Leap to Scale
Leap to Scale is for technology curious leaders of service firms who want higher margins without adding headcount. Each week, Justin Davis and Greg Ross-Munro show how to turn firm expertise into repeatable, sellable technology products: SaaS, packaged workflows, and AI-powered tools clients can buy again and again. With AI, more of your know-how can be captured, standardized, and protected as IP instead of being rebuilt in every engagement.
We focus on practical decisions: what to productize, how to price it, when to build vs. buy, and how to use AI responsibly without risking delivery quality or margin. Clear steps, real tradeoffs, usable examples.
Leap to Scale
Crafting Bespoke Financial Solutions with AI and Human-Centered Design
Use Left/Right to seek, Home/End to jump to start or end. Hold shift to jump forward or backward.
In this episode, Sara Altenhoff is joined by Gregg Hilferding and Justin Davis. The three dive into how AI and human-centered design are transforming the financial services industry.
Key Points Discussed:
- Understanding Terms: Defining AI and human-centered design.
- AI in Financial Services: Advances in AI for personalized services, fraud detection, and user needs prediction.
- Human-Centered Design: Principles and processes tailored for financial products, focusing on user control, transparency, and accessibility.
- Tips & Takeaways: Advice for integrating AI and design, future trends, and recommended tools.
Listen today to learn how the convergence of AI and fintech is transforming the finance space. Don't forget to subscribe and follow Decoder Podcast for more insights in the world of software development!
Okay, hello, and welcome to another episode of Decoder Podcast, where we demystify the world of software development for our listeners. So in Decoder Podcast, we take you behind the scenes of a software development agency to explore how digital products are created from concept to completion. I'm Sarah Altenhof, and we have some great guests here today. Would you like to introduce yourselves?
SPEAKER_02Absolutely. I'll start. I am Justin Davis. I am the vice president of user experience here at SourceTode. My job is to oversee how we build products and make sure that they deliver highly usable human-centered designs that people really enjoy using in our products. And I'll turn it over to Greg.
SPEAKER_01Yeah, my name is Greg Hilfording. Folks here call me 3G. I am our vice president of organizational development. So I am responsible for uh training and systems and structures for our development teams.
SPEAKER_00Well, thank you both for joining me today. Um, the title of today's episode is Crafting Bes Bespoke Financial Solutions with AI and Human-Centered Design. So we'll be exploring the intersection of AI and human-centered design and how that is has the potential to revolutionize the financial services sector by enabling the creation of personalized, intuitive financial solutions for the user. So to start us off, it's always a good idea to define some terms. Everyone's talking about AI today. It's a huge umbrella and lots of things fall under it. So in this episode, when we talk about AI, uh, Greg, can you explain the type of AI that we're talking about?
SPEAKER_01Yeah, definitely. I think that the word AI is getting a ton of attention these days. Um but the reason it's getting attention is because there's a new kind of AI in the last year and a half. Uh it's generative AI. And that term refers to the chat GPTs and the Dolly 3 image generators and mid-journey image generators. Any kind of AI where you're giving it a bit of a prompt and it's giving you back brand new content is generative AI, sometimes also now being referred to as gen AI. And I think that's where we're gonna focus today. That's where uh most of the industry is focused right now.
SPEAKER_00And to take us into the human-centered design aspect of today's episode, Justin, can you shed some light on what we mean by that term?
SPEAKER_02Yeah, when we talk about human-centered design, what we're really talking about is using ways to think about ideating products and building products that really have the end user mind. And that is that sounds crazy, right? Because it sounds like we would always do that. But a lot of software is really not developed thinking about what is the user experiencing, how are they going through each interaction? And we put at source of a lot of value on that. And the field of human-centered design is all about optimizing for that user experience, mostly through the knowledge of the user and developing empathy for what they're going through.
SPEAKER_00And so, how do these two things come together? Like, can you give us a brief overview of how AI can complement human-centered design when, especially when creating like solutions for financial services?
SPEAKER_02Yeah, you know, one of the things that I think has been so interesting about the generative AI tools that we've been able to get our hands on in the past year and a half, a couple years is that we are able to now do things that give a personal, hyper-personalized experience to users, right? Are able to cater to a user's very specific needs and their context in a way that we couldn't do before, right? We used to have to rely on algorithms and switch statements and things like that to say, well, if the users in that category uh show this, if the users in that category show this. We don't have to do that now, right? Like we can really talk to them in the same way, hopefully, that we as individuals do, right? When we have conversations with people, we develop rapport with them and we interact with everyone a little bit differently because we're developing empathy for how they communicate and that kind of thing. And now we're at the point where our products can now do that programmatically, which is a crazy thing to be able to do, but it unlocks the ability for our products to be much more human in that way, which I think is super exciting.
