Hiten Patel: Thank you for joining us on today’s episode of The Innovators Exchange. Today I’m co-hosting with my colleague, Cosimo Schiavone, who leads all of our banking and payments work here at Oliver Wyman. And today’s guest is Ed Maslaveckas, the CEO of Bud Financial. Welcome to the show, Ed.
Ed Maslaveckas: Thanks for having me. Glad to have a chat.
Hiten: Ed, it would be great just to kick us off with a brief intro to your role and the company.
Ed: Yes. I guess I’m CEO and co-founder here at Bud. My role involves doing everything that falls between the gaps—fundraising, sales; a little bit of everything. I always say I’m responsible for nothing in particular but responsible for everything at the same time. We started the company back in 2015, originally a consumer app. Quite quickly, around 2017, we started helping banks to better understand their data, enriching their data with our homegrown language models that we began building in 2017. Today we really just focus on personalization and customer engagement tools. We were founded in the UK, but our primary market is now the US.
Hiten: Just for the non-specialist members of the audience, could you just lay out the products that Bud Financial offers today? Who buys them and what value does it bring to them?
Ed: The core of the product and the platform is really a number of models which are able to take the bank's data and comprehend who the customer is. From there, we feed these insights into specific products that people in the bank can use to understand their customer segments based on product interest, income, and whatever information we can find. Those segment insights can also be shown directly to customers, so that they can better understand their finances.
And what that allows people in the bank to do is to essentially really intelligently sell financial products to those customers, but also the customers stay very informed. You know, we’re all used to seeing these mail shots that we get from banks, you know, a bank that I’ve been with for 10 years saying, "You might be interested in this personal loan." But if you knew anything about me, which you should, because you’ve banked me for 10 years, you would know that this is completely irrelevant to me. It’s the opposite of that.
Hiten: Got it. So, if my bank was using your product, I’d stop getting all those mail shots through the post for the credit card that I don’t need?
Ed: You would hope so, but it’s really up to the bank’s marketing team and whether they still want to do those.
Hiten: So, before Cosimo, we'll drill in a little bit later into exactly what's going on in your space right here and now. But before we go there, talk to me a little bit about your journey before you got to founding this fintech company. I guess, starting life as a business banking advisor at RBS [Royal Bank of Scotland], or you can start a little bit early on that. Talk to me about the earlier years and kind of what has led you to the moment that you find yourself in now.
Ed: Yeah. So, I was working in the RBS call center during high school. And it kind of got me interested in the banking world because, you know, it was all this stuff like lost cards, to begin with, then you moved on to the commercial banking team and then one of my highlights was when I was 17 or something, 16-17.
Hiten: Which town is this? Is this regional in the UK?
Ed: This is in Harrogate, Yorkshire.
Hiten: Fantastic part of the world.
Ed: Exactly. They have a lot of call centers because we have great accents. Mine's a little bit messy. So, you got a bit of a view into these back-end terminals, which was quite interesting. It was all green and black screens, I'm sure RBS don't want to permit that, but I mean, this was a number of years ago. But then you started helping out. Specifically, I remember helping out the Red Bull team. They were having some issues getting some parts across and they needed to move some money around. I was trying to go over and above specifically because I wanted to help the Red Bull team at the time.
Hiten: The Red Bull Racing team?
Ed: Yeah, with the F1 [Formula One] team and things like that.
Hiten: Wow.
Ed: It just got me interested in the banking world a little bit and I was studying economics at the same time. Did it inform everything I do today? No, but it certainly opened my eyes to these banking systems that exist, how archaic they are, going in and pressing Y or N and manually updating systems. So that was quite interesting. And then from there I studied economics, but really, I wanted to be a rugby player. I had all the will, but none of the talent unfortunately.
Hiten: I can empathize with you there.
Ed: I gave that dream up probably about 22-23, which was probably a little bit later than I should have realized. And then from there kind of got a couple of sales jobs, ended up at Salesforce and that's where I was kind of selling tech to fintechs in London. And again, chose the fintech scene a little bit because that was my interest and then realized maybe we could build an app. That brought a lot of those fintech products together. It was 2014-2015 where, well, 2013 to under 2014 where a lot of [companies like], Monzo, Starling, Revolut; all these fintechs were emerging in the UK. And I thought maybe it would be cool to have an application which was specifically helping people understand these fintech products and why they were different and/or maybe a better deal for the customer.
