E684 | Max Schertel, finmid & Tim Rehder, Earlybird: Powering European SMBs with the cash they need

0:00Welcome back everyone to another episode of the UBC Podcast. Today I'm thrilled to welcome two guests who sit at the front lines of embedded finance wave in Europe. Max Schiattel, co-founder and CEO of FinMIT, a Berlin-based embedded lending infrastructure business for B2B platforms. They are, of course, backed by Early Bird, as you know, because that's the people we have on this podcast. And then, of course, Blossom Capital and many other great firms. Tim Reda is joining us from Early Bird. He's a general partner and focusing on FinTech, InsureTech, and embedded finance infrastructure investments.

0:30Today, we'll explore how embedded finance is moving from small pilots to a core part of how platforms operate, what infrastructure and regulatory challenges will stand in the way, and why this shift matters for SMB's platforms and Europe's growth engine. Before we start the show, a quick note. If you're building or running a fund, you know it takes the right partners. At EUVC, we only work with sponsors we truly believe should be part of your tech stack. Please do take a moment to hear about them. And if you do, reach out, mention your VC. It's the best way you can support what we do. Thank you so much.

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2:48So Max, I just told you, a spotlight will be on you. I'll give you the very first question, which is just explain to everyone what you're doing exactly. Absolutely. So we provide embedded lending infrastructural platforms. What that means is that on top of our infrastructure, any platform that serves business can build any kind of financing products anywhere in Europe with one single integration. So whether you're a large food delivery platform that serves restaurants and wants to offer them financing, or whether you're a PSP and you want to offer your businesses financing, or you're a ride -hailing platform that you want to offer the fleets financing, we can make any of that happen.

3:33Really, I would say the platform's imagination is the only limit to what we can make possible in that regard. Tell me a bit about the opportunity of embedded financing, Tim. Maybe you could just say why you love this space. Talk about the nuances of it and how people should be thinking about embedded finance as an investment field. So when we looked at the overall opportunity within B2B lending, we always had the thesis that the embedded part could be the winning overall model in this vertical. And why is this so? We thought that the level of integration that an embedded player can have will have the overarching winning risk model behind this because a player like ThinMid, they sit very deeply integrated into the data platform and can have a completely different way of scoring risk on behalf of these players.

4:35So we think that ideally you can take banks completely out of the equation of sending customers of these marketplaces to these external banks because FinBit essentially enables this platform to become an own bank in itself or a financial service business. And in this context, we believe that the model just becomes in itself fully integrated, very seamless for everyone who is transacting with these types of platforms. And hence, we believe that embedded is the winning approach and B2B lending in the long term. Hence, we also back FinMed here in Europe. Max, maybe you can talk a bit to the nuts and bolts of this type of business, because now we've got the broad perspective.

5:29But what exactly do you then handle? What's on you? What's on partners? What's on the people, the customers of yours to solve, so to say? Yeah, absolutely. So I think maybe if we take one step back, right, what we found so exciting about the topic when Alex and I sat together and set up the company was really the overall economic impact you can have if you get this right, right? You can have a true impact on growth of businesses. You can have a true impact on difficult times that businesses sometimes go through, right? And I think that was the overall idea. How can we make sure the economy can grow?

6:06And I think that's what really excited us about the business. Now, when it comes to the nuts and bolts of running it and making it possible, our hypothesis was always that, in particular, the large multinational platform, they need something that's incredibly simple. It needs to work the same way in France, in Germany, in Poland, etc. Our job is then to make all of the complexity that's behind that, and we can talk about that at length, but make all of that complexity go away, provide the platform with really one simple integration that works wherever they want to offer this to any of their customers.

6:42And I think that was really key. Now, what that meant is that I would say, at least from a regulatory and operational standpoint, you want to own as much and control as much as you possibly can, because only then you can really look up to the promise of providing a simple integration. You don't need to ask other people questions before you can offer platform something. But then I think one very important consideration is that we always also had the thesis that you can build this really, really balance sheet lies, but the capital doesn't need to come from us. And I think that's a really core view on the business here.

7:18And there then we really work with anything from private debt funds or institutional investors. And I think Tim, you said, ideally, banks don't need to play a role there. And I agree from a distribution perspective. I think what banks do have is big balance sheets. They have the deposits of customers. And I think we're actually a great opportunity for them to invest into their funds, their own funds with good risk-adjusted returns, ultimately. So again, like regulatory and technical, fully own that because that's key to the experience. Everything around the data engine, that's really, really key.

