AI and Mortgage Technology in 2025 with Spencer Dusebout of Aidium

[David] Listeners were back in for the real treat. We have Spencer joining us again with Aidium. Spencer is just one of these guys that I really enjoy getting to know. He's got one of these wonderful smiles, but I learned something when I was reading over his bio that he did back when he was 16. We're recording this a couple of weeks before Christmas, it's coming around the corner, but what are you doing for others? I think what's so exciting about Spencer's background is that the age of 16, he co-founded an organization called hands, the number four, others. And it was H4O and it was a transforming idea that he scribbled on the back of a napkin into an international movement that brought safe water to over 250,000 people in 17 countries. If you start out at your life at age 16, doing that kind of stuff, what other great things are in store for him and his future? Spencer, so good to have you joining me. I appreciate it. [Spencer] Yeah, absolutely. Great to be back and it's been great chatting, getting to know you a little bit here as well. [David] Yeah. I really enjoyed it. We get as it grows and grows, you find some relations. Would you meet somebody? They either grow into something or they fizzle out. Ours is definitely growing into something. I really love that. And then when I read your hands for others venture, what prompted you to do that? especially at this time of the year, we should be doing this year round, doing something for others, but really what was the callous for that? Was it something you had seen or heard about and want to do something about? [Spencer] No. It was actually it was firsthand experience. So I was on a trip to Belize and got an opportunity to stay with an indigenous Mayan family and just saw them basically walking hours to get water from a river and the water looked more like coffee than it did water, and just got to understand how that impacted their lives and they had to spend money on medicine and the economic impacts and so I think it was just that and, for me, I think we talked about this last time. I'm an obsessive problem solver and the obsession picked me and that one picked me. It's I guess there's something I can do to help. And that led to myself, some friends raising money to help that community get clean water, which we did and then along the way, we just found a lot of people saying I'd want to do something like this too. And that led to us starting hands for others, which was essentially like a crowdfunding platform for other groups of high school, college students to do the same thing that we did. And but yeah, I was very up close and personal to the problem and that was the catalyst. [David] That's part of what I love about your journey. You are a problem solver and there's a lot of aspects of it, but I really want to get into some of the talk about what your company is doing now, especially when we look at AI and while we can, I love your passion to help others. And that's something so much of what this podcast is about. It got created, it's become something much bigger than I ever thought it would be. But for me, it's all about bringing knowledge to others and I'm really interested in the whole topic of AI as you and I have talked numerous times. This is a topic that is getting bigger and bigger and growing more prevalent in today's world when it comes to AI and the practical impacts it has on industry. I'm really interested in your perspective on how AI and practical impacts and I want you to explain practical impacts, is going to have on the mortgage industry. [Spencer] Absolutely. So I think when you look at the mortgage industry, obviously  there's a lot of moving parts, but I think just to take two of the biggest ones, you have the operations piece, which is getting a loan done, and then you have the sales side, especially in retail, which is your sales force, your loan officers, which are out there with the referral partners or lead gen, or however, going and finding people that they can help get into homes and get mortgages. And so, when you think about that AI is going to play a big role in both of those buckets and I think right now the industry is very focused on more of, I would say the operational side, which is, can we help loans get done with more accuracy, faster? so obviously you save money and just in terms of the process. And then also there's a lot less risk as well. If you have these really smart AI is helping with that. And so I think there's going to be obviously a continued push there. And we're seeing a lot of that, I think, obviously for, from our perspective, 80 and we're more on the sales side of things, which is how can we help loan officers do more business and provide a better experience and how can we leverage AI for that? And, what's interesting is we were just at the MBA conference. There's really not a lot of talk of AI on that side of the equation yet, and so I know we'll talk about that today. But yeah, I think AI is going to touch everything. I think right now it seems from my perspective, it's really touching the operations piece the most. [David] It is. I think there's some real opportunity to pick up a lot of the rep where we repeat things. Why do you think there's been more talk about AI from your perspective on the opts side than the sales side? What's the reason for it? Isn't there a lower, lower hanging fruit or… [Spencer] Yeah, so let me tell you a story, obviously, I'm an engineer technical by trade. And I think AI has accelerated quickly, but there has been AI technology for that’s been around for a little bit. And so in 2021, I built a prototype, basically a conversational AI or chatbot, which would basically help you convert leads. So, someone comes in, Oh, where are you looking to buy? Oh, here. Okay, great. What's your price range? Oh, what's your estimated credit score, like those kinds of things. So, I built something like that. And I remember we were piloting it with a customer. And basically it was, 80%-85% Accurate in a sense, right? which