The Connector Podcast - Humanizing Finance: DACX's Journey to Deepen Client Connections

Welcome to the Connector Podcast, an ongoing conversation connecting fintechs, banks, and regulators worldwide. Join CEO and founder Coen van der Hooijdonk as you learn more about the latest available trends and solutions in the markets.

Welcome to another podcast, and today I've got Yannick with me from Dax. a whole new company from Belgium, from Antwerp. Yannick, who are you?

Hi, Koen. Good morning. Thanks for inviting us today. So I'm Yannick, born and raised in Belgium, worked for the past 15 years in the financial industry. And during, let's say, our journey in the financial industry, we discovered that there's a whole, let's say, sphere out there where companies tend to move more in the direction of customer experience and human experience, customer intimacy. And we've noticed that the playing field is evolving evolving very rapidly, but that there is, let's say, as well a lot of opportunities out there still to be discovered, explored, and confirmed together with companies.

So Dax is in this space of customer experience. How did it all happen?

Actually, it dates back from 2019 when in my previous company we organized a hackathon together with a lot of students who worked on business ideas. And during the 2019 hackathon, actually, the idea of Anamatch, so analytics and matchmaking, came together in one idea that was won by my co-founder, Christophe.

Mm-hmm.

And that's actually when we start incubating the idea. So it dates back, let's say, a few years ago. He was then still studying. And at the same time, we noticed that the idea was actually a real business problem. So even if a company does everything right, you know, being transparent about the costs, getting the best service out there, we still noticed that some companies had a churn. And that was the case as well with the company where I was working. Customers still left. And it was actually all about the fact that they were not feeling a click. They were not feeling a match with the person on the other side of the table. You do have different salespeople. You do have different styles. You have people who like to talk a lot about the macroeconomics, about very financial savvy topics. And you do have people who honestly don't want to understand everything about the macroeconomics. So imagine, Koen, that we are on the same table. I'm your relationship manager and that I'm talking about Xi Jinping, I'm talking about inflation, I'm talking about that we're overactive in the US with our investment strategy. And you're like, okay, cool, but I'm a human. Let's talk human things. I'm not interested about financials. So we really noticed that it's actually a topic that was, let's say, underserved in current emotional sales, which is actually often the case when you talk about financial relationships in a business context. So that's how we really spotted the idea of, okay, that's something we really need to investigate. We research and we need to find a solution to close that, let's say, mismatching on the human side.

So, Yannick, you emphasized quite often the importance of human experience within customer experience. But how does that match up with DAX being a tech-driven company?

We see a lot of companies on the one hand working on customer experience, but it's often still product-driven, we've noticed. So imagine the traditional Spotify example, people listening to this music also prefer to like that music, but it's very product-oriented. We see the same in financial industry. You also already have a loan, oh, let's sell some insurances on top of that. So those examples I think are quite commonly used in the market, but we see that often in those discussions, we tend to forget that actually behind that sales interaction, there is an actual human. So there is a person.

Absolutely.

And that person is driven by certain elements. So example, you have people with, let's say, more an engineering background. They typically have, they prefer statistics and numbers in their decision-making process. So they tend to understand what is the rationale behind this decision. And then you have people more in the, let's say, the creative space. They try to work with examples. They want visuals. They want to understand what's in it for me. They're more like, what we call more like sentiment-driven decision makers and not number decision makers. And we've noticed that both in communication, in product proposition, or in the way people are matched in a business relationship, that it's not from that angle, or very, very little cases it's done from that angle with a scientific background. So a lot of companies, just to emphasize on that as well, a lot of companies tend to move in the direction of persona building. So they try to look at typologies, they try to look at who are those individuals, but they do that on a manual basis. They do manual exercises. So let's say that there's no scalability in the exercise because even having those personas does not mean that you match them on your total client population. And on the other hand, as I mentioned, that's not from a scientific point of view where we started from a scientific psychological model where we are, let's say, sure and certain that we can definitely map your client population based on something that has been studied and is based on research. So that's also, I think, why on the one hand we go for human and the other hand we use it from a technology perspective to make it scalable.

No, that makes sense. No, I had the pleasure and joy to already see your application and I was very much impressed by the lead enrichment tool. I think it can be a game changer for sales teams. But can you maybe explain what type of data that you use? Because everyone talking about data, there's GDPR that pops into our mind. So how does that work?

So what we try to do is data augmentation. Data augmentation from the point of view that typically when you have a lead or you have a prospect in your database or via a website, for example, you typically only have the name. So for example, Koen, you would have your name, but the name actually is a persona as such. It's very limited in terms of data intelligence. So what we do is we augment that data point with open data points. So today it's limited to data from public searches and social media. Those data we use to enrich the data points that a company already has. That's something we can do at the very early stage of a customer relationship. But of course, we can do that during lifecycle as well as, of course, a human evolves. But we see it as leapfrogging for a commercial to actually in 10 seconds jump from having only a name to having actually a view on the human. This could be the age geographically, but typically also the background in terms of professional occupancy or typically the background in studies and so forth. That's one tool. Of course we have more tools, but specifically focusing on lead enrichment, that's actually how we assist a sales team to go from, let's say, only the name into entire view and we call that data augmentation. So we create a persona around, let's say, the name only today.

