In this episode of the Connector Podcast recorded at Nordic Fintech Week, host Koen van der Hooijdonk interviews Sophia, a senior representative from Proveneer, a 20‑year‑old global fintech specializing in fraud detection, financial crime, credit‑risk assessment, customer management and collections. Sophia explains how Proveneer’s platform acts as a hub that orchestrates data from dozens of sources—credit bureaus, government registries, open‑banking feeds, device and behavioral biometrics, and social verification—to deliver a holistic view of a customer during onboarding, credit‑risk evaluation, AML/KYC checks, and collections. The platform leverages AI to continuously optimise decision‑flows, improve routing efficiency, and generate strategic insights about customer demographics. A major focus is the rising threat of deep‑fake and synthetic‑identity attacks, which have surged roughly 31‑fold with the advent of generative AI, prompting the need for advanced liveness and video verification. Proveneer differentiates itself with a low‑code/no‑code, drag‑and‑drop interface that lets customers configure and test decision models in a sandbox before promotion to live, while still offering professional services for initial setup. The solution operates in real‑time and integrates with over 120 global data partners, adapting to regional data availability. Product development is described as highly customer‑led, with rapid feedback loops and forums. The conversation closes with contact information—LinkedIn, the Proveneer website, and a booth at the fintech event—for listeners to request demos.
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Welcome to the Connector Podcast, an ongoing conversation connecting fintechs, banks, and regulators worldwide. Join CEO and founder Koen van der Hooijdonk as you learn more about the latest available trends and solutions in the markets.
Welcome again to another podcast at the Nordic Fintech Week, and with me. Sophia. Sophia, I believe you come from London.
I do indeed, yes.
So what brings you here to Copenhagen?
Well, today I am here to meet new people and make new connections and maybe make new friends, um, and to learn a little bit about what's happening in the Nordic fintech environment, um, and also, uh, learn a little bit more about what our customers might want from our product.
No, excellent. You're obviously here to represent a company.
Yep.
Which is the company that you represent and what do you do?
Yep. So the company is called Proveneer and they're a business that's been around about 20 years or so. So really established global business and we're in fraud and financial crime and credit risk, customer management and collections. So it's a platform that allows you to do all of those things on one platform.
That's amazing. That's a lot of different things, if I may say.
Yes. Yeah.
Now I know that you guys are also sort of evolved, involved better with AI technologies.
Absolutely. Yes.
Can you tell a little bit more how that has been used today?
Yeah. So when you're— so our platform is used for orchestration of different data sources, but also to then take those orchestrated data sources and make decisions from them. them so you can build a decision flow. But what we want to help our customers do is to be more efficient in that, in that process. So not just setting up the configurations in the first place, but also as they use the software over time to make sure they're optimizing the strategies and the rules, the decision flows, to get the best out of all of the different data that they're— that's coming through that system. So we use AI to optimize those decisions and to help customers get the most efficient routes, but also on the later side to use AI to understand a little bit more about what's happening with their customers and maybe help them to get more of a view of their customer demographics and where they should go from a strategic perspective as well.
Would you say that the decision-taking part, it's the glue between the different product lines that you have?
Yeah, absolutely. So bringing together all of the different data sources. So for example, when you're onboarding a new customer, you want to understand their creditworthiness. You want to understand their KYC, their fraud risk, and also potentially some AML elements as well. So PEPs and sanctions, that kind of thing. And the glue part is to be able to bring together all of those different elements and get a view, a holistic view about that customer so you can provide the best service for them. So which are going to be the best products for them at what credit rating, what pricing? And also if they have any fraud risks that come up, do you want to— how are you going to handle that through their customer journey? So you're going to put a flag on that and you're going to monitor it. Are they maybe at risk of being a fraud victim? So you want to be able to monitor that over time. And then when it comes to the later part, so maybe they've gone delinquent or, you know, something's gone wrong on that credit side, you want to look at the collections and how best to reach out to them and how best to get the best, you know, best outcome in that situation.
Would you then somehow sit between the the traditional product systems or the core banking systems or the compliance systems. And I think on the other hand—
Together, yes.
And on the other hand, probably the CRMs where you actually have touchpoints with your clients.
Yes, absolutely. Exactly that. So we— what we are is the hub in between of all of those systems, bringing all that information together so you can get insights into that.
And Sophia, I think when I was doing some investigation about Provenier, that I read something about deepfakes. Was was I correct?
Absolutely, yes. So when you're onboarding a new customer, typically you don't have any information about them. So what's going to happen is you need to be able to validate their identity and verify that information. And so typically what you're going to do is you're going to ask them for some details about themselves, and they might use identity documents, for example, or give you a proof of address, or you might. Need additional verification to be able to do that. And so as part of that process, sometimes, you know, if they're a bad actor, for example, they might be using a stolen identity or synthetic identity or even ID documents which they've manipulated in order to, you know, kind of use other people's details that they might have got hold of. And so that's kind of where the deepfake is getting involved. So with the paradigm shift in generative AI, which has happened over the last 2 years, what we're seeing in the market is a real increase, something like 31-fold increase.
So, wow.
Huge increase in using ID documents and, and various documentation which is gen— which is was produced by generative AI. So they have not—
extremely easy to do also, right?