The original Bud product, which is why it was called Bud, was bringing lots of different products together, trying to make recommendations, trying to be an assistant to people. I saw MoneySuperMarket was very focused on selling traditional FI [Financial Instrument] products at the time. We have this old press release that went out, was ’MoneySuperMarket for millennials’, when millennials were the cool young things. We're not anymore. And very quickly found ourselves in the head office of MoneySuperMarket and then telling us why what we were doing was not a good idea.
But that was kind of fun and then we sort of realized that was a very difficult business model to attract people into an app. Facebook paid ads was really the only way to attract customers at the time. There wasn't sort of that owned media approach that there is now. And it was quite expensive to bring people into an app to then cross sell a third-party product. It was tough. So, what we developed in there was this ability to understand the core data of the banking data of the customers because we were making recommendations to customers based on their data. And we did the first ever FCA [Financial Conduct Authority] sandbox to do that, because it was sort of bordering on advice, but it was sort of technical assistance, but no one had tried that before.
So, we developed some core products and models and then a number of banks approached us and said look, that might be interesting for us. And then started working with HSBC in 2017 and have been B2B [Business To Business] since then. That's a short, long history.
Hiten: Awesome. No, I love that. There're some things in there in particular that resonate with me. I guess, your first-hand experience, right at the start of that journey of seeing and knowing and what it looks and feels like in terms of what are the systems that are underpinning some of those call centers. I think that feels like quite a foundational footprint to give you the instinct that things could be done better here.
And then you are just riding that wave, right? There's a lot going on in that mid 2010 period. You talked about the SBA [Small Business Administration] sandbox, you talk about the rise of some of those challenger banks, who were shifting the standards of what's expected, particularly that next generation of customers. And then what's happening around you with some of the applications, it feels like a well-timed ride.
Just going to bring Cosimo into the conversation here. I'd love to, Cosimo for you and Ed, to just double click a little bit into this whole customer engagement market and shed a little bit of light on what's happening in this space.
Cosimo Schiavone: That's great. Thanks, Hiten. Ed, great to see you. Maybe let's go into you know, the personalization, customer engagement market that you guys are active in. Obviously, you are spending a lot of time in the US, the UK and other geographies. Would love to hear what are you hearing in terms of top priorities when it comes to personalization and broader customer engagement, what are you seeing?
Ed: I mean, talking about riding waves, I guess, you know, it's no surprise to anyone that there's a huge wave right now of people in banks, and again generally customer appetite of people trying to understand how this world of generative AI fits into customer engagement. Because the kind of unique thing about these generative models is it's very much creating this idea of a segmentation of one, it's very good at generating unique insights. You got to feed it the right data points and assets and tell it enough, you don't want your Generative AI models actually making the decisions, hallucinating, things like that. But it's very good for spitting out, let's say a paragraph of text of unique insight based off the training rules and the inputs you put in.
And so, I think there's this really big shift saying like, is it now the time where from a personalization perspective we can actually deliver on the promises that we've been talking about for years in the industry? We very much feel that it is possible if you have verticalized models that are running underneath and that's where we sit. We don't build the sort of full language models, but we certainly are providing the context layer for those language models to create personalization in this space. So that's kind of a big shift that's happening right now and I guess we're taking advantage of that and finding some great partners that agree with us on that thesis.
Cosimo: Interesting. What are some of the challenges from the bank perspective? I guess that's where you guys come in, right? What are some of the challenges to do that? Is it the beat is not in place, it's scattered across multiple systems, what is the status of data? I guess it's kind of the foundation to enable some of those insights.
Ed: Obviously you got to always get the data into the right systems and the right places. That was very much, though, if you're looking at people that are really pushing the boat, that was the move to cloud challenge, which was probably around, I want to say 2019-2020, 2019 onward. So, getting the data to the right places is fairly straightforward, but really, it's now about leveraging Generative AI models for the right things. And the challenge within banking is; it's sort of two things with those models. First of all, from a data security and sovereignty perspective, you don't want to be sending all of your customer data to a bunch of different open model providers.
The second part is, in financial services, we are a picture of thousands of data points. And it's just too many data points to throw at, like if you threw all the raw data at deep research, maybe you did a deep research project with Google or Gemini or something, it could take maybe 15-20 minutes and spit out an insight. But when a customer logs into their app, they want to see insight straight away. Their data enrich straight away. So, it's about using the right models for the right challenges. This idea that Generative AI models and large language models can do everything is just totally incorrect. What we saw was a wave of a lot of PoC's [Proof of Concept] that thought that, so the last two years. And then we're kind of in this resurgence of people going out and saying, okey, we want to solve this problem. We need point providers to create these models, create these insights, do these things and then we can kind of layer in the Generative AI models over the top.
