In this episode of the Connector Podcast, host Koen Vanderhoydonk interviews Frederik Leboeuf, co‑founder and CEO of Data Village, to discuss the company’s recent evolution and the broader landscape of confidential data collaboration. Frederik outlines Data Village’s market expansion beyond Belgium into the Netherlands and the UK, emphasizing a focus on the finance and media sectors where demand for secure multi‑party data sharing is high. He describes emerging use cases such as collaborative anti‑money‑laundering (AML) under upcoming PSR/PFD3 regulations and open‑finance credit solutions for SMEs that require combining sensitive data from multiple sources. The conversation then shifts to the drivers behind growing interest in data collaboration: the rapid maturation of confidential computing technologies, cloud‑provider support, and the need for high‑quality data to train AI and large language models while preserving privacy. Frederik highlights persistent challenges around data quality, trust, and liability, explaining how Data Village’s secure, verifiable environments aim to mitigate these concerns. He introduces the concept of “bulk consent,” a user‑friendly interface that lets individuals grant consent to multiple data sources in a single step, a development gaining traction in open finance and media. Finally, Frederik shares his goals for the upcoming Digital Finance Summit (DFS) on 8 December – networking, panel participation, and showcasing demos – and provides contact information for listeners interested in learning more.
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Welcome to the Connector Podcast, an ongoing conversation connecting fintechs, banks, and regulators worldwide. Join CEO and founder Coen van der Huydonk as you learn more about the latest available trends and solutions in the markets.
Welcome to another episode, the collaboration between Belgian fintech. And today I have a guest which I already interviewed once a couple of months ago. His name is Frederik, and he's the CEO and co-founder of Data Village. Frederik, can you introduce yourself again to the audience?
Nice to meet you, Koen, and thank you for the opportunity to do a nice podcast, hopefully again together. So yeah, I'm Frederik Leboeuf, co-founder and CEO of Data Village. My background is in the financial industry, so I've worked more or less 20 years in the financial industry on multiple topics from cybersecurity to emerging technology architecture and so forth. And yeah, at some point in time, I had the need to create something and something around data. So that's why we created Data Village and to find a way to unlock all these sensitive data.
Interesting. Since our last conversation, how has Data Village evolved in terms of maybe technology, but also on market presence?
Yeah, sure. So we did some significant advancements on both aspects. So on the technology and the market reach. So let me first start with the market presence. So we are now actively engaging on Dutch market and UK market. So not only on the Belgian market. And our primary focus remains both industry, meaning finance and media industry. And the main reason is because these 2 industries are, let's say, high demanding for confidential collaboration. There is typically in the financial sector a lot of interest in the opportunities around open finance and how to make this happen through collaboration. We can talk a bit further later. But also, we see a trend around collaborative anti-money laundering, and especially in regards to the upcoming regulation, PSR/PFD3, which is about promoting the exchange of data and sensitive personal data to enable better And I mean, when we first met, we talked about magic, which was combining 2 data sources without getting insights without jeopardizing privacy.
Has there been any new use cases that came to the market? I mean, anti-money laundering was something on the agenda for a long time, but has there been any new use cases that came across?
Yes, definitely. So there are use cases around credit and being able to provide, you know, better credit, meaning being able to attribute a credit, but also to revoke credit if it does not fit. And we are actively working on this type of use case on the UK market with a coalition around open finance. And it's about giving a way to access credit for SME. And the challenge there, of course, is about combining sensitive data from multiple horizons. So that's where confidential collaboration is very useful. We see also a lot of interest at the level of organizations, especially large organizations, that have that need and challenges to provide services across departments, across entities, and across jurisdictions. Especially these central entities that have that role to make things happen between all the local entities. But they have that challenge about regulation and how they can guarantee that confidentiality and privacy across different countries and these types of constraints. So there are a lot of use cases around large organizations.
Would you say then the perception against data collaboration has changed?
It's evolving quite fast, I would say. Organizations start to understand that some of the challenges they are facing, they will not be able to solve in their own data silo. So that's why organizations are looking in that direction. There are also multiple reports, especially from Gartner, talking about the opportunity and the upcoming opportunity around collaboration. But there are 2 other things that are now, and that's what we see, triggering that interest into collaboration. The first one being the maturity of technology such as confidential computing. So organization, and we see a very strong evolution during the last 6 months, the organization starts to understand that this technology is now mature. And of course, cloud provider works a lot to make this technology mature enough at scale for organization. But they start especially to understand which part of this technology are transformative. And what type of use case this technology can enable compared to what they are able to achieve right now. That's one thing. The other thing, of course, I would say obviously, is all the things around AI and all the things around large language models. There's a lot, of course, of interest around that topic. But there is, of course, also a lot of concern regarding confidentiality and privacy. And usually you need data from different sources, could be different departments, different entities to make this technology efficient or interesting for an organization. And that's where you see also an increasing interest in data collaboration to feed these large language models and AI. to get better insight with these data coming from a different horizon.