sounds good. Obviously the technology now is just so much better. You probably get that a lot higher and here's the funny thing about this is they didn't want to use it and roll it out and it's not like I spent a ton of time on this. This was just like a, a weekend passion project to just have something, but they didn't want to roll it out because what they said is, look, if this thing's wrong, even 10% of the time and it dumps, it takes a good lead and ruins it or puts it in a bucket that it shouldn't be in. Our loan officers are going to kill us, right? Even though 90% of the time it's helping them do their job. The 10% of the time you screw it up, they're going to call me and be like, you guys hurt my business. What's going on here. And so, I think that, when you think about it, obviously, risk is a very important topic in our industry. I think you can very definitively measure the risk associated with the operations piece and really in many cases, the AI piece is helping even mitigate risk. It's more accurate and so I think what's interesting is, I think there is this perception of risk with generative AI. People already worried about loan officers doing noncompliant things. So, then you put a hundred X force multiplier in their hands. Now you have a hundred X more worries in a sense. And then what if the AI messes some stuff up for them? There's a risk there and we can talk about how what our product's doing and why I think it doesn't add anything to the risk profile. But I think that's largely what's happening, with distributed retail and I think obviously you're going to see more and more of this in direct to consumer and there's some interesting products there because I think there's more of a system there, but I think it comes down to risk. That's my perspective. [David] There's a lot. Yes, I agree with you. There's a lot out there, but leveraging it is a challenge. What can lenders do such as tools and strategies that they can avail themselves of to better enable themselves to leverage their own data other than prop that, which is public data that's out there. [Spencer] Yeah, for sure. I think there's so much that can be done with data and now there are products that are starting to use AI that can help expedite this in a sense, right? And at Aidium, we have like a data warehouse light. It's not something, when I started at Aidium it was like, it wasn't forefront of my mind to have a data  warehousing type of solution, right? It's more of  just came up because you see lenders. They have a lot of disparate systems and again, I think it comes back to, you have the sales side of the business, the opposite of the business, your salespeople are not putting leads in encompass, right. and the opts people are not doing their loans and a CRM platform or a point of sale platform. And so I think you have a bunch of these different data silos and for me, I think it's so critical for the enterprise to be able to connect that so they can start to connect the dots on what's working and what's not working within their enterprise. And and what's cool is when you're able to bring your data into one spot. There are now these tools. Whether it's built on top of domo or snow, there's a bunch of these where you can even start to ask questions and they're pulling together these reports and giving you these insights in real time. And, I think over the next 6 months to a year, that's technology is going to be really good. And so I think, these data products have always been expensive and a lot of it is just, I'm building report after report and is it really useful or people really using it? I think where this is going is, once people unify their data, you're going to really be communicating within an AI to basically give you the answers and the reports that you want. And my message would be to lenders that haven't really invested in data strategy yet. Like this is a great time to do so because the technology you're going to get in the coming kind of years is going to really help you very easily pinpoint areas of your business where you can make improvements. [David] We're seeing a definite shift towards AI driven decision making and we're looking at an industry that has historically been very slow at adopting new technology, much less something as what some would characterize as scary as AI. How are we seeing this change right now? What do you see? [Spencer] I think it's a lot of what we've been talking about already. I think you see people adopting it more on the operational side from like an enterprise perspective. And then I think you see individual loan officers, adopting this too and a great example is we partner with a company called Canva which is a phenomenal, marketing and design company. [David] That’s a fairly recent roll out too, isn't it? [Spencer] Yes, for them and for us, we were fortunate enough to get into like their beta group to build in February and release it this summer. And it's just a phenomenal product. But what's really interesting is we found is like there's enterprise customers that we have that maybe there's a couple hundred loan officers there. Half of those loan officers are using Canva on their own with no enterprise oversight and the beauty of it now is great. Those enterprises can go get an enterprise Canva account, have the oversight and then, of course, it connects with our customers. But I think it just shows that loan officers are adopting this technology and that's where my encouragement and yeah, for sure. [David] The loan officers are faster adopting the technology than the companies behind that and I think that's what's creating the problem. We're seeing ourselves with companies always feeling that they're catching up. And some loan officers adopt this product, then another one. And so it's very desperate out there, what's going on in corporate is they're scratching their head. Which one do we do bet on? Which one do we go with? But when it comes to some of the biggest transformation that's happening out there, how are you seeing lenders adopt to this end of these new