SPEAKER_01So, one of the really exciting things about Gen AI to me, um, and it applies to any industry, not just financial services industry, is like we're all familiar with the golden rule, like do unto others as you would have them do unto you. Um, but there's also another idea which is the platinum rule, which is do unto others as they wish you to do unto them. Right. And it's a little different, right? It's still the same idea. And generative AI suddenly gives us the power to build products that are like following that platinum rule.
SPEAKER_02Yeah.
SPEAKER_01Actually giving people what they like, giving them the experience that they want and the experience that they need, not necessarily just the experience that we would design for someone else.
SPEAKER_02Yeah, you know, just to add one last thing on that is that I've always thought about the fact that, you know, when when people use software, when people use something you built, right, they're not using, they're not interacting with a computer. They're interacting with you via a computer, right? Like, and lost in translation because we have to write code to do the automatic part, the interact with it part, is we lose some of those nuances of humanity. This is bringing that back and making the the little wall between the two people much, much thinner, right? And much, much more human. Yeah.
SPEAKER_00So let's now dive into some specifics about AI and human-centered design and financial services. So um, what do these recent advances in Gen AI unlock for financial services and fintech? Um, and ultimately, how will it change how we all manage our money? Um, Justin, do you want to speak to that?
SPEAKER_02Yeah, you know, I think it's really fascinating. And I I had the luxury of of being able to work in fintech over the past few years as part of a startup um right before a lot of the Gen AI stuff comes out, came out. And so I've got a kind of a unique view on the right before like what we wish we could have done side of things. And now looking at it and looking at what what people are doing, it's interesting to see um just how transformative it's been. So, you know, when we look at what AI unlocks for financial services and fintech, I kind of think about it like in terms of what does it unlock for the consumers versus what does it unlock for the companies, right? And so for consumers, it's going to really revolutionize how people interact with their money, interact with investing and saving, and the knowledge around that, it is really going to change it in a in a very material way over the next five years, 10 years, et cetera, right? So some of the things that we'll see happen in the consumer spaces, you're going to see what I think is one of the biggest trends in AI is hyper-personalization of scale. That means we can give people individual advice about their situation, their investing situation, um, the financial planning situation, all of that. We can do that now at scale immediately without having to take on the burden of a human individual needing to understand their narrative and understand um the parts of their life to be able to develop that plan. And so I think the idea that everybody can get something perfectly geared toward them, which a lot of people right now might think that's how it works, but really, those of us who work in techno, it's been a pretty close approximation, but we wouldn't call it really excellent. This is gonna be able to push that to where that can actually be a thing. Um, it's gonna unlock things like value-based investing, being able to say, look at my social feeds, look at what I post about, look at the thing, the places that I shop, and develop an investing strategy for me that supports my beliefs. That'd be very, very difficult to do before now. There'd be a ton of work involved in it. That's gonna be something that's gonna be pretty turnkey soon. Um I think when you also think about uh consumers and what they deal with, there's a lot of data, right? There's a whole lot going on. You get annual reports. If you're an investor, you you're flooded with information about different financial services. And um and it's hard for consumers to understand, right? One of the great things about AI is the ability to help consumers to deal with that data overwhelm and understand what parts they should pay attention to, get it translated to a language that they can understand and make decisions on um in a really effective way. So I think that for consumers, that's what is really interesting. For companies, I think there's a lot of use cases that are um kind of behind the scenes but very valuable. Like fraud detection is gonna get a lot better. We can actually look at things now with a like a human looks at it and detect fraud a lot better than we could have with uh, say, some of our just kind of canned algorithms that we've used before. Um, we're gonna be able to just target things to consumers better. It's gonna make the experience better for consumers, and it's gonna make it better for the companies because the company is gonna make more money, they're gonna sell more things, they're gonna match more people with better products, and the consumer ultimately is going to get a set of products that fits them better, also. So it's a win-win scenario there. And then again, the highly personalized support guidance, um, that kind of thing that's gonna come out of it. You know, again, hyper-personalization of scale at like the financial advisor level, where it's going to it's going to allow consumers and companies to engage in an experience together that is so specific to that pair of people, right? Um, that it's it's gonna make the outcomes a lot better for everybody. It's very, very exciting stuff. And this is just scratching the surface of some of the things that are gonna be able to be done here.
