Abacus Global Management, Inc. (ABX) Earnings Call Transcript & Summary

Full house today. This is pretty cool. Everyone know the history of this room. So just a quick, if you were there last night, amazing, Anna, who had led our history lesson on not just the New York Stock Exchange, but a bit of history that I was kind of uninformed on. She was spectacular and wonderful. And one of the things that she didn't get to talk about was this room. So this room that we're in, we purposely selected for this event because we were very excited, partly because this used to be the kind of ballroom lunch room where the brokers would come in and have lunch at a specific table. And ultimately, what happened was, and I think they've covered some of them now, but there would be scaffolding and other things outside of this room on the outside of these windows here, and you would look for little drill holes because people would sit on the outside and drill holes into the side of the building so that they could hear what the brokers were talking about and try to pick up on stocks, get stock tips, different kinds of things that had happened. It's pretty cool. Like you can actually go through and she showed me one, I don't know if it was real or not, but it sure looks cool. And I kind of think about that now when you're going to sit here today at Abacus' Investor Day. And first of all, we couldn't be more excited, thrilled about not just where we've been, but where we're going. And I have to believe that as the market has really learned more and more about Abacus' story, there's a bunch of people out there along the side listening to these little holes and wishing they were in this room. As the story continues to evolve and become more common and understanding, that is what's starting to happen in real time. And when we think about time, the first thing I want to do is acknowledge each and every one of you for taking time today. We've got a terrific agenda. We'll touch on some of those things, and you're going to have an opportunity to really see, listen to the people that are really driving this engine, really driving this car. And one of the takeaways that I hope that you're able to pull from today is that what an amazing business. I've heard many of you say that to me, but now you'll actually understand. You'll see what I get to see every single day. And you'll sit back and look at this and say, boy, that was a great use of an incredibly valuable resource, my time. That's what I want you to say. Today was a great use of my time. How do you place a value on that? It's really interesting, right? Like when we think about commodities, we think about gold, we think about oil and gas, not very often do we put or think about the most valuable commodity that exists. by far is your time, your individual time. Now some would argue that time is not a commodity. Why is that? Well, because it's not a tradable value. Now I would argue otherwise. Because time is scarcity, it's limited resources, it's incredibly valuable. But they are right. How do you place a value, an incremental dollar, a tradable dollar on time. Let me walk you through a quick exercise. Each and every one of you, just think in your head, if I were to give you a gift and that gift was an additional year of your life healthy and prosperous, no issues. How much would you pay for it? If I were to sell that to you right now, how much would you pay for a year? Think about a number in your head. I think about it all the time. The challenge is each and every one of you has a different number. And what's the basis for the dollar number. Sometimes it's what you might have in your bank account. But more than likely, it's because you're at a different position in time, meaning that when you think about time -- as a period of time, you think about it in a straight line. You think about it, I'm 20 and I'm going to be 80 or I'm 80, I'm going to be 85, it's a straight line. What do physicists say about time? It's a curve. It's actually an arc. So what sets the value of your time is where you sit on the arc. If you're in the front end of the arc, you're going to pay less for that year. If you're on the back end of the arc, how much will you pay? Everything. What Abacus has done has helped you solve and will help you solve and will help everyone solve. What the value is of the greatest, most scarce and most important resource in the world, your time. And how we do it is, is that we help you better understand where you are in your arc. Think about that. We all love market maker businesses. Abacus is a market maker in what we do in our Life Solutions business. We are going to be the market maker, the infrastructure. I'll say it again, the market maker of time. Now you think about that. Tell me about another business or company that you're a part of that can present that type of opportunity. We're going to have a couple of great speakers today and where we sit and you think about that concept of how Abacus is going to be the market maker of time. As we always say, please read those. I'm not going to. Ben Franklin said what? Time is money. So Ben Franklin said, pretty wise guy. It goes back about 250 years that time is money. How do you correlate the two? So many times in financial advice and financial planning, what we talk about is how much you will have at some point, maybe how much you will have in retirement, how much you will have for your legacy and for your heirs. When we think about being the market maker of time and you look at the 4 verticals of where Abacus sits in our Life Solutions business, how do we set the value of time, the net present value of their life insurance policy, right? Pretty incredible. We paid out $0.25 billion as a market maker of time. Asset management, how we manage our portfolio has raised nearly $1 billion over the last year by understanding the value of time. And now when you think about personal finances, the question that's always asked for somebody is how much will you have? That's how we manage assets today typically. We're reframing the question that says, instead, how long will it last? And then we're going to say, how much do you want to spend? So let's take a quick example. We have 2 neighbors, both age 65. These are real examples, maybe not my neighbors, but one of yours. Both age 65, both retiring with $2 million, both handed the same exact financial plan. On that $2 million, what typically happens is neighbor A goes in, sits down with their financial adviser, they're 65. I have $2 million, what does their plan look like? It might be 60-40, it might be 2% to 4%. It might be some standard premise. But what's fascinating is what about neighbor B? The second neighbor goes in and gets the same exact plan. What we do know underlying is a fact though is that their arcs are different. Neighbor A sits on an arc that has lots of time left, very healthy, projected lifespan to age 97. Their incremental dollar value that they're going to place on time is much different than neighbor B, who has a lifespan much shorter. This person is impaired with an 11- to 12-year lifespan, age 65. How much value do they place on their time, much more, right? These customized solutions are not easy to do unless you have all the data to support that. And you're going to hear a lot about that today. All the data we've aggregated over the last 20 years, we are now implementing this to be able to design two different plans as they should be for these two different -- completely different individuals, even though they're the same age. Customized solutions and financial planning, what ends up happening is something very, very compelling. First and foremost, we end up increasing their income on a significant basis. Neighbor B, we can kind of get and understand, 11- to 12-year lifespan, of course, you're going to take out more income, $160,000 a year, leave another nearly $0.5 million a year, shorter lifespan, we get that. What the shocking piece to me was that when we look at this and you have somebody who's going to be in retirement for, in this case, what, 32 years. But when someone is 65 and they're going to live a long time, what's the first thing you say to yourself, go conservative because you don't want them to run out of money. The exact opposite should happen. If you have 30 years to go in your 401(k), right, you want to retire at 60 and you're 30, how do you allocate? Do you go 80% bonds or the reverse. This is the difference in the power of these stories. This is how you place the value on time. And how we're able to do it is that as a financial infrastructure firm, we created an entire line called within our Abacus Intel division called LifeARC. ARC stands for Actuarial Risk calculator. This is helping you better understand the value of your time and making Abacus as the infrastructure of that time, the market maker. And this will apply not just to what Abacus does with our clients, but financial firms across the country. We start with our medical history analysis, all of our lifespan modeling, and those 2 things have such a huge impact to someone's investment and their income. This is a real example, and I'll walk you through this just so that you can kind of get an idea. 79-year-old Floridian, $8 million portfolio. We actually acquired this individual's policy and sat down with him and then went over and said, how are you going to apply your lifespan. So we applied this in two ways. One, the value of his life insurance policy. Second now is how do you apply that to a financial plan. With a 9-year remaining lifespan at age 79, what he was doing was that he was taking out about 2%, about $160,000 a year. That's kind of where it was. What we ran is we said, well, with 9-year lifespan and as you graduate this down, you're going too conservative too early. He could actually pull out $317,000 a year and increase the value of his account to almost $10 million. This is the impact in understanding time. Time related to asset allocation is going to be a huge fundamental difference. How does this all work? And what is the grand scheme and what is the size of this market that's available really quickly. What we see is in the financial services market, do I have to work with every single one of these clients? No. But what we will do is that this will be a financial infrastructure that will be then utilized by every financial planner. And guess what, they'll pay us a little bit of something all along the way. When we think about recurring revenue, the businesses that have been most successful is through infrastructure and financial infrastructure. We will be the financial infrastructure and engine for how financial planning is done not just today, but in the future. By the way, that client that we increased those assets to, they're coming. They're leaving a major firm because no one has ever spoken to them about this in the past. How big is this opportunity? We've all heard about the $124 trillion wealth transfer. Just a point of perspective on what the size and scale of $124 trillion means. If you were to spend $1 a second, when would you have to start spending money to spend $124 trillion to get to today? The ice age, the ice age. You want to talk about the size of a moat and the size of a market, start with one that's $124 trillion. This is a generational wealth transfer that is occurring. Wouldn't it be nice if you were on the other side of this as a financial planning firm and you knew when that was happening. Let's go back to the client. We talked about the 79-year-old 9-year plan. You know the other conversation we had was with his son. Speaking with the son about how this financial arc is developing now changes their financial plan. And you know the next thing you do, you don't underwrite them once, you underwrite them every single year because that plan, that arc -- that individual's arc can change every year. So on a commodity basis, if I were to share with you what a commodity market looks like, that's $124 trillion that we're the financial infrastructure for, you get pretty excited about it. And that's why, hopefully, you see how much excitement I have about this. We haven't started this program on our own. We made a material investment into a firm called Manning & Napier. Some of them are here, so welcome. And that's an $18 billion asset management and RIA advisory firm. We've been launching this program directly with them. In the very short term, we have discovered opportunities to the tune of tens of millions of dollars in the first month. This isn't something that says, "Hey, Jay, that's a novel great idea. This is something that is literally in practice right now and is being effective, and we are literally shifting the mindsets of our clients in real time by helping them better understand what the most valuable resource that they have is as a commodity. And we are the market maker for that commodity. And that's the value of their time and the value of their time increases their portfolio many times 2x in income and 20% to 30% on the legacy that they're leaving to their clients. How big is this opportunity? We're going to meet and sit down with someone here in just a few minutes. His name is Matt Ankrum. He was kind enough to include us in his book, The Coffee Can Investor, where he talks about 100 bagger opportunities. Frankly, when you look at the size, scale, scope of this kind of opportunity, I feel like Elon Musk would say it's at least 1,000 bagger, but Bill would lose his mind if I said that publicly. So I'll stick with what Matt said. And when you have a tailwind of $124 trillion over the next 30 years, it's pretty exciting, knowing that you can build recurring revenue on an infrastructure play through the most core asset. And by the way, you know who else is doing this? No one. Why? Because they don't have the data. We're sitting on the data. We're sitting on the records. We're sitting on the actuarial data to produce this into a $124 trillion-plus market that people are coming to us for, and we're changing the impact in how they view not just financial planning, but the most valuable asset they have. And we're driving that through our data, through our AI-driven platforms. And of course, the product result of that was our LifeARC program. I said that time is not a straight line, physicists agree with that. Your lifespan isn't either. You shouldn't measure it that way. It's an arc of probabilities, and you just are going to sit back now and solve for where that arc is, and Abacus is going to help you as the market maker for that arc. Pretty heavy. We've got a lot of amazing things that we're going to talk about today. Again, as you hear through and sit through our presentations today, one of my hopes is that your biggest takeaway is Abacus has got an opportunity here, and we are just literally at the beginning. It's been an amazing 3 years. Where do you see the next 3? Because it is very, very rare. You have the company sitting in the position that it is today that actually generates revenue with a technology, with a basis and a market size and scale that's doing what we're doing right now in real time, and you're seeing it happen in real time. So as we go through our agenda, again, please enjoy everyone that's getting up here to work through this because I think that they all have something pretty incredible to bring to the table. Just as a point of reference, when we get to the 11:30 portion where we have our 2 guests coming up, interviews, we're going to turn off the live feed, and it will just be a gift to you here live. So don't leave early. If you don't know who John Catsimatidis is, you will. He's a lot of fun. And of course, Maria Bartiromo is joining us later. But before that occurs, and before we launch into our presentation from Bill on the financials, which is also thrilling. Bill, just, yes, we've got a terrific guest speaker with us. I've had the opportunity and pleasure to get to know Matt over the last, gosh, Matt, probably 6 or 7 years when he first started looking at our business. Matt has co-authored a book called The Coffee Can Investor. If you're familiar with Coffee Can Investor, it actually goes all the way back to Warren Buffett, but it's the premise behind 100-bagger companies and the qualities and themes that those companies have had historically. And then he went a step further and actually picked what he thought would equate to some of the next 100-bagger companies. And I'll take a moment and just read his bio here. He is a managing partner at Ankrum Capital. He's a chartered financial analyst. It's been a career studying what actually separates good investments from truly extraordinary ones. That's why he picked us. He's best known for his 100 bagger study, deep look at stocks that multiplied in value 100x across decades and for the long-term compounding and driven investment philosophy that came out of research. That work is the foundation of the book, The Coffee Can Investor. And we're proud to say Abacus is featured in the 100 Baggers companies' book. And Blake, I'm not sure where she is. There she is. I think we have the book or do we order those? We can -- anybody who would like a copy of that book, we have those, and we're going to be sending those out to you. And before I bring Matt up, I do want to acknowledge our team who put all this together. So Blake Gallimore and the ICR team, thank you so much for all the hard work. Last night, if you enjoyed it and you love this today, make sure you tell her thank you. She's worked endless hours to continue to put this together. But in the meantime, please help me join Matt up on stage. Everybody right here? [indiscernible] Okay. What -- how does the company get kicked off the list? I want to make sure we don't ever get kicked off that list. How do we -- so look, Matt, like let's kind of start. We've got a few minutes here. We just want to introduce everyone here to what you did. Could you start with a little bit more detail on kind of your original background? What got you here? What drove the idea behind The Coffee Can? And I know it involves your family and some other things, and I think it's worthwhile hearing that piece.

