Building AI Around the Financial Advice Workflow With Marloo

[00:00:03] What if the real limit on access to financial advice is the paperwork created by every client conversation? Well, my guest today is the co-founder of Marloo, a company building an AI partner for financial advisors. And after helping create retail investing platforms in New Zealand and the UK,

[00:00:25] he saw that millions of people could access investments, but far fewer could receive personal advice when markets move or life changed. So today we're going to discuss why a one-hour client meeting can create many hours of admin work, but how Marloo is moving beyond AI note-taking and going into a much wider advice workflow.

[00:00:49] And my guest will also explain why his team spent months inside businesses before building the product and how AI can give advisors greater capacity while preserving the judgment and relationships that clients rely on. It's a great one, this one. So enough for me. Let me introduce you to him now. So thank you for joining me on the podcast today. Can you tell everyone listening a little about who you are and what you do?

[00:01:18] Hey everyone. I'm Hardy, co-founder of Marloo. We are building an AI partner for financial advisors and we enable financial advisors to do their best work for every client. And I'd love to find out more about your origin story as well. What put you on that path to creating this? Anything you can share around that or the spark that created it and put you on this path? Yeah. So my background is building retail investing platforms. And as you can probably tell from my accent, I'm from New Zealand.

[00:01:46] So I grew up in New Zealand and helped build a business called Sharesies, which I would describe as the Revolut or the Robin Hood of New Zealand. And began with, you know, a suite of ETFs and brought kind of retail investing to the masses and quickly expanded into kind of broader financial services offering. And kind of there and a subsequent company I helped build in the UK light year, basically just saw the demand for financial advice firsthand.

[00:02:13] Like we built these investing products for millions of people. And it was always incredibly frustrating to me when we could never help or provide people with advice when it was really clear that they wanted to engage with it. The example I'll give you is let's take, you know, historic market volatility, the Trump tariffs or the pandemic. All I could essentially do was email a customer base of, say, a million people and say some version of don't panic. The market goes up, the market goes down.

[00:02:39] And maybe with a chart of the S&P 500 kind of showing historical, you know, compounding returns over the last, say, 50 years. And kind of the problem statement for me is it's not that there's bad financial advice out there. There's just not enough great financial advice available in the world. I've seen, I've experienced the demand firsthand. And so Marlou is setting out to amplify financial advisors and help them deliver, you know, great advice to as many clients as possible.

[00:03:05] And I was reading before you joined me on the podcast today that you've spent months studying financial advice firms before even thinking about building Marlou. So what did all the advisors tell you as you were consuming their time and which assumptions did your team have to abandon before you started building? It feels like a really, really cool learning exercise here. But what did you pick up? Yeah, we had a thesis that I labeled go slow to go fast.

[00:03:32] And so kind of the hypothesis was, look, it still takes just as long as ever to create a kind of generational company and one that you're especially proud of. And most people these days are trying to pantomime or speed run success in the early stages of building a company. And so what that looks like is you kind of end up working on the least worst idea you can come up with at the beginning. And so for us, we said, look, there's a big opportunity cost to time here.

[00:03:59] We want to be really confident that we have the foundations of the business right. And to do that, we're going to spend up to a year going deeper than anyone else in a particular space on a problem to find insights that compound. So what can we learn and what's our view that is unique to us and where we can kind of say hand on heart. But we have a product market with paying customers who absolutely love us. And we have a very clear vision of the future that we're building towards.

[00:04:25] And so how that kind of transpired for us was we signed up a number of firms to be pilot partners of Marlou. And it's kind of funny when I say it now, but essentially because we had built these investing platforms that had looked after millions of customers and billions of dollars of assets under management, we had credibility with our customer, with our ICP financial advisors. And so we said, hey, this is our background. We think there's some pain and some interesting problems to solve.

[00:04:55] And we really want to come in and see if we can help you. But to do that, we want to spend, you know, days to weeks at a time in-house with access to all different types of roles and personas in your firm. So managing directors, heads of compliance, support staff, advisors, call centers. And we kind of did two things. We did, you know, informational interviews like this, just asking questions. But we also did a lot of side by side. So we'd sit down with someone and say, let's go through all the emails in your inbox from yesterday. What are they?