Exactly. So it's extremely easy to create it. They don't need any coding experience. You know, they're able to do this on a vast scale, whereas before you would need to use highly skilled technical people who had image processing capabilities, and, you know, they'd be there for hours Editing the images. Yeah.
Now it's just a prompt and you got it, right?
Yeah. Well, yes, a few prompts to make it, yeah, to make it easy.
A few prompts. Black and white.
Exactly. Yeah. So, um, with that, with that capability in anyone's hand, anyone who has an internet connection now has access to generative AI, LLMs, you know, ChatGPT.
Mm-hmm. And, and Sophia, you mentioned documents that are pretty much regular, regulated documents like a passport or a driving license.
Absolutely.
Does it also go further than that? Like, uh, maybe a video of somebody? Uh, yeah, I think liveliness check would come in, but, uh, would it also be like, uh, I don't know, a voice, a video? You can really go very far in that sort of, uh, new world of creativeness, right?
Yeah. So there's some, some more basic documents even. And, um, so in the UK, for example, just to validate An address sometimes.
Proof of address.
Proof of address. So that will come from a utility bill, for example, or council tax bill.
Yeah.
So that's kind of on the basic side of it. But as, you know, the kind of detection platforms have got more sophisticated, we're then asking customers to provide their passport, plus they need to do a live selfie. But Fraudsters are kind of getting around that as well by using deepfake videos, so they can insert those into the kind of projection routine as well. So we have to think outside the box about how we're going to be able to detect these types of attacks.
No, absolutely. And what I also liked about your offer is that you combine another magic sauce, which is low-code/no-code.
Yes.
So you allow the, the users actually to make decisions themselves.
Absolutely. Yeah.
How do you see the, the actual pickup by the users using that sort of platform? Are they still relying— well, are they still using you guys as professionals or do you really see that they literally do it themselves?
Yeah, that's a really good point. So, and I think a lot of businesses in our space talk about low-code, no-code. And in my experience, I've not seen that work in practice as well as kind of marketing—
As it could.
Yeah, as it could, all the marketing kind of side of it. But since coming to Pruvineer, and I've only been there for about 7 months or so, so still learning as well, I've been really impressed by the way that customers can basically do maybe one phase of a project with our professional services team, who are a team of domain experts within credit risk and fraud as well. And then because the, the architecture and the design of the solution has been put together, that helps the customer to be able to do all of their second lot of configuration and any changes. They can just completely do that themselves. It's fully drag and drop.
Very intuitive.
Like, I had never seen an interface like that, and I was thinking, wow, this is a great product. Like, just really easy to use. Um, you can make all your changes, you can test it in the sandbox, and then you can promote it to live.
Oh, great.
And it just doesn't have any of the kind of, oh, you know, I'm gonna have to spend hours trying to, to make these changes, and I'm gonna have to call up tech support. And, you know, it doesn't have any of that. It's been really well thought through, and I think Part of that has come from the fact that we've been around for a long time.
Uh-huh.
So it's a, it is a mature platform, but also the way that we like to do product management at Proveneer is very customer-led. Um, so we'll hold forums, we'll get feedback from customers, and the kind of feedback loop is very quick for that. So we—
Hence the reason why you're here.
Exactly. Yeah, exactly why I want to talk to customers and see what they think of the solution.
Brilliant.
Yeah.
There's 3 other words that also strike out for me, and it's real-time.
Yep.
120 and data partners. Maybe that could be 2 words. So maybe 4.
Yeah.
If you could go a little bit more maybe in the 220 data partners, because that's a lot.
Yes.
What sort of data is in the system?
Yes. So just previously I mentioned that we're looking at the applications, the onboarding, loan originations, that kind of thing. So, well, what kind of data will you need? You'll need to have information about the creditworthiness of that particular customer. And depending on which country you're in, that can be acquired in different ways. So there might be credit bureaus, but in some countries there's also government bodies that provide that information. And then there's also kind of alternative ways to get that information as well, through open banking, for example.
Based on history.
So newer types of approaches to trying to understand customers' worthiness, creditworthiness. And then you've also got the KYC fraud AML side. So you want to be able to understand the customer. So does this identity exist? We can validate the name, address, the date of birth, email address, that kind of thing. But then we want to verify the customer. So then you've got to look at other details that might help you to triangulate that information to get a sense about whether or not that is actually who they say they are. Is that the person you're talking to? So you might look at things like the device—
Non-repudiation.
Yeah, exactly.
To throw out the difficult word.
Yeah. So device, behavioral biometrics. So information about how they're operating on those platforms. Even social verification. So how many times have we seen that email address? Is it active, the email address? How old is that email address? So we can plug into all of these different types of data partners. And because we're global, there might be different data partners for different regions. So we're also going to be able to advise customers on which regions and which data is going to be best for them.
Okay. Well, to be honest, we're almost at the end of our podcast. Time flies.
Oh, that's a shame.
I was really enjoying this. Yeah, me too. Me too. I was surprised, like, whoop. So with all that kind of interesting information, Sophia, how do they best come to you?
How do they best? Oh, right. So they can reach out to me on LinkedIn.
Excellent.
Or you can go to the Proveneer website. You can ask for a demo. Or if you're here today at the fintech event, you can come and speak.
Just pass by.
Yeah, come and speak to us at the booth.
Excellent. Thank you very much for joining me. Thank you also to the audience. You're welcome. Thank you also to the audience and stay tuned. More news from the fintech world. Thank you very much.
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