7:53But then when it comes to pure capital, that's not our job. We make that happen, but that's something that comes from others. What is the economics of this type of business? Is it a super high margin? What is it that's the super attractive case of this? Yeah, absolutely. So I think the very, very attractive thing about it is just the market opportunity is huge. If you think about who needs access to capital, you walk around town, you ask your friends, you probably have a business address as well. Well, probably you have one that doesn't need that much capital, but the average business needs capital all the time for investments, for hard times, for short periods, for long periods.

8:36So there's just so much demand. And I think that's what's really, really interesting about this. When it comes then to margins and everything, you can operate this with really, really strong margins. Today, I think we have a gross margin above 60%. But I think what we really care most about is how can we look at risk and pricing together and then really optimize the net revenue that we can generate from this. And sometimes maybe that can mean a higher margin. Sometimes that can mean a lower margin because then that can have a positive impact on conversion. So it's not like you want to only optimize for margin.

9:16What you really want to optimize for is overall net income. And again, just given the size of the market opportunity, there's no question that you can really build a huge business in this space. Maybe I can add to that, Andreas. I think the platform itself obviously provides the center for the risk pricing, as Max says, because in the case of a Volt or a Lieferando, just to take away some of these FinMid customers, they obviously do the chunk of the revenue of these customers, but you can also obviously access the other part of their, let's say, non-digital revenue by looking at bank data, for example.

9:58So you use the platforms to precisely calculate the risk of that restaurant, but you also use the platform to essentially distribute to them. So your cost of acquisition becomes only acquiring the merchant or the vault, the platforms of the world, but then you use them to distribute the offering to their end customers, which in most of these cases you speak to a few thousands of end customers. So the model is obviously like an indirect sales model, but you use, so to say, the platform to like price the risk to the end customer directly. So there is not this one to two relationship in the sense you don't really know the customer, which is obviously sometimes just risky in the sense of selling indirect early.

10:49but here you really gain access to the true underlying transactional data of the customer directly. And although you don't speak to them directly, you really know them directly, which is, I think, extremely powerful in this type of business model. And maybe to add to that, I think the great thing here is that everybody has the same interest. The platforms want healthy businesses on their platforms. So there's automatically a positive selection. They want businesses that do more and more. Businesses want to grow naturally because, you know, if you're a business owner, you want to optimize money.

11:27And then we obviously want to make sure that we support good businesses as well and we help them grow. So I would say really in this triangular relationship, right, we can really help each other because we have very, very, very aligned interests. And I think that's the great thing about the model. everybody ultimately really has a strong economic benefit from this. Can you share, Max, some of the names of your prototype customers just for everyone to understand? And then we can maybe from there dive a bit deeper into the problem you're solving for each type, so to say. Yeah, absolutely. So let's take an example, like a very tangible example that most people are probably familiar with.

12:11The first very large platform we started to work with was Vault. So out of the food delivery space, we're live in 19 countries with them today. And the way that the product works really is, if I own a restaurant, then I use Vault. I obviously sell the food, but I also have what's called a management dashboard. So if I'm the owner, I look at that and I see how much I'm selling, how much revenue I'm making, et cetera, et cetera. And what Vault's basically doing, they offer me as a restaurant directly in their financing before I ever had to ask for it. And I think that's a huge shift here where you, you know, in financing solutions, you move from a model where I always, if I'm running a business, have to go somewhere and ask for it and then see what happens.

12:56And here you move to a model where somebody is proactively giving me an offer. I know it's there. And when I need it, I can draw the money instantly. And I think that's really what also makes this a lot more convenient for the businesses, naturally. That's why distribution works so effectively, as Tim mentioned before. And again, the platform benefits because they then see the growth of the business. And then it naturally ties the businesses also closer to the platform. If I can see that a platform like Bolt's really supporting me all around, not just with my sales, but also when I need to grow and have a tough time, then that's something that has a really strong impact on retention.

13:34A product like that has a retention improvement of up to 8 % compared to businesses that don't operate. Can I ask you both about the impact of a business like this or of this solution for the market, so to say? Are we giving a more frictionless experience to people or problems that are already being solved by banks? Or is this actually more money being put into the system and thus making smaller businesses more effective in running their businesses? Because normally they would not be able to get serviced. I think it's really the latter. Sorry, Max, but I'm sure we're going to say the same or at least approximately the same here.