[00:05:25] What do you do with that information? What other systems, tools, pieces of software do you interact with? Okay, you need to do some modeling for this client. Let's go and use that tool and observe how you, you know, use it. And so very quickly, what we were able to do is kind of understand the purpose of all these different roles within the firm and then see day-to-day where the friction starts to accrue.

[00:05:48] And essentially what we did was kind of map to the logic or the ontology of financial advice across the whole firm, across all the different people that touch it from, you know, the start to the end of a client engagement or relationship. And start to join the dots in our understanding because we're coming at it from the perspective of, you know, people whose superpower is to build brilliant kind of consumer-grade software for financial services, but not as advisors ourselves.

[00:06:12] And so the two takeaways and learnings were, look, one, all software in this space is Windows 95-esque and it fights the advisor or the user on a daily basis. And that's no fun, particularly when you contrast it to any other type of modern consumer experience that you're using your personal life, whether it's Instagram or Strava or any of these other modern apps, right?

[00:06:36] You have them at your fingertips, but when it comes to work, your profession, your industry, you're just left with kind of clunky substandard software. And then what that has kind of transpired is a lot of this software has historically been procured for compliance purposes and it gets forced top down on the end user. And so as a result, like product quality doesn't have to be there. The bar is exceptionally low and adoption is the first thing that goes.

[00:07:04] So, you know, most companies and firms that we talk to might have rolled something out for compliance reasons. And then within a few months, if you are actually able to look at the usage or get any insights into the behavior, it's quietly dropped off because a financial advisor will say, what am I trading off to have to use this? Where's the incentive for me, et cetera. And it's just not there if it's coming top down for compliance purposes.

[00:07:26] And then the second takeaway and learning was, look, everything is getting much more expensive in terms of my costs to serve a client. So, you know, every time I meet you, Neil, and have a meeting, a 60 minute meeting could turn into 10 to 14 hours worth of paperwork for me in terms of having to evidence the suitability of my advice, how I know, given your goals, motivations, risk tolerance.

[00:07:51] The advice that I'm giving is fit for purpose, good value for money that I've made my disclosures, et cetera. And so you're almost in a scenario where more client meetings are bad for business and you have kind of varying levels of profitability between clients as well. And so it's really kind of capping out and inhibiting the ability for an advisor to scale or grow their business. Lots of people are capping out at the number of clients they can serve. And this shows up in two ways.

[00:08:20] One, a lot of advisors haven't onboarded new clients for years. We've met people who've gone two, three, four years without onboarding a new client and they're not marketing themselves necessarily. So it's typically closed book referral based and you might onboard someone or pick someone who has a large portfolio or body of wealth over other people who might come along or it could be a favor to one of your best clients, for example.

[00:08:44] And of course, if we look around, there are many AI tools for advisors out there that typically begin as nothing more than meeting note takers. But I was reading that you, looking at what you're doing here, one of the things I love is you're going for a bigger opportunity. And that is an AI partner that understands the wider advice workflow. So tell me more about that and what made you take that route? Yeah, so there's a few different kind of stages and acts to how we think about the development of the company.

[00:09:13] So, yeah, you're correct. When we first started, we were a note taker. And so why does that work in the early stages? And you see this across lots of kind of very specific vertical AI plays now, whether it's advice, legal recruitment, et cetera. Note taking is a great wedge product because it's a high pain, high frequency problem. And in our case, it's driven by regulation. So I have a need to take notes in my meetings as a financial advisor.

[00:09:41] I have to evidence the things that I covered off before. And so I can either not take notes, which is very risky for me in terms of my record keeping, my regulatory obligations. I can have a second person in the room taking notes for me, which is very inefficient. I can use a generic note taker, which doesn't understand kind of the context of the advice and what's important. It will just give me an A to Z transcript of the conversation. Or I can use a product or tool like Malu, which is hyper specialized to advice.

[00:10:09] And the example that I'll use is we understand the nuance and the context and the things that are especially important for an advisor to have to evidence. So, for example, if I'm asking risk related questions and our summaries of the meeting that we generate off the back of a transcript, you can do things like always directly quote the client's own words when it comes to their risk tolerance, which is very, very important for an advisor because there is nothing better as evidence to a regulator as to the client's own words and their response.