No, it does. And thank you, guys, for coming out and hearing us. So I was a portfolio manager and analyst for about 20, 25 years. Then I went on and became Head of Strategy for a Fortune 500 company, then went out and cofounded my own FinTech Software-as-a-Service business, eventually then became CEO of a brain neuro-rehabilitation business and then got back into on the investing side. What I think changes a little bit is that when you do both sides, you actually have a very different appreciation for what investing really means, right? Because as a portfolio manager, it's really easy to put a 50 basis points improvement in the margin for the next 20 years and think that's just going to happen. What you end up really finding is when you're running companies, you realize how hard that is and what it takes to do that. So with that, one of the things I did was I went out and said, well, I read this article by Robert Kirby talking about The Coffee Can portfolio. And it's a great article. But basically, he came out and said, here's a way to put great companies and own them for a long period of time and how they compound with time. And so I went in and I was looking at that, I was like, well, which companies would I want to put in that portfolio? And so I went out and did a study, and it's -- I call it the 100-baggers study, but I went out and looked at all companies that went public from 1980 to 2000 that increased in value by 100-fold. And the reason why I was looking at over that time frame was that I wanted to have looked at it about 30 years. So it's 100-baggers over 30 years. And the reason why I chose that number was that that's about double what the market is. So these are phenomenal companies and what they do. And so that's what I'm sure we're going to be talking about is the real characteristics that came out of that. But it really -- the book, one of the reasons why myself and the actual author who -- if you like the book, it's because he wrote it, it wasn't because of me. I'm just kind of the content in there. In fact, I know he's a great author because he actually can make me sound interesting.

He was the President of CBS, right?

Yes, he was the co-head with CBS News. And I've known him for like 25 years. And so what we did was both of us looked at it and said, here's an opportunity to take what I've learned and then be able to basically provide the financial literacy for others. And while doing that, what we're looking to do is actually build a portfolio for my daughters and talk about building kind of generational wealth for a long time. And so that's what the book is about is going through the process of saying, taking the ideas from the 100-bagger study, applying them to actually finding stocks, which is always a dangerous game, putting the ideas down on paper. But then being able and willing to hold them for 30 years.

Yes. I think that's the point, right? I think that's -- when I read the book and I thought about this, and some of you in the audience may be feeling the same way, holding a position for 30 years or considering that hold for 30 years with the amount of digital information that's available to us and the frequency of trading that you now see, would you think that of the relationships that you saw in those companies, I'm just curious within the study at all, whether you had kind of identified that said, gosh, there weren't that many people that held it for 30 years. I mean you as a portfolio manager, you get redemptions, you've got to sell it. I mean, was that -- is that the biggest issue with 100-bagger companies? Is it people just don't stay in them?