SPEAKER_01You know, as soon as you said financial advisor, I just re I just remembered a conversation I had with my financial advisor about 10 years ago. I was looking at the like, you know, you fill out the risk survey every year, and you know, those are very clearly kind of like low, medium, high, asking your your risk five different ways, and you get a score, and then you get that ratio of low, medium, and high risk stuff, right? Very, very basic, very basic algorithmic decision making out of that survey. Um and I remember I looked at one of those funds um and what it invested in, and it was like the like five of the things were like giant oil companies. And I said to my financial advisor, I'm like, hey, I understand it's it's safe, but I'm not sure it's gonna be safe forever. And also, if I'm gonna be investing money for years to come, I kind of care what companies it goes into.
SPEAKER_02I don't want to give my money to those companies that maybe I don't agree with. Right.
SPEAKER_01Yeah. And at the time, it was a difficult question for my advisor to answer. Yep. There wasn't the same like attention to it, and there definitely wasn't any tools at scale to say, like, oh, how can I match the right funds to this customer based on their uh, you know, their their personal beliefs as they apply to investing, right?
SPEAKER_00So how how could AI help in this situation? How could it help in like understanding uh and predicting user needs? Are there any specific ways?
SPEAKER_02Well, you know, like kind of piggybacking on that, right? Going from from talking about this kind of hyper-personalization of portfolios, right? Like what could you like if you if you say, I really kind of don't want to invest in the five big oil companies, because like that might be against my my personal beliefs, right? Is that LLMs gives us an ability to understand people's kind of latent needs and desires in a non-declarative way. They don't have to fill out a form and say, these are the industries I don't want to invest in. No oil, da-da-da-da-da, right? We can just say, look at the kinds of things that you like on Instagram and Facebook and things like that, and we can discern a lot, we can infer a lot about that, right? If you think about it, if you go to one of your friends that you know really well on Facebook and you've read a lot of their stuff for a long time, so you have developed a good memory about what they like and what they don't like, right? And then you would be able to say, I would bet they wouldn't want to invest in that, right? Or whatever, right? You'd be able to make that judgment call because your brain's doing the work that now LLMs can do, uh, and and giving the ability to do that kind of passively, which makes the user experience so much better. Because I don't just fill out a form, right? And like I don't have to go through these state algorithms. It's a real mode shift in how we interact with people's preferences.
SPEAKER_00So for me, if an AI looked at my like Instagram, for example, they make the determination that I really like cute animals, so let's invest in all the cute animal stocks.
SPEAKER_02Right. Build-a-bear workshop.
SPEAKER_00So um, are there any specific examples you can think of of how AI has improved a financial product or services? I know things have moved really quickly.
SPEAKER_02Yeah, you know, it it's really all moving around a lot. And and there's I feel like every week, if you go to product hunt and you just search by finance, right? You're gonna see crazy uh uh cool things that are coming out. But Morgan Stanley has done a lot in this. Morgan Stanley last year uh started this. I I mean, this is kind of like the most corporate thing to do in the world, but they they like came up with the title of this, and it was AI at Morgan Stanley was the title of the program, which I thought was good and descriptive and clear. Um and so they came up with this AI at Morgan Stanley uh program. And what they did with that is they ingested hundreds of thousands of documents from their interaction or like research documents and stuff like that, right? For funds and investments and things like that, and made that available to their advisors. So their advisors now can interact with that information real time in a much easier way than to read a hundred thousand prospectuses of different prospective of different um of different funds, they can kind of immediately get to those answers. So that's one example, and and there's more people doing things like that, right? The advisor market's gonna get impacted a lot like this. Um, they're also doing something else at Morgan Stanley and ABM Amaro Bank is also doing this, which I believe is a Dutch bank, a very popular Dutch bank. Um, they're doing auto recap after client meetings. So essentially what happens is you go meet with your financial advisor, you sit down and you talk about what you want to do, what your goals are, they're analyzing the conversation and sending a recap email automatically to the uh to the client, you know, 10, 15 minutes after it's done. It's a small thing, but if you think about it, right, if you have a hundred thousand advisors meeting with people every day and they're all taking 15 minutes to write the recap, how much time can we be saving through these small efficiencies that also make the the user feel like they uh like got an instant response, right? And it's highly tailored to them. It's like, wow, look at how prompt they are. Didn't come the next day. It came. I haven't even gotten home yet, right? And they sent me the summary. So it creates the impression of a high-touch conscience experience, but in reality, it's actually just AI uh lifting the load there. It's really, really a great example of how that's helping out.