Cosimo: Things are moving very fast in Generative AI. I'll be curious where are you seeing, and you mentioned a lot of PoC's, but where are you seeing real fraction? For what specific use cases? I think, you know, when we connected, you mentioned OnBuy, SpinOne, but you know being a regulated industry how do banks think about that? Obviously, you don’t want to recommend a product that's going to harm potentially the customer. Especially if it's around their credit. So, I'll be curious, you guys playing the personalization space, how is Generative AI or AI more broadly really being used today from where you sit?
Ed: Two major products that we end up working with on that side. One is, like I said, customer facing tools, but the other is the business facing tools. And business facing tools I think is the first adoption space, and I can talk about some of the customer facing tools that we've really constrained down to be safe for customers to use and that's very important. But on the business side, you can push that button a little bit more.
What we're able to do, we've got this product called Drive, we're analyzing all customer data in real time. We then have insights about an individual customer, all the things that they've been doing. But then we are able to extract those insights across the entire customer base. So, in real time. And it really boils down to, now you can, we are at this point where we're kind of calling it like the bankers’ assistant.
Anyone in the bank can ask a question to our model and say, you know, show me customers that would be relevant to this travel card. It might come back and say okey, can you tell me more about this proposed travel card, if you haven't already inputted those things, you know what income ranges might it be, those kinds of things. And then it'll go, okey, cool, I'll go out and I'll find customers relevant to that. It'll search your database and find you like, okey, here's 10,000 customers.
So, it's doing that whole kind of data analytics query and it's grouping those customers together. And that would, typically in a bank it's something a project you go off and get a data analyst to do, and it’s a couple of weeks, or you go out and hire a third party partner to go and do this big long analysis and then they can find and show you your segments, but your segments are “here's your 20 different customer segments” rather than “here's your infinite number of customer segments”, depending on what your query is or what you're trying to achieve with customers. So, we've seen that as a very safe way because there's feedback directly to somebody in the bank rather than going out to a customer, just giving them full financial advice.
Hiten: And just going to jump here and really fascinating dialogue. Just explain to me, it's probably a dumb question this, but why can the banks not get there on their own with what you described? What's the gap that Bud is bridging that means that these large institutions, who have the data, who have many technologists require the proposition that you guys have developed?
Ed: So, I think it's all things, and this is kind of why the US has been such a great market for us. Given a whole bunch of developers, a whole bunch of time, and all the assets – you can do anything. We could go and rebuild WhatsApp tomorrow, you know, technically I don’t think it would be that difficult. But it's really about like, what are the banks, what are people trying to achieve? For us, we have spent since 2017, building a core language model that understands the bank data. You could spin up that project, it's going to cost you probably in the order of two or three years to make it really good, and maybe 10-20 million bucks of training and people time.
So, the way I think about it is it's a supportive service and building systems, which get them to their end goal faster. So, if you want to know anything about your customer, any insight, you could just call an API [Application Programming Interface] from us and it will tell you that, rather than rebuild it yourself. Don’t get me wrong, I think certainly we've got a great team, a great data science team that we’ve had for many years. But the fundamental question of build versus buy, this is why I think it's difficult to operate in banking markets, which have five or six big banks and that's it, because typically they all want to build everything themselves.
Is that a good idea? I don't believe so. I mean, look, if we can just look at these banks have had the last 5-10 years to build these systems, and I don't think a single one has developed these systems for themselves. Now, they've certainly tried. We're aware of lots of projects that have tried and failed to do it, but it's a long-term project to get to real accuracy. Because the accuracy does really matter of the core enrichment for every single individual transaction and then scaling that up to billions of transactions. So, we're processing. We've processed I think well over 50 billion transactions now, making that super responsive.
That takes a while. And then going beyond that. Then productizing these into front-end customer products and then bank facing products where we're simplifying it down to just a question. You can just ask a question, and it will give you the feedback. It's like, you know, that we talk about a duck swimming on a pond, like that seems so simple. But underneath there are at least 20 or 30 different models playing against each other and then coming up with the answer. And sure, a bank could go build it. But you know, give them three or four years and they're going to be behind where we already are.