That's why they don't get the returns. Yes, of course. So -- but for the companies themselves, they're the ones that are just compounding every day. They're doing the little things every day. From a portfolio manager standpoint, the reason why most people can't do it, they just can't afford it. They don't have the intestinal fortitude to go through that. So to give you an idea, these stocks, most of them -- all of them obviously went over 100-fold, but some of them went 300, 500, 600 folds over that time frame. But here's the crazy thing is that the average drawdown from the peak to the bottom was 70%, meaning every single one of those companies, you had the average down 70%. Some of them down 95%. Obviously, Amazon was in there. But to be able to hold that through is what is so hard for a lot of people to do. And what Jay is referring to as well is that the average holding period today, five and a half months. I mean think about it in the 1950s, '60s, it was [indiscernible] five and a half months. And the reason why that is such an important number is because think about you as a leader of a company, the likelihood that you could change the direction of the company and do anything in five and a half months. So a lot of them, they're just trading on kind of predicting some reason why the stock is going to change in the short term.

Sure. That's super interesting. I mean, LifeARC itself, where we talk about this fundamental technology that we're bringing out and that we're rolling out is going to have this huge impact, took us 3.5 years to build, right? And that would have -- nobody could be able to trade on that tech. And that's a super fascinating piece of that story. I'll add one thing to what you said, which is super interesting. I had a conversation with Peter Lynch. And one of the things Peter said to me was that within any 12-month period, particularly small-cap stocks, you'll see 100% spread between the high and low. I mean just think about that, right? And frankly, we saw that with Abacus, right? Like I think we're up 130-some-odd percent year-over-year. But -- and then Peter's premise was, though, is that you kind of reset your lows, right? As the stock continues to grow over time, you're kind of resetting your lows, but you see those spreads happen. When you think about the qualities of the underlying companies, I think what you touched on is super interesting, just compounding returns consistently. What were a couple of others? Was it management consistency? Was it -- maybe that's too basic, right? Or were there some other things that are pretty common that we should be paying more attention to?

Yes. So as I was going through the study, several patterns kept emerging. The first one was that quality comes before everything else. Said differently, no mediocre company compounds its way to an extraordinary stock over time. Second was that growth matters. But the duration of growth is a lot more important than the velocity. Now the average company in the study actually grew their top line by 20% a year for 20 years and that's remarkable, right? But the bigger lesson from all of that is that it was actually -- duration of growth actually beats explosive growth. And so -- and the reason why that comes about is if you think about it in compounding, the heavy lifting all comes at the later years. It's the same reason why Warren Buffett has actually amassed 98% of his net worth after the age of 65.

It's amazing.

Yes. The third was that the best companies actually improve -- continuously improved. So in the study, on average, they expanded their operating margin by 25 basis points a year. That's 0.25%. It doesn't sound like much. And in fact, in the year it happens, it feels almost imperceptible. But those small thousands of changes that they do are the ones that actually create the insurmountable advantage that the companies enjoy years later. So if I switch it to the qualitative side, those are interesting as well. And so one was nearly 60% of the companies in the study were founder-led or family run. And you can say, well, why is that important, right? Well, think about it, if you're owning these things for 30 years, management matters. And what was fascinating on this, too, is that every single company in that study actually incurred some kind of existential crisis, whether real or perceived. And it was the leaders and the winners that came out of this were the ones who are willing to make the financial or the difficult decision to ensure the financial health. And I know this -- others might have a different view on this, but what I've actually found is there's a meaningful difference between owners and caretakers. Just like I think there's a big difference between parents and babysitters. Perhaps the most surprising finding that I actually had from the study was that over 80% of the companies were serial acquirers. Now this was surprising to me because as a young analyst, I was always taught the only -- you want the growth that actually matters that you should value is organic growth. I no longer believe that to be true. And it makes sense, right? If you have a high-quality company generating high returns and growth, they throw off a lot of cash. So it is the smart manager who actually intelligently deploy that money into strategic acquisitions. Now I want to note, these are not the bet-the-farm massive acquisitions like an AOL Time Warner. These are actually very thoughtful, strategic and oftentimes really small bolt-on acquisitions that accelerated the company's strategic and R&D road map. And then the last one I'll actually point out is more of an observation. Not one of the companies in the study came from an industry that we consider glamorous. They weren't chasing the hot markets. In fact, if you look at it, most of them were unsexy, pretty boring industries, but they were massive in construction, financial services, healthcare, right? And these leaders every year took share year in, year out. And what it actually told me was that extraordinary returns are driven more by exceptional execution, not some exciting industry. So if I was to sum up all of my kind of the learnings that I had from that, it'd be this, is that the greatest investments are not built on predicting the next big thing. They're actually built on owning exceptional companies by exceptional management teams that actually can compound for an exceptionally long time.

Sounds like Abacus. That's terrific, Matt. And it's interesting on the Warren Buffett piece. I've said that. Actually, we used that with our case example before when we think about how we asset allocate to 65-year-olds. Warren Buffett wasn't in fixed income, right? And accumulated 98% of his wealth in equities, past age 65. And so when you start to kind of tie all that in, it's really fascinating to then see how everybody can apply similar investment strategies to the same way that Warren Buffett did. We -- I'll give you one more, and I'm sure there's lots of other questions, and I want to make sure that you all have an opportunity to chat with Matt. You'll all have a copy of his book. And Matt can make himself available if you want to dive down deeper to some of these concepts.

It's interesting, though, when you think about these companies, right, over a 30-year period, where did they start 30 years ago, right? I mean did they start as large cap? Did they start as small cap? Did they grow into large cap? I mean compounding 20% per year, I get that. I mean that's pretty incredible over a longer period of time. But particularly founder-based business, I assume like a lot of companies started in garages. But was there any trend there that said, hey, they erupted out of this area or came out of this area? Was it just consistency over time?

Here's something that I think we as humans struggle with is this -- in this concept of compounding, right, is that just -- if you're just in the market over 30 years, you should expect your investments to increase by about 20-fold. Now to put this in perspective, everybody who actually owns NVIDIA if you think that it should just run in line with the market 30 years from now, it's going to be, what, $110 trillion company, which boggles people , right? So what I actually found was it wasn't necessarily the size of the company because they all come smaller, right? And they go smaller to big, after big, kind of larger. But here is what the amazing thing to me was is that all of them actually were fairly derisked at the time that they went public. And what I mean by that is that they already had a viable product. They already were generating good economics, and they actually already had the ability and demonstrating the ability to grow. So that's, again, playing into kind of what a lot of people's misperceptions are is they're always wanting to chase a hot new thing. And the reality is they're just great businesses that continue to grow. And again, they have to start small-ish because when you're increasing by 100-fold, it's a little bit -- it's probably going to be a little bit harder for a [indiscernible]

Where would that put our price target, somewhere around $100, -- our price target somewhere around $100 is what you're saying?

Yes.

Okay. Just that's where analysts are. I'm just kind of lobbing that out. Matt Ankrum said it. So when I go into your offices and I tell you we're worth $15, I think that's fair.

Actually, the price target would be $1,000.

Oh, that's right. I'm only a 10 bag.

Yes, you're only a 10 bag.

$1,000, Bill? [indiscernible] me in.

Yes. But remember, that is over 30 years. And that's why...

30 years, let me think about my LifeARC. I'll be here. How would you say?

I need to see that.