I believe you also have a persona tool. What is then the difference with the persona tool and the lead enrichments?

We reverse engineered a psychological model that we use to create personas. And what is persona is actually a better or elevated understanding of the human behind, in our case, Koen and Yannick. Why is that so important is because if If we want to, let's say, replicate data, that would be an easy exercise. But where we really stand out is where we elevate the data into usable and tangible insights. So typically for me, it would be a hands-on profile, and a hands-on profile typically wants examples to understand why is this interaction valuable for me.

Would then be a logical step the business matching?

Yes, indeed. So once you have actually captured the open data, created the persona, for us, the logic next step is to do the business matchmaking. So if you can take the persona or build the persona from your lead, your prospects, and your current customers, you can do exactly the same exercise with your internal sales team. And 1+ 1 actually equals 3 in this exercise. That means that you can overlay those 2 personas and look at who ideally would we place in front of that prospect or that customer. So to an extent that me, for example, in this use case as a salesperson, would feel comfortable On the one hand, having tips how to interact with my future customer, and at the same time knowing what is important for my customer to emphasize on. So ideally, of course, in, let's say, a theoretical world, we would match the best salesperson's personality or interpersonal profile with the customer that is making the appointment in the agenda.

And then I would say 1+ 1= hyper-personalization. But when you talk about hyper-personalization, then security again comes to the foreground. So I was also wondering, how do you guys deal with data protection? And at the same time, maybe what does it mean from a technical point of view? Are you a SaaS infrastructure? Are you cloud-based? How does that work? So 2 questions in one.

So first things first, security. I think everything regarding data, specifically in this context of person data or personal data, is a super tangible topic. The great thing about DAX is that we've been incubating our solution together with one of the leading private banks in the Benelux. So let's say that it's rooted in our DNA to look at security by design. So during development, we've been working not only on the idea, on the creation of the value, but also on those elements of technology development. So that's a very strong aspect. And we also feel that it's a super important value driver when talking to companies and talking to people who want to use our technology. So having that, let's say, from day one rooted in our methodology is super important. And of course, yeah, we were, let's say, looking at the idea and looking from a technology perspective. So we were very lucky to be, let's say, vetted and reviewed by experts in the industry who on a day-to-day basis have experience with banking and financial insurers' great security levels. So that's, let's say, one. So that's one thing. Second on the security aspect is that we did, of course, all the technical auditing on the Microsoft stack because we're Azure-first. So we're a cloud-first, data-first company, meaning that we use Azure as our, let's say, backbone to host the solution. And that makes us, of course, a SaaS solution. So also the technical and the security screening was done by Microsoft on the solution just to reassure us on our approach and our methodology. So that of course was also documented and so forth. And then moving forward on the second question, are we cloud-based? Yes, we are. And to an extent that companies can, let's say, consume our DAX solution on the one hand via an API. So imagine that you want to really technically integrate, that's a possibility. But at the same time, we have our own portal. So people who just want to test it, try it, can use our website portal. Of course, secure, separated based on the requirements of the test user or the company. And we can even go, let's say, to the most elevated extent. We also make often the joke NASA security standards, and we use that as a joke because sometimes financial companies really not only want the compute and the usage in a separate environment, but they also want the storage in a separate environment. So the great thing there is that we can spin up a complete standalone infrastructure for a company. That really makes us also, I would say, very, very unique as a startup that we have, let's say, that level of technical maturity in place.

Well, it makes sense because if you work for a bank, then EBA is there. The European Banking Association has very strong rules around cloud computing, SaaS computing, and everything. Hey, we're almost at the end of our podcast, a really nice one, by the way. But what What does the future look like? What are the future developments for DAX?

The future looks bright, definitely if it's up to us, because we feel some first traction about the use cases that we have today. But we still have over 40 use cases in place that we want to create together with future partners and with future customers. Where are we heading towards? You already mentioned it, hyper-personalization. On the one hand, where we started off as creating a hyper-personalization assistant for the sales in a face-to-face constellation. So assisting the salesperson in better understanding the human on the other side is one thing. But of course, we noticed that salesperson also sends emails, that marketing team also wants to do segmentation and create campaigns. So we're more moving from the one-to-one constellation into the many-to-many constellation where we want to, let's say, be the single reference partner for personalization throughout the customer journey and also throughout the interactions between the company and the customers.

Now, I guess every one of our listeners would like to get started with you guys. So how do they contact you?

You can take a look at our website, our LinkedIn page. We can give you an extensive live demo. We can start using the tool tomorrow, and we'll be happy to give, let's say, additional context about what are the capabilities and what is the value that we create for, for our partners today and in the future.

So, Janek, thank you so much for sharing your insights. And I know what I'm going to do— be hyper-personal today. So I'm going to do my best. So thank you very much. Thank you also to the listeners and stay tuned for more news in fintech. Bye-bye.

Thanks, Koen. Bye-bye.

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