982. Insights: Things just got personal - The case for better personalisation in financial services

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1:10Today, we're diving into a topic that's reshaping the way customers interact with their banks and fintech apps. Personalization. What does it really mean to create personalized experiences in financial services? Is it just about offering custom product suggestions, or is it about rethinking how we build, design, and deliver value to each individual user? With consumers expecting even more relevance, and 91 % of people saying they're more likely to engage with brands offering personalized recommendations, fintechs and banks are under increasing pressure to deliver smarter, more tailored experiences.

1:44I'm David Barton-Grimley, and in this episode, we'll unpack why personalization has become a strategic priority for fintechs, how it's boosting customer loyalty and driving competitive advantage, and the role of emerging technologies from AI to chatbots in taking personalization to the next level. We'll also explore how data, both online and offline, is being used responsibly and effectively, and what it takes to build trust in a world where 48 % of consumers say they're willing to share more data for better service. So let's dive in and see who's on our panel today. Firstly, we have a FinTech Insider return for Daniel Gold, CEO of Stratify.

2:19Thank you for joining us today, Daniel. Tell us a little bit more about Stratify. Thanks for having me back. So what we're building is essentially your wealth manager in your pocket. So Stratify is a mobile app that enables everyday investors to create their own investment strategies so they can benefit from sophisticated investing and risk management techniques, but to do so in an accessible and fun format. Awesome. Welcome on board. And also with us today is Fernando Dobal, Director of Product at Clio. Welcome back to the show, Fernanda. What have you been up to since we last spoke? Great to be back.

2:54We've got some exciting things planned soon, but one big update for us is we recently reached a million monthly active users. So we've been working on providing personalized insights to a lot of people. Yeah, excited to hear more about that. And last but not least, we have Ken Hart, CEO of Snowdrop Solutions. Welcome to the show, Ken. Could you tell us a little bit more about what Snowdrop does? Sure, thanks for having me here, Peter. Snowdrop's been around for about 12 years. We're a UK company. We provide transaction enrichment and AI capabilities for retail banks. So today we power over 2.5 billion transactions.

3:33We clean up the transactions on a monthly basis. And we work with about 60 banks and all the transactions over 200 territories. So very pleased to be here. Amazing. I mean, I think what's awesome about each of you is that individually you come from kind of different angles on the personalization debate. And so on that note, why don't we start with a bit of a definition of what we think personalization is today, you know, in 2025. So I, for one, have been talking about personalization for well over a decade. It's like a big chunk of my career in consulting is how do we personalize? How do we really do this?

4:09But what is it today? So I'm going to start by going around the panel. Daniel, I'll come to you first. How do you define personalization and how are you kind of deploying it in what you do? Yeah, so I mean, the way I think we define personalization is kind of data-driven insights to deliver a sort of timely and engaging solution that enhances customer satisfaction and financial outcomes. But I think it's important to draw a distinction between kind of the illusion of personalization, which is choice, and true personalization, which is where each customer gets a bespoke solution or service. So that's kind of where I'm coming from.

4:57And an example of that is sort of the traditional order for robo-advisors where they were assigning each investor to a risk profile and then assigning a portfolio to them. So everyone ultimately gets the same portfolio, whereas I think you can go a lot further than that and provide a truly bespoke portfolio to each client. That's where real personalization comes in. Fascinating. And Fernando, what do you think? Yeah, for us personalization is really about meeting our users where they are. So we're building the world's first AI financial assistant and so for us it's not just about what you say but also when you say it because we're talking about behavior change and helping people reach their own financial goals.

5:36It's important to have that relevant information, and relevant insights to meet them where they are. So I think of it both in terms of content and when we reach out. Awesome. Ken? I agree with both the speakers. I'm going to add a little bit more details, if you will. It's not only, I would argue, the what and the when, but it's also the where. And I would call this more contextually aware. So, you know, if I look at my banking app today, pick whichever one you want, all those transactions are mine, right? They're personal. problems, I don't understand them. They don't make sense to me. They're not relevant in the where and the when.

6:14So I would argue personalization, I think Daniel said, can be very elusive. It's really about building context. And then when you have that clarity in that context, then you can really understand what people are looking for. Yeah, I 100 % agree with that. And Daniel, it'd be good to get your perspective on the kind of global view. How are you seeing different kind of markets and adapt to different personalization laws and different perspectives and behaviors on how you would do that. And it's a question for each of you as well to jump in on because what is personalization to one customer in one country or in one sector is going to be very, very different.

6:58I mean, like the example of transactional banking data versus financial advisor personalization are in some ways very, very different, right? Yeah, I mean, the global view kind of depends on a lot of different factors. I mean, different markets are more ready for personalization, and that comes from a regulatory side of things, and also from the readiness of consumers. But on the regulatory side, I mean, there's a couple of regulations here in the UK you can look at, which are quite progressive in terms of personalization. I mean, consumer duty is a big one that's come in the last couple of years.