technologies? [Spencer] I think it's slow, right? It's like anything. I think right now, what we're seeing is there's always like the law of the early adopters and the kind of mid majority laggards, I think the early adopters are all over this and obviously as a newer company, Aidium, that's coming out with a lot of new interesting technology, we work a lot of the early adopters. And so we are seeing a lot of our lenders that we work with. They are trying multiple products on the operation side, and they're trying different products on the retail sales side as well. And I think that's happening and they're basically saying, look, we're going to take some compliance risks because I think we got to get ahead of this a little bit. But I don't think there is a I don't think there's a pre prescribed path quite yet for lenders to say these are the tools you should get and it's they're safe. They're compliant and they're effective. I don't think you have that yet. I think what we're still in the phase of a lot of these companies trying these different products, new products coming out and I think You know from our perspective at Aidium, with our intelligence platform, using propensity modeling to basically predict the likelihood of people purchasing, refinancing, closing loans, those types of things, it's basically a new flavor on things that the industry has seen, it's AI powered in a way for you to get the most out of your database and convert the most leads that you can. And so I think there's not a lot of hesitancy for people to engage with that because it's something they're more familiar with. I think what you're seeing is a lot of these newer platforms that are dramatically changing business processes. I think that's where it hasn't quite made that shift yet where like kind of the mid majority is saying, we're going to start to really use these things at this point. [David] We're seeing a lot more leveraging of data to make better decisions, but there's data that's readily available and then there's data that's not so relatively available. Could you sort those two out for us a little bit? [Spencer] Absolutely, at Aidium, we try to think about the needs of the enterprise and the needs of the loan officers. Not just one or the other, we want to try to bridge that gap between the two. And so for us, like when you think about the needs of the of enterprise, it's really enterprises make decisions thoughtfully and more meticulously and they're looking at something like, okay, they see the whole picture of the business and so for them, I think it's giving them access to more data and better data. And we just recently released our new AI scoring model we're scoring the propensity for a loan to close once it's basically like a file started, right? And it's really accurate. But what that's doing is it's providing almost like a weighted pipeline for the enterprise to say, Look, I know you've got these in these different stages, not all loans with application submitted are created equal, right? These ones are probably going to close. These ones probably aren't right. And therefore you can start to think about how you're running your business around that and so I think that's how we're looking to help the enterprises and then LOs are it's different, right? because they're on the field and they're busy and get a million phone calls, they're not sitting down with five people and saying, how are we going to improve our processes on this thing? it's more of trying to put stuff in front of them that's actionable, right? in other words, hitting them with the data of, Hey, look, most loan officers at your company are converting leads at this rate and you're not. Why don't you click this button and let's help you do that. Let's turn on some automation for you and so it's more of that kind of almost try to get the dopamine rush of Hey, we can help you make some money or improve here. And this is what the data says and just click this. And I think that's what we've seen to work is like building these beautiful reports and presenting it to LOs, it's just hard for them to find the time to sit and really ponder. I got this great report. What do I do? It's more of putting the solutions in front of them and say, quick, press these buttons, it's going to help. So that's how we think about it. [David] Yeah. One of the things, when I look at the various roles that are involved in doing this. When someone's looking at this and getting into it, how do you help your clients begin to assess the various roles? What are the best way to start is what are the various roles for having immediate actionable insights that play a help in working with loan officers. [Spencer] With loan officers, it's really the funnel, right? It's how many leads do they go to app fund? Recapture the two biggest drop offs are lead to app, right? Most loan officers convert 20% of that roughly. And then it turns out once an app is complete, they're actually pretty good at funding that there's a 50% roughly ratio we see, obviously you can improve, but it's a lot better than 20% and then it's the recapture piece that's really tough too, right? You close 10 loans and like 1.6, 1.8 do business with you again. 