This has been terrific. Our time is a little bit short, but I also just wanted to acknowledge and thank you for including us doing the research, you did the work. And the information and data that you're providing is incredibly useful to investors everywhere. And look forward to seeing you again up here. Thanks, Matt. So in summary, $1,000 price target. Okay, I'm kidding. I won't even say it out loud just because I'm sure David will lose it, our Head of IR. But it's just important to note, there are some basic great qualities that encompass businesses. And if you heard that list, we check a lot of boxes. And so I think it's fair to say why we were included in Matt's book. And when we did go public, we were a business that had produced consistent revenue for over 20 years in the same industry, which someone might seem as a pretty boring industry, right, in acquiring insurance policies and using medical data and lifespan data, but then you look at how we've grown. We didn't break out '25, but 20% a year is exactly where we target. And if we go out and you're a long-term investor and you start to see some of these visions, which I'm hoping you'll hear today, we will affirm that there's a great and significant opportunity here for everyone. And we're going to continue to grow because we've got a phenomenal business that generates revenue with consistent management. And we're excited to have you be a part of it. And speaking of that, our next presenter is Mr. Bill McCauley. Mr. Bill McCauley, who has recently assumed the role as well, was earned the role of our Chief Operating Officer. He's our Chief Financial Officer, wearing a little bit of dual hats as well. If you haven't met Alexei, he's here in the office or here in the audience as well. He's our Chief Accounting Officer. And the point is that we're bringing from within some pretty amazing talent. And Bill has been with us now 6 years, I say it right this time. Sometimes I extend it. But he's been with us 6 years and has seen the growth and how we've been able to expand this business, growing from where we were, I think, our year 1 public was somewhere around $35 million EBITDA to, I think consensus has us at $150 -- Patrick, where are we at now? North of $150 million. I'm not going to say whether that's target or not, I've just thrown out a consensus number. What an incredible asset to our firm. He's worked at and had significant financial roles at Transamerica, MassMutual, McKinsey, John Hancock. We were honored to get him 6 years ago, and I'm even more honored to introduce him here today after 6 years. Thanks, Bill.

Thanks, Jay, and thanks, Matt. What a great interview. I want to take a few minutes and surprise, put some numbers up on the screen because I think that criteria that was discussed, that financial DNA of 100-bagger companies, that maps almost perfectly on to what we're seeing in our actual financial results. So let me show you the scorecard. Q1 2026, we had revenue of $59.4 million. So that's a 34.6% increase over Q1 2025, well above the 20% sustained growth threshold that the 100-bagger framework suggests. We had $32.7 million in adjusted EBITDA at a 55% margin. And we've been in that 54% to 56% margin for multiple consecutive quarters. So that's not a 1 quarter number. And then there's the operating cash flow story. So in Q1 2025, we had negative $61.6 million in operating cash flow. And in Q1 2026, we had $91.7 million. So that's a $153 million reversal. A lot of that had to do with the LMA Income II Fund coming to the end of its initial term, which also reduced $76 million of debt off of the balance sheet. So the 100-bagger framework requires 3 things working simultaneously: revenue growth, expanding margins and strong returns on investing capital. And Q1 2026 was that framework in action with a balance sheet that's getting cleaner by the quarter. In 2025, we built the foundation. Gross revenue of $235 million, which is more than double where we were in 2024. Adjusted net income of $85.7 million, adjusted EBITDA at $133 million at a 56% margin and return on invested capital and return on equity, both at 20%. And we ended the year with approximately $3.6 billion in gross assets under management. On the right side of this slide is more of the forward look. So earlier this year, we increased our guidance -- our full year 2026 guidance to $100 million to $106 million of adjusted net income. So that's up to 24% growth on top of a year that we more than doubled the business. But beyond the headline numbers, we have an AUM target of over $5 billion for year-end. A lot of that is going to be driven by inflows into our longevity funds, where we had targeted about $500 million in the first half of the year alone. And we also have Abacus Intel revenue target of $3 million for the year as we begin to monetize the 2.8 million lives across 100 -- more than 100 institutional systems. And then lastly, pushing our recurring revenue mix to 20% towards our goal of 70% fee recurring earnings by 2030. So the path to scale. So the path is going to be paved by catalysts that we've already put in motion. We're going to scale our longevity fund complex with new funds and larger vintages. We have our securitization platform as well as the newly launched interval fund that hopefully, you saw the press release on that a little bit earlier this week. And those are going to be creating repeatable execution and predictable AUM growth. And then there's the longevity -- I'm sorry, the wealth management build-out, which would include the Manning & Napier referral flywheel. And so those things are starting to build the fee revenue layer on top of the core engine. And so those asset-based fees, advisory fees and our technology revenue will move our total recurring revenue mix towards our long-term target. On the right side of the slide, it shows the numbers along the path. So in 2025, we're at $135 million of adjusted EBITDA. By 2028, we expect to be at $250 million. And by 2030, we expect to be at $450 million as our AUM scales and our revenue shifts more towards fee recurring revenue. And we expect the margin profile to hold or improve because every dollar of AUM-based or technology-based revenue carries a structurally higher margin. So why is that important? Multiple expansion. So today, our revenue breakdown is Life Solutions is about 84% of our total revenue. It's the engine. It's fantastic. But by 2028, we expect that to be about 40% of total revenue and by 2030, 30%. And to be clear, that's not saying that Life Solutions is going to shrink in total. It's just as a percentage of total revenue, it will be smaller because of the anticipated growth we're going to see in asset management, wealth management and technology, all of which carry a higher valuation multiple than Life Solutions revenue alone. And here's where it really matters. So we're at 16% fee recurring revenue today. Every 10 percentage points that we make towards our goal of 70% is an estimated 2 to 3 turns multiple expansion. That's not incremental. That's transformational. On top of a return on invested capital backdrop of 20% at the end of 2025, which is well above our cost of capital, which means every dollar we're reinvesting is compounding at meaningful spreads. So the 100-bagger framework requires compounding, compounding revenue, compounding margins and compounding business quality. The platform that we've assembled, LifeARC, our asset management business, the Manning & Napier Strategic Alliance and Abacus Intel are all strategically designed to deliver on all 3. And before I hand it over to Elena, I just want to -- I want to leave you with this. We're delivering strong results. Our trajectory is clear, and our compounding business is just getting started. So I'm now going to hand it over to Elena, our Chief Investment Officer, who will be our host for the rest of the day. Thank you.

