In this episode of The Connector Podcast recorded at the DFS Digital Finance Summit in Brussels, host Koen Vanderhoydonk interviews Bastien Durand, Business Transformation Director at DataIQ (formerly Dataiku). Bastien explains DataIQ’s AI and analytics platform, emphasizing its ability to democratize data science through a blend of low‑code/no‑code visual tools and full‑code environments, enabling both data experts and business users to collaborate on end‑to‑end AI projects. The platform accelerates development with pre‑built data‑prep recipes and integrated models, and it builds trust by providing full lifecycle auditability, transparency, and governance features that align with the EU Data Governance Act and AI Act. Durand highlights the company’s broad customer base of over 600 organizations, with a strong focus on banking and insurance (e.g., BNP Paribas, Morgan Stanley, Aviva, AXA, Generali) where DataIQ helps automate stress‑testing, pricing, claim management, and marketing, delivering speed‑ups of up to five times. He stresses the importance of data collaboration, upskilling business teams, and the synergy between human expertise and AI, describing the platform as a “human‑AI partnership” that makes AI accessible to everyday users. Looking ahead, Bastien predicts the emergence of planning‑capable AI agents and stresses the need for flexibility: DataIQ acts as an orchestration layer that decouples AI services (LLMs, cloud data lakes) from applications, allowing organizations to swap models and infrastructure as technology evolves. The platform also offers a marketplace‑style integration of the latest AI tools. Finally, the conversation turns to regulatory compliance, where DataIQ provides centralized governance “control tower” capabilities, pre‑built AI‑Act‑aligned templates, automated workflows, and GenAI guardrails that manage cost, security, and compliance without hindering innovation. The episode closes with contact information (LinkedIn, website) for listeners interested in the platform.
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Welcome to the Connector Podcast, an ongoing conversation connecting fintechs, banks, and regulators worldwide. Join CEO and founder Koen Vanderhoydonk as you learn more about the latest available trends and solutions in the markets.
Welcome to another podcast from DFS by the Connector, live from Brussels, and I have here with me Bastien. And Bastien works at DataIQ. And I'm very curious, what do you do and where are you from?
So very nice to be here. Thank you for having me. So I'm from France and I'm the Business Transformation Director for DataIQ, advising customers in their value roadmap and also in their operating model.
And can you elaborate a little bit? Because I'm just very curious.
Yeah, of course. Let me explain also what DataIQ is about.
Thank you.
Leading platform for AI and analytics, enabling data experts, business experts to collaborate on AI initiatives and to bring this initiative across their organization. So together they can work on data prep, on extracting data, on designing, developing, deploying AI initiatives. And I think what's sets us apart also from, I would say, the rest of the industry here, that we drive democratization. Because data, both data experts and business experts can actually collaborate on this complex initiative no matter their skill set, because they can leverage our interface, which is low, no-code, but also full-code. We also drive acceleration because through DataIQ, the end-to-end process, the data science process can be simplified, can be automated with pre-built recipes for data prep, with pre-built models that are integrated within the platform, etc. And we also drive trust because the full lifecycle of the AI initiatives can be tracked. Every step can be tracked within the platform. And that's actually driving auditability. It's driving transparency and governance.
Which comes very close to what is required in the Data Governance Act.
Yeah, indeed. Indeed. And so we are actually helping customers like Macquarie, like Convex in the banking space to anticipate these upcoming regulations.
Are you only active in the banking space or is it more wide?
No, it's a good question. We're actually working across many industries. We've got more than 600 customers globally, but I would say that only a third of them are actually in the banking and insurance industry, which is a significant part. So it's a top priority for us. And so we're working with companies like Morgan Stanley, like BNP Paribas, Crédit Agricole, AXA, Generali, etc. For example, in banking, BNP Paribas is working with us across many entities, including risk and stress testing. Now they're automating tens of thousands of stress testing scenarios thanks to us. And in insurance, we're working, among others, with Aviva in the UK. Their data science team is leveraging DataIQ for marketing, for pricing, for audit, for claim management AI use cases. And they are now 5 times faster actually leveraging our platform.
Well, earlier you mentioned the word data collaboration. And I was wondering, because if you look at cross-functional teams, people are all using data and they're all trying to create value. Is that something that works better using your tool?
Yeah, it's really a core part of our value proposition. And the reason is Dataiku enables actually teams with various skill sets to collaborate on these data and AI projects. So no matter if they like to code, if they like to code, they can just do Python, R, use their own Jupyter Notebooks. But if they don't know how to code, if they are business experts, then they can just leverage a very visual, no and low-code interface. So it's bringing together basically the AI builders and also the consumers. It's bringing together data and business teams. And in the end, you're right, it's really generating value because You need to embark the business in order for your AI initiatives to be relevant and to be impactful. And also, this is a way to upskill your organization and to demultiply the number of AI initiatives that are actually taking place. So really bringing scale into your AI motion.
Well, and what you see in the financial industry is that many banks and insurers, they want to sort of make benefit from their data, so monetize the data, as they say. Do you see a difference between the bank sector or the more financial sector and the other sectors that you provide businesses to or services to?
