American International Group, Inc. (AIG) Earnings Call Transcript & Summary

Good morning. Welcome to AIG Investor Day 2025. Today's remarks may include forward-looking statements, which are subject to risks and uncertainties. These statements are not guarantees of future performance or events and are based on management's current expectations and on assumptions currently believed to be reasonable. AIG's filings with the SEC provide details on important factors that could cause actual results or events to differ materially. Any forward-looking statement made during this presentation speaks only as of the date on which it is made. Except as required by applicable securities laws, AIG is under no obligation to update any forward-looking statements if circumstances or management's estimates or opinions should change. Today's remarks may also refer to non-GAAP financial measures. The reconciliation of such measures to the most comparable GAAP figures is included in our earnings release, financial supplement and earnings presentation, all of which are available on our website at aig.com. Finally, today's remarks related to General Insurance results, including key metrics such as net premiums written, net premiums earned, losses and loss adjustment expense incurred, underwriting income, margin and underwriting leverage are presented on a comparable basis, which reflects year-over-year comparison adjusted for the sale of Crop Risk Services and the sale of Validus Re as applicable. We believe this presentation provides the most useful view of our results and the go-forward business in light of the substantial changes to the portfolio since 2023. Please refer to the non-GAAP reconciliation section of the presentation for reconciliations of the metrics reported on comparable basis. Ladies and gentlemen, AIG Investor Day 2025 is about to begin. Please prepare to join us. Ladies and gentlemen, please welcome, Chairman and CEO, Peter Zaffino.