7:35And that recognizes at its core that personalization is a key benefit that the FCA wants to promote. But that needs to be reconciled with the traditional oversight function of the FCA, which is imposing this advice guidance boundary. So they are also limiting personalization and for good reason. So that is something that the FCA is reconciling at the moment. But the FCA, I think, as I say, taking quite a progressive stance. They're also looking at relaxing their constraints, for example, by introducing targeted support rules, allowing for simplified advice based on identifiable factors. So this means that you can start categorizing customers into certain segments and then saying that this particular product or service might be appropriate for you based on what category you fit into.

8:28So I think there's a lot of regulation which is coming in the UK which is promoting personalization. And in terms of, you know, to take it a bit further, open architecture, open banking and open finance, I think the UK was at the forefront of this whole movement. And that's really sort of turbocharging personalization. But taking a global view, I think the UK has been recognized slightly falling behind in that in the last few years in Europe and like Australia are overtaking. at the moment. So there's, you know, different markets are at different stages, but I think the general direction of travel is still towards personalization on the whole.

9:07Yeah. And I guess as more data becomes more available and more standardized, then, you know, you can then do something with that, with that data. I suppose there's been one of the issues with open banking is that there's just not much data available. Yeah. There's transactional data and all of that kind of stuff, but to get that holistic picture of a customer, you need, you need just much more data sources. Fernanda, I'd love to get your perspective. Is there anything that you're seeing maybe in the market in the US, for example, with where Clio operates that's maybe different? Yeah. I mean, I think that for me, the big shift is around consumer behavior, consumer expectations of personalization, but also AI more broadly, right?

9:48We're looking at conversational interfaces having gone full-on mainstream in the U.S. And we did some recent research showing openness to using AI and this big shift that's happening as people become more comfortable with these technologies. And we see finance is such a taboo topic. It's something people feel a lot of shame around. They don't want to admit they don't know yet. And so sometimes personalization is just the right information at the right time or the right educational content at the right time. I don't want to admit that I don't know what's going on with my 401k, my pension in the U.S., to my peers.

10:24And so then I can ask an AI, I can start to talk about what are the gaps in my own behavior that I should be mitigating. And so from that perspective, we see a really interesting shift. People aren't Googling anymore so much as they are using these tools. And it's how we position ourselves, not just, you know, we don't give regulated financial advice at Clio. it's more around closing that gap around managing your personal finances. And we see there's a huge demand for that, increasingly so with AI. Yeah, because I guess AI is going to give the customer the ability to access that knowledge in a much easier way, whereas, you know, it used to be through kind of interfaces and graphs and UI, which in some ways I found has been very difficult to kind of show.

11:11Right. And so personalization can be, you know, I've got these insights about your spending, about your data, these patterns that are relevant to you, but it can also be this generic piece of information that I know you're missing presented at the right time. Yeah, 100%. Ken, what are you seeing from the kind of the technical side of things, like the availability of data, I suppose, to provide these insights? Have there been any major shifts? You know, it's still a long, hard slog, right? So if you think about just transactional debit or credit card data, we've been cleaning this up now for eight years.

11:47And if you're right, as the point you made earlier, open banking is just a poor cousin of already bad transaction data. And so it's really hard to come up with those signals about user behavior to ascertain what's going on. But if you take a step back, at least I'm not going to talk about the wealth management that, you know, the other people could talk much better than I. If you look at what's called PFN, personal finance tools, they've been around for seven, eight years. Five to 10 % of people use them, no more. It's exactly what you said. No one clicks on the charts or the graphs. It's not engaging.

12:20It's not meaningful. To tell me that I'm out of money doesn't give me more money, right? And so what people really want is be it the natural conversation that Fernanda's talking about, you know, you can actually have a conversation with someone and it's intuitive. So our big belief is that you need to enrich in what poor data or existing data is out there. You need to contextually blend it together. And then you create what we call intuitive experiences. So, you know, if I asked you, David, how much does your car cost? You know, you would have to go chronologically probably through all your different transactions.