[00:10:39] And so we're able to very kind of like clearly and succinctly pull out the most relevant points and tick all the boxes for an advisor in terms of the obligations that they have to meet. And what that does is it drives adoption for us. And so to begin with high pain, high frequency problem, we got pulled along. So there was huge demand and we were able to build a context window on the client. So we captured a transcript, which was a set of information which didn't exist anywhere else.

[00:11:08] If you think about a CRM, at least in the advice space, most of it's a static compliance record. It's just, you know, a historical bank of information as it relates to that client and their relationship with you, the advisor. Whereas when you take a whole transcript from a meeting, you have this really rich and new window of information, which is way more up to date and current than anything that exists in a CRM.

[00:11:32] And so what we've quickly been able to do is to leverage the context of the client and use that to begin to do work on behalf of the advisor. So we are not, you know, issuing or giving advice end to end, but we are, you know, empowering the advisor and cutting, you know, 80% of the time, for example, in some cases on particular tasks to then go and deliver that work.

[00:11:57] So instead of, you know, outsourcing a report that could be 300 pounds per client in a two week turnaround time, you can use Marlu, which has a much richer up to date picture of that client to do it in 30 to 45 minutes, for example. And so you start to see the unit economics and, you know, the underlying kind of like P&L of an advice firm begin to change very, very quickly.

[00:12:21] And so kind of act one was what we call the assistant, which was very much capturing every client conversation and keeping the record of it. Act two is kind of what we describe as the worker. So everything that comes kind of beyond the initial meeting note. So the writing of the advice, the presentation, that's all, you know, features and functionality that we've now expanded to. And kind of the third act, which we're now moving on to is kind of the partner.

[00:12:50] So moving beyond just, you know, the record of the meeting or the file note of the meeting or the advice document of the meeting, but really being the central kind of operating system and hub that work gets done within an advice firm. And that's tied much more to, you know, firm level spend and firm level labor and accurate rather than just like a kind of subset of the specific tasks and subscriptions, for example.

[00:13:15] And I was also reading before you joined me today that a third of your team at Marlowe has actually worked as financial advisors. So how has that experience influenced what you automate and what you deliberately leave to the advisor? It feels incredible that you've managed to surround yourself by like almost members of the community to create this. Was that important too? Yeah, absolutely. And many of them have actually been customers or clients at Marlowe that we've been fortunate enough to hire, which is even crazier when you think about it.

[00:13:44] But look, it's really important to us to have advice experience at the heart of our business. And what we've been able to do is take, you know, brilliant, young, ambitious advisors and really kind of teach them our view of the world in terms of how to build products, how to build a company and pair it with their subject matter expertise.

[00:14:07] You know, these are people who have won awards, been on really great kind of trajectories themselves as advisors, but always been frustrated by the software, the inefficiency, just the really high manual load and paperwork. And so it's an opportunity to pair that with the cutting edge of AI and solve their own problem.

[00:14:26] And there's nothing more credible than one advisor, you know, selling to another advisor or, you know, developing a product specifically for a pain point that they have encountered themselves hundreds, if not thousands of times. And so it's definitely part of our kind of secret sauce. And it's one of the reasons why we've been able to build a product that is so loved by our customer base. And financial advice obviously involves sensitive personal data, regulation and decisions that could affect somebody for decades.

[00:14:56] So there's always going to be an element of a trust issue there. So what must an AI system prove before an advisor should begin to trust it with client work? Yeah, it's one of the most important questions that we're asked. And of course, you have to prove to advisors in order for them to trust us. We handle very sensitive information across, you know, a large span of customers these days. A couple of things. When we did that in-house stretch, this was one of the things that we tested.

[00:15:21] So we met with, you know, heads of IT or outsourced arrangements, for example. And we asked them if you were going to procure or use a piece of software like Marlu, what is the standard that you hold us to? And so it just meant that we were able to kind of make key technical decisions, particularly as it relates to data privacy and security up front.