Finally, we get to present. Welcome, everybody. It's great to have you here with us today. We're really excited to take you through our story. I do want to just do quickly the agenda, what we're going to take you through today. I'm going to open up and give you some perspective on what's happened at AIG with a little bit more color. Keith Walsh, our CFO, is going to get up and give us some of the financial information to support that and give you a little bit of view in terms of the future. We'll stop there and do a little Q&A. We'll take a break. We're going to bring up our top business leaders for Q&A and talk more deeply about the business across the world. We'll then pause and start to shift to AI. And we're going to have Claude Wade, who's our Chief Digital Officer, Head of our Business Operations and Claims, take us through as he's been a pivotal part of our journey. Then we have an unbelievable panel discussion with Dario Amodei, Alex Karp, Anthropic, Palantir, narrated and worked through with Sara Eisen. So we're going to be really excited to take you through that. They are our partners, and we'll show you that. They are incredibly important to us, but also a validator in the work that we've been doing there. Then all of the presenters will come up, and we're going to do Q&A. So let me talk about where this begins. As many of you know, I joined AIG in September of 2017 after spending nearly 17 years at Marsh & McLennan Companies. And when I was at Marsh & McLennan, I worked on AIG my entire time there. So I thought I knew the company well before coming to AIG. And what I would find out as I was here for my first 100 days is I really didn't know the company at all. As I started to do business reviews, deep operational reviews, I learned a lot. And the problems that existed were not hard to identify just because there were plenty. But the bigger ones were there was no underwriting culture. The underwriting discipline was not as strong as we would have liked. We had massive aggregation and exposure issues that needed to be dealt with. There was no end-to-end operational capabilities, and we had no insight really in our data. There was no consistency in our data. And we had the highest expense ratio, in the bottom decile of all of our peers, with no real path to kind of get to a place where we would have a better expense ratio. And by the way, we hadn't visited south of 100% combined ratio in a very, very long time. So it reminded me of a story where a young boy went to President Kennedy and asked him a question and said, "How did you become a war hero?" And President Kennedy told the boy, "I had no choice. They sunk our boat." So AIG had a choice, and AIG's choice was to swim. We needed to restructure the entire company. We needed to elevate the talent level because the path we're about to embark on was unprecedented, and to try to put a company back in place, that was so vital and important to the global insurance industry as a top performer. I took our top 100 leaders in early 2018 away to talk about the path in which we had to journey and what was going to be in front of us. It was really important, and I told them it was going to be one of the hardest 24 months they've ever had in their careers. They're going to work incredibly hard. We're going to make excellent decisions. But we're not going to have any financial results to show for it for at least 24 months. But when we bend the curve, and we will bend the curve, we're going to be unstoppable, and we'll never look back. And I remember telling them, there's 3 people you don't want to negotiate with or trade with. One, somebody who's smarter than you. Two is somebody who's a better negotiator. Or three, us, somebody with nothing left to lose. And so we began, and we talked very detailed about what was required for this. And so over the next 3 hours, my colleagues and I want to take you through our journey of nothing left to lose. I don't use these words lightly. We've done an unprecedented turnaround. And we feel we have unparalleled opportunity in front of us, and we want to outline that for you today. I can't take the virtual flip into the back page for guidance, so here it is. And by the way, I'll do it at the end as well. We're very committed to the financial guidance that I'm providing now. Over the next 3 years, on a compound annual growth basis, so it may not be 1 year, but it will be all 3, we're going to have 20% plus EPS growth. The core operating ROE will be 10% in 2025, but believe, over the next 3 years, the range is 10% to 13%. We will continue our path on expense reduction through operational excellence and other variables we'll take you through today. It will be below 30%. And our Board intends to support dividend increases over the next 2 years of 10% for '25 and '26. So I think that's a lot of guidance. It's ambitious. But we will achieve it. Six parts I want to take you through today, and it will go by fast: how we revived our brand of underwriting and operational excellence; our reinsurance strategy and why I think you really need to know what you're doing in order to maximize value; an overview of our global businesses; how we've exhibited operational excellence as a core competency. I will give you my perspective as a business leader and the CEO of driving GenAI and how we're going to unlock unparalleled opportunities in front of us; and then how we're going to relentlessly continue top-quartile performance and give you a little bit more perspective, not only on the path, where we are, where we're going. Let me talk about our brand and our underwriting and operational excellence. This is a snapshot, actually quite a bit of information on this page, of what our global businesses look like. $24 billion in net premium written. International Commercial and North America Commercial, you can see very balanced, 35% of that overall portfolio, and Global Personal makes up 30%. Really strong geographic diversification. We're in the big countries where insurance is prominent. United States, in North America, we are $8.5 billion. You can see in International, U.K. with our global specialties, Talbot in our domestic business, over $4 billion. Japan, we're the largest nondomestic insurance company in the country. We have strong presence in Asia Pac and in Europe. We have the capabilities in over 200 countries for our global clients and multinational, which is significant, and it gives us an advantage to service across the globe, and we'll talk about that. And what's on the bottom is the amount of change that's happened in the company. And so again, this is something that you don't typically see in companies. This is a significant amount. Since '17, 100% of my leadership team is new. 80% of the top 100 leaders are new. Our underwriters, which have done a phenomenal and exceptional job, 67% of the 3,100 underwriters we have are new. And then the backbone of our company, led by Julie Chalmers, who's here today, 4,200 claims professionals, 45% are new. What would I draw from that? We're a new company. I mean we have the same name, but there's so many differences that we want to outline today, and you can see the dramatic change. This is how we break it out by segment. So 48% is Commercial Property and Casualty. You see we have sizable businesses that exist within P&C; one of the world's largest commercial specialty underwriters with our Global Specialty business out of London, led by Gordon Browne; Lexington, led by Lou Levinson. And then we have our syndicate, Talbot. We'll talk about Global Personal. Within that, we have a tremendous global A&H business, homeowners, auto. We've talked a lot about high net worth. We'll go into that a little bit as well. But it's a really good balance. So let's look at the journey of what we had to do. So 121% combined ratio. And these are restated for apples-to-apples as though parent expenses were fully allocated like they are today. So there's a few things I want to draw your attention to. 121%, we all know, is bad. I mean so it was 83% on the loss ratio, 38% on the expense ratio, so that's a hard combined ratio to sort of drive outcomes from. If you look all the way to the far right, in 2024, on a calendar year basis, it was 93% combined ratio. 28 points of improvement since 2017. And for those who know the business well, even if you perfectly underwrite and change everything in a portfolio, it takes a while to earn in. I mean if you -- you don't have every effective day coming up on January. It takes a year. Then it takes a year to earn in. This is a dramatic change in terms of improvement from where we started. This is how it will compare to the industry. So this is what I just took you through, the 121% to the 93%. Our -- the industry average started at 103% in that period of time and worked its way down to 96%. If you take our peer average, you see they started at 99%, and they improved to a 94%. And then the upper quartile of our peers started at 96% and found their way to a 93%. So since 2017, we found our way all the way to be in the upper-quartile performance of our peers, and it wasn't the case in '17. I hesitate to comment on this slide because it kind of speaks for itself, but I will. This is again another unprecedented because no company would have survived that 10-year period. But from 2008 to 2018, the company had $33 billion of underwriting loss. And we began the reunderwriting, the repositioning, the reinsurance, which we'll go into in detail, and we started to bend the curve, as I said. And then it became a profitable portfolio. And then we started to become more reliable, more consistent. And you can see over the last 3 years, we've averaged around $1.9 billion of underwriting profit. Now that's very interesting. It's unbelievable. But just think about the portfolio that we had to work with in order to get there. It really took dramatic and drastic change, discipline and execution. One of the big parts, we've talked about this, not on every earnings call, but it comes up frequently, again, there's 4 numbers I want to draw your attention to here. In 2018, our gross limits were $2.7 trillion. If you go all the way to 2024, it's $1.4 trillion. It's almost a 50% reduction. Well, you would expect to see a dramatic falloff in premium if you were able to reduce your exposures by almost 50%. That didn't happen. Yes, we took a couple of steps back. A lot of it was reinsurance. A lot of it was repositioning the portfolio. But we were $14.8 billion; today, we're $16.8 billion, with roughly half the exposure. That's been through excellent underwriting. And excellent underwriting is risk selection, limit deployment, attachment point, terms and conditions and pricing. And it's largely in that order. Let's talk about catastrophe for a moment. These bars represent the percentage of loss ratio and contribution to the combined ratio from cat from AIG. So you see in '17, it was 16%, and the last 4 years have been very consistent: 5%, 5%, 4%, 5%. That's planned. That's underwriting. It's reinsurance, and that's the consistency we're talking about. This demonstrates the bar charts are the nominal, not inflation adjusted, but the nominal industry cat losses for each calendar year. And you can see in '17 at $134 billion. You take the walk, and we know the world has gotten more complicated in cat, not less, and so you wouldn't expect to see the ratios get better for a company, unless you are AIG, unless you are going to reunderwrite, manage limits, manage reinsurance, predict volatility. And so what you can see here on the black dots is our percentage of the industry loss. And so in 2017 and in '18, we're roughly 3% of the industry loss. And if you look at '21 through '24, it's less than 1%. And so I don't believe it's luck. As I said, I use the Thanksgiving analogy. There's no like wishbone on the plate. We're not hoping for it. This has been planned, this has been executed, and we become a very consistent company that you can rely on when we're writing property. And by the way, the combined ratios, even with, as we outlined, some of the reinsurance, have never been stronger. We don't talk too much about severe losses, but it's an important part of the journey as well. How you define a severe loss is it's a single loss that's greater than $10 million. So what you would see in the $628 million in '18 would be the aggregation of all the losses greater than $10 million. So we had $628 million of severe losses in '18. That contributed 2.3% to loss ratio. Now if you look the reunderwriting and what the effect was, you look at over the last 5 years, and severe losses have decreased by 70%. We're now 1% or less. And that is a reflection of all the great work that we've done. And I do use the analogy: if you think some of this is lucky, I say, in golf, hole-in-ones are lucky. It just seems to me the more quality shots you hit, the luckier you get. So there may be some. But by and large, this is performance based. Let me talk about and transition to reinsurance and why do I say you have to know what you're doing. Anybody can buy reinsurance. Anybody will sell reinsurance. Brokers love to do that. And so you want to go buy cat, you can buy cat. You want to buy risk, you buy risk. But do you know what you're doing and what you're buying? And I think, look, we talk a lot about it because it's an important part of our strategy, but we have Charlie Fry here in the front, best reinsurance buyer in the world. This is a very strategic part of our business, and it's different. I don't think there's any place in the world where reinsurance is bought by someone of his seniority or experience, and it doesn't come right to the group CEO. I mean it usually goes into a business or goes into the CFO. It's not strategic, and it reflects in results. How do we think about reinsurance? Well, a lot. And we also think about the details that go into it. But we start with balance sheet protection. What's the financial impact? How do you reduce volatility and control it, it becomes more predictable? What's the gross underwriting strategy? Because you need to know what you're going to put into reinsurance. First, you need to know what you're underwriting. So like having that correlation is really important. Your enterprise net underwriting strategy, and then you have to take a long-term approach to this, and you'll see how it's evolved for us. You can't buy it year-to-year and then change next year. This is all about building to reflect the portfolio, the strategy, and the execution. Now people want me to take this slide out because sometimes it could be confusing, but I won, and we kept it in. So there are a few things here that I would just look at. One is if you look at just the gross portfolio, you have obviously much wider outcomes, and we see that in the industry with companies that take significant nets. You just don't know. Like so it's further to the right on the curve. If you buy reinsurance, it's to the left, and so therefore, it means that you have more predictable results, you're more likely to understand what the profitability is, standard deviation is tighter, and you can never eliminate the box, reflects that you can substantially reduce tail risk by understanding your portfolio, modeling it and coming up with a reinsurance strategy that is very thorough. So gross, you tend to have like -- the theory, the academic exercise is you're seeding off profit. But that doesn't take into consideration real volatility that exists in the world and exists in terms of portfolio. So this is how we look at the enterprise, it's how we actually start modeling reinsurance. Back to '17 and looking at what reinsurance was purchased, what was the risk appetite compared to today, it's like dramatically different as you can tell. $1.5 billion net retention, that was a single occurrence, by the way. So if you blew through it, there was nothing left. We have $500 million in North America Commercial. Japan, you can see the differences, again, dramatic decrease in retention, so we can control volatility. Rest of the world, they didn't buy reinsurance, so there's no real comparison. We like $125 million as a retention. And then we don't talk a lot about property per risk. That's an individual risk loss, but they could take up to $600 million net. We take $25 million net. So it's just controlling that volatility. Now if you said, well, reinsurance is expensive, and if you're buying more reinsurance, of course, you have less volatility. But what does the cost mean? Well, it's a cost of goods sold. I mean I always ask, never really get a good answer, but what's the difference between what you would buy in reinsurance versus what you ought to fund net? And a lot of times, people change the subject because the answer is probably not much. And so I think when we look at this, it's a fully loaded cost that goes into our products, and therefore, we know what the premium is going to be and what the expected margin is. Casualty, same story, if not even, I think, more dramatic. Well north of $100 million net in the U.S. historically. It's $12 million today. And in International, pick the number, you don't buy reinsurance. It's whatever the largest gross limit you put out. It was a significant exposure on an individual risk basis but also on a portfolio basis. And that's sometimes what you've seen historically at AIG is just the volatility. And then in International, we have a $15 million retention. Look at the different return periods. And so again, I won't spend a lot of time on this slide, but what I will do is point out what I think is really important, is that when we look at return periods, so 1-in-10 is frequency, 1-in-250 and beyond is severity and more tail. We did not structure our gross underwriting or reinsurance to any one particular return period. You can see it's consistent all the way through, which is best-in-class. That's what you want to do. A lot of times when you reunderwrite, you eliminate the tail, you may pick up more frequency. If you want to eliminate frequency, you end up picking up more tail. The gross reflects what the underwriting did. And so you can see at the 1-in-10, it was a 46% reduction in the PML, probable maximum loss. If you applied reinsurance, it was 70%. And so you can look at every return period and see it very consistent. And if you go to the 1-in-250, same story, like it's a 43% reduction in gross, 70% reduction in net. That goes back to the chart that everybody wanted me to delete, like you just -- you end up having better net retentions. You have better predictability of volatility. And you can see the substantial reduction in the portfolio during that period of time. This is for worldwide all perils. Casualty structure for reinsurance, just because I want to show you something that I think is really important for everyone to understand. We talked about International having a $15 million net retention. We buy $85 million in excess of that. It's 100% placed. So Jon Hancock, who runs International, him and his team issue $100 million policy. Most loss we could have is $15 million. North America, the reason why it's [ $50 million ex of $25 million ], we don't deploy 100s anymore. And if we do, we'll buy facultative. So we purchased a treaty to reflect the gross portfolio, so [ $50 million ex of $25 million ]. And then we buy a [ $10 million ex ] of $15 million. And we have a quota share to supplement that. So that's how you get to the $12 million retention. It's the only other slide that people didn't want me to put in, but I'll explain why I like it, I think. So be patient with me on this. But the [ $10 million ex of $15 million ], a lot of times, insurance companies buy excess of loss to protect for vertical loss, which is a good idea. But what happens, because this isn't cat where you're not going to have -- I mean, today's day and age, you could, but so many different catastrophes that you need 5, 6, 7 or more limits. In casualty, you might. So if you look at this, the [ $10 million ex of $15 million ] has $320 million of aggregate available. That means there's 32 reinstatable limits. And there's no APs. I mean we preprice this on Casualty, so it's fully embedded. And if you hit it, you can hit it 32 full times and still have reinsurance available. The [ $50 million ex of $25 million ] for U.S., you have $525 million available. And then in International, you have $765 million of horizontal. So you have vertical protection, and you have multiple limits that you can reinstate. Just think that's really important because what it says up here is that extreme tail scenarios companies tend not to buy the return periods. They buy a couple of limits. We did it in modeling at return periods. And I think it's really important to look at that and stress-test it. So what does this all mean? I'll just give you an example. At the 1-in-250, which is already starting to become tail, if I actually had a bigger chart or is allowed to design this the way I wanted to, I could have brought it out to 1-in-10,000. That's where it exhausts. So at 1-in-250, you can just see that, even if we hit that, which is starting to become extreme, we still have approximately 50% left in the International. We have 65% left in North America for the [ $50 million ex of $25 million ], and we have almost 50% left for the [ $10 million ex of $15 million ]. So this is built for vertical and horizontal and extreme tail. I think it's very conservative. I can't really go into it in great detail on earnings, but I wanted to show everybody this because I think it's incredibly responsible. But also you'll now know why we're confident in terms of like large losses. If there's things that happen to go different than that's modeled, we have unbelievable reinsurance protection. Let me give an example of a business like what's happened. So North America Excess Casualty, we look at the total exposed limits. So if you look at the green boxes, that's the net premium written. If you look at the blue bar charts, that's the net we've had for each year. And then if you look at 2019 all the way out on the green line, that's the cumulative rate increase. And then the white line is the gross limit reduction. So the conclusion is that we started off with $243 million in '19 with a $12.5 million maximum net retention. And if you go all the way to 2024, what happened? 254% cumulative rate increase, gross limits reduced by 80%, and the net premium written is $474 million. Part of that is we readjusted some of the reinsurance, but most of it is through excellent underwriting, Barbara Luck and her team driving outcomes, and the business is performing exceptionally well. But you can just see not only do we have confidence in the portfolio, the way it's been underwritten. We also have a lot of reinsurance protection and a very thoughtful strategy in terms of how we're going to position that business. Let me transition into who we are, our global businesses. Let me start in North America. Very balanced, $8.5 billion. You hear us talk a lot about, and we will today, Lexington and the excess and surplus lines. But we also have very big businesses, retail, casualty, financial lines, Glatfelter, which you knew we acquired, our programs business and also our retail property. All very strong businesses with lead underwriting capabilities and very well-respected in the industry. Our distribution, 55% retail, 23% wholesale, and then we have these other distribution channels, could be agents or specific programs that support Glatfelter, Programs and Captives. And I know there's a view in terms of our large commercial, which I think is actually a positive, but 45% large commercial and 55% middle market, small commercial. And we define that with clients with revenue of $1 billion or more [indiscernible] $1 billion or less is in the middle market. So I think it's a good snapshot of the business and its balance. Here have been the results, really good growth. And don't forget, at the beginning, we're still, I don't want to say re-underwriting, but pruning the portfolio. I think the growth probably is artificially lower than what I feel like actually the momentum is. You can look at the accident year combined ratio. I mean memories fade, but North America Commercial was the focus on every call because of the portfolio, how it performed, its combined ratio. And of any guidance, including what I gave you today, I've been the most nervous about, is saying we get below 100 combined in the business, because that was hard based on where we started. But we did it. We never looked back. And Don Bailey and his team have done a phenomenal job. You can see 16.7% points of improvement on an accident-year combined ratio from '19 to '24. Calendar year, similar story. We started where we started, but you see a significant improvement to 13.8% from '19 to '24. So the performance has been just outstanding, and we really have a balanced portfolio now of profitable businesses. New business, and I think Don is going to take us through how he has focused on that, where we're absolutely targeting the best risk-adjusted returns and how do we actually start to turn that on. It's really important. So you can see the strong new business. You can see the contributors, Lexington Property, Lexington Casualty, Retail Property over the course of the year, the opportunities present themselves. We're prepared to take advantage of that. You can see this a couple of times. The E&S market has changed dramatically. If you go back to '18, $50 billion. And then if you look at the 7%, above that, it represents the total non-admitted premium as a percentage of the total industry direct premium written. And then the 14% represents Lexington's percentage of our overall net premium written within North America Commercial. Now I like to think I'm pretty good at math, but I can certainly count by ones. I mean so if you look to 7%, 8%, 9%, 10% it's already going to 13%. I think that's pretty impressive, and it's telling a story. And those companies that have mostly agency distributions or don't really want E&S to be successful, they're not talking about the fundamentals. I'm talking -- but this is growth. This is market share. And also, there's a lot of momentum here. And so there's just a different wholesale market today. What does it look like in the future? 10% compound annual growth is conservative and very realistic because they have 3 different channels, the normal E&S, agency placement, MGAs, MGUs, delegated authority, pick your bucket, it's all growing. And you can see it's grabbing market share. And we're no exception. Our industry-leading capabilities are allowing us to deliver those returns. Now if you look at -- this is -- again, you measure KPIs. I like to look at new business submissions. This is like unbelievable. So the bar charts reflect the gross premium written from '18 to '24, but we were getting 30,000 submissions a year in '18. And then in 2024, we got 300,000 submissions. It's 10x the volume. And no, we're not getting to all of it. When we do business reviews, the team has done an amazing job, net premium written growth is very good, new business growth is good, we talk about it every earnings, but this presents a real opportunity for us in the future. And also it does show that there's a lot of change going on in the industry. Let me transition to International Commercial. Very diversified, very high-quality business. It's going to have a similar story, but didn't start where North America Commercial did, led by Jon Hancock. So you can see we have a big specialty business, global specialty, Lloyd's Syndicate and Talbot, and then Financial Lines, Casualty and Property round out the balance, $8.4 billion net premium written. These businesses really demonstrate leadership in our international market and present us with really unique opportunities. Distribution is a little bit different than North America, as you can see. Global brokers of the large of 46%, but we have international brokers, domestic brokers, agents and partnerships. So there's more diversification, and that is what you should expect in international. And then Large Commercial represents 56%, Middle Market and Small Commercial, 44%. Great chart. 6% compound annual growth, 13.4% points of improvement in the accident year combined ratio, and it started at an underwriting profit. So that's the big difference. World-class combined ratios and very good improvement on the calendar year as well, just executing on the business and actually trying to shape it, and we've done an exceptional job of that, the businesses we want to grow, Global Specialty being the #1. New Business has been very consistent, very strong. You can see, as I just mentioned, Global Specialty has been the big driver of that. The syndicate has been a major contributor, and we see opportunities in casualty. We're selective, we're disciplined, but we're prepared. And so we saw some growth there in New Business in 2024. Global Personal will have some attention in this discussion today, very good balance. What I will draw your attention to in 2024 is we still have travel in there because travel is still here. But it's a very, very good A&H book, Auto and Home, high net worth, and it's rounded out with warranty. The A&H portfolio is always been something that has had a great reputation at AIG and one that we believe will continue. We have a growth strategy. We'll take you through that. Geographic distribution is very balanced, Japan being such a large country. And in personal, North America, is really driven by high net worth and then Europe and Asia Pac rounded out. It's had mediocre growth. We want to do better. The combined ratios are not where we want them to be, and we'll give you some guidance in terms of what we expect over the next 3 years on an accident year and combined ratio. It's been very steady. We like the business. We like the segments we're in, and we like the countries we're in. And so we have a plan to take you through as to how we're going to reshape that. Operational excellence is a core competency. Everybody knows AIG 200 to the left are some of the distinct work streams we had, but this was so incredibly important. The underwriting culture needed to change. I would say the operational culture had to change more because we only have one. And so how do you build an end-to-end operational process is really important. Some of the key accomplishments, it was all about building the foundation for the future. And you'll see when we talk about AI that we've been able to do that. We achieved $1 billion of run rate savings with a 1.3x cost to achieve. And that's very tight for a project like this, particularly when so many of the investments were highly dilutive, speaking of which, we invested $500 million to digitize our commercial underwriting platform end-to-end. And so the returns, of course, you're going to be able to do renewals better and new business, but it was dilutive, but it needed to be done, like in order to shape the company for the future. We reshaped our operational infrastructure. We upskilled talent, added supplemented to what we had. We scaled our public cloud adoption, went from 20% to 80% in 2 years. And so we saw an opportunity as we have across AIG in multiple cases, like going linear is not getting us there. So we've just got to transform and jump. And we did, and we did an incredible job of getting that done in 2 years. When we did that, we eliminated 1,200 legacy applications, and that will sound boring, but when you start to get some standardization of how you're going to move to the cloud, you don't want to just like forklift everything. That's expensive. So we were able to eliminate a lot of the applications that were no longer fit for purpose. And we modernized our data and document foundation. That feels like a throwaway line. It's probably the most important line out of the key accomplishments because it enabled us to have single definitions for data and then to take on what we're doing today and in AI. Strategic Divestitures. Those are usually done from a point of weakness. We did it from a point of strength. How do you shape the portfolio? How do you position the company for the future? What do you want the company to look like in order to have outperformance? So you know the strategic divestitures, 2 biggest ones were Corebridge and Validus for different reasons. With that, we transferred 13,000 full-time employees, which is $1.1 billion of less cost. We eliminated $250 million of stranded costs. A lot of companies can't get the stranded costs out. We were all over it, and we eliminated those costs very quickly after the divestitures had closed. With the migration to the cloud, we needed to get out of the legacy data centers, so we sold those. And it was not only a $100 million proceed, but more importantly, is it reduced our annual run rate by $25 million, but also enabled us from a cyber perspective and from a risk perspective to be very focused on what we're doing with the cloud and not have legacy data centers as part of our footprint. And then we reduced our real estate by over 40%. Last one, which we talk a lot about now is AIG Next. You can see we had -- and you know this, we had a significant amount of costs in parent and other operations, it wasn't always clear. So we need to get to a future state operating model that we have a lean parent company that we would eliminate expenses, eliminate duplication and what wasn't eliminated would be transferred into the business. And the business would have to absorb it and the combined ratios aren't going up. And so we did this at pace. And you can see as we look to the future, we are going to hit our targets, $500 million of exit run rate savings, get to a lean parent company of $350 million and allow us to recognize the target operating structure. We accelerated things by creating and offering a voluntary retirement program. It just allowed us to get on with the structural changes and move the organization forward. And then it enabled us to have investment in the future, AI, digital, data. Let me briefly talk about AI. I'm like very, very excited about this. I mean we never have enough time to really go through it. But between me, Claude and our panel today, we'll start touching on more detail and why there's substance behind what we're doing. We're focusing on this as an end-to-end process, not on the fringes, not just for expense savings. This is end-to-end. And we want to focus on growth. That was the entire premise of our strategy. And the 2x or 5x reflects there was 2 piles. Like if you have a strategy for GenAI that can reduce cycle time or improve revenue by 2x it goes in one bucket; it is 5x, it goes in another. Let's get on with it. Everything was documented, everybody was involved, and we need to make sure that there was a path forward that we could execute on. And so we basically broke it down for simplification into 5 categories. Start with underwriting. For us, Claude will call this underwriter in the loop, which means the underwriters are still making the decisions. But we need to enable them. Today, there's so much time still spent gathering data, gathering financial statements. But this is about why I say you give an underwriter the opportunity to identify the 125 items you'd like to have a perfect submission. What would it look like? And so they do that work. Then we need to make sure there's consistency. When you're extracting that data, does it come from a bunch of different sources. If you ask underwriters, typically, they will start to get the same things, but they get it different ways. And so it makes the process very inefficient. So we want a consistency in data and extraction. And then we want to talk about the cultural shift of how do you -- you can't just like overnight say, "Okay, you're not going to do 5x the amount of underwriting today. Here you go, can't wait for the outcome." Like you got to start to shift what happens with people, how do you train them, how do you prepare and how do you engage with distribution. That's where we started. So then you go into the data, where it comes in from brokers, agents, I can't even count the number of forms that come in, and you're not changing broker behavior. So you get it, it's structured, it's unstructured, it's PDF, it's text, it's whatever it is. And you got to be able to extract that real time to get insight to be able to fulfill what we're looking for in those 125 pieces of information. There's AIG systems. We've seen the account. It's a renewal. We used to have it. There's data. And so how do you extract it within AIG to be able to supplement what comes in through distribution of brokers and agents. And last, if it's in neither of the first 2 categories, how do you go to reliable sources that are approved that have great data that will help you underwrite and fulfill those specific requests that an underwriter wants to make great decisions. And so we've had all of this done, and that's why Alex will be here today. We've done it with Palantir Foundry. It's unbelievable outcome in terms of what we get. You could give underwriters, and I'm going to exaggerate for effect here. I could give them unlimited time. 2, 3, 4 weeks, they still can't get the amount of data that I can get within 2 to 3 hours through Palantir Foundry. Okay. Well, that's not going to just magically rub a Genie bottle and end up in the underwriter's pockets. Like what are we doing? We have to focus on how do we actually train large language models to know what to go to extract. Now of the 125, like we don't need to train large language models to confuse it. Can you please get the client's name? We hopefully have that. I mean so there's some data points that are already put in, but the very important insightful data that needs to come to the underwriter is trained to the large language model. And we use Anthropic Claude 3.5. Now I thought Claude Wade, you'll see for the first 6 months, I thought it was just making up the large language model name to name it after himself. But I guess it's really a model, and Dario will take us through that. But we started Claude 2.0 and then we are now Claude 3.5. And just the unbelievable advancements in these large language models to be able to extract data real time from the data ingestion, the conversion into the underwriter is unbelievable. We could also -- not from an algorithm, but we could also prioritize risk characteristics like an industry group, like a geography, like the size and then start to train the large language models to start to prioritize submissions. So our underwriters are actually reviewing where we believe the best risk-adjusted returns, but also the prioritization you would see hopefully, the bind rate go up as a result. And then the data augmentation and learning with source means we can augment data. There may be a request, but there's other information that can be helpful that will come to the underwriter. But also talk about hallucinations 12, 24 months ago, that was very prevalent. Yes, it still exists. However, we can now look at the source of where the data came from. So the underwriters can say, "Oh, that is very good." It came from a rating agency or came from something that is incredibly factual, and I would have got that myself, so they can actually go and check it. So that is going to be a dramatic change for us. This is not -- I mean, I go to [ WEF ] and say, can I meet with somebody that's not going to give you a pilot or something that's theoretical. Is there something that's actually really happening? This is happening for us. And it's something that is real and something that's going to be a big part of our company going forward. We will optimize the portfolio. That turnaround was optimized in the portfolio. We already do it. But can you get it from a manual process to what we just did with our special purpose vehicle, which Charlie will go into more detail. Can you actually do that across the portfolio in more real time? The answer will be yes. We want to kind of get the data ingestion, large language models and underwriting a little further along, but the answer is absolutely yes, and you'll be able to allocate capital better for better risk-adjusted returns. And we have a lot of examples as to where that will take place. So I remember I said I would come back to this slide. It was about the E&S market growing. It was about AIG's percentage of the E&S growing for us. And then what does it look like in the future? So if you said, okay, I believe in the 10%, that means in 2025, the industry for E&S will have tripled since 2018. The submissions, 30,000, 300,000, 10x. We have a choice. You can see what we did. We restructured. We had to reposition. I would say we were the catalyst that drove the E&S market to change because we had a multiple distribution channel, large limits, changed the whole thing, how to flip the portfolio, did that in 2018, everything started to change. And I think others in the industry were followers, but we set the mark and we're able to deliver year after year after year. Okay. We did that. Then it's a strategic turnaround. Are we known? Are we back as a company that's incredibly well respected for underwriting, for our insights on risk? The answer is yes, we start growing. New business starts flowing, can't get to it all. So if you look at the bottom dotted line, can we keep doing 10% and stay with the industry on a CAGR basis? Absolutely, we can. I mean that would be very good by normal business standards. But I want to challenge us to think differently. I want to think about 20% plus. How do you grow 20% with what I just showed you in terms of data ingestion better, large language models, getting it to the point of sale, the underwriter, to be able to quote more and buy more over time? Well, let's just give you a practical example. What did it look like in '18? 2018, we had 30,000 new business submissions. Buying and submit was 4%. I don't know if that's good or bad, it seems low to me. Average premium size was $260,000, and we did $300 million of new business. 2024, we're spiking the ball. It's like 300,000 submissions. That's great. The buy and submits at 2%. So I think that's -- we just got to be better underwriters. Well, yes, but I also think we didn't get to the volume. Went down market, which was good. We thought it was more profitable. Average premium size, 140,000. We did $1 billion of new business in 2024. That's very impressive. But how about like -- again, I'm an optimist. I'm a CEO, I'm supposed to put up things that like, oh, like if you do this, this is what happens. I think this is really conservative. The $500,000 -- 500,000 new business submissions, again, just think of it over the next 5 years, that's just staying in line with where the market is growing, the 10%. And my hypothesis is can we do 6% on a buy and submit if we adopt a new way of doing business. I certainly hope so. I mean I'm not going 15%, I'm going to 6%. And then not going to increase the premium size, just keep it the same. What happens? When you get 4x the amount of new business, you're able to underwrite 4x as much. And I think when we do that, it's not going to be just adding volume, it's going to be better risks. I don't even know what happens with the market. I can give you a view, which is they're going to want to come more. I think the 500,000 will be light, like we're going to be able to buy more. So this is the direction we're going. I give Lexington as an example because it is the one that is right there in front of us, but there's a lot of other businesses within AIG that we're going to be rolling this out and adopting it. It's for real. And this is not something that is for companies like us. Like I don't believe this is a choice. This is -- we're doing this. I mean, like we have to do this and drive change. Let me end with what we are doing in our top performance and some of the things I'm most proud of. Okay. We've made significant progress on capital management. You know the story. Keith will give you the exact numbers, but we've reduced share count by almost 300 million shares. We start to have confidence in our earnings more liquidity and dealt with so many of the capital issues that we started to increase our dividend. We're giving guidance again in 2023, 10%; 2024, 10-plus percent. One of the things I'm most proud of is our leverage. And what we did, it took enormous discipline at a time where there's a lot of moving pieces, just continue to reduce debt. And now we've gone from $22.2 billion in '17 to $8.7 billion and a 17% debt-to-total capital ratio. And we've increased our subsidiary dividends. The dark blue is ordinary dividends and the green is extraordinary. It went from $350 million to $2.5 billion, and then we actually were able to get $4.1 billion with the extraordinary in 2024. Now I don't have time to go through the history of AIG or what happened and like why we didn't break up the Life and Retirement business in the past, talked about DTA, talked about capital, but this is a big issue as well is that how is AIG having ordinary dividends of $350 million going to service $4 billion of obligations. Like the answer is you can't. And there's no place to go in terms of getting more liquidity. That's for another day. But you can see the discipline of going from with $1.5 billion of Corebridge, which was Life and Retirement at the time, ordinary dividends, we're still $2 billion short -- $2.150 billion will be specific in '17, discipline, retiring debt, getting more liquidity, getting a capital structure that's fit for purpose for the future. And now we have a surplus in 2024, where we generate $2.75 billion. That does not include the extraordinary dividends and the blue is like our dividends from Corebridge. So like we are self-sufficient, generating liquidity, generating profitability and we're all over the uses and the obligations. If you look to 2025 through 2027, we should be generating around $3 billion of ordinary dividends. It may not be in '25, but it's between '25 and '27. And our uses will be $2 billion or there or thereabouts, generating $1 billion of excess liquidity just based on how we run the business compared to 2017, not a chance. How are we going to drive earnings and earnings growth for AIG in the future? Global Personal, we've talked about it. There's lots of opportunities. We're going to improve our combined ratio of over 500 basis points from today over the next 3 years. And you can see, yes, we put every category down because we believe every category can improve, got to have more growth, improve an accident year loss ratio, reduce CAT, acquisition and expense ratio will improve, we'll get here. I mean a 94% is an aspiration, but it's a very realistic objective. And then we talked about expenses went from 38% to 33.2% this year. Take out travel, 32.4%. We'll get below 30%. I mean we're going to have a lot of different ways in which we can do that. And I ask you to give me a little bit of a benefit. In 20 years that many of you know me, I don't miss expense targets, like I just don't, haven't, won't. Like -- so this 30% will happen, and we're all over it. But like with AIG Next, with AIG 200, let us go at the pace where we know that we're investing along the way, and we're driving outcomes that are sustainable. And so that's the ask, but we will absolutely get there as fast as possible. M&A, we have financial flexibility. We have strategic intent. We're going to be very disciplined. Some of the key characteristics and assessment criteria we use is, are there product capabilities that could complement where we are today? Is additional scale in a business already has scale helpful to us or maybe access to new geographies helps our global footprint? We'll be relentless on focusing on culture and that is an actual fit within AIG and that it's an underwriting company. That's what we want. And there may be some adjacencies that don't exist today that we may want to explore over time. The financial targets, though, it will be accretive to EPS, it will be accretive to ROE and we'll be very thoughtful in terms of its impact to tangible book value. You'll see this slide, I don't know, maybe 4 times. Keith has it, Q&A. But here it is. I mean this is how we're going to build the 9.1% in '24 to the 10% to 13% in '25 to '27. I don't need to read all the levers, but underwriting income is going to grow, expense optimization. We have opportunities in net investment income. Interest expense, we've done a lot with debt. I wouldn't spend like a lot there, but we may get some more. And then the other 2 variables are going to be capital management and how we think about tax. So there's a lot of levers to pull. As Keith will tell you, like don't try to measure the boxes because they are put up there equally, so there is no discussion around it. They're all going to contribute, and we'll get there. One more note on EPS is that I think this is dramatic. I think it's exceptional. I want to point it out. If you look back to '19 through '23, Corebridge and Validus Re made up more than 50% over that period of our EPS. And so when we made the accounting election in 2024 that we were just having EPS from AIG, it was bold. It was right, but here we are. And so when we look at what we did in 2024, I think it was exceptional. And we gave up a lot of EPS in order to replace it with core earnings growth that's sustainable. And if you look back, we need to reposition this business to be leaner, more profitable, more consistent over time. So that's the 20% CAGR. But look at what we've done. I mean, in 44% through 2022 to 2024. And then, of course, it's the 20% going forward. But you'll do the math, but you get to 2026 is that we replaced all of Corebridge's and Validus' earnings in basically 3 calendar years. I don't know -- I mean, we'll have to talk at the break. Are there other companies been able to do that and have confidence in it? We are and really proud of what we've been able to do here. Yes, some of it is capital management, but some of it is like really driving core operating performance consistently. So where we start is where we end. This is the guidance. EPS of 20% plus over the 3-year period. Our core operating ROE, 10% to 13%, but we're going to do the 10% in '25. The GI expense ratio will be below 30% and the expected dividends per share in '25 and '26 will grow more than 10%. Thanks for your time, and I'd like to welcome Keith Walsh up to the stage.