14:17It's definitely the latter because you include a part of the overall market economy that didn't have access to capital before. Yeah, or at least partially they didn't have access to capital before and ThinMid now enables them to look at a complete different manner to grow their business. So some of these small restaurant chains, obviously their whole transactional data that ThinMid is using in order to price the risk of the restaurant has never been used before. It's nothing that really banks pay attention to. So they look at very static, historical type of data in order to understand whether this is a customer they can provide credit to.

15:05But the way that Finlid dynamically scores the risk on the different transactional data that flows through the business in a very dynamic way provides a complete different profile of the restaurant itself. So you really enable them to look at different marketing initiatives for their business. You enable them to maybe look at different assortsmen, but maybe enable them to look at a different brand campaign for their small restaurants. So it's definitely enabling a part of the economy to grow, which couldn't do before, which we ultimately loved about the model. I mean, ideally this is, or I think generally this is the overall equation of alternative lenders in itself.

15:52I mean, you have seen some of these maybe e-com lenders where there was a similar type of inclusion risk before. But here, we believe that the type of embedded infrastructure, so sitting as part of the marketplace itself, provides a complete different way to really look at the underlying risk equation. Yeah, I agree with this. Where we are today is you have more data points that you can look at, just stuff that wasn't possible to ingest into data models before. And you can look at not just the business individually, but you can look at tens of thousands of businesses at the same time. And you can look at the historical performance of those.

16:37And I think that's really what creates here the opportunity to first serve a part of the economy that wasn't served very well. But now if I think maybe five years down the line or longer, then I think this notion of embedded will become more and more popular. And I think it will attract really the broader economy. And the way I like to think it, and I'm sure this will resonate with Tim, when I started my career in financial services, it was actually consumer banking with N26 in very early 2015. Back then, mobile banking was a niche thing, so to say. When I told my family and friends I was going into a mobile bank, it was like, what is this?

17:17Why do you need this? Maybe there were a few people that started to use it, but it wasn't popular. And I think, obviously, over the past decades, it's absolutely normal that everybody's using this. And I think you see a similar notion here where it works really well now is a segment that you could not address as easily in the past. Smaller businesses, because they also choose convenience, they need the speed, that's what they really care about. But I'm confident that over the next five years, the latest within the decade, we will see that this will be a product that every platform will offer. And that it will be something that will be normal for businesses to use because, again, it's just so much easier to use.

18:01it's just so much more convenient and the data is always better than what you get from the bank and that will ultimately then drive A, because customer acquisition is just much more efficient, right? It will drive prices down. And then because of the convenience, because you can really create a positive selection there, you'll just be able to address, you know, not just a portion of the market, but I'm really confident that over time, you will be able to address the market as a whole. It will take time and it's not where we are today, but that's definitely where I see things moving. Can you talk a bit about the typical finance sizes, like the size of the lendings that you're doing?

18:39I imagine that they're not very big per client and it's quite more often that you would go to your bank and ask for a loan. Yeah, that's a very good point, right? And that plays, I think, into what I've been saying that you move the markets or you move as your data miles move and improve, right? You also move to different segments in the market. I think financing is one of those sectors where you can make endless money today, but you want to make sure that you don't just make endless money today, but you make that in the future. So we very consciously said, and maybe worth taking a step back and explaining how we look at data.

19:18When we look at platform data and we look at the traditional financial data and anything else we can adjust in terms of data into that, We want to make a prediction about whether the business will still be with the platform within period X. That's what we care about. And that period X, it defines how long the maximum repayment period is. And then because we look at the revenue businesses generating all the time, it also defines how much we're willing to finance for an individual business. And the range today can be anywhere between 1 ,000 euros and 250 ,000 euros, in rare cases higher. But I would say where the majority today's playing is really anywhere between 10 ,000 to 20 ,000 euros.

20:02And then again, with financing durations of up to one year, what we do see is a really, really strong renewal rate. I think 85 % of the businesses that take financing, they actually renew the offers. So there's a strong recurring component. And what we also see, and this is probably what you wanted to touch on, Yes, there is demand for longer periods. Yes, there is demand for much, much higher amounts. So we're really trying to restrict ourselves. Let's say, were we really comfortable with the data? Where do we think we can make reliable predictions? And this is really something we're working on, right?

20:40How can we be better and better at forecasting what the future will hold for business? And that will that drive how the offering evolves over time. And that's then also how you're able to attract different segments in the market. Tim, you spoke about maybe there's a future where the banks will not be needed at all. So one thing is that you can pull data with this from the actual transactions of the business and you have much stronger data to build on than most banks would ever do, especially for a small loan. I imagine that there's a future where, given the entire AI boom and everything that's happening, where you would be drawing in tons more data, even on consumer loans.