[00:15:41] And for us to actually demonstrate that we've understood the needs and the use cases of advisors and to make Marlu a place that is actually the best possible home for advisors to do work as it relates to AI versus, say, generic tools or models who are more generalized. So specifically, a couple of things that we do, which, you know, prove that out.

[00:16:06] One, with the likes of OpenAI and Anthropic, we have, you know, zero data retention like options and agreements with them, which means that when, you know, we pass a call through their APIs, that isn't audit logged and retained. Whereas if you just go to chat GPT or Claude right now and were to enter a query, it automatically gets audit logged for 30 days.

[00:16:28] So that's a way that we can demonstrate back to advisors and help them understand like, hey, we understand the expectations of not only you, but your clients and the sensitivity of this information and how we can prove that we are actually a safer use case than non kind of like specific or specialized models.

[00:16:47] And of course, you know, things like SOC2, cyber essentials, we have kind of a whole suite and information pack that we provide to firms upon request that cover, you know, all of the data privacy and security measures that we've put in place, essentially. And for the advisor to also give confidence to their client, particularly when they're using Marlu to record a transcriber meeting.

[00:17:10] And an advisor said it to me the other day, but, you know, the framing that lands the best is, hey, if it's okay with you, I'm going to use Marlu to record this meeting. It enables me to be fully present, not miss a detail. I can actually be way more efficient overall. And it allows me to provide a higher level of service to you. And in, you know, like very few cases will you find that people have exception to that framing. And again, that's from an advisor themselves.

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[00:18:05] And you can learn more about how to start trusting your agents to make business decisions. But now, back to today's guest. I also read that you warned advisors against signing long-term AI contracts. So tell me more about that and why flexibility is particularly important while products, pricing, and capabilities are all changing so quickly at the moment. Yeah. So we're living in this kind of like weird world at the moment, right?

[00:18:35] Where on one hand, the promise of AI to kind of be transformative for you, your life, your profession has never been greater. But on the other hand, kind of never been more sick of it, right? The hype, the noise, the uncertainty. Like I run a company that does this, right? And even though I'm kind of reaching my limits.

[00:18:57] And so the question is like if both of those things are true, what really matters when it comes to kind of adoption and usage? And our view is that things are moving so fast that it's dangerous to tie yourself to one provider. And we've seen lots of people be over-promised and under-delivered, right? So what we're very good at is procuring software. That problem is solved. We know how to do a demo, get excited, swipe the card. It's like a gym membership.

[00:19:26] You, you know, get really excited in January. You go a few times. February, you're starting to drop off. And by the time March rolls around, you're not using it anymore. And what we're seeing play out is, you know, the market is moving at such pace and advisor consumer expectations are matching that pace that very quickly, if you have been, you know, like sold a really slick demo that hasn't actually come to fruition or promised certain features or functionality that you are being left behind.

[00:19:55] And so by locking yourself into a long-term contract, you're not allowing yourself to make the most of the opportunities that come by. And kind of our view and my view is we come from a consumer background and we're happy to stand behind the product and the value that we deliver, which means we need to do what we say and deliver on that. Otherwise, you can leave at any point in time. And so we offer monthly contracts only.

[00:20:23] Secondly, we do, you know, annual for enterprise, but typically they prefer a longer commitment to give them certainty that we're around and other users are more than welcome to commit annually as well. If they want to, I'm happy to do that. But our default is monthly and we have extremely low churn as a result. And so ultimately, what does that give us confidence in that we've created something of value that stands on its own two feet and we're really well aligned to deliver for the customer?

[00:20:50] And I think anybody listening that has spent any amount of time doom scrolling down their phone, they would have seen a lot of horror stories and uncertainty around a token spend return on investment from an AI project. So I'm curious what you're seeing. Where are firms seeing measurable value from AI right now and which use cases still create maybe more work or risk than they move? What are you seeing? I still think we're super early in terms of adoption.

[00:21:19] A lot of people are not getting maximum value. There are certainly like firms who are early on the adoption curve, but to move beyond meeting notes into, you know, work that is much higher leverage and value takes a lot of effort and attention at a firm level. And so what you need to do is get the fundamentals right when it comes to rollout.