But like I said, the US, as I was saying before, that's why the US has been so great because there's so many of these mid-market banks and small cap banks, which are just like “look, we are never going to build this, so just do it for us”. And that's allowed us to move so much faster. We launched in the US two years ago, and it's just been completely day and night. And then we see those advantages being brought back to our home UK market in that with our partners we're able to do more. So, when we go and speak to a Barclays, or an HSBC, or whoever that might be, we're like “look at this whole product, here's all the successes we've had with banks in the US”. So, it's quite a funny dynamic of how that's ended up working.
Cosimo: And maybe just to round that up, on the customer facing front, any interesting use cases worth highlighting?
Ed: There's this new product we've just announced and launched, which we call Intelligent Search. And what it is a very constrained version of our financial assistant. What you can do is you can ask any query about your transaction data. You can say “How much did I spend on bills?”, and it will go through last month or whatever, and it will go through and find out your bills and say, “Here are your bills”. Then find opportunities to save money and do all that kind of stuff within that flow. Now, you can say “Can you find me places where I'm overspending?”, and it can do that, it can do all these very simple things. Now, we have another product that we call Jas, which is a full financial assistant.
But it's not time yet. It's not ready for a full rollout, but this Intelligent Search is very constrained. It's just very much simple questions, simple responses, but the generative capability of it, it can find unique insights every time you engage with it. And you can save those insights, and it can create, the next thing we'll be launching with it can create unique UI [User Interface] components. So, you can have your own generative customer experience, but it's not the scary financial advice for basically telling it. If you're asking certain type of questions, just saying “I can't respond to those questions”.
Now, it could respond to those questions. We just don't let it. It will get to the point where it could respond to the questions. And then going a little bit further out into the agentic world, we've started developing last year. We were researching some models that can actually do actions on behalf of customers with the understanding of their finances. For example, sign up to new products or move money and optimize money depending on how much interest is in different accounts. But again, that's coming. I think this Intelligent Search is like that first piece of that's very constrained.
Cosimo: Can I ask you, you mentioned agentic, right? Just a one-on-one question. What does agentic banking mean for you or for the industry? Can you clarify that for the audience?
Ed: Sure. I think about it like workflows. So, think about the workflows we power today. Inside the bank it is segmenting customers based on a query that you're asking. Where we've gone to the next step of that is, we've actually started to build a couple of models which are finding segments that are interesting. Like, oh, we’ve noticed there's a bunch of customers, as an example, with loads of well, we call it ‘lazy cash’ by end of every month there's just cash sat in that account and actually, that is better off swept into a higher yielding interest account.
And so, you know, that's again a model that we have and that we will detect those types of individuals. And then we can just ping you a little message saying, by the way, we've found these customers that might be relevant, you might want to push them that or the other. So that's kind of taking one step out of actually the person needing to find an insight on the platform. The next step is then actually going ahead and messaging those customers, refining the message, looking at what the customers did after they got the message. We get some kind of, I guess clues as to what the customer did.
If we told them to take out a new product, do we then see within the next two or three months that there's outflows to that financial product, as an example? Basically, it's about the more we go down the agentic path, it's just about doing more of those steps together and then optimizing those things and doing those feedback loops by itself without the human in the loop.
Cosimo: You mentioned that we're not there yet. Is it more because the banks don't feel comfortable, like compliance will shut them down, what is holding that?
Ed: I don't think I feel comfortable, and I don't think they feel comfortable. I would say that. I think I would feel comfortable before they would and I don't feel comfortable yet. And, you know, when we were showing this, we call the interest optimization model Bob. Right now, it's a working inside product that's been working on a few of our individual accounts in the company. Bob is pretty good 95% of the time, but 5% of the time, if it does something wrong and it's moving your money around, that's not great. So yeah, we just need to get that a lot more research and just like. A lot of research is happening in the market anyway across these different products. So, we don't need to reinvent everything.
Hiten: That's fascinating. I'm just going to just dig in a little deep there. For someone who's got their hands on the levers and the plumbing. You're in the flow, you know what's going on. You talked a lot about the financial assistance use case there, a little bit of, how could I describe it, a little bit of cautious hesitancy about, hey, there's some optimization, but when this goes wrong, there's some potentially material negatives, right?
Your money is in the wrong place at the wrong time. Fast forward the clock. I don't know, you choose the years. Is it five? Is it seven? Is it 10? There's a time frame under which, well, question, is there a time frame under which those challenges you raise are overcomeable and if they are, what does the world then look like? Are we living in dreamland? Because there are a lot of people out there who are not practitioners who write about this stuff.