Appreciate it. If it looks a little off, I made him buy a new suit. I couldn't take the brown anymore. Thank you for that, Peter. It is wonderful to be here with you all, see so many old friends. And we have a great story to tell. As Peter just outlined, AIG is not a turnaround story anymore. It has turned around. And so what I'm going to take you through today, we're going to go through the balance sheet in some detail and talk about the financial flexibility we've built. We're going to continue on the balance sheet and go through our reserves and investments. Then we're going to turn to capital management and expenses. And then finally, finishing with the ROE and targets. The company on the journey that we've been on has methodically built this balance sheet for strength over the last many years. And we're going to walk you through that today. Let's start with our insurance subsidiaries. We have tremendous flexibility within our insurance subs to grow. If you look at 2024, we finished with about $24 billion of premium, on $27 billion of stat capital, as you know, at 89%, that ratio has come up over the last several years from 72% to 89%. We have more room to grow. What does that mean? It means we can self-fund our growth, both organically and inorganically. In other words, as we grow and add premium on, we need very little capital to add incrementally to do that. It's highly ROE accretive. What else? Within our insurance subs, our cash flows have grown dramatically. Peter has talked to you about this already. In 2020, we were able to dividend $1.3 billion from the subsidiaries, $4.1 billion in 2024. That's a 3x change. In fact, it's a 4x change when you look at ordinary dividends. As Peter mentioned in the last -- one of the last slides, we believe a good target run rate for ordinary dividend distributions is about $3 billion on a run rate basis. That's before any extraordinary as we move out. These cash flows are a direct result of the underwriting improvements that have happened in the company. We expect these will continue to grow as our underwriting profits and stat surplus grows over time. So what does that mean? We've generated financial flexibility within our insurance companies. We've also built more debt capacity on our balance sheet over that period of time. We've paid down $18 billion of debt. More importantly, since 2020, we have simplified our capital structure with the separation of Corebridge. Additionally, we mentioned the 17% debt-to-cap ratio already. We went from probably the highest leverage ratio in our peer group to one of the lowest. This is foundational for our growth. We have financial strength. We have flexibility. We have the ability to play offense and defense in any macro environment. Let's put this all together when talking about the balance sheet. We've got financial strength. We've got flexibility. $8 billion almost of parent liquidity we ended in 2024. 407% risk-based capital ratio within the U.S., and we are well above targets in all of our major international entities. We mentioned the debt-to-cap, and of course, over the last 2 years, we've had positive rating actions at all of our rating agency partners. Good companies have good ratings. We are committed to that. Let's pivot now to our reserve position. This is another good news story, and frankly, it's one that wasn't such a great story 6 years ago when the new management team came in and started changing some of the underwriting, and then we've seen the reserves follow. We've gone from deficient to what we feel is a very healthy level that we're proud of. So what are some of the principles? We have $40.1 billion of net reserves on our balance sheet. One of the biggest principles, and you hear us talk about this all the time: recognize bad news quickly and allow favorable trends to develop. That is a core principle. Additionally, developing conservative initial loss picks, right? Watching them develop over time as well. We need strong and frequent triangulation between reserving, actuarial, underwriting and claims, right? That is a relationship of challenge and of collaboration. It's critical to what we do. And we do deep dive reserves on an annual basis as well as monthly and quarterly. And as we touched on in the last quarter call, we have a holistic way of looking at our reserves, and we will react every quarter. We're not going to just highlight on the annual reserve reviews. We'll react to news as we see it. Let's look at this in practice. If you look over the last 10 years, you can see the underwriting improvement has translated to our reserve development. From '15 to '18, we took over $10 billion of reserve hits. That was an 11% hit to our book value per share on an adjusted basis. Over the last 6 years, which coincides with the improvement in our underwriting, you see 6 consecutive years of favorable development, which is a 3% impact cumulatively to our book value on an adjusted basis. Now we don't rely on this. We don't budget for this, right? And it is not a major part of our earnings. As you saw in some of the prior slides, we have about $2 billion of underwriting income over the last several years, and this is not a large percentage. I want to touch on a couple of pieces of analysis that I know gets some attention. And what we want to do here is we want to look at our U.S. long-term commercial Schedule P data over the last 10 years. And what do we mean by U.S. long tail? It really is other liability occurrence, it's workers' compensation and it's commercial auto: 3 of the lines that get a lot of attention. So if you look at this, this is our initial loss picks versus the industry. And as you can see from some of the earlier years, we were well above the industry, and we should have been well above the industry. Then you see some of the actions that we took. On accident-year '16 to '19 -- back in 2019, we took $1.2 billion of reserve strengthening on those years. That's $900 million on our other liability occurrence line and $265 million on commercial auto. And we took our loss picks up significantly higher than the rest of the industry, and higher from where we were. Additionally, you can see as the lines start to converge over more recent accident years, that's from our re-underwriting, as our book has become very profitable, consistent with the rest of the industry. Now we didn't take those picks down in those prior years. And we moved earlier than others. 80% of these actions were done before 2020. And so we feel really good about our relative positioning. Let's look at the same analysis, drilling in specifically, on the left, to other liability occurrence line, and on the right, commercial auto. You see the same relationship here. Additionally, we got cumulative rate on these long-tail lines of 82% since 2019 and 108 excluding workers' comp. Additionally, we put in loss cost trends of 10% or greater on all lines -- on all of our workers' comp business at post-2022. And we were at a significant number before that. Let's look at another analysis at IBNR. So what we're doing here is we're going back to 2019, which represents about the 6 years -- 5 to 6 years of the re-underwriting strategy that's taken place. And what you could see from this chart, and these are 10-year rolling accident years, so for example, in 2024 -- that's our 2024 year plus the 9 preceding years before that, 2023, 2023, 9 years, et cetera, as you go back. And what you can see is that our IBNR as a percent of total reserves went from 68% to 80% over that time, a 12-point differential. You can see for the industry, a 4-point increase. We think this is a prudent metric. Once again, drilling down into those specific lines of business, you can see the relationships even more pronounced. We have a 14-point increase over that period of time in IBNR as a percent of total, the industry is at 5. So in other words, we feel really good about where we went on our reserves. We were deficient to strength. We reacted early, took those loss picks up, re-underwrote. And so we feel like we have a very healthy position. Let's turn to investments. We have a high-quality portfolio, about $90 billion. And frankly, over the last 5 years, we've been defensively positioned, really all about maintaining capital, liquidity, right? Just more defensive. And so we have an opportunity as the underwriting improvement has taken hold to be a bit more strategic around the portfolio. A+ rated credit, 3.8 years duration of assets, which matches our liabilities. So let's dig in a bit more. There's 2 pieces I want to talk to you about. And the first would be around our core general insurance portfolio, which is $77 billion of that almost $90 billion. The second is our other ops portfolio, which sits outside of core GI. When you look at the net investment income driven by both of these pieces, it's about $3.5 billion. $3.1 billion in 2024 was driven by the core GI piece, other ops drove $420 million -- $424 million to be exact. What I want to talk to you just first about other ops, because we have a lot of moving pieces here. What does that make up that $12 billion? It's primarily 2 things. It's about $8 billion, which is our parent liquidity number we showed you earlier. And then there's about $4 billion of our remaining stake in Corebridge. Now the $420 million that sits in other ops net investment income is going to materially decline over the next couple of years for 3 reasons. Number one, interest rates are lower than they were a year ago. Number two, parent liquidity, we use that money for our share repurchase. So as we buy back stock, that number will naturally come down. And number three, as we continue to sell down Corebridge, we will receive less dividend income, and that's where it sits. So that number is going down, okay? Let's move on to the $77 billion because this is really where our core strategies take hold. That's the $3.1 billion. Now we're not immune to short-term rates in the core portfolio as well. And what I would tell you is that for 2025, when you take all that together, we won't get a lot of growth in our net investment income because of some of those dynamics we just talked about. But for '26 and '27, we expect our strategies to take hold and to grow our net investment income, will be an important contributor on our ROE journey. There's really 4 things we're looking to do. Number one, our invested asset base should start to grow again, right? As we've divested businesses over the years, we have not grown the invested asset base that much. So that will start to change. The second thing, we have some incremental opportunities in parts of our portfolio overseas, specifically in lower-yielding places such as Europe and Japan, to get a little more yield. Third, we will continue to invest our runoff. As our portfolio matures, we reinvest at higher new money yields, roughly 100 to 125 basis points above the current level. And lastly, increasing allocations to private credit. We're talking about modest increases here. We're currently about 8% of the GI portfolio. We expect to take that to about 12% to 15% over the next several years. And of course, you get higher yields than you do on public equivalents, so about 150 basis points. So as that takes hold, that will help us. So in other words, a very liquid, strong portfolio, and we believe we are taking actions to position it for upside. Let's turn to capital management. This is the fun stuff. What do we do with all the money, right? And the one -- so this is a snapshot. Peter has touched on some of these topics already. We've spent $45 billion on basically 3 categories since 2019, right? What is that? $21 billion on leverage reduction, $18 billion on share repurchase and a little over $6 billion on shareholder dividends. One of the key messages I want you to walk away from today is that, every dollar we earn, we're done divesting, we're happy with our portfolio. Every dollar we earn on a go-forward basis is for productive use in growing our business, investing in our business and returning capital to shareholders. That's it. Let's drill in a bit more to share repurchase. Peter mentioned this in detail in one of those last slides that you saw. We have used share repurchase as a tool to rightsize our equity base as well as rebuild our earnings per share power within the company. So a little bit of information here, there's a few moving pieces. This morning, we announced a new $7.5 billion share repurchase authorization. That replaces the existing authorization. So just to be clear, $7.5 billion from today going forward, okay? We anticipate we'll buy back roughly between $5 billion to $6 billion within 2025. And through the first quarter, we've repurchased $2 billion -- a little over $2 billion of stock. So an incremental $3 billion to $4 billion over the next 3 quarters of 2025. Now I want to put your attention on the right side. You've seen some of these numbers already. We believe we have, on a target run rate basis, once we're done with the Corebridge sell-down -- and just as a reminder, we still have $4 billion of liquidity that we can monetize from Corebridge, we've committed to hold 9.9% through December 2026, so we have an ability to get more monetization and to do more buyback. But on a target run rate basis, we're driving $3 billion of ordinary dividends. Peter mentioned in one of his slides, we have $2 billion of uses. What are those? Roughly $1 billion-plus shareholder dividend, corporate expense and interest expense, roughly $2 billion. That means our share repurchase on a run rate basis, without any asset sales, meaning Corebridge, is $1 billion or less on a go-forward basis. Just want to make that very clear. Let's move to dividends. Peter mentioned this as well. We grew our dividend 10% plus the last 2 years, after 6 straight years of stagnation before that. This is an important metric. Dividend increases is a sign of a healthy organization, a healthy company. We believe in it. We think it's important. We've committed to 10% plus for the next 2 years, right? Why are dividends important? Some of our long-term shareholders have actually published research on this where we see over long stretches of time, reinvestment is as much as 40% of long-term TSR, dividend reinvestment, right, over the last 20 years, and it's even higher if you go back longer than that. So we're believers in dividends. It is a sign of a strong company, a growing company, and we're committed to being a good dividend payer as we go forward. We're going to go back to the same slide again. Peter did this, I love this slide on the expenses. I want to talk a little bit about some of this. This is adjusted for the asset sales we've done, meaning Validus, Crop, et cetera. So when you look at the reduction from 38.3% to 32.4%, that's a real almost $1 billion takeout of cost. The other thing we've done to try and make this more apples-to-apples is, as we've said to you in the past, we believe $350 million is a good number for parent expense. So what we've done is taken everything over $350 million and reloaded it back in into those years in general insurance to give you more of an apples-to-apples look about the real change in our expense ratio. We're confident we're going to drive that below 30%. Why? A couple of reasons. Number one, Peter said it, okay, so that will be part of it. But secondly, and more importantly, we have real opportunity. AIG Next will continue to earn in over the next couple of years, and we'll get benefits from that. But more importantly, Peter mentioned this, that we have stranded costs that we had taken out. Stranded cost is the worst towards for any CFO to hear. It is really hard to take cost out when a business isn't growing as much. As we are now, our growth strategies are taking hold, we will get normal operating leverage in this ratio that will benefit us. It's as simple as making sure our expenses don't grow as fast as our top line. So I'm going to repeat this slide too, because it's a good one. I know you guys care about it. The ROE. We are laser-focused on the ROE. We know what this means. We know 10% is a minimum number, and we've committed to getting there in 2025, 10% plus. And we expect to improve within that range over the subsequent 2 years. And we've got multiple levers and multiple paths to get there. So in summary, here's the targets again. We think these are good targets. These are tough targets. But we're committed to achieving them. 20% earnings growth, '25, '26, '27, obviously, not exactly the same as a CAGR. Growing the ROE in that 10% to 13% range. Taking our expenses below 30%. That's an important metric. And growing our dividends per share double digits in '25 and '26, growth on growth on growth. We're really excited to be here with you today. It's a lot to take in. There's a lot that's going on. We've got a great story, right? And we're just getting started. So thank you very much. I would now like to welcome back to the stage our Chairman and CEO, Peter Zaffino. And we're going to do some Q&A. I would also ask -- Quentin will hand the microphone out, if you could raise your hand. And then when he hands you the microphone, if you could stand up, ask your question and just state who you are and where you're from. We'd appreciate it.