12:55Well, that was gas, that was parking, that was the repair shop, that was Department of Motor Vehicles, right? Instead, an interface could just pull that together and say, you're spending X, you probably should lease instead. You may save some money. So that's the difference from coming from very poor graphs and charts on PFMs that people don't engage with. And actually talking a natural language with people and making it intuitive. The right thing, the right way, the right subject matter that I want to talk about. Yeah, 100%. And building on what you were saying, you know now we have maybe slightly more dependable data sources you've got an ai that has the ability for you know a customer to have conversations or at least interpret the data that they they see and ask it something ask something of it fernanda i want to come to you as you know because clio is a very interesting case study for this because um clio i think was one of the very first fintechs out there that was allowing that kind of conversation between the customer and the fintech as a as a as a first principles way of interacting i mean i remember all the way back eight years ago when when clio started that that was it right it was the it was the chat window you could talk and interact with it what do you if we fast forward now to 2025 what do you see in customers ask and you know the extent to which they want that that personalized um experience versus just tell me, you know?

14:22Yeah, I think it's a real mix. From what customers are asking, I think one of the things that brings a lot of value is being able to see all your information in one place so we can connect multiple accounts and really have that big picture view. But we do have an insight that people don't always know what they don't know. And so being able to proactively reach out and kind of preempt what's going on in a person's journey, whether that's your paycheck just came in, Do we need to talk about how you're going to spend it for the next month? Do you have bills coming up? That sort of just-in-time interaction is really important to us because, like we said before, your financial health can be taboo.

15:02It can be something you're kind of, oh, I don't even want to look at it. I know I overspent on my credit card. And so initiating that conversation is super important. But we have this great feature, for example, called challenges, where people can set up a spending challenge for the week ahead, two weeks ahead for a particular category. And we've seen users curb spending by over$12 million by using these challenges and kind of chip away these micro behaviors, which is really exciting. That's very cool. Daniel, what's your perspective on this in the kind of wealth industry? What are people asking?

15:41So it's a slightly different approach for us. I mean, I think the sort of chat approach is hugely powerful, and it's certainly something we've got our eye on, and I think it's going to be part of the future. But the way we use, you know, AI for personalization is slightly different. We're using more traditional machine learning techniques for parameter optimization, so it's kind of lower down the food chain. But people, you know, to answer the question, it's similar to what Fernando was saying. They don't always know what they don't know. They can give a view on what they want to achieve in terms of goals, objectives, investing style.

16:25But I think they want to rely on that combination of inputs plus a sophisticated investment engine behind the scenes. That combination of tools gives the real power to people. So giving the choice and the inputs in a digestible format and then hiding away the complexity and the processing behind the scenes is what we're seeing it's what our view is or what people want abstract out that complexity give me a few controls that allow me to personalize to an extent otherwise just do do the thing for me that's very interesting and I want to pivot the conversation to protecting the customers and security And I think, Ken, it'd be very good to get your perspective on this, that kind of meta view, all of those billions of transactions that you're looking through and standardizing and cleaning.

17:21How does personalization enhance a customer's security? I mean, I guess there is this balanced trade-off between knowing a lot about the customer, but then maybe also knowing too much about the customer and getting to a point where, I don't know, maybe you're beginning to step a little bit too far into privacy. I mean, how do some of your customers maybe think about that? Yeah, I'd like that. There is definitely a spectrum. You know, even if you look just in Europe. So, for example, we have customers that in the UK deploy everything. You show on a map where people are spending their money. People are pretty comfortable doing that now, at least in the UK.

18:01That wasn't the case a few years ago. And that transparency, here's where you're spending your money, click, get more detail about it, builds trust. I also have customers in, say, Germany that literally freak out whenever they see a map. And they're very arguably, I would say, obsessed on privacy. So just even in Europe, the consumer behavior is radically different. We also have customers to do stuff like, this may be germane today with some fines that have been levied recently to the FCA, people who do KYC. So they'll register for an account. Maybe they've given up the perfect address, you know, Buckingham Palace or, you know, 10 Downing Street without naming names.

18:43We all know what I'm talking about, right? But what we can also do is say, well, why don't we track your phone for the next 30 days if you're comfortable with that? Because maybe you don't have a utility bill that you can snap and share to confirm your address. So it's really getting that trade-off between convenience and really security. So we work a variety of ways. There's no one silver bullet, if you will. That personalization is just more secure. In fact, if anything, at least with the big traditional retail banks, the more personal information, the more risk averse are the banks and the more fearful they are.

19:21Yeah, I guess in some ways it gets terrifying as you're ingesting more and more and more information. You then have to figure out what to do with it. I mean, Fernanda, how do you think about those trade-offs between knowing lots and lots about the customer and their security and finding more and more sources of data to enrich this kind of picture? Absolutely. I think it's one of the reasons why we've decided to build a lot of this in-house. And the more data we have, the bigger responsibility we have with our customers. That's how we like to think about it. And so managing that data thoughtfully from kind of a first principles perspective.

