we need to rewind for a second and basically explain that when we launched Moniz, we were the early pioneers in the space and we did something.

Thanks to technology that not had not done before, basically, which was completely mobile based on boarding and bank bank in your pocket, so to speak. So in order to, do this, we needed to build our technology from scratch because there is, there was nothing that existed at the time. And, I think it's fair to say that we are, actually have always been a technology business that just happens to be in financial services sector, right?

So we just happened to be in a regulated space. So that technology. Over time, I had been approached by many banks who wanted to take, take part or have access to this technology because they saw what we had built. And I think opportunity now [00:27:00] has arised. Not too long ago, we launched a new brand called XYB and XYB is a formula.

X is us. Y is a client and if you put us and the client together, something awesome can be born a new bank perhaps. So it's basically a formula and a little bit of a workplace. So X, Y, B was basically a spin out from money's and it's a technology play and this technology we call this core less banking.

Platform. And what we mean by that is it enables others, other regulated companies and even non regulated companies to, to replace their systems, something that is legacy, something that could be when we look at big banks deploying hundreds of millions a year, you know, that to maintain legacy spaghetti.

Technology. So we out there, X, Y, B is there to, make it [00:28:00] easy. And basically, frankly low cost and fast. So we call this coreless banking system whilst everybody else calls it. There's a competitive yeah, core. So we like to think coreless because. Again, if everything is tied into around a single core, what happens if the single core malfunctions while your systems come down?

So that's why we, think coreless is way better because you have tens if not hundreds of, yeah, modular, exactly. And that enables banks basically to do things and transformation in a careful way. So for example, a bank can choose to replace one piece of the puzzle, put our module there.

Then carefully deploy another module. So it's much less risk. There is much less risk involved. If you don't do a massive sort of a core transformation, which could take 3 to 5 years to change an underlying infrastructure. [00:29:00] So that's where the core display comes in, and we like to think about X, Y, V offering also as we are accelerating that basically the time to value.

Again, I mentioned three to five year transformation for a bank to replace the technology. So because of this modular or coreless approach, a bank can take one piece, replace it very quickly, and one use case is one of the clients that we are currently working with. We enable them basically to, to build and replace one of the core modules in in only sort of seven months.

From start to finish, basically to launch. So that's that's been, I think, a game changer to, enable banks to move at that sort of a speed, which is, I think very,

Monica Millares: rare. Yes, definitely, because anyone who has worked in either a FinTech or a big bank, we know that a migration is, [00:30:00]

Norris Morris: it's difficult,

Monica Millares: It is a fact, it is difficult. So if you can reduce and simplify, then it's Oh, that's really good. So just let me try to understand better why I think in my mind, I still haven't answered the question, why is this going to revolutionize?

Norris Morris: In terms of revolution here, I think the speed, is a key keyword here, and the second one is a core list as well. When I look at, again, the history of a banking core providers and so on, everybody has been always around this core. And it's, it's basically incredibly time consuming to to change anything.

So imagine you're a bank who runs on a legacy core banking platform, for example, so you need to change something. You have to send a change request and there are many people involved. There are millions, hundreds [00:31:00] of millions, manual basis. Sometimes you won't do certain things, maintenance and expensive and so on.

And when you want to change that provider. Three to five years basically to, to get this done. So I think this coreless approach enables, for example, us X YB to come in and you can replace a specific module. For example, you don't need to use XYB for everything, although it can be used for everything.

But you can also a plug and play a little bit here. So I think that approach reduces risk. It increases the speed to market. Let's say you're a bank. You want to also, you have a new idea, you have a new region, you have a new geography that you want to attack, new vertical, you go in, you deploy XYB module somewhere, you can test the market very quickly.

You don't need to spend two, three, four, five years to do so you can do it very quickly. So speed to market is a key. So I think that's where the revolution really [00:32:00] applies.

Monica Millares: Yeah, now I understand. And then you also partnered with Google and you're using AI Google's capabilities in this new brand proposition.

Can you expand on what you're doing?