[00:21:41] And so that's what we have become really good at is helping advisors and firms successfully roll out, not just meeting notes, but features and functionality beyond that. So to kind of give you a few figures like, you know, an advisor the other day said using Malu in a meeting is saving them two to three hours per meeting. That's what they were able to quantify as part of a trial, because it's not just the meeting notes. It's the follow up. It's the internal compliance record.

[00:22:09] It's the client facing version and follow up of that meeting. It's the ability for other members of the team who work on that client to have access to the same context and then go and do the work that they need to offer back of that. So that's just meetings. It's before you get into things like product research and recommendations. So if I'm recommending certain investments or products, I need to go and research to compare them to confirm what the possible options are. Then I need to typically go and do modeling.

[00:22:39] So say in terms of cash flow planning, if I'm looking at retirement, given kind of different inputs and variables, you know, when may I run out of money? And am I going to have enough? Can I afford to spend more now, for example? Can I retire sooner? Can I have enough money to do that? Then you have a whole compliance piece and element to that. So, again, the evidencing of everything you're doing. And then you have what we describe as, you know, the client facing kind of report or recommendation or document.

[00:23:07] So that's kind of the aggregate of all of those steps previously that I've just described. And those reports, as I mentioned earlier, can, you know, run 40 to 60 pages long. There's lots of kind of like regulatory disclosure and evidencing of everything that you've covered off with the client. Things like your costs and charges, your fees, the funds that you might be recommending if it's, you know, to make investments, for example.

[00:23:30] And we are seeing people, you know, stop using outsourced power planning arrangements, which are who you would typically use. So you would pay three to four hundred pounds per document. The average advisor will do three to five a month. So that's automatically, you know, two to three thousand pounds of savings. Plus, each one comes with a two week turnaround time. Whereas with Marlu, you are now doing them in, say, 30 to 45 minutes, maybe an hour.

[00:23:57] And it's perfectly kind of created in terms of your firm style, your tone, your branding. We match and mirror that kind of instantly. And so, you know, automatically off the bat, we have clients who have increased, you know, capacity by 20 percent. And we're very much kind of pro-choice in a sense of whether you are an aggressive kind of roll up growth consolidator mode. Like you can use that as leverage on your on your capital and your time.

[00:24:23] Or if you want to spend more time, you know, building a lifestyle business with your kids, family, et cetera. Like that's also great. It's kind of there to give you choice and optionality and to, you know, essentially like give you relief because you got into a profession that you were, you know, incredibly excited about. You were passionate. You wanted to help people. And like to give you examples of the types of things that people get advice on, you know, it's material life events.

[00:24:50] It's retirement, inheritance, divorce, serious illness, injury. There's lots of different life driven events, whether you like it or not, that you have to kind of confront at various points. And so the value of an advisor is not just, you know, investment or like product related. It's really kind of like acutely understanding you, your goals, your motivation, your personal situation, helping you to make the best possible decision.

[00:25:18] And so for us, the goal is, you know, eat all of the work across an advice firm. That's goal one. And we're well on our way to doing that. Give kind of material cost and time savings such that you transform the shape of a P&L for an advice firm. And then kind of the third act, which we're into now is very much kind of going beyond the work that has been done previously to deliver the best possible client experience.

[00:25:43] So, for example, let's say that the Bank of England changes interest rates tomorrow. Marlow is able to go and do, you know, cohort analysis on your entire client book. For whom is that an opportunity? For whom was worried in past, you know, previous conversations about an event like this? Who's holding cash that might look to invest it? And it's really making the most of that relationship and being able to treat every client like they're your best.

[00:26:10] And automation also promises to give advisors much more time with their clients as well. So how do you see firms making sure those savings improve relationships and access to advice rather than simply just increasing case volume and getting more people in? Yeah, it's really interesting. And this was an observation that we made when we first kind of begun in the space.

[00:26:35] A lot of a client relationship, wherever you are in the world, revolves around an annual review meeting. Yeah. Which is kind of a silly concept because in my personal experience, I would want, you know, always on advice as frequently as possible rather than having to wait for, you know, an annual tick box exercise. To evidence to the regulator that I've met with you and we've got an update on kind of your situation and everything else.