With the necessary protection, if you want.
Of course. That's the main concern, especially in the financial industry.
Because I remember in our last conversation, we also talked about challenges. But at the time, one of the big challenges was the quality of data. at financial institutions. Would you say that there also some progress has been made in the last year?
It's still a challenge. Of course, the large organization, the financial institution, and that's the same in more or less all industry, are still in the path to improve the quality of their data. Nevertheless, If you focus, you know, on one specific or 2 specific use cases, you can meet that quality. So it's not that you need to reach out to quality on all your data. Better to select, you know, which use case you want to focus on, which business value you want to get, and then you can reach that data quality. The challenge that we see around collaboration is more about trust and liability. So let's take the assumption that the quality of the data are there, which is most of the time the case in the use case we are working on. The main question is, how can we make sure that, you know, different participants of a collaboration will engage? Will the trust be high enough? And who will be liable of what? These are the 2 main questions. And this is exactly there that, you know, our solution can help. Of course, it's not that the technology can solve all that problem, but at least technology, and especially our technology, can help. Because by providing these secure and fully, you know, confidential environments, the trust to the participant is very high because the participant can always verify. We always say trust but verify. So they can always verify that it is highly secure and protected environment. And for the liability, the, let's say, entity, department, team that will manage, you know, that collaboration, because at some point in time you need someone that will run that collaboration somewhere. By letting them that way to never see the data, it makes them happy because they will not be— or it reduces their liability, or at least they can make sure that nobody can see the data. So we reduce that liability regarding the different participants.
It almost sounds like a complete B2B story that you bring, but I'm wondering if you bring in the C, the customer, the consumer, how did you see the role of the consumer changing in terms of consent in this particular case?
It's a very good question and we do learning more or less every month on that aspect. The last one I wanted to share with you is around what I call now bulk consent. So there is a concern—
I've never heard about that.
Sorry?
That's new for me.
That's new. Let me explain a bit.
Thank you.
So of course, consent is very important if, of course, you deal with personal data. So you got the point in a B2B landscape, enterprise data, Usually there's not that concern, it's more about confidentiality. When you want to engage, you know, with personal data, the consent needs to be part of the journey. Typical use case in open finance, usually you always have, you know, would it be an individual or a corporate mandate?
Mm-hmm.
There is always a consent in it because usually you need at least to get access to the transactional data, And then you can enrich this data with other data. But what we see is that, especially in the open finance, and that's the case also in the media industry, we see more and more the need to bring something very user-friendly and easy to understand to the end user to manage consent from multiple sources, which means that you can handle in the let's say, one screen, just make it a bit visual. It's much more technical, but in one screen, you can handle a consent for multiple sources coming even from different organizations. That's what I call bulk consent. Because from an end-user point of view, it's not that you have to go to each organization, give your consent to each organization. Again, you can go through what I call a bulk consent. And this is something that we see now coming, as I told you, In open finance, finance, and also in the media industry. It's not an idea. It's more really a concern in the user journey to make the user journey smart enough or frictionless to have that new product accessible for the end user.
Now we're talking about things that are happening in the future. One other thing is happening in the future, which brings me to the last question also, is the Digital Finance Summit very soon on the 8th of December. What are you hoping to get out of it?
Primary goal is to have a rewarding day similar to the positive experience we had last year. So DFS is definitely an excellent event with You know, very good keynotes, panels, and also a mix of industry professionals, you know, from organizations, large organizations, financial institutions, and startups. So that's what we like, and that's definitely what we are looking for also next week, is about engaging, of course, with the attendees, being able to listen to these very good keynotes and panels, also participate. So I had the opportunity to participate in one panel. Nice. And of course, showcasing and making some demo of our products. So we have a booth also at the DFS. So we'll be much more than happy to showcase what we are doing.
Well, amazing. So everyone listening, please come over and come and see Frédéric. But in case they don't, where do they find you then?
Website. They can reach out on the website. So email contact@datavillage.me. There are also a way to To schedule a meeting through our website, through LinkedIn also. So yeah, the usual way to contact us. The usual way.
Frederik, thank you so much for joining me again, second time in this podcast. Thank you also to the audience for tuning in and wishing you all a good day and hope to hear you soon. Bye-bye.
Thank you.
Thank you, Koen.
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