You're in the engine rooms. You're in the weeds. You've been on this art from Harrogate call center. You've seen where we've got to on the first wave of that development. You're on the cusp of the next one. Like what's your view on where we may head? What would the time frame be? And what would the world look like? Particularly around the financial assistance dimension that you described?
Ed: When you look at training models, there's this sort of curve, this line that we can't cross at the moment with all of the training methodologies. And as you find new training methodology you can get closer to that line faster, with less compute. But there's still this sort of line that they can't cross when it comes to accuracy, and compute, and time, and all that kind of stuff. So, I guess there is some general questions of this utopian dream, where humans no longer need to be in the loop for anything.
And we can all sort of, I don't know, whatever we want to do, or be kind of like Victorian passion project people. You know, we sort of sit and play the piano and do paintings and things. And I don’t think that's anywhere near happening. Certainly, in the next two to five years. Unless there's some significant breakthrough, there's some significant “okey, we found this new thing”.
But I do think what's going to happen overtime is just, as I mentioned, these workflows. We get more comfortable that this agent can do this part of the workflow better and we feel more comfortable doing it. So, then we feel like we can take a human out of the loop and then allow that model to speak to this model and do two or three parts of the journey. And I feel like that's going to be the same for customer products. Is it really that scary to say “Hey, we found you're overpaying, your credit card is a bad deal, you're overpaying on your insurance, whatever that might be. Here's four or five different products that may be relevant. Would you like me to sign up for one of them? Yes? Okey.” Click which one and it will go off and sign up. Go on to use the web, take your data, sign up to it.
An interesting thing from people that actually do stuff in this world. Because agents are going to be able to use the web on our behalf, we don't need API's into the complete systems to actually create actions. And I think that's a really big step change and I think that's very close. You know, there are agents that can use the web for us already. They don't always order the right pizza, but that's coming. And I think the progress is pretty quick. So, I think that's going to happen for the next two years for sure. But I think every time we'll just need to do less financial laboring, which is kind of the dream I think for individuals and then for people in the bank. It's less that they need to get rid of a bunch of people, it's just that they can actually do a lot more.
Hiten: I'm just going to shift direction a little bit and I'm going to pick up on something that you've referred to today, this kind of transferring from the UK to the US. Your description so far has kind of centered around, hey, there's just more banks in the US, so there's a larger addressable market. A lot of column inches and spilled ink right now over what does it mean to innovate in one concept over another? Anything more you want to reflect on your experience from kind of building a fintech, trying to scale a fintech to continents? Is it purely demand driven or are there other elements that are worth highlighting in this debate?
Ed: We've had an idea to come to the US in 2019. That's why my only regret today is that we didn't do that then. I think it's just a market dynamic thing. The big banks in the US, you know, five or six big banks are just as hard to work with and just as hard to get large projects off the ground with as the ones in the UK. It's just how they act in large corporations. You have 10,000 people in your tech team, so you're always asking that question, why can't we do it ourselves? Why shouldn't we do it ourselves? And so here what you have is hundreds, people talk about thousands, but I'd say core market that you're focusing on and we're focusing on. Let's say there's like 500-600 hundred banks; they have 50-60 billion assets under management.
And there's a whole bunch of these banks. They have a tech team of 20 people, and they're just like, look, we want to do these things, and we're not be able to keep up if we try and do it ourselves. And I think that's why we've seen the financial services B2B market really grow in the US. Sometimes the challenge of a lot of banks here, there's a lot of very unhappy vendor bank providers. I think, you know, a lot of the vendors have got very big and almost bigger than the banks they're working with and almost become the bully of the bank.
For fintech, especially UK fintechs that we're very focused on quality and delivery. And I think that's something we do actually very well in Europe. To come here and to then just be able to bring that to some of these smaller banks that have kind of been bullied by some of these tech providers, if I'm honest. It's a really good feedback loop, so we don't get that in the UK. We have great big UK banking customers. I think by the end of this year we'll be working with the majority of the big UK banks. But it's very difficult to build a company when the reality is you probably have like 20 really good enterprise customers rather than, you know, 700. I think it seems obvious now saying it.
Hiten: No, that's helpful. That's helpful framing. Talk to me about one of the most interesting challenges you faced on this journey and what was the big learning from that, that the audience would benefit from hearing about?