[00:27:02] And so the great news and what we've been able to prove out is we have advisors who have gone from seeing their client once or twice a year to five or six times a year. And that's why they got into the profession. That's the value of the relationship that they have with the client. And so it's much more of what you do best in terms of be client facing, build rapport, build the relationship. And Marlu does the heavy lifting and gives you leverage on everything else. Absolutely love that.

[00:27:30] And also adoption is something that depends on changing habits across an entire firm. So any advice you'd leave businesses or what they should be doing in the first 90 days with AI that they get their hands on to move from just experimentation to dependable and worthwhile and measurable value in the daily use that they use it with? Any advice there from everything you've learned? Yeah. So we typically recommend a few things.

[00:27:57] One, have a really clear trial period. I would typically recommend two weeks because it's short and it creates action. Trials that are like four weeks plus result in a lot of inaction in the first week or two. And so you end up just pushing everything to the back end of that. And we would typically say, hey, get your kind of three to five most likely power users and evangelists within the firm to take part in that trial.

[00:28:24] Set a really clear goal or hypothesis, i.e., you know, this is how much time we think we might save or this is how we might measure, you know, the results of the tool or the product that we're using. And then at the end of that two week period, typically two things happen in the case of Marlou. So, one, we're very clearly able to articulate kind of the value and the time saving to the advisor.

[00:28:49] And in an advice setting, financial advisors have never had software that, you know, they'll bang their fist on the table for. And so we're able to evangelize the user and then use them to help, you know, roll out to the rest of a firm. And so it's absolutely about enabling, you know, adoption within the firm to accelerate rollout. Those are a couple of kind of key principles for us.

[00:29:14] And, you know, again, coming from a consumer background and building something that has to be loved by advisors was always the goal for us. In a way, it's kind of B to C to B sales, meaning we care about the advisor as a consumer, as an individual. We deliver them a great experience, which causes them to turn around and evangelize and advocate on behalf of us. And then that helps kind of the spread and the growth and the adoption. If you almost think of like what kind of roots growing through a firm.

[00:29:43] And so that enables not only us to be very efficient in terms of the way we grow, but for advice firms to, you know, get 90 plus, you know, sometimes 100% adoption in the case of a rollout within a period of four to six weeks. Which is kind of unheard of in this space. Well, thank you so much for sitting down with me today and sharing your story. And for everyone listening, want to find out more information about anything we talked about and obviously learn more about Marlou.

[00:30:12] Where would you like me to send everyone listening? Yeah. Best place is our website, marlou.com. M-A-R-L-O-O. That's us. And fun fact on the name. I actually grew up in New Zealand. We are a kind of seafaring nation and the name of the boat that I learned to sail in, which was a kind of a bathtub dinghy called an optimist, was Marlou. And so that became the name of the business. Fantastic. What a great story.

[00:30:38] There's so much I love about what you're doing here, especially that you were built with the profession, not just for it, with your 30 year old team having worked as financial advisors themselves. And I think that part of your story is every bit as important as the tech behind it and everything that you're doing here. So I urge everyone listening to check you guys out. I'll include links to it all. And more than anything, just thank you for sharing that story today. Really appreciate you, Tom. Brilliant. Thanks for the time, Neil.

[00:31:04] I think Hardy's story today offered a useful reminder that successful AI adoption begins with understanding the work, the person doing it, and the reason that that process exists in the first place. Marlou started with meeting notes because they were frequent, painful, and tied to regulation. But the wider opportunity appeared in the research, the modelling, compliance evidence, and client communication that followed each conversation.

[00:31:33] And that outcome that Hardy values most is time. And he says some advisors using Marlou have moved from seeing clients once or twice a year to five or six times. And this gives firms a choice between increasing capacity or creating greater room for the personal relationships, rather than just assuming that every hour must become another case. So remember, you can learn more at Marlou.com. Thanks to Hardy for joining me today.

[00:32:02] And over to you. If AI gave your team several hours back after every meeting, how would you invest that time? Well, you can get hold of me at techtalksnetwork.com. You can learn more about anything we discussed today. We have 4,000 interviews. You can meet me on the road or send me an audio message. Have a look and let me know. But that's it for now. Thanks for listening as always. Bye for now. Bye for now. Bye for now.

[00:32:32] Bye for now. Bye for now.