Norris Morris: So with Google Cloud, we are using the generative AI machine learning tools, basically, and the idea is that we will Enable our bank and non bank customers to build cutting edge products and offerings at speed, basically again, speed to market, right? That I was talking about.

So we think that by leveraging Google Cloud's Gen AI, we can help our bank customers to automate very manual processes like investigations that I mentioned. Imagine. Everything on one screen for your agent to resolve [00:33:00] block payments or, fraud and investigations. And again, onboarding is in the mix as well.

And second, so two, two things that we are working on with Google Cloud is specifically about this, what we call assisted investigation, which is what I described earlier agents able to resolve complicated, block payments and so on matters very quickly. And second is very interesting is the natural language risk rules, which basically what it means is that right now, if your risk team wants to change something in a system that enables, to detect again, broad or move customers through the funnels and basically where systems are set up in a specific way that catches specific bad behavior or on the [00:34:00] identify as good behavior. Right now, this is all manually written basically. Risk rules, somebody needs to actually code this stuff that is going into the clockwork.

But if you want to change anything, you have to go to your engineers or people who can actually code and they will change the risk rules. And it takes time. And they're competing priorities and so on. So, imagine now, if somebody can use this no code approach, what if your risk people are able to.

Write it in a natural language, like English language, what they want the risk rule to be and AI changing it into code. And then it of course has to go through testing and whatnot, but you don't basically need developers at the end of the day to, to rewrite your risk rules all that stuff. So that's pretty cool with it.

Yes.

Monica Millares: And you know what? It's the third time. I haven't heard it more, but it's like third time that I hear the word no code. [00:35:00] The first time was. When I was in Money2020, these like in Amsterdam this year, and I just I was like, Oh yeah, no code. Heard the word, didn't investigate more.

The second one, I had a guest in the podcast that she has a fintech on lending no code, and I was like, Oh, that is so smart. But now I'm like, yeah, it's pretty cool. Now we're saying, because I can relate to the pain point of the risk team and. Like writing the rules, now we're saying we can expedite efficiency of all the teams.

If we're saying, Hey, we think because many times what stops us is this conversation with, especially when it comes to building product or improving efficiency, let's say it's a pain point is we come up with all these amazing ideas as non techie people. And then we have to go to tech and then, [00:36:00] of course, tech, it's quite complex and we may not understand all of it.

We understand the layer, but not all of it. And once we understand what we need to do, then it's a matter of, Oh, and now we need to put it in the roadmap and prioritize and it takes all this time. But so what we're saying is that now with no code solutions. We as fintecher humans that do not work in the tech department, come up with our idea.

Like we say, we write it down in English and then AI goes and implements, quote unquote, this piece of code or this idea. Of course, tech people don't kill me for saying, Hey, I will go and implement it. There has to be like all this infrastructure behind them, process and this and the other. But basically that's the core of the transformation that could happen.

Yeah, and of course,

Norris Morris: and in the regulated environment, things are even more complicated, right? So to test any outcomes like thoroughly, and [00:37:00] you also have to make sure that basically a human being still needs to be in control and sign things off. But imagine if you don't need to actually go to engineers and allocate a couple of months of road time in order to deploy something.

Sometimes these changes can be quite sort of a minor, but again, if it doesn't hit the roadmap in the right time things can take time. And again, time is everything, right? So time to market and adjusting risk rules when the nature of crime changes and fraudsters are always one step ahead when they change is very important that you are changing.

As a crime changes as a nature of crime changes financial crime, you have to be moving very fast. You don't have the luxury of waiting a few months or a couple of, I don't know, months or a year before you change your rules, because otherwise you're going to get your customers will be out of pockets and you have as a company, you will have [00:38:00] losses because you need to compensate.

And you also have to have more people on your payroll to do actual coding. This approach will hopefully, I believe, change quite a lot of the way we, do things and we, increasing efficiency and reduce the cost base, I think in many levels.

Monica Millares: Yeah, definitely. So then coming back to the beginning of the conversation.

It's the full circle here. High personalization now we've talked to AI, we've talked to high personalization, X, Y, B, your solution, no code, your dream. What is the, okay, now let me rephrase that question. So now that we've talked about all of these, what's the role of X, Y, [00:39:00] B and AI basically in bringing that hyper, hyper personalization, world to life.