Good morning, everyone. I'm Elena Plesco, Chief Investment Officer at Abacus Global Management. And I want to spend the next few minutes on something slightly different. Bill already given you the financial update. I'm not going to talk about fund management. We have a whole section on that. My job this morning is to help frame how we believe investors should think about Abacus. So the common mistake is to define a company by the most visible transaction it facilitates rather than the infrastructure underneath that helps facilitate enterprise value. So with that in mind, we'd like to walk you through what kind of company we're becoming. And I will start with a question. I'm expecting participation from the audience. What is Amazon's largest revenue-generating business? That is incorrect. I was hoping -- I was planning to plan someone to say that, but I didn't need to. So the answer to that is still core commerce, selling goods. It's the oldest part of what Amazon does and clearly to a lot of you and not a very exciting part. So now let me ask you a different question. What is Amazon's one of the most important profit centers? And that answer is AWS, yes. Cloud infrastructure, a business that did not even exist for the first decade of the company's life. And here's what I find instructive. AWS did not come from a strategy offsite where someone decided that Amazon should become a growth company. It came from e-commerce. Amazon needed to build technology infrastructure to operate its own marketplace at a massive scale. And over time, that infrastructure it built for itself became valuable to companies far beyond Amazon. The core revenue engine funded and necessitated the infrastructure that became one of the company's most important profit centers. So that is the lens I want you to use for Abacus. I know people were asking me, is there going to be an analogy? Yes, this one. So today, origination is our largest revenue engine. It's bringing policies, bringing clients, bringing data into the ecosystem. It is the oldest part of what we do, and some may find it not very exciting. But origination is exactly what allowed us to build LifeARC. We did not wake up one day and decided to bolt on a technology story. We needed better data, better mortality insight, better verification and better pricing. We needed tools to understand how long assets may last and how to think about individuals longevity. So we built those tools. And just as with Amazon, the technology that we built from an internal need is now becoming a business in its own right. But before I get to that, and we will talk about LifeARC a lot today, let me frame the company itself. Depending on when you -- where you enter our story, you may think we're an origination company, an asset manager, data provider, a wealth platform, a technology company or some sort of business connected to insurance assets. And there is truth in all of those descriptions. But none of them really capture the full picture. The mistake would really be to look at one part of Abacus and assume it's the whole company. And you've heard us talk about the flywheel a lot, and we will continue talking about that more today. But I want to touch on 2 concepts that sometimes get used interchangeably. So the rails are what we own and the flywheel is what happens when those rails reinforce one another. So what we're actually building is the infrastructure for lifespan-linked finance. We're building the rails. So origination brings assets, clients and data into the ecosystem. Abacus Intel through LifeARC turns that flow into personalized lifespan insights, verification, underwriting and pricing. Well, the Manning & Napier turns a consumer liquidity event into a long-term planning relationship. And lastly, asset management turns our proprietary access and underwriting discipline into institutional products and fee-paying AUM with our new parlay into ABF really extending our runway into the broader asset-based finance space. And not to forget about distribution because that moves products, relationships and capital, both domestically and globally. So origination is how assets enter our system. Distribution is how capital enters, and you need both to create liquidity. Later on today, you will hear from Corey, Monty and Martin on all of those pieces of the business. So why is it that owning the rails matter? Well, the more rails we own, the more we control our own destiny. A traditional asset manager oftentimes relies on third parties to bring them capital and even product. A traditional originator has deal flow, but frequently fails to capture the downstream economics. A traditional data business has analytics but lacks captive assets. And a traditional wealth manager owns the client relationship, but fails to provide any proprietary insight. Well, as for us, we do not wait for someone else's deal flow, and we don't rent someone else's data. We build the rails, so we would like to set the terms. And in the Abacus flywheel, those rails allow us to do a multitude of things such as provide consumers with liquidity, put forward institutional-grade products and build recurring economics for our shareholders. We built the rails and the rails are what made LifeARC possible. And LifeARC is not just simply a product that sits on top of our platform. It is really the intelligence layer that we have been building towards. And I just want to kind of like caution you, LifeARC is not an insurance tool. It came from insurance, just like AWS came from inside of a retailer. But what it actually does, it turns lifespan into a personalized quantified financial input. And lifespan should not be an insurance variable. It really is the missing variable in nearly every financial decision a person makes. So think about how we build portfolios today. We have spent decades getting really precise about risk, return, correlation, volatility, like we've modeled markets to the basis point. But when it comes for the most important input in any individual's financial life, we reach for an average. We solve a deeply personal 40-year problem by applying the lifespan of a population the person doesn't even belong to. That is the gap. Your portfolio is built for the average person, but you're not an average. Nobody is. And LifeARC closes that gap. It is the input that lets us build investment portfolios personalized for you around your lifespan. It is not a guess. It is personalized to how long your money actually needs to last. So now every retirement drawdown, every annuity decision, every glide path, they all depend on one number, how long? Until now, that number was an average. LifeARC makes it curious. So once that input exists, we believe it really belongs in every single portfolio. And we do believe personalized lifespan will become a standard input in portfolio construction. And the company that owns most accurate, most defensible view of an individual lifespan will own the input that everything else runs through, and that's not simply a feature. That is real infrastructure. So as you listen to the rest of the team today, I would encourage you to not hear each section as an individual business unit update. Each of them is a rail in the same system. And when those rails connect, the flywheel starts to turn. And that is the investment thesis, not one product, not one segment, not one transaction. The whole system is the thesis. And this system has been building towards the input that finance has always been missing. If we execute, Abacus does not merely become a participant in lifespan-linked finance. Abacus will become a company that is building the infrastructure that allows this entire category to scale. So the various parts of Abacus are, of course, interesting, but the platform is what matters. So please join us as we're building the intelligence layer for lifespan-linked finance. Thank you. Now we will move to the more interesting portion. And I know last year, you have met a lot of our division leaders. This time, there will be a lot of new faces as well. So first up is Jeff Smith, our Chief Marketing Officer. Jeff has been with the company for almost a decade, I believe somewhere in the fall is his 10-year anniversary. And Jeff probably remembers the time when the marketing budget was probably what it cost to throw this event. And now he's in charge of million -- multi-million dollar ad buys, and he will take you through a lot of our AI and data strategy as well. Welcome, Jeff.