16 or 18%. I think those are the two areas right there that we really focus on, which is how can we help you get more leads into push them deeper into the funnel to complete that app. And then how can we look at your database? And help you identify who you need to be talking to and I think with the Aidium intelligence, we're really trying to help them should be proactive in a sense. Not reactive of oh, this person's pulled credit, which is great data to have but you're playing a little bit of defense at that point. And so if we can try to help them play offense, which is there's a lot of things going on in this person's life here and they're shopping out of some change. They have a new credit card, but they've got equity in their home and all of that stuff. It's hey, this pot is slowly boiling over here. I think it's a good time to reach out. Let's be a little bit more aggressive, so that way you're being a little bit more offensive. I think that's been the missing piece on the recapture pieces is I've done loans with a bunch of people. I have a big database. How do I stay friendly with all of them? The answer is you can't, right? and so how do we help you know, these are the people you should be friends with these people this month. Can we help you do that? [David] Which is really getting into the evolving lead prioritization process that's going on. The traditional lead scoring methods are really becoming outdated. How is this new technology, especially the AI component that's coming into it, empowering lenders to do a better job of scoring and getting the right leads in front of the right loan officer at the right time? [Spencer] I think a lot of it comes down to the underpinning technology in this technological revolution we're going through with AI. When you think about machine learning, a lot of it is more of these regression models, which are pretty linear in nature. So it's like someone they're really good at, someone does this, then they do  this and they do this, then we can predict.  The thing is life isn't usually that simple, right? When you think about a consumer, not every consumer has a kid then changes their shopping habits, then buys a car, then buys a house, that's where the linear it's actually, there's thousands of things going on. And so that's the cool thing about a lot of the new AI technology is it's very flexible and how it's building these connections and it's not linear, right? And that's just how very rarely is linear. And so I think the cool piece is being able to, the intent of the traditional lead scoring mechanisms is great. It's just now compared to what the technology allows us to do, it just is far less effective. It is wild to see with some of our models, the things that the models are saying, this makes a difference, right? And it's one of our models I was looking at the other day it's things like somebody who is looking to buy like an electric vehicle, right?  seeing those shopping habits, that actually is largely is actually very predictive of someone maybe looking to purchase a home, right? It's you can see the connection, but would you really think that, but like when the AI shows you and proves it, like there's a strong connection here and here's the data shows, it's interesting, conversely, someone that's owned a home over 10 years, the model says much less likely to purchase a new home because they've been there for a while and so it's like those kinds of things where you're taking these 5,000 data points we have, and the models are saying, these are the things that are predictive. It's really fascinating. And I think a lot of it comes down to just the technology advances that we've had and they're allowing us to build these really interesting, robust applications with it. [David] Where's this leading when it comes to lead generation or lead prioritization, what's your vision for the future in this? [Spencer] It does both, right? Because what it's essentially doing is it's scoring every person with their likelihood to do a purchase or refi based on all the stuff going on in their lives. And so, there's the lead prioritization aspect and you lay lead comes in your database. We will tell you to fit, based on the models, which are very accurate, we think this person's 40% likely to purchase versus this person's 5% likely to purchase. [David] So, you're putting a probability of a percentage probability of it. [Spencer] Absolutely. [David] And is that turning out to be fairly accurate? [Spencer] Yes. Yeah, for sure. [David] Are you getting more so I'm assuming? [Spencer] Yeah. The more data, the better it gets for sure and the more models we're running, the more we start to see what works because, we don't commingle data. Each lender we work with has their own, and but I think, so the prioritization piece and then there's the recapture piece as well, which is when we turn the model on and day one, we've actually throttled this because the first person we did this for, you've got your database of, let's say it's a lender, you've got half a million records. We're now we're showing you like a thousand people you should be reaching out to. It's overwhelming to loan officer, right? And so what we're doing is throttling it where the loan officer. We're identifying, Hey, look, there's a hundred people you need to reach out to. We're sending them like five a day. So, here's five people today. Now, here's five people the next day versus here's a hundred. It's overwhelming. [David] Most loan officers I'm not sure ready to handle five a day. it depends on how   their discipline is and what kind of process. When it comes to engaging clients through changing content and consumption. You talk about something called content consumption habits and they're evolving. Explain what do you mean by that? [Spencer] I think what's happening is loan officers, obviously the past two, a couple of years, it's not raining refinances. They've been thinking hard about how do I differentiate myself, right? and a lot of that has been, I'm going to take some time to figure out, establish my own brand, my own identity and the value I'm portraying to the marketplace and of course, AI is accelerating your ability to do that. I give the example of Canva, there's where all these people were, can you imagine five years ago, half of the loan officers at a company using Canva, like now they're actually like, they realize that's an important part of what they're doing. And I think  from our perspective, what we're seeing is a lot of. loan officers really look at leaning into, I want to put my own spin on this, or I want to do things our own way a little bit. And we've obviously from the very beginning, we initially worked with top producers and I've moved more enterprise centric and our software, we want to make it as flexible as possible for the top producers. But we're seeing a lot more of that than we were two years ago, where these producers are, getting in and