21:23As an example, we have VCs that are underwrite founders based on their trajectory in life and how quickly they've built up their LinkedIn network and blah, blah, blah, which in a sense, allow you to loan out to a person on a very different risk scale, so to say, than any normal bank would do. Could you talk a bit about the implications of AI for a space like this and where you see these platforms moving? Yeah, 100%. So I think first of all, Mac's analogy in that context was right. I think, or we believe internally already since quite a bit, that the banks will ultimately stay, but the service offering will somehow be reduced to like providing balance sheet and being like the overall partner to fintechs like Finlitz in the long term.

22:20But then you have obviously APIs, such as the embedded API from FinMed, who build the deep integrations to external providers and then also take over the overall distribution, which traditionally banks are also not very good at. So you basically reduce them towards their core and the core they can do well, but everything else will be taken over by other providers who just become overall just the tech part within the equation. And I think that AI overall is already there in most of the parts. So you obviously have seen some of the consumer lenders who started their ML-based risk models, but then they obviously continued in order to become more reasoning enabled, i.e.

23:18becoming more gen AI driven or opening up their risk methodologies to include some of the general AI components. And I fear Finmet is doing everything to enable this component as well because I think in an ideal world, you're trying to become as holistic on the restaurant. But you guys, I mean, we are only talking about restaurant, but obviously this is a quite horizontal play in the medium long term and they are they just signed first customers on the fleet financing part where they also enable taxi drivers to now buy their cars in a complete different manner and it's also completely integrated into the driving platform so i think this holds true for for many other applications but in the end what you're trying to do as a financer become like the most holistic platform for trying to understand what your customers are doing.

24:18And in that instance, they already have the PSD2 integration right now at these for loans that are above a certain size. But then they are trying to understand, okay, what are these types of customers doing outside maybe of their core business? Can we include some of the maybe social media signals that can drive overall conversion of certain business areas? Do they launch a certain brand initiative that can have an implication of the business? And I feel like the AI part in this is trying to enable these platforms to become even more holistic, which means the risk models will become better over time.

25:00And then the model obviously also becomes stronger, et cetera, et cetera. So I feel this is for all fintech companies that are in this financing landscape, just a must do, to be honest. There's nothing they can eventually decide whether this is good for them or not, but it's an absolute essential part of understanding your customer. And obviously this ChatGPT component just gives people, could be different context generally on the customer. No, 100%. Maybe I can give you a few more tangible examples of what that looks like in practice. because I think the potential lies both in running the business and then the ability to look and analyze the data.

25:47So when it comes to running the business, I think we've made huge, huge strides, in particular in the past one to two years. I'll give you a practical example for me would be adverse media screening. So that's something where before you make a payout, you check out, is this a serious business? Is there anything I should know? the traditional approach, maybe you skim a few databases, right? So somebody takes a look at something and then you take a decision. What we've seen is that like with an agentic workflow, you get a better result than the traditional financial databases that you use for this.

26:24You can pay, for example, LexisNexis and they'll give you a result. You get a better result there, you get it much, much quicker, and then you get it much, much cheaper, and much, much cheaper certainly than any human could do it. And it's, you know, that's, I would say, really on the operational side, a very practical example. On the data side, which for us is the biggest question, right, how can we use those millions of data points to create predictions of the future? I remember four years ago when we started the business, you know, we hired a more traditional risk person because that's the right thing to do.

26:58You want to make sure you have a solid baseline. And what we've realized over time is that that's ultimately not what you need. What this is, is a data science problem, not a problem where you're getting somebody that's greatly qualified from a bank and that opens a drawer and pulls out the risk model. And I think what we've seen is that naturally human nature is a limitation in terms of how creative I can be, how many ideas I have when it comes to looking at data. And then their AI has really opened up the possibilities where you say, look, here's literally millions of data points. How can I potentially look at this?

27:38What are new ideas to do this, right? How I can really on a daily basis almost create new models, backtest them on my historic performance, and then come up with something new, right? And I think that's just something that just wasn't possible. And I think that the advantage that we obviously have is that we're much, much quicker in deploying these things than, yeah, obviously a bank would be. And then last but not least, the bank just doesn't have that much data, right? And I think we're just, which is an advantage on top of that, right? So you can both execute quicker and you execute quicker on much, much more data.