Thank you, Elena. On my first day at Abacus, Shane McGonnell our CRO, had to go down the street to our local Best Buy to pick up my first computer. At the time, as Elena just mentioned, my advertising budget was $100 a day. We had maybe 15 people in the entire office. That was 2016. We're now a New York Stock Exchange-listed company that originates over 100,000 consumer direct leads every year, has participated in billions of dollars of alternative asset transactions and is active in 4 unique distinct separate business lines, all in infrastructure that we designed and built ourselves. Now at the outset, I want to clear something up. My title is Chief Marketing Officer. But that word marketing doesn't necessarily do a great job at telling you exactly what we do at Abacus. We integrate marketing and operations by design. We build tools that improve close rates, not just lead volume. We own the attribution infrastructure across TV, digital and radio. And right now, together with Armando Cabrera, who you'll hear from next, I'm co-leading a complete digital transformation of all of our companies and merging them into a single data infrastructure that allows us to do things with data and clients that weren't possible in the past. And that may not be where your head goes when you think about marketing, but that's by design. And one principle we consistently come back to every time we're planning or building any tools like this is the same thing. We don't borrow tools. We build them. That's been true in marketing since day 1, and it's what I want to show you here today. The way I think about marketing is as a revenue engine, not a cost center. In most organizations, marketing and operations are separate roles with separate functions. Marketing generates leads, creates interest in the business. Operations handles everything that comes next. But at Abacus, we made the deliberate choice to integrate the two. Increasingly, those integrations are being handled through the use of AI. I'll give you one example of many, and we'll talk more about AI in a little bit. But right now, when a lead enters our system, machine learning is working instantly, scoring that lead, enriching all of their data and routing them across every single one of the companies in our umbrella to find the best possible chance for a revenue-creating event. It used to take a human hours, days, might not even happen at all, now happens in seconds. And the best part about that is it's not a future state. That's how we operate right now. And operational integration is what makes that model work. And it's what allows us as a marketing department to do something most companies can't. We're able to connect every single dollar we spend to a specific outcome across all of our business lines. And before I go too far into the future state, I think to understand where we're going and where we are today, it would help you understand where we started. When I started at Abacus, the job was pretty straightforward. Generate business, don't spend much money. Over time, as we continue to approach the foundation, which involved doing the SEO work, hunting down media placements free as often as possible and building out the brand, we proved out what worked with the model. And as we generated leads, generated revenue with that model, the budget increased. And as the budget increased, we were able to spend more intelligently. And one of the ways that intelligent spend actually materialized for Abacus was through the construction of proprietary targeting algorithms with our own data. So that means without relying on any third parties, without bringing in other data sources, we took 20 years of Abacus' data and built targeting algorithms that allowed us to generate business at a fraction of the cost of our competitors. We're still using those algorithms today. And every new lead we get, every phone call we make, every e-mail, every piece of client data further informs those algorithms and makes our spend more intelligent. The key insight from those early years was that every piece of infrastructure we built, we built to last. Now I want to go into the thesis that I've been driving for this fiscal year because I think it shows one of the ways at least, the vertical integration creates value in our business. The goal is simple to state. I never want an unqualified lead. Now that obviously doesn't mean that every lead that comes in through every channel needs to qualify for exactly what they expressed interest in. But what it does mean is that across 4 business lines, we should be able to find a fit for every single consumer who raises their hand. And I'll give you an example of that. On the Life Solutions side of our business, someone might express interest in selling a policy. But often, those leads don't qualify. We have a very specific buy box. But what we know about that lead is they expressed a dissatisfaction with their policy in some way. So what we can now do is have the conversation, connect them directly to AccuQuote, for example, where they might be a perfect fit or take a wealth management client, for example. We're now engaged in conversations with that individual across their entire financial lifespan. Products like LifeARC, Life Solutions, really every part of our business will come up over the course of those conversations. The verticals feed one another, but only when the infrastructure exists to enable that. That infrastructure is something we've spent the past several years perfecting. And with our unified data platform now in place, we're able to score, enrich and route leads in real time. We generate over 100,000 leads a year. The question has never been, can we generate them? The question has been across 4 business lines, how can we turn that volume into real revenue for all of our companies and not just one. Now I'm going to talk about AI. I mentioned it earlier. And when I talk about AI, I don't mean plugging into someone else's models, licensing a chatbot or bolting a preexisting vendor tool onto a process we're already doing. When I talk about AI at Abacus, I mean machine learning models that we built with our own data. I mean agentic automations that we built for our own workflows and tools that we own outright that don't rely on anybody else's models or any form of third-party data to operate. Now distinction matters, and it matters for the same reason that our first-party data strategy matters. Ownership creates a moat, and that moat gets harder to cross every single year. And here's what that looks like in practice. One example is AI voice, which has effectively extended our operating hours by 16 hours a day and a full 2 days a week. In the past, when I run a national broad -- national prime time television campaign, most of that interest is generated in the evening or over the weekend. But our call center operates 9 to 5, Monday to Friday. AI voice effectively closes that gap. And we're now able to meet consumers where they are, no matter when they reach out. It doesn't matter if it's in the middle of the 4th of July weekend or at midnight. That effectively introduces them to our pipeline instantaneously and allows us to start actually acting on that client much faster than we did in the past. So leads no longer go cold overnight or during a long weekend. But AI voice is just the most visible example of something much deeper. Origination is becoming effectively more data-driven and AI-enabled across our entire platform. We're using AI to identify needs before consumers even raise their hands. We're utilizing better segmentation, more personalized outreach and serving them relevant education at exactly the right moment. We're also ingesting more signals than ever. And we're using those signals to generate higher intent consumers, reduce friction across our pipelines and better equip advisers to make decisions immediately. The end result is a better equipped adviser on the backend and a more qualified lead entering our system. We've also deployed AI agents across the entire spectrum of our business. That includes case processing and making it more streamlined. That includes automated fraud prevention. It includes things like internal LLM-powered chatbots that we use on all of our websites that we built ourselves and aren't reliant on another model. The true line across all of this is that we built it. And the important thing to take away from this is that marketing isn't just advertising anymore. It's a scalable education and acquisition engine that makes every single aspect of our business more productive. Now I want to walk you through media strategy because I think it's a little bit different than how most companies handle it in our space. When I consider media strategy, I focus on intent capture and intent creation. Intent capture is what you probably think about when you think of platforms like Google, Bing, Yahoo!, maybe meeting people directly in their inboxes. Increasingly, that means ChatGPT, Gemini, Claude. It's showing up when a client is expressing interest in your brand and being the best possible option at that moment. And what we find here are people that are searching for our space or people that are tertiarily related to our space within 1 to 2 degrees of separation. So when you talk about next of kin, when you talk about people that look like a good fit, that's what this looks like. It's inherently data-driven. It's very efficient spend, and it creates really high-quality leads that close at a really great rate. So hearing all that, you're probably thinking, great, that's where we should spend all our money. You're telling me the leads are attributable, high quality, easy to generate, great. The problem is intent capture is inherently finite and self-limiting. There's only so much demand in the space. You can only capture so many clients. That's where intent creation comes in. And that's when we talk about things like the national TV campaigns, the radio buys, even things like billboards or brochures. A lot of people would usually call this traditional media. It's a little more expensive to originate. It's a little less efficient, and it's very hard to handle attribution around that space, sometimes impossible in some cases. But it does something that you can't replicate in any other way. It creates demand, it builds intent and it drives consumers to our platform in a way that nothing else can. And in that way, it actually makes our intent capture model more efficient and makes it more productive because more leads are coming into our space. So we're taking a spend with some weaknesses, driving it into a spend with a lot of efficiencies. And in that way, interestingly, the more money we spend on TV, typically, the more efficient our spend becomes in gross. The strategy for us was always to build intent capture first, perfect it, capture every consumer that enters our space and always be the best option and then and only then move into intent creation. You don't build the fire before the fireplace is ready. And that's why you didn't see Jay's trademark sweater on TV until 2023, not 2016. Now I want to take a step back and talk about how everything we've talked about today actually connects. Some of this will be a rehash because I think it's important that we bring it all together. Abacus operates across 4 business verticals. And the question investors reasonably ask is, how do those 4 business verticals actually complement each other rather than just operate alongside one another. The answer is the operational spine. As previously mentioned, we recently completed a full refactor of all of our separate operating environments, bringing all of our disparate data points into a single source, every lead, every client record, every transaction, one environment. Now what does that actually mean in practice? It means that when a consumer enters our system through literally any medium, we can now score, enrich and route that lead in real time across all of our businesses to find the best possible revenue-generating result. Now I want you to take a second to think about what happens, for example, when we facilitate a Life Solutions transaction. Let's just say $1 million policy that we purchased for $250,000, just for illustrative purposes. That's money in motion. And the question we can now reasonably ask because we have the infrastructure to ask it is, does the client have a plan for that capital? What happens next for them? Usually, the answer to those questions is they don't know and know. But now with the infrastructure in place to properly facilitate all of these things, we're able to meet every single consumer exactly where they are. I started at Abacus with a computer, Shane McGonnell got me a best buy, a $100 a day budget and a blank whiteboard. What we've built since then isn't just a marketing department. It's a proprietary data and origination engine that generates over 100,000 consumer direct leads a year, routes them intelligently across 4 business verticals and helps to dig the competitive moat that gets harder to cross every single year. Under Jay's leadership and with the support of my incredible team, I've had the privilege to expand on what it means to lead marketing at Abacus. Thank you so much for the opportunity to talk here today, and I'm excited for what's next.

Up next, we call Armando Cabrera.

He currently serves as President of Abacus Intel since you saw him last, he got a promotion. And as you may recall, he is really the mastermind behind every technological piece Abacus has put in place. He will also be joined by Dr. Jay Olshansky, who's our Academic-in-Residence. I will not attempt to read his entire bio, but Dr. Jay Olshansky is one of the world's leading experts on aging and longevity and biodemography, sorry, English is my third language. For more than 4 decades, his research has shaped our understanding on lifespan, healthy aging and the outer limits of human life. Dr. Jay Olshansky is a very prolific author with dozens of papers. He has been collaborating with a numerous amount of business entities and entities in academia, and he also currently is the Professor Emeritus at the University of Illinois, Chicago.

Thank you, Elena. So you're going to hear from Dr. Jay a little bit in a second. But today, we're going to talk about the foundation that LifeARC is built on. We're going to talk about the development of LifeARC and how it actually works as well as the applications we've been seeing in our business as well as in the future. And after that, we're going to have a quick MVerify update and discussion on our mortality database. So first, what is the foundation that LifeARC is built on. We talked a lot about the data that we have and something that we've been aggregating over the last 20 years. But let's think about in our core business of life solutions, when we're purchasing an individual's life insurance policy, what information is needed? Well, we need to get the medical records for this individual to understand their impairments, all the comorbidities that they may have to understand what that asset may look like and what the duration may seem. So from there, we've aggregated millions and millions of pages of medical records that help inform our models. But it's not just the medical record data that we have. In addition to that, we need to be able to attach real outcomes to the individuals we've seen over the past 2 decades to understand what the true lifespans they actually experienced. And with that, that's where our mortality verification, mortality database or MVerify yields results for LifeARC. But it's not just the data. The data is a vital component, but something unique we're also able to do at Abacus is provide expertise that no one else in the market has. You heard Dr. Jay's Bio. When we look at our data, we're not just simply putting a model or a machine learning model or AI on top of it and hoping for good outcomes. What we're doing is we're applying longevity expertise to help interpret and understand the context that this data is in. So things like understanding why certain outliers occur and adding nuance to scenarios that no model can understand. This allows us to take our data to the next level. But now what's the last set of expertise that we have here at Abacus? Well, today, we've talked a lot about accurate lifespans and the fact that LifeARC can produce accurate lifespan estimates. But when we use that word accurate, what does that mean? Think about that for a second. When I say our lifespan estimates are accurate, how would you define that accuracy? Just take a second to think. I'm thinking too. So I think the answer is very dependent. But let's say for an individual, they have a 10-year lifespan that we estimated and they live 10 years. Would you say that was an accurate estimate? I mean I hope so. If you said, yes, I'd agree. But that's not the world we live in. What if that individual live 9 years, maybe 11 years, maybe 15 or 20. At what point do you say that is no longer an accurate estimate and that accuracy falls off. And I think the asset management expertise that we have at Abacus allows us to answer that question a lot more intelligently. So if you think about our core business, when we're purchasing life insurance policies, we may want to optimize our models based on a different factor than we will for in the financial planning space. The most sensitive area of cash flow in a life insurance policy and when affecting the value of that policy is in the early-stage mortalities. So maybe instead of optimizing on the midpoint or the lifespan of an individual, we will optimize the precision in the early years of their survival distribution. But that question kind of flips when you ask an individual, what are they most scared about in retirement? And if that fact is running out of money, do we really care about the midpoint or the early-stage mortalities as much as we do as the worst-case scenario for them. So instead, what we can do is we can apply this expertise to optimize the models based on these 90th or 95th percentile that give our clients in financial advising, the confidence that the data that they're seeing is accurate and precise. So the data that we have builds that foundation and the expertise we apply sets us apart as well. From there, I'm going to allow Dr. Jay to kind of go into the predictability and longevity science behind lifespans, and I'll continue after that.