customizing and configuring stuff. And I think what's also interesting here too is, it's something we don't talk about as much. It's not as appealing as like the fancy modeling, but we do have a persona builder as well, which is segmented. [David] Persona builder, explain that. Explain what you mean by a persona builder. [Spencer] Let's say you have a database of 1,000 people, right? If you look at certain traits, you can probably, roughly put them into buckets. So what we see is Muslim officers or companies have fortified buckets where they groups of people, right? And to give you an example… [David] The companies have four to five buckets of people, are you talking about leads or MLOs leads? [Spencer] Leads. So they might have some that are let's say, they're maybe it's a first time home buyer. They're really stretching to get to DTI and all that. And then you might have a group of leads, people in your database that are very comfortable and maybe it's more like they're going to be looking to downsize because kids are out of the house or they're leaving the house, right? Those are very different groups of people that are very, very different parts of life. And, unfortunately most people are treated in the same way. I'm sending the same content to both parties. And in reality they both care about very different things. And you always got to be careful with the content because you can go down a rabbit hole and you could have a hundred personas, right? But I think what we're looking to do is can we provide four broad buckets here and maybe some personalization, especially with the monthly newsletter content or something? Can it be a little personalized based on the persona? and then of course, with the reporting, we're tracking what's working, what's not working, but I think you're going to start to see more and more of that and Gen AI will make that more doable because content creation is hard, right? And Gen AI makes it easier to create it. Then great. Let's start segmenting this a bit so we can get much higher engagement and so I think that's going to be a big trend that we start to see this next year in the industry for sure. [David] There have been automated playbooks to a certain saying there's content creation platforms. And then now AI is playing into more and more of that. How would you guide lenders with your firm and what you're doing to create and deliver a more personalized, relevant content to build the stronger relationships? [Spencer] I think there's three aspects to this. First, it comes back to the data. If you don't know what your engagement and what's working, what's not working, it doesn't really matter. You keep, there's then, okay. So you have to have the data set up. And obviously we have the marketing reports to show you like these types of people are engaging with this more than others and it's just the data shows like this is working and this isn't working. And I think the second piece of this is bucket in your database. And obviously we have the AI models that are doing this and I think it's pretty cool, but you can even do this about this. Like you could go in and create some manual buckets by age or by certain traits. Like you can manually do something like this too, and then from there, I think it's if you're doing like, I'll say a monthly newsletter or something like that, I think it's just, okay let's tweak this a little bit based on the personas and let's see what happens are we getting a lift? Like last time, the young, the younger bucket of people really didn't engage in this content. Oh, this time, they did. And so it's a little bit of trial and error. I would say, and I think we're going to see, some of the stuff you'll come into play is. You could probably feed this stuff into a ChatGPT and say, Hey, look, here's my last four newsletters. I got much better engagement on this one. Can you take this general newsletter copy and update it to be a little bit more in line with the one that got better engagement, right? A lot of these tools can do some of that stuff today. But that's again, the beauty of the Gen AI. It just makes what would have been painstakingly, monotonous to something that's a lot less painstakingly monotonous. [David] It's not monotonous, but most MLOs just don't have the skillset to do that. There's those that are the content creators and those that are just out there selling. And where are you seeing the role of the loan officer going as we see more and more of this technology coming on? is there a change of what type of MLO we should be hiring in the future? [Spencer] I think it's a good question. Because you not only have the technology change, but of course you have the NAR stuff too, right? Which I think the NAR stuff is actually favorable for loan officers that get a little bit higher up on the funnel. I think you see a world, maybe it's not next year, but you see a world in the coming years where the initial point of contact is the LO, not the maybe not the realtor or there's more of a more of a blend, then there has been historically. Yeah, I do think that, obviously having a strong referral partner base is really critical and creates predictability. But I do think the LOs that are using this technology and thinking about how they can leverage it to go out there and find new business are going to do better and take more of the market share. [David] When you say find new business, is there a consumer direct component to that, or they're going out and connecting with the consumer? Is that what you're meaning when they're saying finding new customers by connecting with a consumer? [Spencer] Yes, it'd be more direct to consumer. But I don't really see, at least in the short run or maybe ever, this idea where direct to consumer just, basically everyone pushes a button and gets a mortgage, right? I think it's very complicated and there's a lot of risk and compliance and anytime you have a lot of compliance, it becomes really hard to fully automate it. There needs to be a person, and sanity check there. And I don't see the retail LO going away, I think