All right. Thanks. In the interest of time, we're just going to ask everybody to limit themselves to 1 question and 1 follow-up. I'm Quentin McMillan, the Head of Investor Relations for AIG. And we'll take the first question from Elyse Greenspan from Wells Fargo.

Elyse Greenspan, Wells Fargo. The first question I have is on the expense ratio. So a lot of improvement. I think that was one of the last few slides, Keith. And obviously, you talked about expense leverage. There's also some from AIG Next. Could just spend a little bit more time, that's obviously been -- through the years, we've seen AIG at a very high expense ratio, and it seems like the big driver of the ROE improvement? So can you help us just go through the numbers in a little bit more detail. And over the 3-year plan, is the 30% at '27 target? Maybe sooner? How should we think about the time frame as well?

Thanks, Elyse. We're not going to itemize the target and we're not going to give you by year what it's going to go. We're moving in that direction. We commit to getting below 30% over that period of time. One of the things is we have about $250 million of AIG Next that will continue to earn in. Probably about 2/3 of that, let's call it, in '25 and the other 1/3 in '26. So that's an important component. But I can't stress enough the operating leverage piece, which we talked about. And that will really just give you -- just model it out, just say, if our top line is growing, whatever you think our premiums are and grow the expense base as a percentage of that, you'll start to see some of that come off. So I think we've given you some really good parameters to go off there.

Can I add to that, Keith, a second is like premium leverage, AIG Next earn-in. We have more efficiencies to gain from how we're structuring our business. There's better end-to-end process opportunities outside, forget about AI for a second, just in terms of how we digitize some of our businesses. And if you look at the discipline that exists within the business today, to be able to absorb some of the costs that came from other operations and parent, they created that room. And so we're constantly finding ways in which we can improve the expense ratio. I think some of the big countries, as you start to dig in, like we are -- weaving the company together is not a way to describe a business strategy, it's about weaving it together. There's a lot of duplication. There's still inefficiencies that exist. He's always the one that has to be cautious, I'd be disappointed if it was 2027. This is not a hockey stick aspiration. We gave the range, I would expect us to get there earlier.

And then my follow-up, you guys alluded -- pointed to excess liquidity generation of $1 billion per year. Does that bake in projected earnings? And then in terms of buybacks beyond this year, is that $1 billion the base case buyback ignoring, right, the sell-down to the -- when you go [ 9.9% ] to potentially not of Corebridge over a couple of years, just base case is kind of $1 billion repurchase?

Go ahead, Keith.

Yes. I mean that's what we're trying to -- again, the $1 billion is without any other asset sales. As you know, we have a $4 billion position still in Corebridge. That's just a run rate you should be thinking about for us. And obviously, that could grow as we grow going forward. I didn't quite hear your first question.

I was trying to understand if the deployable capital, that $1 billion, does that include projected like earnings growth within the business?

It's based on our current view of ordinary dividends, right? So as our underwriting income grows, as I mentioned, that number can grow over time as our stat surplus grows.

We'll take our next question from Mike Zaremski from BMO.

Mike Zaremski from BMO. One question on capital, maybe probably for Keith. Should we -- over the last year or so the RBC ratio has come down. I'm not sure about the JGAAP or what are the Japanese ratios. Maybe you could provide some color there. But do you expect to be able to continue to bring down the RBC ratios or the regulatory capital ratios? And if so, would extraordinary dividends be in the picture as well in the coming years?

Do you want me to grab that?

Yes.

Yes. So the RBC is at a very comfortable level, and yes, we have taken it down because it was way above any normal standard within the industry. I think we can take it down a little bit more. I'm not sure we will because I think that there's opportunities to grow into that, but we're at a very comfortable place now with RBCs. I do believe that there's still capital efficiencies that exist, as you just mentioned, with Japan and some of our international structures, I mean, they've been -- they're historic, they're legacy. But there's opportunities really across the world to be able to consolidate some of the capital structures, and I would expect us to get capital out over time, meaning over the 3-year period. But I wouldn't expect us to be looking to give targets on RBC that are kind of below where we're running as we exit 2024.

Got it. And my follow-up is on top line growth. So I don't want to steal any thunder from the AI panel that's coming up. But do you -- the opportunities for growth that you're talking about, are these kind of like you flip the switch on once the technologies are in place and you can start growing into meaningfully? Or does it also matter what kind of -- how the operating environment is on a competitive basis? I'm just kind of curious if you think the competitive environment is directionally easing or still staying just as competitive? On the P&C side.

Yes. So a few things. One is I think we can grow at or above where we've grown absent what we're doing with AI. And again, if the market -- we're an underwriting company, we're going to drive profitability, we're not going to drive top line. But still think that there are very good opportunities that exist in the market with our specialty businesses or actually what we've done in many parts of our global property have run exceptional combined ratios. And again, you have to think of like back to this cost of goods sold analysis is that in many ways, like the reinsurance cost on a risk-adjusted basis are going down more than what actually the primary. So you got to think about that in terms of combined ratio expectations. But I think we can grow, maintain profitability, continue to maintain discipline. So say if you keep that constant, I would expect a little bit more growth. When we are starting to talk about AI, this is -- it's hard to give a time frame. And I think you're going to hear that from Dario and Alex say, they're more confident in the 3- to 5-year period than they are next year. And we want to make sure that we're investing to be able to capture that 3 to 5-year. We have to wait then? Probably not. But I think that that will become aligned with risk appetite underwriting and actually accentuate on a risk-adjusted basis more profitability, not less. And so what that growth looks like over time, we won't know, but I think it's going to be much greater than what we would expect in a normal environment like we are today.

Take our next question from Brian Meredith from UBS.

First one, just dive a little bit more into operating leverage. You highlighted a bunch of different things you're doing to try to get growth. That 13% return on equity, where are you kind of thinking the operating leverage is going to be at the company at 13%? And where do you think a comfortable good level to be is for the general insurance business, so premium to capital levels?

Keith, do you want to take that?

Yes, I think we can get to onetime. I mean obviously, it's business mix-dependent. You see a lot of -- original companies can run much higher than that. It's not a perfect metric. There's a lot that goes into that. It's a simplistic metric just to compare across companies. But I think if you see some of the longer-tail companies, you can get to one time, and I think that we'd be very comfortable in that range. And you clearly see we have a lot of excess capital within our insurance subs. We're well capitalized within our insurance subs.

Brian, you didn't ask this question, but somebody else will or somebody will want to. For M&A, if we look at M&A, we think we're going to be incredibly disciplined. We know we will be. We have a criteria. Think there's going to be opportunities. And expect over a period of time -- like today is a moment in time, but over a period of time, I think we'll be able to acquire something. It will be additive to earnings and accretive to ROE and we move forward. If we don't, because with our discipline, it doesn't meet our criteria, over a period of time, not to be defined, and we still have excess capital, we'll return that. I mean so like we're not going to hold on to capital forever if we have too much capital relative to the size of business we are. That's not our preference. I don't think it will be the base case. But over time, if that happens, we'll lower the equity. That will obviously boost ROE, won't be for that reason. It will be that we don't want to hold on to excess capital for an indefinite period of time.

That actually was going to be my follow-up. But maybe going, adding on to that a little bit, Peter, maybe you can talk a little bit about what areas do you think M&A makes sense from a business perspective. You talked about scale, culture, competencies. You don't have -- small commercial, was that an area at E&S that kind of make sense to you all? Other areas that kind of make sense? How do we think about M&A and kind of areas you want to potentially add to?

Look, it's harder in an insurance company than it is on a broker. A broker will decide where you want to go and you find assets and then you try to embrace them into a company and a system. Have to make sure -- the criteria, I said it was like third or fourth, is really important, which is a good underwriting company, good underwriting culture means probably got a good balance sheet. And so like we don't want to have to drive company to turn it around. But still it's a big world. I mean, there's a lot of opportunities for product enhancement on what we already have. You mentioned small commercial. I don't know that we have to have it. You saw the breakout of North America and International, we already have a very good small commercial and medium portfolio. But it would be good to add to that. I mean I think it would be a good ballast. There's a lot of places in the world. I would lean more towards International, not to say we wouldn't do something in the U.S. But it has to be something that would not require a lot of integration, very committed to the financial metrics, product enhancement, geographic enhancement or something. I don't know that we need to add something to like Lexington, we could. But where we already have scaled that will accelerate our path is very interesting. The other one, not to make everything about AI, is that companies that don't have scale or expertise are not going to be able to do it. They're just not. It's just going to take too much time. You play catch-up. So if there's opportunities in the future that a company can come in, we can integrate it and adopt the work that we've done, there could be significant accelerated growth, that's going to be something we look at as well.

Next question from Wes Carmichael from Autonomous.

Wes Carmichael from Autonomous Research. On the 20% EPS CAGR, I know we can't measure the boxes there, but if we think about 2025, we've had the California fires early, should we expect that to be a little more back-end loaded '26 and '27 when you get maybe above 20%, with expenses coming online as well?

I wouldn't think of it that way. I mean I don't know what's going to happen. It's March. We've got a long way to go in the year. But the wildfires for us will not be an inhibitor in terms of driving the EPS expectations that we've outlined. So I wouldn't think of it that way.

And I understand most of the levers on ROE. I guess one on tax efficiencies. Is there anything incremental? I realize maybe you're earning a little more and maybe utilizing the DTA a little bit more. But anything else there?

No, I wouldn't. It's a lot of incremental. There's a lot of things we can do better. I think as we've turned the underwriting strategy around, we have an opportunity, I think, with the tax strategy to just do better blocking and tackling. The DTA is certainly a part of that. But yes, I'm not going to go much beyond that.

We'll have a Q&A later, but we have time for one more question, Andrew Kligerman from TD Cowen.

Great. sounds very impressive the work you're doing with Palantir and Anthropic at Lexington, and you talked about 20% growth. My question for you is, versus your peer group, are they doing similar things? And if they are, how can you be confident you'll grow?

The short answer is I don't know what they're doing. I don't think they are. I mean when they go on to earnings calls or my just general observations is like there's 300 instances, it's operations, it all sounds all interesting, but nobody that I'm aware of is doing end to end in terms of what we're doing with AI. And I'm not particularly concerned, honestly, with what they're doing. I just know the path that we're on. I'm convinced it's the right path. I've seen some of the things that we've done early days, and this is not hypothetical, it's real. And this is the way we're going to drive scaling our business. And whether -- I would expect that's the environment we're going to be in, in the future. I don't believe we'll be by ourselves. But we're going to be a trailblazer in terms of driving industry standards.