I would say that data is a priority for every sector. But it's true that there are not so many sectors like banking where you've got so much information about about your customer, where you've got such a breadth also of data to monitor for regulatory purposes. So we said that definitely the banking and the insurance industry are more innovative in that space than other sectors.
A lot of things are happening in the space, and the product that you describe sounds very innovative. But more as a general question, what do you see as the next steps within the realms of AI?
It's a very good question and a fascinating one. And I'm convinced that we will see planning-capable AI agents in the very near future, if not already. But if I'm truly being honest here, I think the reality is that we don't know. Okay. I mean, what we—
That's sort of disappointing. No, just kidding.
Yeah. But what we know, however, for sure is that AI is changing fast. We know that it's unpredictable. We are seeing new LLM models outpacing others every month or every week. And so instead of— I mean, while it's important, of course, to think about the future of AI and what it will be, I think it's equally as important to try to stay future-proof.
Okay.
And by this, I mean to to keep flexibility, to maintain the optionability in your tech stack so that you can switch your models depending on what makes sense at a given point in time. And so that's part of the innovation that we're actually bringing within Dataiku, within the platform. We are an orchestration layer that can help you decouple the AI services that you buy, the LLMs, to the AI application. That you can switch your LLM so that you can switch your data lake or your cloud investment, you know, depending on what's good for you and what will be good for you in the next 2, 3, 4, 5 years.
So you're almost like a marketplace of the latest technologies?
I mean, yeah, we are integrating with the technology and on top of a marketplace, we are allowing customers to build these AI projects on the platform and to collaborate on them.
Okay. Now we're here at DFS here in Brussels, and one of the themes is natural intelligence. And it's a very sensitive question in a way, because AI and humans, how do they go together?
It's a great question. And indeed, when you watch Terminator or things like this, indeed, Indeed. We are right to think about it. In the business, I would say, I mean, humans, they definitely play a capital role in AI. And it's really a core part of the philosophy of DataIQ. And when I say human, it goes beyond data scientists. It's also the business experts, the people working the business in the field, the AML experts, the risk experts, the marketing experts. Because these are the persons that understand the data. They also know the processes, the business processes, and they know what needs to change to embark AI into these processes. They're the ones that will consume also the AI insights, the output of these AI use cases. And they're the ones that will act upon these insights. And if they don't act, no matter how good your modeling is, your system, your technologies, no value will be generated. Okay, so it's really at the core of our philosophy to make AI simple, understandable, accessible to everyone every day through this collaborative platform. And so it actually helps to unlock the power of data within the business. And it helps these companies to scale. And so we've got many customers like BNP, like Morgan Stanley, also outside of banking like GE, like General Electric, so Michelin, etc., that are really scaling self-service analytics, scaling citizen data program within their organization, leveraging DataIQ to unlock the power of human with AI. And I think cherry on the cake also for the person actually doing this, it's not just about unlocking AI with human intelligence. It's also an amazing talent attractiveness dimension. Because if you're embedding data and AI within the business day-to-day of everyone, you're really helping them to upskill. You're making their job more interesting and more appealing.
I guess what you're saying is it takes two to tango.
Yeah, indeed.
And we're almost at the end of this conversation, and it's nice to talk about AI. And it's clear that you say that a lot of banks are using it. And in the introduction, you also mentioned to a small extent regulatory challenges. And since that's one of the themes also at this event, how do you see that link between the usage of AI and the fact of being compliant to regulation?
Yeah, it's— no, and we were discussing scaling. And actually, you know, I mean, you're right, it's critical as well to scale with governance. You know, it's not just about scaling people, etc., but you need to put your house in order in terms of regulation if you want to scale correctly. And it's definitely a challenge, a struggle that I keep hearing from every single customer I speak to. So how can I manage the proliferation of generative AI within my organization? How can I manage the growing costs and complexity from my AI portfolio, et cetera, et cetera?
Right.
And so here, indeed, Dataiku's latest solutions when it comes to GenAI, to governance, are helping our customers in banking and somewhere else to actually manage this complexity and I would say to establish a centralized governance in many ways with a different set of capabilities, such as a centralized control tower to get full visibility on all AI initiatives, such as—
Again, a requirement for the AI Act.
Indeed, yeah. And we also have actually pre-built governance solutions that you can customize but are already pre-integrating some requirements from the EU AI Act. We also have automated governance workflows that you can bring into your projects, templates, framework to enforce specific standards for every AI users. We also have capabilities that are bringing guardrails for GenAI to control the cost of LLM and also the security of LLM for every generative AI projects within your company. And so by establishing this centralized governance, you're allowing your company to actually get the full visibility and to be compliant. But at the same time, and that's very critical, this is seamless to the person actually doing AI. And so it's not detrimental to the pace of innovation, to the pace of scale, to the pace of change within your organization.
Well, Bastien, I think it's very clear why a lot of companies are interested in you and your company. How do they contact you? How do they find you?
You can— so I'm Bastien Durand. You can find me on LinkedIn. You can check out our website. Many— a lot of content is available there. And yeah, I'd be glad to get in touch.
All right. Thank you very much for participating to this podcast.
Thank you for having me.
And have a nice DFS. And thank you also to the listeners. Please stay tuned. More to Thank you very much.
Bye-bye.
Bye.
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