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The Connector Podcast - DFS Digital Finance Summit - Bridging Data and AI: Bastien from Dataiku on Transforming Collaboration Across Industries
On our latest episode of the Connector podcast, business transformation director Bastien from Dataiku joins us live from Brussels to unravel the evolving landscape of data and AI initiatives. Whether you're a coding expert or prefer a more visual approach, Bastien demonstrates how Dataiku's groundbreaking platform redefines collaboration between data specialists and business professionals. Discover how this unique synergy simplifies the data science process and enhances transparency and trust throughout the AI project lifecycle. With over 600 global clients, including major players like BNP Paribas and Morgan Stanley, DataIQ is leading the charge in preparing organizations for upcoming regulations like the Data Governance Act.
Tune in as we explore the profound impact of data collaboration within cross-functional teams and how Dataiku's tools are accelerating and amplifying AI initiatives across various industries. Bastien provides an insightful look into the company's substantial influence in the banking and insurance sectors while also shining a light on their ventures beyond finance. Learn how the platform bridges the gap between AI builders and consumers, enabling businesses to monetize their data and achieve unprecedented scalability in the fast-paced fintech environment. This episode is packed with insights that could transform how your organization leverages its data assets for innovation and efficiency.
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Koen Vanderhoydonk
koen.vanderhoydonk@jointheconnector.com
#FinTech #RegTech #Scaleup #WealthTech
Welcome to the Connector podcast, an ongoing conversation connecting fintechs, banks and regulators worldwide. Join CEO and founder Cohen van der Hooydonk as you learn more about the latest available trends and solutions in the markets.
Speaker 2: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?
Speaker 3: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.
Speaker 2:And can you elaborate a little bit, because I'm just very curious.
Speaker 3:Yeah, of course, Let me explain also what DataIQ is about 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 sets us apart also, you know from, I would say, the rest of the industry here that we drive democratization. Okay, because data both data experts and business experts can actually, you know, 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.
Speaker 3:We also drive acceleration because through DataIQ, the end-to-end process, the data science process, can be simplified, can be automated with previous recipes for data prep, with previous models that are integrated within the platform, etc. And we also drive trust because the full life cycle 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.
Speaker 2:Which comes very close to what is required in the Data Governance Act.
Speaker 3:Yeah, indeed, and so we are actually helping customers like Macquarie, like Convex, in the banking space to anticipate these upcoming regulations.
Speaker 2:Are you only active in the banking space, or is it more wide?
Speaker 3: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, credit Agricole, axa, generali, etc. For example, in banking. Bnp Paribas is working with us across many entities, including risk and stress testing.
Speaker 3: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 five times faster actually leveraging our platform.
Speaker 2: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?
Speaker 3:Yeah, so it's really a core part of our value proposition and the reason is that IQ 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, 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.
Speaker 2:Well, and what you see in the finance and industry is that many banks and insurers they want to sort of make benefit from their data, so monetize the data, as they say. 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?
Speaker 3: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 get so much information about your customer, where you get such a breadth of data to monitor for regulatory purposes. So we think that definitely the banking and the insurance industry are more innovative in that space than other sectors. Mm-hmm.
Speaker 2: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?
Speaker 3:It's a very good question, and a passionate one. 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. That's sort of disappointing no, just kidding. 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, every week, and so instead, 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.
Speaker 3:And by this I mean to keep flexibility, to maintain the optionability in your tech staff 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 DataIQ. 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.
Speaker 3:That you can switch your LLMs so that you can switch your data lake or your cloud investment, depending on what's good for you and what will be good for you. Switch your LLM so that you can switch your data lake or your cloud investment.
Speaker 2:You know, depending on what's good for you and what will be good for you in the next two, three, four, five years.
Speaker 3: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 a customer to build these ai projects, you know on the platform yeah, and to collaborate on them okay.
Speaker 2:Um, now we're here at dfs here in brussels and one of the teams is natural intelligence and it's a very sensitive question in a way, because ai and humans how do they go together?
Speaker 3:it's it's a it's. It's a great question, and indeed, when you watch Terminator or things like this, we are right to think about it. In the business, humans definitely play a capital role and it's really a core part of the philosophy of DataIQ. And when I say human a capital role in AI, and it's really a core part of the philosophy of DataIQ. And when I say human, I'm just. I just it goes beyond data scientist.
Speaker 3:Okay, 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 person that understand the data.
Speaker 3:They also know the processes, the business processes, and they know what needs to change to embark AI into these processes.
Speaker 3:They are the ones that will consume also the AI insights, the output of these AI use cases, and they are 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. 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 that are really scaling self-service analytics, scaling citizen data program within their organization, leveraging data IQ 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, okay, because if you're embedded data, and ai within.
Speaker 3:You know it is a business day-to-day of everyone. You're really helping them to upskill. You're making their job more interesting and more appealing.
Speaker 2:I guess what you're saying is it takes two to tango.
Speaker 3:Yeah, indeed.
Speaker 2: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?
Speaker 3:Yeah, and we were discussing scaling and actually I mean, you're right, it's critical as well to scale with governance. 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 portfolio? And so here here, indeed, dataiq's latest solutions when it comes to Gen AI, to governance, are helping our customer in banking and somewhere else, to actually manage this complexity and to establish a centralized governance in many ways, with a different set of capabilities, such as a centralized control tower to get a full visibility on all AI initiatives, such as, again, a requirement for the AI Act Indeed yeah.
Speaker 3:And we also have actually, you know, 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 project's template framework to enforce specific standards for every AI user. We also have capabilities that are bringing guardrails for Gen AI 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 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 care to the pace of change within your organization.
Speaker 2: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?
Speaker 3:find you. So I'm Bastien Durand. You can find me on LinkedIn. You can check out our website. A lot of content is available there and yeah. I'm glad to get in touch.
Speaker 2: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. Thank you for having me and have a nice DFS, and thank you also to the listeners.
Speaker 1:Please stay tuned. More to come. Thank you very much. Bye-bye, bye. Thanks for listening to another episode of the Connector Podcast. To connect and keep up to date with all the latest, head over to wwwjointhekonnectorcom or hit subscribe via your podcast streaming platform.