And Keith, you talked a little bit about how actuarial and claims and underwriting talks to one another. Is there something structural at AIG that kind of institutionalizes that? Or is it just more of them talking to one another?

I think it's, culturally, as the re-underwriting took place, it was, I think, as Peter said, it had to happen. And so I think that accountability from the leadership that came in, the way we drive it, internal and external reviews, there's a lot of robust engagement back and forth. So it's more, I think, the necessity out of it and culturally the way the underwriting change, and that's been part of the reserving process as well.

I think Quentin is supposed to say we're going to take a 15-minute break, right?

Take a 15-minute break and be right back.

Ladies and gentlemen, there will now be a 15-minute break. Thank you. [Break]

All right. Welcome back. I hope the break was great. Okay. We've got a great panel discussion today with 3 of our business leaders. They need no introduction, but I'll do that just in case. Jon Hancock, who is the CEO of our International Global Commercial and our Global Personal Insurance; Don Bailey, CEO North America; and Charlie Fry, who's Global Head of Reinsurance and Portfolio Optimization. So guys, looking forward to it. Jon, let me start with you. We talk a lot about our global specialty business. It's performed exceptionally well. I talked about that earlier. Why is the specialty business unique and really valuable to AIG? And why do you consider as an industry leader?

Okay. Thanks, Peter. It's great to be here with everybody. First off, Global Specialty, everybody defines specialty in their own way. So to be clear, specialty to us, it's marine, it's energy, it's aviation and it's our credit business. And you can see from this slide, we've got scale and we've got fantastic performance in every single one of those businesses. And we've got a very, very big specialty business, $5.6 billion of premiums. But you're right, I mean we're big. But yes, I think we're the leaders, I think we're the best. Why do I think like that? Well, I start with financial performance. Combined ratios around 76% average for the last 5 years, whilst we've been growing our business 40%, yes, whilst our customers like us. We renew more than 90% of this business. We're writing more than $700 million of new business every year. This is a really, really strong business. And that strength, that size, that gives us influence. We're an influential player in this marketplace, which means -- this is a complex business. This is a business where you need to know the industries and need to know your clients. And we are influential, we're the standard setters, we're the rate setters. We're not just the followers here. And that makes a big difference to this business. And it's something we've built up over decades. It's a real differentiator for us that we spent decades building our reputation, our portfolio. And it's impossible to replicate that overnight, either the portfolio or the expertise. And it's also a place we're big, we're great at this, there's also lots and lots of opportunities. I talk a lot about marine and energy where we have clear leadership positions, but those are growing sectors, growing industry, lots of room to keep growing all over the world. But beyond that, in our aviation and credit, and all the specialty lines, we have got huge expertise around all of those. And it's recognized. And because of that expertise, we attract the best talent in the industry. Align that with, sorry, those financial results, that gives us, with that expertise we've got, that gives us the confidence to keep growing this business. Those combined ratios are not one-off. Those are 5-year averages. We do that year in and year out. It's a terrific business with lots more to come.

This will feel like a throwaway line, but I think it's really important, is maybe just talk about the structure. Because like we run global specialty as a global business. It's not like divided by territories. Gordon runs the global business.

Yes. So we do. We run it globally. And there's good reason for that. So that expertise, that capability, if you try to build that everywhere, that's crazy. You can't build that depth of expertise everywhere. What you can do is do it centrally and then deploy it through our hubs, which is what we do. We're headquartered in London, which is the heart of the specialty market. But then we use hubs strategically placed all over the world so that we can use an expertise, deploy it locally close to our customers where we've got big knowledge of.

That's great. I'll come back to you in a second. I'm going to go to Don here. Similar, Don, we talk a lot about the Lexington, E&S growth. Again, that's something else I mentioned in my prepared remarks. But we have other businesses. So can you share a little bit about our larger commercial businesses, how important they are, how they performed and their relevance?

Yes. Well, all of the work you highlighted in your early comments, Peter, have delivered us in North America just a large scale, very healthy, highly diversified portfolio. And we would say it's a portfolio, that gives us great competitive advantage in the marketplace. We can be very thoughtful about where and how we're growing our business. But there's 3 large commercial retail businesses that we operate in. We've got casualty, we've got financial lines, and we've got property. On the casualty business, you made a few comments on it earlier. It's a very healthy, it's a very resilient business that we've got. Through all of these, our ability to lead, and excess is another strategic and competitive advantage. But the casualty portfolio is, it's strong, it's resilient. And it's such that we're able to be on the offensive in the marketplace right now with a lot of the disruption that's playing out in the market, particularly in excess. We can be very thoughtful about the opportunities that we're pursuing. In the financial lines space, very much our brand in North America, you think about financial lines, probably D&O in particular when you think about us, but that D&O is highly diversified. And again, it's primary in excess. And so we've been able to be very effective in strategically deploying our limits and our attachment points in the financial lines space to drive profitable growth. And then in property, which is, in many ways, a very interesting conversation right now as well, with all of the rate swings that we're seeing and the risk dynamics that are playing out, we've been very nimble with our property capacity, and be able to deploy that in ways that drives profitability for us in both retail and in wholesale regardless of the market. The opportunity, Peter, if I could just add this on to the commentary, is about how we sell and distribute those assets even more effectively. Like that's the name of the game for us. I spent, as many of you probably know, a lot of my career on the broker side, and I got to see a lot of carrier distribution models and face off with those. I ran global sales for Marsh, I was head of Willis North America. So I was in those markets dealing with those carriers every day. And overall, I would say those distribution models were fairly low value. They were tended to be very internally focused, very product focused, very geography-based and didn't drive a lot of value for me as a broker or my clients. So when I got to AIG almost 2.5 years ago, spent a lot of time just thinking about distribution model as an asset to the organization. So we've created a unique model for us where everybody in AIG distribution is part of the national broker team or a national client team, where the focus and intensity is on the external stakeholder, the broker or the client. It works for us because we've got density in our brokers from a retail and a wholesale standpoint. But in retail, 83% of our premium volume is with 10 brokers. So it allows us to be very intentional about the growth that we're driving and the alignment that we're driving with them. Our share of wallet with those top 10 is only 2% to 7%. So we can double the size of our business within each of those. So alignment is driven with this model. Deployment of target account programs is driven. And we're able to much more thoughtfully use data to drive clear and unprecedented opportunity. So the model works. You can see it in the new business, you can see it on the top line, and we're excited about where we go forward.

Did you like your boss at Marsh?

I was -- I learned a lot.

Good answer. I think your ability to have fine-tune this distribution approach, I mean, again, it's things that sound very simple, but companies tend to be unorganized. So having an organized approach to risk by using data, I mean, like you've seen it in the numbers, but I mean, do you feel like you have more momentum now as you start to execute on this?

Yes. We have been -- the data part that you just referenced there, Peter, has been a huge part of it. We spent the last couple of years, been working with Claude and his team, in building broker and client insights that we just never had before, that I can just, at the tap of an iPad, see exactly what the trading relationship is with broker, and that accountability drives value totally.\

Thank you, Don. Charlie, I talked a lot about property cat from '17 to '25. For those who don't know, Charlie was the first hire that I made at AIG, and he thanks me all the time for that. But can you just take us through -- I outlined the differences in structures, like in philosophy, but what are really the fundamental differences from a reinsurance structure in '17 to today? Because we've talked about that long-term journey, but just maybe you can connect the dots for our audience today?

Yes, sure. And I think the starting point, we're talking a period of time where there's been $1.1 trillion of natural catastrophe losses to the industry. So it's certainly a significant level of activity. And you in your remarks earlier, you talked about the philosophy we have in every decision we make when it comes to purchasing reinsurance. You got '17 when we arrived here, there was none. And if I was going to describe the strategy, it was, well, it was sporadic, it was opportunistic, it was decentralized. So essentially, there wasn't one. And there was nothing like the in-depth data and analytics that we would utilize to be able to make informed decision-making. Now I think if you compare the 2017 cat structure to the one today in 2025, it's the epitome of having a lack of that strategy. So we had very high retentions. We -- single shot, which you mentioned, so therefore, one event and one event only. And in some places, we didn't buy at all. So if you look at the North America as an example, so the company attached at $1.5 billion, had one limit, one limit only. Now for context, that was a year there were 17 named storms in the hurricane season. Ten of those were catastrophes, 6 of those were major catastrophes. And then you think 3 of those made landfall in the United States within the space of a month. So we saw in the earlier numbers that it was a heavy cat year for AIG, but it wouldn't have taken much and it could potentially have been significantly worse. You then turn into Japan, we have a sizable business, under Jon in Japan, and what was doing in '17 for me, it was the epitome of the problems with decentralized buying. So we had a personal lines business and the commercial lines business, and they rolled up into different people. So they bought separately. But of course, the businesses are subject to the same perils. We end up with 2 retentions. And again, you only had to roll forward to 2019, 2 of the 4 largest typhoons in history in terms of losses hit Japan. Could have been a very, very different story for AIG had we perpetuated that buying philosophy. And then you touched on it, I mean, we've got this incredible footprint and it seems surprising to me that the decision was made not to buy internationally. And again, you don't need to go back too far in time to think through to double-digit billion-dollar events in terms of tide floods, Christchurch earthquake. So that takes you forward to 2025, we've got low appropriate retentions across our business, with reinstatable limit. So Japan -- North America Commercial is $500 million; Japan, $200 million, but that's 1 retention to be clear. And of course, we buy for the rest of the world, and you've talked about that. There's another important part of our structure, which is our aggregate cover. And I don't think our aggregate is comparable to when you hear others talk about aggregates in the reinsurance market. A lot of discussion around aggregates. What they really mean is high attaching, so dealing with a series of extreme tail events. With ours, it's much more focused around frequency. And you think, there was a question earlier about the wildfires, obviously, tragic event. But within our North American attachment for the aggregate, there's a sublimit for secondary perils of $450 million. So you've got to see, given what's happened, a sizable amount of that aggregate is already eroded. So we're really happy with where we are today.

Does it aggravate you as much as it aggregates me with like in terms of how our aggregates compared to others? I mean, like it's like nothing else in the industry. I just think one more click-down like we were talking about.

Yes. I mean it's sort of American English and English English. We both talk about football and there's some comparisons. But fundamentally, they're 2 completely different games. Look, when we think about our aggregate, we don't think about it as stand-alone. We think about it as part of our overall buying strategy. So if you think what we've got, we've got really strong protection in first event, second event, third event. And that's how we'd go about buying, rather than let's see what happens towards the end of the -- put it this way, I'm very happy where we are.

Yes, me too. Let's transition to the SPV that we just launched and announced really innovative, something we've been working on for quite some time. Can you provide a little bit more detail what is it, what's its purpose and why we think it's a foundation for the future?

Yes, absolutely. Look, we're extremely proud of what we've done here. We collaborated with Blackstone in what we believe to be a truly innovative, actually, first of its kind, some of the features of this vehicle. What we've essentially done is we created a brand-new reinsurer, but it's a reinsurer that's exclusive to AIG. Now again, a little bit of context. It's the second largest new syndicate in the history of Lloyd's, and it's one of the most sizable capital raises for reinsurance since the class of 2005 and 2006 and KRW. And it really involved a lot of strong collaboration across all of our business. Now if you think through, as I said, it's long-term, exclusive reinsurance to AIG, backed by absolutely first-rate capital and a first-rate partner. But it also provides us with access to some fee income, which is highly accretive in terms of capital base. You then go a little bit further and you think for them, they're going to access to the vast majority of the treaties, a sizable share of our out with reinsurance, because, of course, it gives them access to the platform that Jon and Don run, that we talked about, which is I think it's an incredible platform in terms of our ability to originate risk. And I think that's what's so exciting for me about the SPV, it's fantastic what we've achieved, but it's where we can go which I really feel excited about, this ability to originate risk and, in actual fact, match the risk and optimize portfolios to the most efficient capital available, of course, being our balance sheet, but also third-party capital. So we retain the balance within our own business, but also have the opportunity to generate sizable fee income into the future. So, I think it's really, really exciting.

Is that 30,000 a typo, or is that real? It's just modeling?

It is -- there's an astonishing amount of work that goes into it. Yes. And of course, it's -- why is it -- it's foundational, right? So what we're looking at, we're looking at the entire portfolio of AIG. And we're talking -- you highlight, and the guys have highlighted, the amount of change the company has been through. So it's not just looking at the data, it's looking at the trends, applying macro trends in terms of what we think inflation will happen, climate change, social inflation, but also looking at the underwriting changes we both made but plan to make into the future. The good news is with that foundational modeling done, it gives -- we don't need to do it again repeatedly to continue to build.

But I think what I wanted to draw, Charlie, which is exactly what you just said, is that what I talked about with AI before, the work is done on the portfolio optimization. We need to update it. There's different factors, like you said, it's an ongoing model. But we're not building something else. The SPV was a portion of that portfolio work, but the foundational work has been done for us to be able to leverage.

Listen, 100%. And I think we're going to -- you've talked about it in the next session coming up and used the word turbocharge for the business. And it turbocharges our ability to develop these structures as well. Super exciting.

It is very exciting. Thank you. Jon, let's talk about Lloyd's Talbot. You personally, AIG, have a very special relationship with Lloyd's. And why is having a syndicate matter? Why does it give you advantages in underwriting? And maybe you can just bring it back in terms of from your perspective having had very senior roles in Lloyd's, like why we're performing really well?

Okay. Yes. I mean, it is a really important complement to our other distribution and our other access to risk. And we do have a special relationship. Me personally, lots of you will know, before AIG, I was the Performance Management Director at Lloyd's. So that gave me a -- yes, effectively, that means I run underwriting across Lloyd's, and that gave me a real rare insight into the market. And I think if I may, just step back. I know some people will know this, but I'm not sure everyone knows, but what is Lloyd's? Firstly, it's not an insurance company, and I think that's really important to understand. It's a marketplace. It's a $72 billion marketplace. It's made up of 55 managing agents, about 100 syndicates who all trade with, compete against each other, but are also held together with a mutual interest to the Central Guarantee Fund. And that's what makes the market really unique. At the middle, you've got the Society of Lloyd's. It regulates the market. But more than that, it sets the standards. It sets the underwriting discipline. It upholds the reputation as well. So it's a real glue that holds the thing together. And we have a really strong position at Lloyd's through Talbot, which is an outstanding managing agency there. Currently 3 syndicates, 2019 and 2478 the SPV that Charlie has just talked about, gives us the opportunity to deploy our capital differently or manage third-party capital to support the AIG portfolio. And that's a terrific benefit for us. And then Syndicate 1183, which is our trading syndicate at Lloyd's, is one of the leading syndicates at Lloyd's. And yes, I said it earlier, I do have that rare insight. My role at Lloyd's meant I got to look at every syndicate what they do, how they do it, how they perform? I really do know what good looks like at Lloyd's, and Talbot really is a very good syndicate. Look at its results, combined ratio is below 80, 10% CAGR, and still plenty of room through. We are recognized leaders in the number of specialty classes that we really like. Combining, for us, having that presence at Lloyd's with the power and the reach of AIG behind it, not just the balance sheet, but the expertise, the capability, how can we deploy all of that around the world? It's a huge advantage for us around the world. And we use it. It's a really critical part. And then we were talking about specialty earlier. We have a really unique franchise in the U.K. We have a U.K. AIG platform. We have our Talbot at Lloyd's platform. We have a global specialty headquarter there. We've got our multinational. Using all of those 4 together is phenomenal. The reach, the distribution, the advantage it gives us is not to be underestimated.

And you still buy into -- it still sees the world's risk. It's like the only place in the world that has access to all the risk across the world. If you have stamp capacity, if you have the risk appetite, you can find the distribution into Lloyd's.

Yes. It's -- I mean the talent pool of specialty underwriters and claims in that marketplace is like nowhere else. The pool of specialist brokers there, and there's reasons, some of which I fully understand, some of which I don't because I think they're traditional emotion actually. Specialty risk finds its way to Lloyd's. It's specialty risk and the type of client that we love, that -- whether we write it in specialty, whether we write it on the Talbot platform, it gives us access to risk that we would not otherwise get, and at a really efficient way as well.