Norris Morris: I think our job really is to, ultimately, what we want to do is we want to use the multiple things. Hyper personalization, ultimately, we are going to be. Providing X Y B will be providing this these tools and innovation. We were working on with Google Cloud. We're able to provide this to end users.

Sorry, not end users. I'm talking about clients like banks and non banks. But ultimately, what? Apart from the benefits that those banks and clients will get. What about the end customer, right? So the end customer ultimately needs to benefit as well. And I think I would like to, I would like to [00:40:00] think that when Moniz was started, it was designed to impact many people positively and remove friction from their banking services.

So I would like to think that now through X, Y, B and X, Y, B working with, many banks who have millions of clients. That we can actually impact more end users than we can do as a, as our own consumer. So we will touch points. The end users will benefit. I think so. Enhancing this customer experience through hyper personalization and the AI activities and, AI innovation that they're doing.

So ultimately it's all about enhancing customer experience. And, I think this is all really about that. So that I would like to think that way. And obviously there will be companies who will not maybe consider this but I'm hoping that there are more that will those who don't.

Monica Millares: Yes. And [00:41:00] what's I was going to say, what's most fun about this?

That's the geeky me that's fun, but what's most interesting is that we started talking about AI and the bank of the future and how we've transformed the industry in the past 10 years, but it hasn't been fast enough. So probably solutions like yours and the many others that are probably coming to the market.

That's going to accelerate change even more. So these. World of accessibility, hyper personalization will become more real for all of us, for the the consumers across the, world. So it has a huge impact in terms of, helping people.

Norris Morris: Yeah. And again, coming back to the credit, right? So credit is still so broken and not in one country, but I would say globally.

And especially. If you move between countries if you, don't have credit [00:42:00] score and there are countries where credit score doesn't exist and it's a, it's very much needs disruption. So I would like to think that hyper personalization and AI can really able us To to help people and make their credit experience also a lot better because it takes into account more data points than let's say a human being can consume within reasonable amount of time.

Monica Millares: Definitely. And as you say, more data points I was thinking, Ooh, and all the execs will be asking, Oh, what's the business case? Because today we cannot talk about just like growth. We need to talk about profitability. How do we, yeah.

Norris Morris: The business case, right? As with everything, there are companies who can deploy a silly amount of money and and chase chase, [00:43:00] rainbows, but then those living in the real world and also us as a, business we are very much still, moving towards profitability and we are still venture capital funded.

So how do you have this use case and make sure that your board is happy with with with, Amount you're putting into AI and so on so I think when you look at when you look at. The market, there is a UK energy company who recently announced that they deployed AI in the customer support and within I think one quarter or something that they already is.

Doing the work of two hundred and fifty people, which means that they don't need to hire two hundred and fifty agents. So you can do the math very quickly. You very quickly come to a handful of millions that this energy company is saving. Thanks to [00:44:00] AI. So if you put any. Business case in front of your board and say, we are doing this and that's going to save that much money or the efficiencies are there, it becomes a no brainer, right?

The board will ask you, can you get it done sooner, please?

Monica Millares: Yeah, no, it's like the business case. It's very important. But yeah, you're right. It's if it's actually going to save that much. Yes, the board will be that's, a not the board, but that's a question I ask a lot, especially now that we're planning, how can we accelerate?

Exactly. How can we accelerate? Let's do it faster. Okay. So I love technology. It's awesome. You have a really innovative product as such, I think but technology and Innovation and processes are worthless without a very [00:45:00] strong culture. And I think as we incorporate new technology, AI, and all the solutions that will start coming up, like for example, no code solutions to be very specific in the coming months and years that impacts the mindset and the ways of working of.

People, even though like in FinTech, we have the innovative crowd, the young crowd, the used to change, this, the other, it's still a change. And we'll have to go through some sort of transformation, cultural transformation within the teams. What's your take? How do we do this smoothly? So

Norris Morris: in terms of making sure that people are with the company and they are motivated by what the company does and so on. So I think it needs quite, thought through, a [00:46:00] process and ultimately it becomes a little bit of a process. Again, having run monies for almost 10 years right now, I can very much say that initially you can go in guns blazing and things can be undocumented and you are changing the world.