SPEAKER_01Yeah, and I would just add in that this is kind of a theme that we're seeing. There's a lot of amazing ideas of how to use AI at scale directly for your customers. Um, but a lot of what's happening today is more just like augmentation of your employees. And so sometimes, you know, AI instead of artificial intelligence, I I like it when we toss around that AI really stands for augmented intelligence. Um it's gonna give us our own personal assistance before it necessarily gives that directly to customers. Um, but it's just a really exciting time, right? That we can have everyone can have a uh an assistant with almost perfect memory of everything that your company does and has ever done and all the the research that it's gathered. That's that's pretty amazing.
SPEAKER_00Yeah, just thinking about like like Justin said, all the time saving, like it really stacks up. And yeah, it's it is a very exciting time. Um so that brings us to another point. So with AI, like taking notes of all of our conversations, um, uh leads us to like sort of ethical considerations and data and privacy. Um so Greg, like what are the ethical considerations that companies should keep in mind when they're implementing these um implementing different Gen AIs in their financial products?
SPEAKER_01Yeah, I think that for most companies in the financial services space, you're already very aware that you have to be very strict with the protection of customer data, PII, like there's you already have regulatory compliance needs. Um and Gen AI doesn't change any of that, right? Like it doesn't it's not a a uh a free pass to to start spreading that information around to the to the AI systems. Um as long as companies though are vetting the services that they're using, ensuring that those services are also protecting that that user data and not using it to train their own models, right, for for other clients, um then you're probably pretty good there. There are still ethical concerns though, and I think this you know, I think a great example in the financial industry is you know using AI to make decisions or to advise on decisions. So I think it's a pretty clear example. Uh if you're in financial uh services and you are a mortgage underwriter, um Gen AI maybe is not the tool to use to decide who gets approved for a loan yet. Right? And the reason for that is because if you're gonna upload all the the whole package about the person seeking the loan, and you're gonna give this to an AI and you're gonna say, are they should they be approved for this loan? If you don't know what data the model was trained on, you don't know what biases are going to be included in that decision-making process, right? And there's all sorts of ways that that could creep in, and suddenly your approval rates for certain demographic groups um starts going down, and it's because there's some like weird bad training data in that particular model, and it's suddenly saying, like, oh, that type of person should never get a loan. And that's not something that's good for anyone. Uh it's definitely not good for businesses and for your reputation to suddenly start denying loans because the AI told you so. Um, you really still need to have a human in the loop uh and make sure that your training data is not introducing biases. Um if you're using a big popular uh platform, that doesn't automatically protect you from that, right? Like you still have to know and test um for those biases.
SPEAKER_02Yeah, that's right. I mean, like this stuff is like I mean, it is trained on real-world data, right? So it it it can easily come in with real-world biases. So I think it's a great reminder. Um, and the other thing about this, I think, is you have to remember that you know, Gin AI is a really, really powerful new piece of technology, and one of the most powerful things about it is its ability to effectively replicate human communication in a very convincing way. Um, this is going to create a lot of problems for the security community because uh we as humans, we right, we have our own little red flag detection mechanisms that we use uh when we are um uh when when we're evaluating situations, right? We and we try to see like, is this look suspicious, right? One of those that we use is we look at language and we say, language not look right. Does the does it look like this wasn't written quite correctly, right? It's it's an internal mechanism we use a lot to filter things out. We're gonna lose that ability. And um, and it also means that advice that you're given can be given in such a way as to sound so persuasive that it's difficult to understand and be like it's difficult to be objective about it. So I think those are some of the things that we have to think about as we design these systems. Yeah.
SPEAKER_00All right. Well, let's switch to something a little Bit more fun. Let's talk about design. So, Justin, can you walk us through a typical design thinking process for a financial product?