I think that, with our scale, underwriting expertise, gives us real advantages.

Absolutely. Yes.

Thanks, Jon. Don, let's go back to North America, and let's talk about Glatfelter programs. It always just isn't sometimes large enough for us to get out on earnings calls, but it's a really important part of business. We acquired Glatfelter in '18, totally overhauled our program business. Can you provide a little bit of insight how you think about that business, how it's changed and how we should think about it?

Yes. When you -- and you touched on this, again, your comments earlier, Peter, but when you think about AIG in North America, you think about the brand being large, complex, global risk, and I think it does surprise people when you put up on the slide that there is a split there between what we do in large commercial versus middle market and small commercial. So the -- with Lex, with Glatfelter with AIG programs, we are very strong players in North America in the middle market and small commercial space. Glatfelter and AIG programs themselves are about 14% of our net portfolio overall. And the average premium in each of those 2 businesses is $20,000. So you can see where we play in that space. Glatfelter, 2018 acquisition, stable, incredibly stable, well performing, very consistent, 75-year-old organization. It's an owned MGA model. And the basic model is that they deliver what now are very long-term, well-established programs through long-term, well-established distribution partners. They tend to be multi-line programs into what we call 4 like community-based verticals, and that works for us. And they've been very successful over the course of many, many years. AIG programs, also programs technically, but a different story, a different journey, much more of an overhaul story in terms of that journey. There are risk class issues, historically. There were distribution issues historically in that business. But what we did was took a lot of the best practices and the standards of Glatfelter and applied them to AIG programs. And as we sit here today, that portfolio at AIG programs is very strong and poised for significant additional growth. It's a third-party DUA model. So it's a bit of a different model, delegated underwriting authority. We tend to work with highly resourced program administrators who have expertise in underwriting or specialty technology, that we find very effective and very efficient. So that journey has been one of how we actually do more programs with fewer partners. So 5 years ago, we had 24 programs with 18 partners. And as we sit here today, we've got 30 programs with only 13 partners. So we're making that journey, and it's working. It's a strong business for us going forward. With the 2 of those businesses, Peter, what we have is rate retention stability, which is very powerful in our portfolio. We've got strong diversification, as we talked about, in terms of product channel and segment. And we've got a very predictable growth engine, which is attractive for us being a part of the portfolio. So we're very excited about that segment of our business overall and the profitable growth prospects of both Glatfelter and AIG programs.

It's a great story. Glatfelter came in, set the standards what we do with programs. You re-haul basically the underwriting strategy to sort of mirror that, and they both elevate at the same time. And I think it's just a tremendous outcome. It's really well done.

Yes. And we're -- coming back to the first question, we're able to be thoughtful in terms of how we're distributing those programs in the marketplace and being very synergistic in how we're doing that.

It's very disciplined. All right, we have one more question. Jon, I'm going to go to Global Personal. I think I recall the conversation is like, congratulations you're promoted, and not going to give guidance on Investor Day that you're going to deliver 500 basis points or more of profitability improvement.

Yes, I remember that.

Yes. Me too. But maybe just take us through -- I had mentioned in my prepared remarks, it's a really good business. We like it. There's a lot of great aspects to it. And why you're confident we can actually deliver what we've outlined over a 3-year journey.

Okay. And thank you again, Peter. Yes. I mean, you said it earlier, right? I mean, so firstly, I do like this business, let's be clear. You said it earlier, we've got all the components of a really good business here. We just need it to perform better, and we're all promising, not just you and me, the whole organization is behind this, it will perform better. And when we look at this, this is a new global segment. It's a different portfolios at different stages of evolution and different stages of performance. And we see opportunities to improve everywhere, which is great. But we also see some portfolios that are performing terrifically. We just need to turn the dial up and get even more of that. And part of our improvement, yes, it's fixing the bad, but it's doing more of the good as well. If you look at the portfolio, it's high net worth, well talked about. We're on a multiyear improvement journey. We're starting to see the results of that come through. There's still a long way to go, and we're committed to do it. A&H. Yes? A&H is a brilliant business. It combines every year less than 90%. We just need to do more of it, and we'll do more. And you look at warranty, across auto and home, there's a whole mix of portfolios there. Some doing well, some doing not well. Some need remediating, some need scale actually to build them up into something meaningful. And we recognize that and there's actions everywhere. And as we pull it together, we've now got a global operating model for this. And this shows us, yes, they are different businesses, but there's a lot of common themes that run through those where we can improve them. And through growth, through loss ratio, through expense ratio. And growth for just like A&H, it's almost like an annuity. It's so predictable. It's low volatility, it's short tail, fixed limit products. It's -- we do it really well. We just need to really grow it more. And that's where we're focused. Within high net worth, focusing on E&S, which performs much better, and growing that, outpacing the rest. And we're already doing that, 26% growth last year on it. Loss ratios again, so I'll go to high net worth. Again, rating above trend still. Changing the business mix, not just through E&S, through other things. Auto and home, exactly the same levers, through rate, through forcing that business mix change. So all of those actions recognized and underway. And then expenses through our GOE, you and Keith have talked a lot about what we're doing on our expenses, that applies here as well. And I think we can turbocharge that here. But acquisition costs are a big part of our expenses as well. And we paid too much in some places. And we've already renegotiated the terms of PCS. We'll start to see that through. We're doing that across the portfolios everywhere. So those common themes, that laser focus by bringing it together globally, maximizing the good stuff as well as fixing the not so good stuff, that's what gives me.\.

That's really helpful context, and we're very focused on repositioning this business for more long-term profitability.

Yes. Absolutely.

Okay. Great discussion. Thank you, gentlemen, for giving us a little bit more detail. They'll be back up when we do Q&A in the final panel, and we can dig in even deeper if we like. In the meantime, thank you very much. Please join me in thanking Jon, Don and Charlie. I would like to welcome Claude Wade to the stage. Claude is our Chief Digital Officer, Global Head of Operations and Claims.

Good morning. I'm pretty sure I have the longest title in insurance. You can just call me And, as things keep getting logged on. So I'm excited to walk you through how AIG is building for the future. You heard Peter, Jon, Don and Charlie just talk about our growth drivers. Now my role is to enable and accelerate that growth through process optimization and also through technology. And it's what everybody is talking about these days, specifically generative AI. Now I want to caution you, this will not be a hype presentation about GenAI. We are not a technology company. What we are is an underwriting and claims company. So what you're going to hear from me is our practical application of modern technology to overcome business challenges and accelerate growth. Now the insurance underwriting process, unfortunately, has remained largely unchanged over the last 50 years or more, and AIG is not immune to those challenges. There are several significant inherent inefficiencies that exist that challenge scaled growth. The lack of data standards is the one that has to jump out at you. The insurance industry is one of the few within financial services that doesn't have a national regulator, and therefore, there are no agreed-upon data standards, which leads to extreme data heterogeneity across our broker partners and results in expensive and error-prone manual data industry. Now this issue gets further exacerbated by inconsistent data exchange formats, PDFs which traps data, nonstandard Excel files, and even our legacy technologies are hard to get data out of. Now, however, even as we leverage modern technology to overcome these challenges, our complex business underwriting relies on human expertise and experience, and that's the AIG underwriter. So we set out to leverage technology to turbocharge our highly-experienced knowledge workers, not to replace them with technology. In today's process, brokers send in submissions, which are a compendium of documents that provide underlying facts about the insured organization. The examples include the application, statements of value, property locations, to name a few of the documents that we get. Now we have an army of people that take those nonstandard documents and go through them looking for the 100 or so data elements that our underwriters need to assess the exposure against our risk appetite, our underwriting guidelines, and then to price the coverage appropriately. The underwriter then needs to query our internal systems, looking for history with that client, claims history and the like. And finally, depending on the business, we may need to go externally into a third-party search for relevant data about the business. So as you can imagine, this is a highly manual and error-prone process that, on average across our businesses, takes 3 to 4 weeks to complete a submission. The results are substandard data quality, inconsistent assessments of risk, and unfortunately, as Peter mentioned earlier, we do not consistently get to every submission we receive. That leaves profitable business on the table. So with those challenges in mind, we launched a generative AI initiative with one single objective: to unlock and accelerate growth at scale to the timely review of every submission we receive. We've taken a disciplined approach to apply GenAI to the underwriting process through 5 key build principles. And I'm going to highlight a few of those build principles. First, we target a single GenAI use case, and this is something that Peter talked about earlier, focused on solving real immediate business challenges, rather than experimenting with GenAI in noncore areas of the firm. Second, we co-created the solution with our business teams. This isn't just an IT or data science project. We convened an underwriter council, and then we co-located them with our digital teams. So we can ensure that the solution we built aligned with real-world workflows. Third, we adopted a human-in-the-loop philosophy. The underwriter is at the core of our business and at the core of our GenAI strategy. We sell to turbocharge the underwriter, our knowledge workers, not to replace them. Our goal is to enhance their human expertise. So fourth, we adopted an agentic modular architecture, to both easily integrate and adopt new technology solutions because this is a quickly developing technology space. And we were able to capitalize on the AIG 200 investments Peter mentioned earlier, in data, cloud modernization, to accelerate and build our foundation. And this foundation will help us continue to rapidly evolve GenAI as the regulatory and technology landscape changes over time. And lastly, our investment in these new tools are measured against predefined data metrics. So earlier this year, we proudly launched an industry-first end-to-end underwriting assistance. Executing on our idea, our concept, to full deployment in about 10 months. AIG Underwriter Assistance is in production in financial lines in our private and not-for-profit business. With Underwriter Assistance, we've eliminated the underwriters' busy work. They now arrive at their desk to find each submission has been ingested, augmented and prioritized. All the pertinent data, unstructured qualitative data from those submissions that I talked about earlier, and the structured data from our relevant internal sources are all immediately available in a curated summary, ready for them to begin underwriting. At the heart of Underwriter -- of AIG Underwriter Assistance are 3 key capabilities operating at scale: ingestion, augmentation and prioritization. For ingestion, we use large language model powered document classification to identify and categorize the submission documents like application, financial statements and loss histories. And we do that consistently at an accuracy level of 97% using the models. Then using data extraction tools, we capture the specific data points such as revenue, number of employees or physical location. This leverages very context-specific language models like Anthropic Claude 3.5 and Palantir AIP. Next, we augment the data with our own internal data, such as our policy and claims history, and then with third-party data and external research from trusted sources like Dun & Bradstreet and PitchBook. Finally, it's prioritization. We apply AI and machine learning to estimate the propensity to bind. And what that means is it's ranking the submissions by their likelihood to convert from quote to policy. This allows us to direct the underwriter time to where it's most likely to generate profitable business and to align with our broader portfolio strategy you heard Peter describe earlier. Together, with these 3 capabilities, ingestion, augmentation and prioritization, they address the biggest hurdles in the underwriting process: data heterogeneity, manual data entry, time-intensive manual reviews, and inconsistent risk assessment. AIG Underwriter Assistance is live in production, North America private and nonprofit business, and has reduced the underwriting time line from 3 to 4 weeks per submission to less than 1 day. And with that extra capacity, we are now reviewing 100% of every submission that comes into our business without the need to add additional underwriting capacity. Data quality has increased from our manually input data to over 90% where we're leveraging Underwriter Assistance. And most importantly, most importantly, our buying to submit ratio has increased from 15% to 20% in this business. So it's fueling organic growth without the need to increase submission flow. We're now rolling out Underwriter Assistance to North America, all business lines and international, with a target date of December of 2026. So why should you care about this? Well, as Peter mentioned earlier, Underwriter Assistance will accelerate organic profitable growth, both within our current submission flow and as submission flows increase over time, giving the underwriters more capacity, 2x, 5x, as Peter described earlier. Now AIG Underwriter Assistance goes far beyond underwriting. The 3 underlying capabilities of ingestion, augmentation and prioritization powered by the agentic ecosystem I described earlier are applicable to another key part of our business, and that's claims adjudication. Later this year, we'll be launching AIG Claims Assistance, which leverages the capabilities that we built in Underwriter Assistance to accelerate claims adjudication and payments, improve claim outcomes and fraud and improve the client experience, all designed with our philosophy of human in the loop, turbocharging our claims knowledge workers and not replacing them. Now in addition to helping enable AIG's growth agenda, these products have a profound impact on our stakeholders. For our customers, they're going to receive multiple benefits, better accuracy in their policy and data coverages, more accurate rating and pricing in their specific risks, and both improved responsiveness in both underwriting and claims. Our distribution partners don't have to change the way they interact with AIG, and yet they'll have a greatly improved experience. We can meet them where they are on their own digital journeys. They'll get a response on all of our submissions quickly, thus seeing a near real-time transparent view of our risk appetite. And they'll receive faster responses and more consistent underwriting decisions and pricing, thus translating to a more productive relationship. And finally, our employees. Our employees will do less of the work they don't want to do, such as data wrangling, reading through hundreds of document pages, and do more of what they want to do, such as analyzing risk, engaging with our broker partners and simply doing the work that they were hired to do. This is a win for all of our stakeholders. Our agentic ecosystem approach to designing AIG Underwriter and Claims Assistance has resulted in 3 key strategic advantages. Let's get on the right slide here. There you go. One, we now have componentized our architecture so that we can evolve alongside any new AI technology as they come into the market. Two, we have an architecture that will rapidly scale to new lines of business, products and geographies. And three, we've assimilated a best-in-class solution for our unique challenges across the data, orchestration and the application layers of our architecture. So Peter mentioned this earlier, so I want to take a few minutes on this one. We've all heard about some of the known challenges of large language models. Even powerful models like Claude 3.5 can produce inaccurate, outdated or fabricated information, often called hallucinations. And they can struggle to cite exactly where the source of the information provided or how the answer was derived. We've designed and implemented multiple patented technologies and a custom RAG framework to deal with these challenges. So what's a RAG framework? It's an acronym. It stands for retrieval augmented generation. It's designed to help large language models improve the accuracy of their responses. So let me break it down: retrieval, the process of finding and extracting relevant information from an external knowledge base; augmented, the large language model, the knowledge is enriched by the newly retrieved data, thus enhancing the model's overall context; and then finally, generation, the large language model then produces an answer based on its internal knowledge and the newly retrieved information. So let me bring it to life by walking through a real example. So let's say, Underwriter Assistance is looking for clients' total 2024 revenue, which is one of the 100 or so data fields that we need for underwriting. In our RAG framework, we would generate a prompt and a query for total revenue and then send both to our corpus of underwriting and operational knowledge. The query then returns the relevant context, in this case, the 2024 income statement, thereby limiting the vectors the large language model can actually search for the answer. Next, we send both the prompt and the relevant context to the large language model. The large language model then generates a response, including the source document chunk from which the 2024 revenue was found, which has been reviewed, confirmed or corrected by our underwriter or, as we call them, the human in the loop. This approach substantially minimizes hallucinations by limiting the source context for the large language model, but it also drives better efficiency in terms of response time and token costs because we're only sending the most relevant data and context to the large language model. And as a core design principle, the human in the loop has to validate the response and determine the next best underwriting action. I started my presentation by saying we're not a technology company. We are an underwriting and claims company. And to create Underwriter Assistance and Claims Assistance, we built an agentic ecosystem of best-in-class technology capabilities. Anthropic Claude 3.5 is our large language model. Palantir Foundry AIP supports our overall orchestration, prompting, data layer and governance. And it all sits on AWS Bedrock and the AWS Cloud. This agentic approach gives us the flexibility to adapt to the rapidly evolving landscape with minimal effort. So as the technologies and regulations evolve, we can integrate to this new capability really easily. We're extremely excited about Underwriter Assistance and Claims Assistance and the solutions we've built to enable and accelerate growth, but we're equally excited about the ecosystem partners that we've assembled. These partnerships will ensure that AIG remains a leader in AI-powered underwriting claims and processing into the future. So with that, I'd like to invite AIG Chairman and CEO, Peter Zaffino, back to the stage and also invite a few special guests: Anthropic CEO, Dario Amodei; Palantir CEO, Dr. Alex Karp, to join Peter on stage to discuss how generative AI is transforming the future of insurance underwriting and claims in a segment moderated by distinguished CNBC anchor, Sara Eisen.