But at soon, at some point, quite soon, you will find that actually you need to write things down. So your culture, your approach, including your approach towards innovation needs to be written down. And and at some point when you exceed your team exceeds hundreds of people and you're constantly hiring people then it must become a process where.

Yeah. You say this is our culture. This is what we represent. We are trying to change the world here, and this is a way we change the world. And you, as a new team member, these are the qualities that we expect from you. This is how we would like you to these are the areas we would like you to think about and your approach to your colleagues, your approach [00:47:00] to getting things done and how do you react in.

So that when things don't go well, it all needs to be written down. And then we have to think also, how do you keep the culture of innovation, in, place. And how do you make sure that people are staying motivated? It is, it's number one. Process incredibly important second is rewarding people when they do something game changing, even if it's just a good word or recognition in front of the team members or publicly or even a warm word, basically, it it changes quite a lot.

And not punishing people when they make mistakes, because after all people are, if they're trying to do something that has never been done before, which is almost the definition of innovation, right? So mistakes will happen. You will get a lot of things wrong before you succeed. So embrace mistakes, no punishments, no blame game.

And again, [00:48:00] I have people having a little bit of a phone to say out loud, but I think and also, but collaboration with others and not making decisions only by committee are very important.

Monica Millares: Yes. I like how you're making it very practical as in, because culture can be very vague, right?

But now we're like, no, culture is not vague. It has to

Norris Morris: be written down, it cannot be vague.

Monica Millares: Yeah. It's not vague. It is written down. There's processes. There is. What, how we work, that's what it means. That's how we're having impact. I love that. Yeah.

Norris Morris: Value, system. Yeah, exactly. Yeah.

Monica Millares: So as we approach to the end of the episode, it's been a fascinating conversation, by the way.

Where can we find more about you Moniz and XYB?

Norris Morris: So a simple search engine search probably is the easiest to type in monies or x, y, b, there is a bunch of stuff that comes [00:49:00] comes up. So definitely have a read. And if you are a bank or if you are just services mover and shaker, check out x, y, b, and the innovation that we are able to bring to you as well.

X, y, b is a relatively new player, but it has 10 years of experience. We have built our own neobank monies. We have millions of customers on, that platform. So our technology is proven and we have some pretty big game changing banks in our client base already who are using our tech. So check it out.

And I, my details also are incredibly easy to find online. So give us give us give us a ring.

Monica Millares: Definitely because I'm like, I am not being paid to say that, but yeah, I loved it. It's I love the product that you are building and how it can impact. To the industry as such.

Thanks Monica. Thank you. So one very last question before we go, that it's one [00:50:00] of my favorite questions because it's a difficult question, but I ask everyone, if you were to change one thing, it has to be just one thing. If you were to change one thing in the industry that could have the most impact in customers, colleagues, and shareholders, what could that

Norris Morris: be?

Take more risks, but not with customers money.

Monica Millares: Ooh, cool. Can you expand?

Norris Morris: Banks are very conservative organizations and rightly because I need to protect customers money, the integrity of the ecosystem and so on. But I do see that there must be some openness. You have to put your risks maybe in a box, but don't put that box, don't lock that box away.

So if you're doing something that is important, you have to be. Open to [00:51:00] measured risks and so on. So that's what I'm saying is you cannot apply the same level of conservativeness. Everywhere, so we have to take. Some stuff and and, make sure that it's properly safeguarded, like sandbox environment.

And this is where you innovate. This is where you break things in a safe and sound manner. But if you don't do anything at all, and you're basically applying the same. This is too risky. We're not doing this. This is not, then, there is no innovation, right? There cannot be innovation when there is no risks.

Innovation equals risks.

Monica Millares: Awesome. That will go into a short clip. So that's a great way to end this episode. Thank you, Norris. It's been an absolute pleasure chatting with you. Thank you, Monica.

Norris Morris: Thanks for inviting me. Have a good day. Bye bye.