SPEAKER_02Yeah, you know, I think like for a financial product, when I think about, you know, kind of the design thinking, human center design process, it's like any other, any other product to me, uh, which is that it starts by understanding like what the users need. You know, we build we build products to solve problems for people, for users, right? We don't build them in silos. And so it every successful product starts with a deep, empathic understanding of the user needs. And I think that for financial services, it's no different. And I think we've talked about how AI, AI systems, some of the Gen AI stuff allows us to now develop that empathy and that understanding of users in a much better way, right? I think that for finance, one of the things that is uh particularly worth thinking about is the fact that finance is a highly personal thing that has big impacts on people's lives. Arguably some of the largest, right? And those of us who are designing systems to facilitate those transactions, we are also facilitating decision making, right? And what that means is that it's not like a to-do list app where, oh, I decided to put it on a different list or decided to do this. When you are helping people make decisions about their money and what to do with it, you're making permanent and irrevocable decisions, potentially about their well-being over time, right? And so those of us who are designing those systems have to think about that uh a lot. And I think financial services is unique in that. There was a great book written about this, about all of the cognitive biases that comes up called Thinking Fast and Slow. And anybody who designs for this, I recommend reading this book. It's one of my favorite books on really anything, it's one of my favorite books. Um, and Daniel Kahneman um is one of the kind of godfathers of behavioral economics and talks a lot about the built-in biases that we have, things like fear of loss, et cetera, loss aversion, however you want to say it, um, that really affect how we message and how we talk to people in the financial services world, how we how we communicate risk and versus reward and how we write how we help people to understand that in an even and an objective way. It puts a lot of demands on that. Um, so I think that those of us who are building things in this sector need to take extra care in and above our normal care on product design to make sure that we're thinking about the things that are going on in this little space up here, uh, in terms of what might be biasing people in their decision making.
SPEAKER_00Yeah. Um, so I'm wondering if there are any like specific key principles that are of human-centered design that you think are very, very effective in financial services specifically, Justin.
SPEAKER_02Yeah, I think you know, some of these things, you know, I mean, one of the key principles is keep in mind that like everything you do is supporting decision making. So think about what does what you're doing that might or might not influence that decision making, right? One thing that we also talk about in in human-centered design and UX a lot is the concept of keeping the user in control, right? Everybody's had this experience. You use a computer, you use a uh an app or something like that, and you're like, what's going on? I don't, I feel like I why can't I change that? Why can't I do this? Why da da da, right? And you feel like you don't have control over the system, right? And one of the principles of UX is about ensuring that users always feel like they have control. Well, if you think about financial services, we're talking about money, something that is highly personal, right? And highly, again, impacts people's livelihood. And so that idea that we need to keep the user in control, again, is really, really important in terms of some of the kind of principles that we think about in uh human centered design. I think also things like transparency, knowing where's the data coming from, when you recommend this thing, or you talk positively about this and negatively about this thing, or you tell me to do a certain thing, why are you making that decision? What inputs went into that? Help me understand as a consumer, like help me see the supply chain of influence, if you will. Um, and I think again, just remembering that overall, in financial services, especially, you're not building platforms to manage dollars and cents. You're building platforms to manage decision making. And I think looking at what we design through that lens kind of helps people to take a little bit more care and what they're doing and help to ensure that we're trying to put the user first in all those decisions.
SPEAKER_00So, speaking of users and consumers, one really cool thing about AI and scaling um financial services is that it offers these services to a much broader audience of people. Um, it puts these tools in the hands of many, many more people who wouldn't otherwise have access to these services. Maybe they wouldn't be able to go to a brick and mortar and speak with a financial advisor. Um, so when we're scaling things like this, um, how can we ensure that financial products are remaining accessible and user-friendly for such a broader and diverse audience? Uh, Greg?