what I see is the retail LO being able to maybe start to incorporate technology that almost looks a little bit direct to consumer in a way, is maybe how I would say it. [David] That's a good characterization of it. I think there is some more of a shift to that. I think the more we can get in front of the consumer ourselves and establish that relationship before they start talking to a realtor. That individual is going to fair, far better than the one that's just relying on the realtor to bring them in the business. And I think you provide those tools that really begin to help people connect with a consumer. The whole journey, you really do so much. What is the best fit customer for your product? You think? [Spencer] I think it's mid to mid to large size independent mortgage banks is our bread and butter for sure. And then, we've with the propensity modeling and the AI, it definitely has opened up a lot of avenues for us with credit unions and banks because they want that 360 degree view of the customer as well. But I think we do really well with the distributed retail. Obviously that's what we built the platform for. And yeah, and we love working with those types of companies. [David] Last year you rolled out the Canva integration. It's a brilliant move, seeing especially when you see how many loan officers are working with Canva. What do we have to look forward to with Aidium as we move forward in the 2025? [Spencer] Yeah, the big 2024 thing was of course, the propensity modeling, the Aidium intelligence, which is we'll continue to improve upon, of course. [David] Canva, that was a cool thing to do in addition to the technology. I was just really, [Spencer] Yeah. And Kim has a great platform and we have more planned with them for sure. I think without giving too much away, here's what 'll say. I think that what you're going to start to see just broadly speaking with technology is you're going to see the UI or the interface matter a lot less and so for instance, do you value Uber because it's a slick app or do you value it because it gets you a ride, right? In other words, if an assistant would just go book your ride. Then do you really like how much value is there in the app? And so I think that, not to preview anything, but, we will have some launches around this, in the summer is what we're looking at where there's going to be a component of that where loan officers that maybe aren't used to using technology. There's going to be an AI component to help them get the most out of what Aidium offers without them, maybe they don't need to be in the app. There is that kind of interface, there is that almost assistant kind of concept that is going to and so that's as much as I, I want to tease without it, but it's going to be pretty slick. And I think that is where the future is headed and we're excited to build to that and offer that to the world of mortgage for sure. [David] I think 2025 is going to be a much better year overall. It'd be still coming out. 2026 is where we're really looking forward to, but 2025 is going to be a good year. And I recommend companies to check out Aidium and learn more about yourself. How could they do what's the website and how could they connect with you if they want to talk to you, Spencer? [Spencer] Yeah the site is think aidium, so think A-I-D-I-U-M.com and also on LinkedIn. I've spent some of that stayed away from social, but our lenders are on LinkedIn and so I'm starting to be more involved in LinkedIn and have some conversations there. So connect with me on LinkedIn and, for me, like I'm again a product engineering person, so I love when people throw interesting problems at me, and so to the extent people have ideas for the propensity modeling and stuff like let's, find me on LinkedIn and let's have those conversations for sure. [David] That's good. Excellent. Thanks so much for taking time to be with me today, Spencer. I love what you're building. I love the team that's around you. I got to tell you some of the most upbeat, positive people. Every time I'm at the conference, I run across you and your team. There's just some energy happening around you guys. It's really fun. [Spencer] Awesome. No, I appreciate that and yeah we're working hard and it's been fun. To your point, I think 25 is going to be a even much more of a fun year for the industry. So excited to lean in. [David] We're glad to be in partner with you. Have a great evening and a Merry Christmas to you, Spencer. [Spencer] Awesome. Yeah. Thanks. Merry Christmas as well. [David] You bet. Thank you.

Important Links

• Aidium website
• LinkedIn - Spencer Dusebout

From a young age, I've been driven by a relentless passion to solve problems that others deem too complex. At 16, I co-founded Hands4Others (H4O), transforming an idea scribbled on a napkin into an international movement that brought safe water to over 250,000 people in 17 countries. This early experience ignited my obsession with using technology and innovation to address critical challenges.

Over the years, I’ve channeled this obsession into building several successful SaaS companies, with a focus on business intelligence, automation and machine learning. My journey through the tech world has been fueled by a deep understanding of the gaps in technology, particularly in industries where the stakes are high and the need for robust solutions is critical. More recently, I’ve turned my attention to the mortgage industry, where I see immense potential for automation, AI, and data analytics to not only streamline lending operations but also empower leaders to make smarter, more informed decisions. I believe that the future of this industry lies in bridging the gap between traditional practices and the advanced capabilities that modern technology offers. My latest venture, Aidium, is a highly customizable mortgage CRM and business intelligence platform that leverages AI-driven predictive analytics, robust data reporting, and intelligent automation to drive loan volume, enhance business decisions, and bridge the gap between loan officers and enterprises.