All right. Well, thank you very much for having me here, by the way, it's an absolute honor and a pleasure. I'm actually going to be brief. I have one slide with almost no words on it. So I do like to keep it simple. And I actually want to emphasize something that Jay Jackson said earlier, which has to do with this issue of healthy life. So 4 years ago, I testified before Congress on this very issue of manufacturing healthy life and as it turns -- and which is what aging science is all about, and as it turns out, there's a direct link between how well you deal with your finances during the course of life and how much healthy life you can manufacture later. There's a direct link. So a lot of this concept of a LifeARC, which gives you a sense of where you're likely to be headed in the future is extraordinarily valuable. So this looks like a pretty esoteric figure here. It's actually not. So what you're looking at here is one of the most famous lines in public health, in epidemiology in a variety of different scientific disciplines. About 200 years ago, an actuary by the name of Benjamin Gompertz came up with a formula, a very simple formula that described the dying out process of humans. It was pretty simple, depending on how old you are, what's your risk of death. I mean all of you have been using the Gompertz formula, believe it or not, even though you're probably not aware that you have been using it, you have been using it for quite some time and it's fairly simple. The risk of death for humans doubles about every 7 to 8 years. That line there, which, by the way, is on a semi-log scale. So right, it's a log scale vertically, arithmetic horizontally, which means when you see a straight line, that is a definitive explanation for an exponential increase in the risk of death. So in humans, the risk of death doubles about every 7 to 8 years. It has never changed in human history. It likely will not change in the lifetime of anyone in this room. So what did we do? We took all of the Abacus data from the last 20 years. We wanted to see how valuable that database actually is. Fairly straightforward exercise. We uploaded all of the data. Did it fit the Gompertz Law of Mortality? Well, the green line is the Gompertz Law of Mortality and the red dots represent the Abacus data. What does that tell us? It tells us that the Abacus database is extraordinarily valuable. It can be used to help predict duration of life at the individual level. It can be used in a variety of industries, for example, in wealth management, it's sort of perfectly suited for that purpose. And keep in mind, at the individual level, of course, let's just say you're looking at age 85. We know that some people have a lower risk of death that's going to be below the line and some people have a higher risk of death that's going to be above the line. LifeARC is designed to determine where you are on that distribution. It's not -- nobody can determine definitively, exactly how long you're going to live, but we can come pretty darn close to figuring out which distribution you're likely to be in and that's indicated by those green lines in the upper right-hand corner. At the population level, we've got very stable data at the individual level. You need more personal information about individuals. That's what you heard Armando talking about earlier. So we've created what -- and I like using imagery, by the way. We've created a number of knobs that we can turn that give us a better sense of how long individuals are likely to live. The more information you put in there, the more knobs we can turn, the closer we can come to figuring out how far above or below that average you are likely to be. So we've actually created what I refer to as a gold standard set of life tables, Abacus set of tables that are designed to help us determine how long individuals are likely to live. And it's an extraordinarily valuable resource. It's particularly comforting that all of the data follow the Gompertz Law of Mortality. I would point out, by the way, that we've demonstrated definitively over the years that this trajectory has, in fact, never changed. But the fact is, is that some subgroups of the population do much better than others. For example, individuals that are wealthier, more highly educated tend to be on the lower side of that distribution, lower mortality, longer life, individuals that have more challenging health conditions are on the upper side of that distribution. So I'm just trying to emphasize the importance and the value, which is -- of the database that Abacus has in hand, and it will grow more valuable with time. I'm going to stop there. Thank you.

Thank you, Dr. Jay. So now I want to emphasize the point that we've kind of reiterated today. LifeARC is not something that's new to Abacus. LifeARC is something that's been powering our core business for years now. When we think about acquiring life insurance policy, what is one of the key inputs? Well, we need to understand the risk profile of an individual and how long they're expected to live. LifeARC has been powering us to make smarter acquisition decisions on these assets before we buy them. Then once we own these policies, what does it help us do? Well, as we continue to aggregate more data and more medical records for a given individual, it allows us to make more intelligent sell or hold decisions on the assets we actually currently own. And this sets us apart in the market as we have additional data that we can then utilize to manage our book more efficiently. But now we're stepping into a new frontier. And that frontier uses the exact same engine of LifeARC that we've been utilizing for years. That engine is the same. That same point you need to value a life insurance policy is that same data you need to use to create the most educated and intelligent financial plan for every consumer. And again, Jeff said it, and we've said it before as well. These are not licensed or leased products or data that we bought from anybody else. This is data that we've been building for decades, and this allows us to have no third-party dependencies, and it's something unique to us. This cannot be easily replicated. So now as we shift focus, how does LifeARC actually work? Well, let's think about some of the data that we have. If we look at the medical records that we have, what do those really look like? Well, a lot of times, it's going to be scanned digital PDFs. Maybe it's going to be a scanned paper document on somebody's phone. Maybe it's doctor's handwriting, which might be a little bit more difficult to read, at least for me. All of this information exists in an unstructured format that's not usable for any modeling. So what is our first step? Our first step is to ingest all of this unstructured information and use natural language processing to understand the context around all the medical records as well as optical character recognition to read somewhat unreadable doctors' handwritings or scan PDFs to allow us to put this in a central structured database. And that sets the foundation for our models. Once we have our central database, we now have to think about what makes an individual unique. What factors about an individual allow us to understand their unique life. So simply put, maybe we're going to extract features such as gender, maybe we're going to get age. Those are more of the simple ones. But then let's think a little bit more complex because the human population, especially in the U.S. is very complex. We're going to need things like how many impairments do they have? What is their most severe impairment. But not only that, what is the progression of that impairment over time. These are just some of the hundreds of features we're extracting from our central database to create an accurate model. And this model, again, I talked about accuracy, and it depends on the context. This model produces accurate lifespans and a point estimate, but also a distribution of survival for that individual. Additionally, we're also creating a clinical summary that is easily interpretable for both financial advisers and clients to understand where does their lifespan come from and where is the scientific backed research that justifies this in addition to our data. But not just that. LifeARC is not static. Your LifeARC is an arc of probabilities, just as Jay has said. And as your LifeARC continues to grow and you have new investment goals or you have new medical impairments or medical records, LifeARC updates with you and in real time. We not only adjust for the real-time trends we see in the population, but also with the data that's specific to you. This data is so vital to you and it's so hyper-personalized that nobody else can recreate it and it constantly updates no matter what happens in your life. And you might say, Armando, "wow, wow," you're talking a lot about how LifeARC works and what you guys did to develop this. Aren't you a little bit scared? Isn't that your secret sauce? And to that, I would say, if I bundled our models and created our complex models and gave them to you today, you're going to have a great lifespan estimator. But in a week, you're going to call me. You're going to say, look, this has been working great. And I'm going to agree with you. I think those models are great. But you know what, you're actually a week behind us now. And why are you a week behind us? Because the infrastructure we've built allows us to capture the data that's occurred. There's been a week more of medical records we've aggregated, a week more of real mortalities that could affect trends that are affecting each individual. This information sets us apart. We're not just data. We're the infrastructure to aggregate and analyze that data. And so what does LifeARC look like now and in the road ahead? We've said it a bunch. We want to be the intelligence layer of financial planning. We're going to be the AI and data tool that advisers use to educate their clients on one of their most important inputs to their financial plan, their lifespan. So as we look at what we're doing, we've had a lot of excitement around LifeARC, several meetings and several integrations that we worked on and LifeARC was built to be modular. It was built to meet a client or adviser at every phase of life. So we can integrate with seamlessly into existing wealth management platform so that advisers can use our information immediately and without adjusting their workflows. But we've also built a proprietary platform where if you want more detailed and interpretable results, clients and advisers alike can log in and see where the lifespan comes from and how it's generated. In addition to that, LifeARC, as I said, is not static. The mortality data that we aggregate on a daily basis continue to feed the models and create the most up-to-date information without the need of actuarial estimates or studies that could take years to occur. And so I think that yields us into a good transition point to talk about MVerify or mortality verification. So MVerify is our product that aggregates the deaths that occur across the United States every single day. We boast a 97% national coverage as well as a less than 1% false positive rate in the deaths we report. So MVerify isn't just an internal product. It's something that we also sell to hundreds of clients, as I think Bill had mentioned earlier. And so what do these clients look like? These clients are usually pension funds, unions or life insurance companies. And MVerify allows them to prevent fraud and overpayments when an individual passes away to stop their pensions as well as for life insurance companies to either stop annuity payments or pay faster life insurance claims. And if we think about it's not only the data that MVerify has, but it's also the speed to that data. Normal state databases can take 2 to 3 months to report deaths, whereas MVerify usually does it within the first week. And so if you can see here, we've made significant market penetration. We've over doubled the amount of lives we've been tracking since Q2 -- since Q1 of 2025. And why is that important? Well, MVerify is a subscription-based product that our clients pay an annual fee for based on the number of lives we're tracking for them. And the reason why we're able to charge the subscription-based model is because as mortality events occur every single day, we continue to add value to our clients. But just think about the technology we've talked about today. Everything we build at Abacus is extremely intentional. If we think about why are we incentivized to build a better mortality verification product. If you ask yourself that question, well, we have a whole servicing division that focuses on finding when individuals have passed away and getting our life insurance death benefits quicker so we can rotate our capital sooner. But not only that, MVerify feeds directly into LifeARC, just as we've talked about today. And so whether it's LifeARC or whether it's mortality verification, everything we do is built upon our core and has continued to grow and create a scalable future for Abacus. Thank you.