19:57I know in the U.S. it's very different, right? You don't have some of the regulations that you have here in the U.K., but a lot of our product team is here. And so that's the way we approach and think about these things is with this U.K.-centric view. while respecting the regulations of the US. But yeah, I think even when looking at how we work with AI, for example, and what kind of data we're going to send or how we're going to process that data to ensure that people are seeing reliable information when we're using LLMs, for instance, is something we do very thoughtfully. Interesting. Daniel, how do you think about it?

20:32So I'm an optimist at heart. So I think the opportunities are vast when you have access to more data. So that's the basis of how we've built our whole kind of business cases. Getting access to data gives you the ability to provide professional style oversight and investing techniques. But that oversight extends into things like trade surveillance, fraud detection, transaction monitoring, which are techniques which are employed in a sophisticated way within banks, but not always done so in the wealth management and investment management space. But I think they have huge potential. I mean, I think everyone can relate to the case when you get like a bank calling you up about a transaction and blocking it until you've approved it.

21:21It's a bit of friction, but we all appreciate not being as susceptible to fraudsters as we might otherwise be. So that's the benefit I see. I think you kind of touched on an important point though that If this becomes too personal or too intrusive into someone's behavior, then it becomes creepy. And that's a fine line to paraphrase. I think it's the CEO of WealthCX, but it's a quote which I thought resonates quite a lot in this context. Yeah, it definitely does. You definitely don't want to be creepy. That's for sure to your customers. And on that note, we're just going to take a quick break. Back shortly.

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23:09Welcome back to FinTech Insider Insights. And in this next part, we're going to be diving into how we can build better personalization in this current climate whilst navigating changing needs and new technologies. So let's dive back in. So before the break, we were talking about the trade-off in, you know, maybe being too creepy, I think, as Daniel was saying, versus security and privacy. all of these kind of trade-offs that you need to make in personalization. I think it's worth having a discussion also around data sources. So, you know, where do we see in the future more data sources that are going to be powering this personalization?

23:44Because at the end of the day, you can have an LLM that sits on top of something and do something great, but that LLM has to be powered by very good quality data that comes from somewhere. So we were talking about open banking in the first part in Canada. And I think it might be worth coming to you for that kind of meta view. Like, you know, where do you see, you know, better sources of data coming in? Is open banking, you know, going to be that source? Probably not, to answer your question directly. So the example that I have in mind is we're working on a project to help people from the Middle East to invest in real estate in the UK.

24:20Think of the first step towards mass affluent, high net worth individuals. And what we're using there is nothing with open banking data, right? We're using maybe some of the people's spending behaviors and income and so forth. But what we're really doing is linking to Zoopla, Rightmove, Land Registry, and other data to sort of a-ground the AI. That's real property. It exists. Here it is. Here's the valuation, et cetera, et cetera. So it's important to be able to think beyond, frankly, the banking sector or the financial services sector and pull in really good data sets from other sectors. Real estate, we do a lot with Maps, right, with Google Maps.

24:59That's part of our core business. So we're very familiar with that. But I'm sure other industries will pull in stuff from maybe insurance or healthcare or whatever it may be. But I think you need to look beyond open banking data. Yeah. Daniel, what do you think? Yeah, I mean, the way I think about this question is kind of the short-term answer and a long-term answer, at least in the context of our business. So short-term, we're dealing with the traditional problems of data sources that banks and wealth managers always access. So pricing data feeds from different trading exchanges, and this is a perennial problem.

25:35It's a complex challenge, and we can probably have a podcast, or at least I could have a podcast on that all in itself. but the personalization doesn't come from those data sources as such. It's more in how we use the data and the derived data we generate from it. So we do personalized analytics for each user based on those common data sources. So for example, if you want to invest into US tech stocks, we'll analyze those according to your criteria and generate those bespoke signals for you. So I think distilling my answer down is that I think we can create new data sources nowadays using cloud computing and sophisticated AI.

26:18But to take a longer term outlook, again, from the context of our business, I think there are actually really interesting opportunities in open finance and open banking. You know, we can, you know, I'm not saying this is what we can do, but there are, you know, ways you can incorporate open banking, open finance data to create a whole budgeting. app so you can incorporate your investment lifestyle along with your spending patterns and look for opportunities to save costs on your bills and transfer those into your investments. And creating that holistic solution to people is possible now with these new data sources.

26:59I think it's a really exciting future. Yeah. Fernando, what do you think? Daniel, were you just describing Clio? Maybe. Oh, what a plug. I love that. No, so bear with me as I get a little bit technical, but I think one thing we're seeing that's really exciting in the context of LLMs and AI is this idea of making data interoperable. So Anthropics come out with model context protocol and MCP, it sounds like a fancy techie thing, but really you just think of it as a USB-C port for data towards LLMs and frontier models. So how will data sources communicate with these frontier models so that can be ingested in real time in a way that lets us unlock some of these opportunities?