Ed: Honestly, something you never expect when you're starting a company is that you'll be affected by macro events. That's insane to think that your little company will be affected by macro events. You know, we had a recent thing here where there were some challenges thrown up. I won't get into specifics. The recent tariff thing, and then it through the banking index off, and then a lot of organizations here in a very short window lost faith in investment and fintech. Trump announces something that affects my business directly. You know we went through Brexit, but equally regulation has been a big thing for us both in the UK, the US is 1033 [Consumer Financial Protection Bureau, Section 1033] being on and off, and off and on.
You never expect to be hit by macro events. And I mean, we even had developers across Europe that you know, when the Ukrainian war broke out, we had to deal with a whole bunch of that kind of stuff and like move people around. There are just things that when you're being kind of like an ideologue about building a company, you think “I'll never deal with these types of issues”. And you do. And that's been the most surprising thing. The learning from that, I guess, is resilience. It's like, okey, what's the cr*p that's going to roll up this week or next week. Every time I get a call from my co-founder or COO, I'm always sort of cringing before he starts talking. Like, what is it?
Hiten: Never good news.
Ed: No.
Hiten: It's interesting hearing you share that anecdote. Just joining the pattern between many of the other founders, there's clearly a sense where when you're building something, there's a strong desire to turn inwards, close ranks, really focus on product, client, customer and almost shield yourself, as you say, from some of those external macro factors. But as you've painted the picture, there's clearly some that get through and probably right now the frequency of which we're getting buffeted by some of those is probably increasing. So, no matter how small the ship is at your stage in the journey, you still get rocked by the waves, it seems.
Ed: Absolutely. And then more so like even in the tech scene. Because you know you're attached to the ever-changing wins of multiples and how that affects your capital raising. Just get profitable as soon as possible. That's the learning. That's a huge learning.
Hiten: The golden learning. Talk to me a little bit about what you do outside of work, is there a hobby or an interest that you're active in that helps shape who you are in the day job?
Ed: A few different things. I have a kind of a love-hate relationship with fitness and well-being. You know my evening monster just wants me to eat all the bad food, not do anything, you know, have a couple of drinks. But yeah, you know, obviously I used to play rugby, and I think feeling fit and healthy kind of keeps me on the front foot. And often honestly, that always is the first thing to drop and everything if anything happens. But my sister recently got me to sign up for my first Iron Man, which I am not ready for her. She's very fit, kind of like HYROX UK champion. And I'm like, okey. But I think that honestly gives me a nice little release side project kind of thing. That's been good. I try my best to keep fit. Keeps you feeling healthy. You need a lot of energy for this job.
Hiten: Sounds like you are jumping straight into the deep end if that's your challenge.
Ed: It's very much the all-in mindset. It's all or nothing. If I didn't have something that was going to scare the **** out of me then I just wouldn't do it.
Hiten: I love it. I think also just your description around, you know, you literally sound like you give it your all to build the company, right? And that includes sometimes sacrificing your own well-being or fitness for some of those chapters hearing you describe that.
Ed: Yeah, there are some bigger sacrifices in fitness, but it's probably not for a podcast.
Hiten: Last one, as we wrap up, we always like to invite guests to share the spotlight. So, call out an individual or a company that's in impressing you right now that you'd like listeners to go out there and look up and learn a little bit more about.
Ed: I think I'd be strung up if I didn't call out Taktile and Maik [Taro], who's the CEO over there. I think when you move; two things, you know, I think they're doing some really cool stuff, bringing AI to this decisioning space. There are a few people in that market. But I think they're doing a really great job. I think they've got a real core focus on actual AI in financial services; that's always the challenge. But moving to New York, one of the blessings of moving to New York is there are a bunch of European founders here and none of us have any friends here. And we all kind of cling together.
So that's been like really nice to make friends here, but also if I was in London me and another family wouldn't become fast friends. We'd just be focused on our business and our people around us already. So, I think they are doing a really good job and a great team, I've met a bunch of them. Very positive and they invite me to work in their office, but I don't know if they want that. I don't know if they really know what they're asking for. They are good people.
Hiten: Awesome. Well, look, Cosimo, thank you for getting Ed on the show and Ed, thank you for taking us on the journey from Harrogate to New York, from call center, black software screens to a view of hyper personalization and AI financial assistance. There's clearly a lot of roads travelled and a lot of roads to travel further on so appreciate you coming on, appreciate you sharing your views with us and been a great guest. Thanks for coming on.
Ed: Absolutely. Pleasure. Thanks for having me.
Cosimo: Thanks, Hiten.
This transcripted was edited for clarity.