So I'd like to invite back Jay, Bill, and they will also be joined by Jim Morrow, CEO and Founder of Callodine Capital. And for the next few minutes, we will do a panel on wealth planning. Thank you.

We were just going to have Bill talk about this, but I thought it would be way more fun to crowd his party. So I'll start. For some of you who attended our Investor Days in the past, we are always honored and excited to have James Morrow with us from Callodine Capital. And you've got an awesome history. I did learn in actual meeting with Mr. Peter Lynch that you were assigned to him or how did that go? You were with Fidelity for what, 17 years, right?

18 years.

18 years. $50 billion in AUM and equity income fund. Yes, that's fine. But then like you were -- how did they do that with the mentor, right? Because Peter Lynch is there, right?

I started as a summer intern. And when I got hired full time, they assign you a mentor.

And they're like, your mentor is Peter Lynch. Okay. No pressure. That's a pretty wild way to start your career, I spend a lot of time with them. That's super cool. And Jim has made investments in all kinds of industries and businesses and runs what I believe, one of the top hedge funds in our country and has grown exponentially. And he has a unique outlook on not just Abacus. Now I do have to say all hands on table. His funds don't have any type of ownership, but was part of our original IPO when we went public and has some shares at the corporate level. So and with that said, one of the things that we get to do is I get to engage and get perspective from people like James Morrow on -- how do we think about the opportunities that we build, like LifeARC. And when we first thought about entering the vertical of wealth planning and what that might look like, we knew we had to have some kind of key differentiators because as a market maker in the insurance side, which you just heard from Armando, what would this look like? And how do we capitalize? You heard from Jeff, on all the leads we generate, how do we capitalize on those? For us, this flywheel was incredibly important to be able to say we can monetize this in other ways in a very thoughtful and intelligent way, but it didn't happen overnight. Bill's background, for those of you who've heard some of this, yes, he hasn't just been with us for 6 years, but Bill was the CFO of TransAmerica Financial Advisors, right? I got that one, right? Different financial roles with John Hancock and also was at McKinsey and that experience he had at TransAmerica Financial Advisors thinking about kind of where these products may or may not actually fit. So Jim, I will start with you. When you think about some of the things you've heard today, specifically around LifeARC, the scalability of that market, and I threw around a number, $124 trillion wealth transfer. What does that typically mean? Like when you look at companies and you say, hey, there's like big opportunities here. How do they -- where do they fit? Like is it important to be the guy selling it or the person building it?

Yes, I think both. I think building it and leveraging what you've built is sort of the key value proposition. And I think markets in general and humans in general have a hard time differentiating between linear and exponential sort of change. And I think your original core business, $250 billion a year of policies that lapse that you can address, that's an amazing opportunity. 5% of what you described is $5 trillion or $6 trillion, right? That's exponential change in the opportunity set and your ability to create recurring revenue models around that, changes the story of Abacus and from what it is today to what it can become in a way that's really hard for markets to understand and appreciate. So it will take time. You'll compound over time with that story. But that type of rate of change is one of the things that Peter always talked about is that the market usually struggles in that moment to fully grasp, right? And everybody is obsessed with AI right now and everybody knows about NVIDIA and other things. That's the building of the infrastructure. The ultimate winners will be companies that can apply that technology. And I can't think of a bigger market than $120 trillion to apply that kind of technology against with proprietary data. So that's the real change that the market will have to absorb and price in over time.

And when you think about it over time, you see this happen often, like over time in mindset from your perspective, like when they start to price in not just on the Abacus stock, but you think about some huge players in the wealth market who are talking about this. Like I said, I was on stage at the Milken Institute, with JPMorgan and the Milken and HSBC. And their primary focus was on product to address this. And I think what we were trying to talk about was some customized solutions, like how long do you think until when the market looks at something like this and they start to see, hey, we should start to adapt it. What do you typically see in those cycles?

I was told never to give a price estimate at a time. But time is tough. I mean markets -- it can ignore things for a while and then suddenly price them in. But again, if you think about wealth planning and you think about asset allocation, right now, that whole process in an enormously attractive industry is missing an incredibly important piece of information is like how long am I planning for. And so I think that addressable market for LifeARC is just -- I don't even not quantify it, quite honestly. It's sort of like, well, that's a really important input to that process that I'm missing today. And can you capture that market with a host of advisers that are out there that all of their clients will benefit from that knowledge. That's a pretty -- it will take time for it to penetrate and when the market recognizes it is hard to say.

That's interesting, too, because we've talked about, if you think about $124 trillion, 5%, that would be amazing as a market share. Was that, Bill? What was that about $6 trillion. Yes. That's what's super interesting. I'll tell you what I found interesting about LifeARC was that one of the outputs you saw, specifically in our case example, we have lots of these now. And let's be clear, we are literally generating converting leads like the one I showed you, that person's policy who had $8 million of liquidity and net worth, you know what their policy size was that we purchased, $300,000, right? So this mindset of, oh, they only have a $300,000 policy, therefore, they must not have a lot of net worth. But I still think the thing that I really excited him in the end, like and he was so fun because I don't need 316, just give me 200. It was like, oh, okay, well, 200 is the number you're taking 160, so great. But the fact that's a 25% growth to legacy, right? So when you go to the $120 trillion, and we're going to add 20% to 30% of additional value to that wealth transfer. We can all do the quick math. That study was done by Cerullo & Associates who came out in very conservative asset allocations. When you add what LifeARC brings, LifeARC actually brings another $20 trillion to the transfer. $155 trillion is actually what LifeARC, we think that wealth transfer will be. That's what I think is so unique about that. And Bill, you're TransAmerica Financial Advisors. Think about going back then, like some of the things that you guys were selling, some of the products that you're representing in both insurance and financial planning, how do you think LifeARC would have impacted?

It would have been a game changer. I mean you just think about all the different things that are impacted in the financial plan by the length of time that you need it. So I mean, obviously, duration, but like how are you going to structure retirement income, how much you need to reserve for just long-term care. It's just -- it would be a complete game changer. No one is doing this today.

When you sold the TransAmerica bid, you sold that, right? You were part of...