It's a pleasure. I can't believe you're willing to be seen in public with us.

Sara is going to control everything.

Sorry, I didn't want to roll down the stairs, so I had to go do a little flip. I'm excited to be here today. And I met Peter a few months ago, maybe, I went up to see him. And after speaking to him at length, I realized this is a very different company than the AIG that I remember and that we've covered for many years. And then when he called me and said, I have Alex Karp and Dario Amodei coming, I thought not only is this a different company, this is a really cool company. So thank you for having me here today. Peter, I mean, like how did you get all this together? And how much are you focused on gen AI and your business with these two these days?

Well, as Claude said in his presentation, they've become very important partners. I'll start with Alex, from 5 years ago, we were exploring -- he will explain it better than me, but we were trying to explore how do we extract data, here's our broader strategy, and we just regularly continue to evolve together as partners. And you never know, The World Economic Forum actually was -- I mentioned this earlier in my comments, like some meetings are good, some are not. My meeting with Dario was like unbelievably good. We were talking about the same things. We started to learn more about what he was doing with large language models and just started to align more in the partnership. And I think that both Alex and Dario see what we're doing, see how the strength of the partnership and I gave it a shot, asked them to speak at our Investor Day, and they were both able to do it.

And here they are. I was going to say it was a match in heaven. It doesn't always happen. Alex, so you -- I mean, a lot of people think of Palantir, they think of what you do for the military and for the government. And increasingly, I mean, you've been booming in the world of enterprise. So how does a relationship like this start for you? And how do you think about that?

Well, first of all, I'm honored to be here, a great partner in both cases. And we started -- look, first of all, 5 years ago, when we started talking, the world was very different. Our products were built presupposing large language models, but without their existence. So they were performative if we held them up 5 years ago. But now, done in a very special way, they're transformative. You see it in our numbers in commercial, which is less important, but you see it. What basically I think you've done excruciatingly well, and I think is a cornerstone for U.S. enterprise, which is the only -- basically where the action is, is you've basically said, "I'm going to see if the core parts of my business or the most important part of my business, 'Can you have simultaneous revenue growth and better economics,' meaning lower cost of going to market while having radical growth, and if that's possible, that will change the way in which everyone does business, most importantly, the way I do business." And that, especially given where you started before the curve, took a singular and somewhat prescient focus. And then long story short, there's a famous line from the most famous philosopher that's unknown to most people, Wittgenstein said, to follow rules -- to say you're following a rule is not to follow a rule. And so a lot of people talk about doing these kind of things are the rubric of gen AI. And then there is really having very performant models, which is absolutely crucial. But in reality, the tricky thing about this revolution is a lot of the stuff is not working. So investors are like, "Well, maybe it's not real." But this is really working. And what you're going to see is 4 to 5x growth in the core part of your business with, I believe, half the cost currently.

So it's not just productivity, it's growth, too.

Well, what makes the business strong is, as in Palantir, it's like in software, we're focused on not just growth, but quality of growth. So you have these rules, and that's what they track it. And then the thing I would say to people in this room is this is important to look at, to learn from, because if you do not learn from this, you will see that some enterprises you're invested in do this correctly and the delta is not just on up, it's on the quality of the revenue. And underwriting, and I'll leave it to you, is one of these use cases, which is incredibly difficult to target because you need the underlying data structure to work. So that's a product we have. You need to then manage the large language model and you need a highly performant large language model. But if you do this, you can do -- you can get the 5x output with half the cost. And think about what that means where other people don't do it because they're buying things that don't work. It's really a tale of two cities. We have some other deployments that we can't talk about in government, same thing.

Enter the large language model. So what is it that you do? How are you changing underwriting?

Yes. So looking, I guess, from -- starting from kind of the technical perspective on the generative AI side, right, the technology is already capable of incredible things. There's this huge overhang, much more than is being applied to the economy, right? If we look at something like all the unstructured data that an insurance company has, the models are already very good, can already perform many of the key tasks with reasonably high reliability, and they're getting better every day, every month. But the real trick, the real differentiator, right, is not in the technology as fast as that's improving, but finding ways to deploy it in enterprises, finding ways to revolutionize an existing business. And what we found over the last few months as we've been talking is that AIG has really leaned into this area. They've picked 1 or 2 use cases that they really have conviction in. Like, folks are adopting AI across the enterprise world, but often, it's, "Oh, we're going to try this, we're going to try this, we have a bunch of pilots." They really had conviction on the claims cases and the underwriting cases and have moved quickly to get a lot of this unstructured data in and really, really bet with conviction. They've been using Claude for a while all the way back to Claude 2.1, which I think was late 2023, early 2024, was it? But now things are really ramped up with the new stronger models. And again, the technology can be great, but if there isn't that conviction, if there isn't that will to move quickly and that focus, it doesn't happen. And this is one place where we really have it, and that's why I feel good about the partnership.

How does it change the business of underwriting, Peter?

Well, for us, it's going to be getting us access to data more real time that we just don't have the ability to harness today. So an underwriter, by their very nature, wants to look at as much data as possible to make a good underwriting decision. And where we've started is in the data ingestion is that -- and it comes in from our distribution in so many forms. And so like with what we're doing with Foundry, you can take a PDF and convert it to text. I mean you can take some things that we just weren't able to get to the underwriter for insight. And then with what we're doing with the large language models, you get it a fraction of the time. And so like there was not necessarily early days as much belief and we said to the underwriters, "We'll give you an infinite amount of time, if you'd like." And we did. And within 2 to 3 weeks, I said, "Okay, I have what I need." And they got probably 75% of the data that we had outlined. And then with what we were doing with Palantir and Anthropic, we got 92% of the data in 3 hours. So all of a sudden, there was a shift in a dynamic that is cultural and that we're going to not waste time in underwriting and inputting data, we'll have more data, more insight and better decision-making. So it's going to be profound for us over time.

Are your competitors doing this, too?

I got that question from someone in the audience, I don't think so, but I don't think it much matters. I mean I think this is the way it's going. We talk about the -- both Alex and Dario have conviction in this 3- to 5-year period, almost more than the 12-month. I don't want to speak for them, but we know this is the direction in the way business is going to be conducted and so we are just fully committed, but I don't believe any of our competitors are doing end-to-end like we are.

Alex, what have you learned about deploying your software and your tools, your AI tools, for insurance and financial services more broadly?

Just to reframe what you just said, if you start with a simple statement, can AI outperform a human in what they do in the following way, can AI make 1 human 5 humans? So that's basically if you want to -- and here, the human is doing something very technical. So we talk about underwriting, whatever the use case is, you have an expert who's been trained in understanding not just data, but proxy data. It's very hard to teach people proxy. Like, you guys are all watching this. And you have the people who are -- you're very good at what you do. So you're not just looking at what I say, you're looking at inferences for what it means based on years of experience, right? So it's like that's how you know if what I'm saying is actually going to change your model of their business, right? So like -- and so 5 people say the same thing. One is convincing, one is not, and that's how you make all your money. You can tell the difference. You can hear what people -- so that's de facto what a human, a technical human, is doing. Can the large language model, combined with, what we call, our ontology, make one human 10x more valuable, meaning they have 5x more output at half the time? Okay, so that is actually a crazy hard thing to do because you're going to have to figure out where do you deploy the large language model across the decision tree. It's not one decision, just like I'm making many statements and you're bracketing. That makes sense, that turns the dial, that changes something that's different than what I heard. That is what I've heard before, but because of that, it's commodified, I don't believe it, right? And those are assessments you're making. Underwriters are doing exactly the same thing. So it is a huge milestone if you can actually come in and change the unit economics dramatically. And dramatically is important because there's a huge institutional cost to this. So the question you're going to ask yourself is, okay, I -- or many of you are going to say, I assume they're -- "I believe them, he's a little crazy," whatever. But you're going to de facto. The next question is, is this a commodified way of doing things, right? And what I would tell you is it would be if you actually could do it. And it's going to be very hard to do it because first, you need the CEO who's like, "I'm going to go to core principles. What is the core principle of my business?" Many CEOs do not have the agency to do this. Whether they believe they have the agency to do it or not, they can't do it either constitutionally, intellectually or because they're owned by someone who doesn't give a f***. So then you have somebody who's willing and able to do it. And then you have somebody who's willing to basically talent-spot and say, "Okay, this could work. Let me see it every step if it's working." And people on the other side of this are going to be slow to adopt because they're going to have to get to the other side of the transom and see the results before they're willing to put up with the pain of doing the culturally internal changes. And that is a huge barrier to entry simply because what we're going to be doing together in 6 months is going to be dramatically better than what we're doing now. So it's like you get better and better. Like, the models are already better because we know the use case. Our way of managing the models is dramatically better, and it's not easy to replicate, not easy/I don't want to say impossible, but it's very, very, very hard. You don't believe me on this. They're very basic things like why does America -- why are we both American companies? That doesn't make sense. Like, it's because there's a lot of cultural, tribal and basic ways of doing these things, very hard to replicate.

Do you agree, Dario?

Yes. No, no, I mean, I definitely agree. I think as I said before, I think getting this stuff actually into the enterprise, right, connecting, it's almost like there's this impedance mismatch you have to solve and that we're solving some places faster than others, which is you have this incredible technology, you can do a demo, you can see it's capable of incredible things. But actually plugging it in, actually making the two things connect, I think that has enormous mutual value for both sides, right? You're not just selling electricity, you're not just selling water, you're kind of creating mutual value. I mean one thing I think I saw is, if I look kind of across the enterprise world, there's sort of like, I would call it, the periphery and the core. So I think enterprises are having a lot of success deploying in the periphery that's kind of common across all companies. So all companies need -- they need like customer service, they need internal productivity for their developers. That's the same whether you're in insurance or some other area. So a lot of success there and a lot of aspiration to make progress in the core of what they do. So there would be underwriting for insurance companies. It would be drug development and clinical trial prediction for pharmaceutical companies. It would be the core of what legal companies do. For a company that does trading, it would be kind of trying to figure out the key algorithms. But in many cases, more aspirations.\.

By the way, this is a very important point, and I don't think it should like what -- I'll translate this in my more vulgar language. Lots of companies are doing stuff that don't matter. It does not matter at all. Like, you commoditize largely because a lot of these things are -- I don't want to call fraudulent, but it's like it does not matter for your core business. The impedance mismatch here is really big, and therefore, people don't have the courage to go into the core part of the business and say, "I'm going to change the unit economics of the part of my business that drives the business," because that's really.\.

Is it cultural?

No, because it's technically very hard. I mean there's a longer.\.

The models are capable of it. But just every little detail, particularly in a regulated industry, there are lots of challenges. And you guys are confronting those challenges head-on, which is why we have this conviction that we're going to make it work together.

I think this is like a heavy-duty compliment for you, Peter, that you're getting.

I don't understand it, but great.

But was it a [ tall task ] technically?

I don't think it's just regulated, by the way. I think even if you take that out of the -- it's like there's -- first of all, you have the regulation. Then you have the core security models and the way the data is modeled on the inside. Then you have where do you deploy the model and under what condition. And then you have how do you train the model and to what use case. And each one of those would require a really world-class player. And the minute you don't have one of those things, the whole thing collapses. And people have figured this out, which is why your phones are ringing off the hook for like, "Hey, we can help your call center." It was like, "Yes, we can make your call center 20% better." That's great. That does not change your business.

So how did you do it? So how big of a lift was it, either culturally, technically, all these challenges that other CEOs have?

Well, it's been a significant lift over time. But what we did several years ago, not knowing we'd be here today and talking about large language models or how we ingest data differently, is just getting foundational end-to-end process, which the company did not have built and get single definitions of data. So for us, we were committed to changing our company, and that took a lot of will. But once we started to get there and introduce new ways of doing business -- there's always reluctancy in big companies, there's always -- I mean I say you have to bring an industrial weed-whacker to work every day. Like, I mean if you don't beat back the weeds, like it's going to take the house over. So we kept pushing. We didn't roll it out to the whole company because we weren't looking for buying. What we were looking for is learnings. And so I think working together and seeing what was possible and how that worked for us in the business that we were in became really aspirational. And we just made that commitment, made the conviction and we've been enormously pleased with the progress that we've made. And I think the future is even brighter.

Dario, a question on Anthropic and Claude. Why Claude? Why is that uniquely positioned for doing these underwriting tasks? What's the edge with using you over OpenAI or Gemini or any of these others?

Yes, a few things. So one is I think we have the best models overall, right? There's some general factor of model ability and intelligence. And Claude models are arguably the best on that axis. I mean people release models all the time. But we've been on a very, very positive trajectory, and we have a lot of conviction that we're going to have the best models in the future. But I think separate from that, we've focused a lot on things like trust, safety, reliability and responsibility. And that's particularly important in these regulated industries where you have to make sure that your customers trust you, you have to make sure that you're doing the right thing by regulators and by society. So there are several levels at which we've focused on this. So our models are trained with this method called constitutional AI, where they're trained with a set of principles that they operate according to. This makes their behavior more predictable, more reliable. We've always highly valued privacy and security. Some of that is with our cloud partners like AWS, but it's always something that we valued ourselves. And a new emerging area, we've actually been working on it for several years, is the ability to see inside the models and make their decision process transparent. There's a field of research called mechanistic interpretability that's just starting to get commercialized, that allows us to look inside and trace the thinking of the model and understand why it makes the decisions that it makes. And of course, in things like insurance, like underwriting, like claims, it's very important to society that we'd be able to understand what's going on inside these models and that they make -- we understand why they make the decisions they make and that those decisions are fair. And there's no other company that has made anywhere near as much progress in this area or that focuses on it or holds it as a value as much. And so we're very excited to these methods that we've developed to bring them out into the world and to apply them to many of these important applications.

So do your competitors not value trust and safety?

I mean this is one of these things where everyone will, of course, say that they've.\.

You've been there. You've been asked.

If it sounds like a good thing, everyone is going to say, "Oh, yes, we have that. We do that, too." But I think just the research and the deployments and how fast we're growing in the enterprise and developer space where trust and reliability are at a premium. I think those things speak for themselves in terms of who is really serious.

I mean, Alex, how do you do that? How do you build a culture of trust and safety while also just moving forward and fast with innovation?

Well, let me just reframe the question and the answer. So let's just assume that you don't trust anything we're saying. So like maybe a different way of saying it is, by raising the complexity of the problem, so in the anti-terror context, it would be civil liberties and killing terrorists. You raise the technical challenge and then the output of the software, the quality in aggregate comes better even independent of the claim you're making. So like a different way of maybe answering the question is that, well, maybe if you espouse safety, the underlying model becomes more performant because the challenge you're trying to solve is harder, the engineers have to be better, your culture has to be more focused internally as opposed to just delivering what the client says they want tomorrow. And I think that is actually the real answer and the secret to like what we've done, is you raise the complexity of the problem to the point where it's nearly impossible to solve. And by solving it, you solve lots of other problems. So then the model is -- there's always a question of what do you mean by intelligence. All these things are proxy indicators. Is IQ really an indicator for success? It's kind of a proxy indicator, but it's not a -- so how do you have software or models that are more performant than even the test you would give, so the Elo score, it's by raising the standard. And then in our case, it's like we built this thing called ontology, which allows you to micro-control inputs, whether those inputs are humans or they're from a large language model. In the institutional context, that is mandated. And it's really because, if you take the next logical step from what you would need to do something, you end up with a series of products. I would say, again, I don't want to be like ridiculously only pro-American here, but this is like a very American way of solving things, which is like let's bring fairness and integrity into the core problem, which is probably how you ended up assembling us. It's not -- and then the aggregate output, the sum is much greater than the parts. And if you try it the other way, you get a very dysfunctional thing that is not strong enough to stand up on its own legs and certainly will not work in enterprise. I mean from the outside, coming into an enterprise, going into enterprise is always very difficult. Your value proposition has to be dramatically better than what an enterprise can do itself because it's painful for the enterprise to bring you in even if you have the best sponsor in the world. And so -- and that's how you do it. And honestly, the way you build software is the way exactly what you did. You took a micro thing and said, "Let me see if this works." And you use that thing to convince your people because if you had just said, "Hey, do this," they would be like, "Well, why?" And then it spreads. And then you put more gasoline on it. And so it's like it's cutting the weeds, which you're right about, and you did a great job of that. It's also putting planting seeds and making sure they can grow.