SPEAKER_01Thank you. This is one of my favorite topics. I love talking about accessibility and bringing technology and knowledge to more people. Um and Jen AI is really, really good at that. Um I mentioned earlier this idea that like I fill out a risk survey every year with my financial advisor. And I know that my financial advisor talks to me differently based on whether I am focused on risk or whether I'm focused on growth. And the thing is with Genai now that you could actually use it to tailor all the information for uh each user's, you know, their specific needs, their specific priorities. Um I also I don't have to fill out a survey about my financial literacy because my financial advisor can tell right away that I'm not very financially literate. But if all the information on the portal that I use could also be tailored to my level of financial literacy, uh I'm a huge fan of metaphors. If it could explain some of this to me in metaphors, that would be helpful to me to help understand it better. Um and just a couple years ago, if someone said, hey, we want to have our our portal uh change the the adjust the the level of financial literacy, adjust the level of risk versus growth focused terminology. Like if someone came to us two years ago and said they want to do this, we'd just be like, okay, hire a thousand people and train them in writing this stuff. And today now we can say, okay, yeah, there's an API for that. We can do that, we can do that at scale. Um, we can build this whole thing out for you. Um and I love there's also uh there's the have you seen those dem those Discover commercials? I think it's Discover the the customer calls into the call center. I think one is like surrounded by a bunch of parrots or something, and the person that cuts to the call center is the same actor playing the customer service rep, right? And the whole deal the whole deal is like we get you. Um well eventually with Gen AI, that's gonna kind of work that way. Like you're gonna like they're gonna know based on the information you've given them and how you interact with the site, they're gonna almost have a digital twin of you, and that digital twin kind of knows how to talk to you and knows how to explain things to you in the way that works best. And you know, sure, that means that it'll be in the language you speak, literally, right? If you if you speak a different language than the main language of the website, but it's gonna mean so much more. It's gonna mean like so much um it's gonna be tailored for you in a way that just was never possible before.
SPEAKER_00Yeah, that's so cool. It'll be such an exciting space to watch. And I can't wait to get financial advice in terms of like cute animals. Okay, so uh to wrap up the episode, why don't we give our audience um some advice? Um so if they are, you know, researching um different types of AI to integrate into their um financial services, um, and they're curious about like human-centered design and how all of this can uh work together. What advice would you give these companies um looking to integrate AI and human-centered design?
SPEAKER_02I mean, I think for me, I think the the biggest thing, especially in the AI space, I mean, the human-centered design side of things, I would say the biggest thing is go talk to your users. Just go talk to your users and listen to what they're saying, and a lot of it will solve itself, right? Um, but I think on the AI side of things, the real key to remember is like we are very, very, very early, right? And that means two things is one that you need to be building and experimenting and working with these tools now. And like if you are not already, you have lost a lot of time. Um, and this is go, this is not an optional type of thing. People who are using these tools will end up beating the people who are not. I mean, it's really a mode shift type of technology. If you are not experimenting with it, hacking on it, trying to figure out how you can use it, do that now to familiarize yourself with how that's going. And the second point is also don't fall into the trap of thinking that just because it can't do a thing today, that it's not going to be able to tomorrow. And that sounds obvious, but there's there's kind of a belief among some people about Gen AI who say, well, you know, it's still not good. It kind of gets some things wrong, it hallucinates. The I the point is that the fact that we're even where we are right now is almost nothing short of a miracle. And we're very early part of a growth curve that's gonna see all of those problems solved in the next 18 months. Not me not all the problems, but a lot of the problems solved very, very quickly, right? And what that means is that if you put it off and you say, eh, it's not very good, I'll check back in in a couple years, you're gonna get steamrolled. Don't let this thing sneak up on you. Get into it now.
SPEAKER_01And I would add on to that that the best way to go about that is to start, and Justin touched on this. The best way to go about that is to start with yourself. Like, how can you use Gen AI today for the things that you already do? And then you take those skills and learnings and capabilities that you start to have augmented through Gen AI, and then you go to your team and you say, Okay, team, how can we start using this stuff in our team? And then you go up to, okay, in our department, how can our department start using it? I don't think you jump straight to launching a feature on the website or in your mobile app for users until you've already understood and figured it out for yourself, for your team, for your department, for your company. Um, and so that's a journey, right? It's a journey. And the sooner you can get yourself on that journey, and the sooner you can get the people that you work with on that journey, the better off you're all gonna be. Yep.
SPEAKER_00Absolutely. Well, uh, thank you so much, Greg and Justin, for hanging out with me today to talk about AI and fintech. Um just a quick recap of everything we covered today. Uh, we talked about some of the basics of AI. Um, we talked about some specific uses of AI and financial services and how to center the human and how human-centered design is really going to revolutionize financial services. Um we also gave some advice on like if you're looking to invest in some of these technologies, um, some you should start playing around with them right now. Um so we encourage our listeners to explore more about AI and human-centered design. Um, and please share with us your thoughts and experiences. This is an actively growing dynamic space, and we're so excited to see what happens. Um, and thank you all so much for joining us today. If you'd like to continue getting insight into the world of software development and digital product development, then please subscribe and follow Decoder Podcast. And until next time, goodbye.