So on that note, Peter, what are some of the problems of the future, problems that you deal with in the business, that you can have these guys try to solve? Climate change? I don't know, fires in California?

There's a lot of that. But I think the next evolution is we have really focused on the front end of the business, which is data ingestion, getting underwriting criteria, train the large language models. I think how to be more nimble and allocate capital and optimize a global portfolio more real time which you'll need more computing power, but you also need ways in which you can develop large language models to know how you're going to take a portfolio and apply it to individual customers. And so I think that's the things we're talking about with Alex and Dario as a next step. But also just I bookend myself with really smart people. But what I do know through this is that -- and I talk to Claude about this all the time, is what we knew 12 months ago, I know like so much more today. And I assume in the next 12 months, I'm going to know a lot more than I know today. So having that sort of mindset of that we're just going to continue to build foundational work and try to adapt to the advancement these guys make has been fantastic for us in terms of advancing our business.

How do you see the future of the partnership? And just in general, where are we going with all of this?

Yes. I mean I am just excited for the rate of progress of the models. So I've been following this for 10 years since I was an individual researcher working on the models. And it is incredible the regularity with which the autonomy, the ability, the accuracy of the models just gets better and better every year. And we have no guarantee. The music, in theory, could stop at any time. But we now have a very long track record of the models fundamentally getting better at what they're doing. And as they get better at what they're doing, you might think, "Oh, they're smarter, the complexity goes up." Actually, the more autonomous they are, the more the deployment friction goes down rather than up. If a model is very weak, you have to put all the superstructure around it to make up for its failures. As the models get stronger, our ability to deploy them for things that are more and more core to the product, right, more and more core to the underlying product and the underlying financials of the business in question, that's going to be very much more possible to do. And of course, we will mutually learn a lot more about -- even if we were to hold constant, even if we were to freeze in place the quality of the current models, over years, we'll learn more about how to deploy them. We'll deploy them much more broadly. I'm sure we'll make some mistakes. We'll learn from those mistakes. We'll iterate rapidly and we'll produce great results. So you put this all together, and there's a lot to be.\.

So it's not hitting a wall, contrary to some.\.

Very -- I would say very unlikely. I don't speak in certainties, but we have a very long empirical track record of evidence against that.

And is it going to need less compute which is kind of a hot question.

Yes. I mean I think the dynamic we've seen is that to make -- the cost of making a model of a given intelligence quality and capabilities is going down and down and down. But the amount of money that we're putting in to make models is going up and up because the models are so good at what they do, that it -- they're so valuable that it just makes sense to put even more effort to train them.

And final word, Alex, where -- what -- how do you see the future? What are you thinking about capabilities that you wish you could do now with the technology that's not there yet, but that's where we're going?

Well, there's a lot of debate around this, and I would say I go back and forth. I do think there's a separate question of not just how good they are, but how reliable they are at the point of use. So you could have the models getting much better, but they only work 80% of the time. There's some statistical issues there. What I like currently is, first of all, it's a revolution born and bred in America, the bastion of all good in this world.

We're all about America.

Well, I don't know if we're all about that, but everyone should.

You are.

Well, I'm trying to spread the wealth of wisdom. And two, you're going to see in the next 2 years, let's just figure -- not 5 years, next 2 years, a lot of theory is going to move out. We had this -- by the way, Dario never did this, but there are some people in the Valley who've like sold more than they could do. And the theory of AI is going out of the market and the reality of what works is coming in. That's very good for Palantir. It's as good for everyone on the stage. I'm looking forward to it. I think it's crazy important on the battlefield, a subject not for this conference, but -- and the concern I tend to have about AI is much more societal. It's going to make -- I do think it will lift boats, everyone's boat, but it's going to lift the boats of people who do it well disproportionately, and that's going to create societal and investor issues. Getting these things right is going to be crucial to everyone's life.

What's the best way to see who's doing it well besides using Palantir and Anthropic?

No, no. Well, no, don't know exactly. Start with nothing. Don't assume anyone and then go -- like, I would assert this is one of the strongest implementations of AI you can find. Great, invite yourself in, take a look at it and then invite yourself to some other people who've spent more time, more money, better at propaganda, compare the results. And then don't make the mistake people make. They then say, "Oh, okay, well, give credibility to the people who are actually doing it." Like, the biggest mistake people make in software, and I would say also in the implementation of large language models, is it's way too theoretical. Do not listen to what people are saying. Go watch the results and then listen to the people who deliver results and push the people who are very good at propaganda and very good at persuasion out of your business, and that's how you will do well. And this is a very good example of something that is very strong. Take time, go look at it and learn from it.

Peter, I think you're happy, right? Thank you very much for inviting me.

No pressure to top that.

All right. Well, probably it will be a tough act, but hopefully, we keep it going strong. There are microphones coming around. [Operator Instructions] And we will kick it off with Meyer Shields from KBW.

All right. I'm going to stand up because you told us to. Meyer Shields, KBW. So I'm going to start with a question on the last panel, and that is just give me -- well, I'll let you be political in responding. Historically, the insurance brokers have generated most all of the returns in the P&C space over time. With these tools, how does AIG ensure that it's retaining as much of the value that you're creating through better underwriting and claims handling?

Thanks, Meyer. I mean the idea is not to change the business model. We know that brokers, agents, very strong partners of us. I don't think that what we're doing can be replicated by them in the short run or even like -- they have to get the capital. And so how they submit data, they may change, they may not. I mean -- but I think what we're trying to do is be agnostic in terms of how that comes in from our partners, but changing our business model to be better service, better capabilities, better insight. And over time, you heard from Alex and Dario, that the models are going to get better. And I think it gives us the ability to underwrite more effectively over time. What that looks like in terms of specifics, we'll see. I mean -- but I think today, it's a very frustrating industry and that things have not changed. And whether it was algorithms, digitizing workflow, you still can't change the way the data comes in. And I think this is a -- that's why we're doing what we're doing. I think this is going to be a dramatic change in terms of how businesses conduct in the future.

Okay. And a completely unrelated follow-up, but I wanted to ask Charlie. A lot of the slides so far have been forward-looking in terms of ROE improvement, expense ratio improvement. We didn't get a lot in terms of optimizing reinsurance purchasing now that AIG is fundamentally more credible as an underwriter. And I want you to take us through what we should expect there.

Sure. Look, I think it's really important to go back to what Peter was focused on, about that philosophy, because that's been the real heart of everything we've done in terms of reinsurance. So I talked a bit about the cap structure earlier. And what does that do? Well, it's protecting capital. It's managing volatility. We have an earnings lens on it as well. And all of that is -- all of it is contributing to improving and increasing the quality of the underwriting earnings. Our view, it's a real short-term view, to turn around and say, "I'm going to flex my reinsurance structure to try and look to short term, whether it's growth or short-term profitability." Frankly, where I think you've seen people do that in the casualty space, it really shows. If you think about the casualty performance, again, one of Peter's slides, a very consistent net retention. Casualty goes wrong on a calendar year, not on an accident year. When people flex their reinsurance structure, that tends to cause and lead to problems. So I think we're pretty happy with where we are.

Next question, Josh Shanker from Bank of America, please.

I guess, Charles or maybe Pete, so I'm not supposed to engage people who are smarter than me, who have nothing to lose and I guess are better negotiators. Why should I be doing any reinsurance with AIG? In terms of if AIG is all those things now, how do reinsurers act as partners with AIG instead of being opportunities for AIG to have a long-term relationship?

I'll start, and Charlie, you can add. I would say our reinsurers have been one of the most important partners for us in this sort of evolution of changing AIG's reputation in the market, getting to underwriting profitability. We treat them with enormous respect, with enormous transparency and they trade across the portfolio. And so while we have very strong reinsurance structures, it is a multiyear approach. Our reinsurers back AIG. It's not a transactional trade of there's property reinsurers, there's casualty. We get the world's best reinsurers to look at our portfolio. After we get things done on treaties, Charlie is right back in with our partners in terms of thinking about the strategy for the future. So they have a great balance, and they know we don't trade on a transaction. So it's not -- can we push price more? Absolutely. Could we do things more short term? Absolutely. But I think this evolution process has benefited us because of the partnership approach we've taken. And they should trade with us because they will make money over time. This is not an income statement trade, it's a balance sheet trade, and that if they stay with us over the long period of time, they're going to get their returns and get their target ROEs by being part of us. Charlie?

Yes. I think I agree with, obviously, all of that. And I think if you go back to when we were talking earlier a bit about 2017, I think had the organization sought to buy more thorough, more thoughtful reinsurance, as I said, I think I mentioned it was very opportunistic. And that's a short-term strategy in terms of with reinsurers as well. And we spent an enormous amount of time, Peter and I, really rebuilding the trust in AIG because reinsurance is not a substitute for poor underwriting. That's the key. And the relationships we built, they didn't -- they started at the very most senior levels within our organization and with the organizations that we trade with, the largest reinsurers in the world. And so I think there is that mutual trust and that understanding of what they offer and how it matches what we want and that it's there for the long term. So it's not something we worry about at all actually.

And then the ROE guidance of 10% to 13%, we knew the beginning of that coming into 2025, the 10% ROE guidance. Some people were skeptical that AIG might be able to deliver on it. And then within 2 weeks, you had a $0.5 billion non-cat loss with some additional reinstatement premiums that are going to go on top of that. And you're still confident about the 10% ROE for 2025. Has anything changed since the year began? Or were you going to greatly exceed 2025's goal when you started the year, even though we were surprised by the L.A. wildfire losses?

Yes. Nothing has changed. And as Charlie said during the panel, like the $500 million, it was modeled. It was modeled incorrectly, which is most cats, but that one in particular, cut off the tail, was much bigger. It's January. But we have -- back to the slide I put up, our percentage of our loss ratio on cat has been very steady at around 5% over the last 4 years. And that's the way we structure our aggregate. So I mean, who knows what distribution of cat is going to be for the rest of the year? But I wouldn't look at the $500 million as additive. I would look at it as part of our expectation of frequency within cat for the full year. Again, not knowing the distribution, knowing it's March, we haven't hit wind season, things happen. But that $500 million is a contributor towards what we're comfortable with as retaining net with the currents and aggregate. And so could it be a little higher? Maybe. Could it be a little lower? Yes. And so that's why we have a lot of confidence in reconfirming the guidance.

Next question from Paul Newsome from Piper Sandler.

I was hoping you could expand upon the role of private capital with the SPV. And just how far can you end up expanding that across your business? Is that something that we should expect and broadly? A little bit more color, I think.

Charlie, let me start and maybe you can provide a little bit more color. The idea of the special purpose vehicle was an excerpt from the portfolio optimization work that we've done and felt that if we can create something with an enterprise model that shows that the investor is going to get a very strong return from diversification as well as what our expected losses are, that it would be a good match. We've been working on this for 2 years. And for us, looking at how we place reinsurance, maybe it's like 15-plus percent of our total reinsurance outwards, that it's a really good way to secure capacity that's more consistent, that will follow the leads and be there over a long-term period. The idea always has been that, that becomes a base to build on other risk pools over time. What that looks like, what it is, we will explore it. There are definitely opportunities in the marketplace. And we figured that our own reinsurance at roughly $750 million of placement is sizable. It could be a base that we can then diversify as we see different risk pools to be able to raise additional capital where we would get fee income, but also see investors be rewarded for scale and diversification. Charlie, do you want to add to that?

Yes. I think we're -- as I hopefully came across in our panel discussion, we're really proud of what we achieved, but we're really excited about what the future opportunity is. We have this incredible platform in terms of generating risk. And I think we also have the capability and the skill set to manage that risk into portfolios that really are about finding the optimal capital. I think what distinguishes ourselves maybe to where you see on the distribution trying to do this is we also have our own balance sheet. So we can take the risk ourselves and shape the risk ourselves. You can't do that as a distribution company solely. So we think we're as well placed as any company in the world to really capitalize upon this, and we're really excited about it.

Next question from Daniel Lee from Morgan Stanley.

Daniel Lee from Morgan Stanley. My first question is just in regards to the last panel. It does seem like it's a very core collaboration for sure with Palantir and Anthropic. It does seem -- it's definitely a mix of build versus buy when it comes to tech improvements. How should we think about the mix of build versus buy going forward for AIG?

Claude, do you want to take that?

Sure. As I said in my remarks, we're not a technology company. We're an underwriting and claims company. So we don't build technology. I mean everything that you've seen in terms of our end-to-end ecosystem, we describe it as this modular agentic ecosystem where we're plugging in fit-for-purpose solutions that work for our unique data challenges. And that's where Anthropic, Palantir, AWS Titan all come into play. The only thing we've built is the overall wrapper and the workflow that connects them. But outside of that, everything is a modular approach this way. We can always have best-of-breed, and we can grow as those organizations continue to improve the capabilities of their models.

I think probably one thing I would add is that we have, though, in order to be prepared for that, have spent a significant amount of money on our foundational capabilities, our data insight. And so that's been a journey between AIG 200 and then what we've advanced in terms of building out the business. I don't think we'd be able to do what we're doing, as Claude outlined, with Anthropic, with AWS, with Palantir, if we hadn't made those significant investments to build the foundation.

It all starts with the data.

Cool. So my second question, I guess, would be for Keith in regards to cloud. So you guys mentioned you guys are now at 80% on the cloud in terms of workload. And in general, we know cloud expense can be a variable expense. So in terms of as you guys expand your AI capabilities and other tech workload onto the cloud, how should we think about how you guys would manage expenses in this area going forward?

Can I take that, Keith? So we know there's like a variable cost on the cloud. But having partners that are embedded with us with Bedrock, Anthropic, within AWS, we know the per cost for quote. I mean we are able to monitor that and not let expenses sort of get away with this hypothetical experiment, but it's thought-through. And there will be some incremental expense as we start to adopt this more broadly across the organization. Having said that, there is a commensurate growth element to this that we should be able to absorb it. And this is not introducing this today of saying, "This is on the come. Doesn't it sound great? And by the way, there's going to be more expense." We'll be able to manage the expense on an incremental basis in terms of what we're driving over the next couple of years and provide guidance if there's something that is going to be accelerated beyond that. But we have a very good, deep understanding of how we use all of the technology and applications on AWS.

I would just add, it's why we spent so much time walking you through the individual steps and components of our RAG framework because we're only sending the models what they need in order to process. We've actually lowered our cost for each transaction. And so we expect to see that continue to be lowered as the models get better and as we get better in terms of providing the context to the model.

We'll take our next question from Dave Motemaden from Evercore ISI.

Just on the last panel, I thought it was really interesting just on the new technology driving growth. Particularly within the commercial lines, how much do you think that, that can turbocharge growth versus the 7% net written premium growth that you guys had last year? And how should I think about, maybe just a follow-up for Don, on the ability to get more share with your trading partners within that?

Don, why don't you start with that? Then I'll take the first.

Yes. As I said, in North America, I'll just talk about the retail business, I mentioned the data point that top 10 or 83% of our premium volume, share of wallet, which I talked about data availability, share of wallet with them ranges from 2% to 7%. So it's not like you're talking about going from 30% to 40%. It's like going from like 2% to 4%. It's like, "Can we double our business with these top brokers that we do business with?" The question lies in, to what level of connectivity and alignment have we had to date? And I think there's -- I'm talking about my background as a broker. I think there's a bit of a fallacy that there's been a high level of connectivity. There have been highly strategic partnerships. I don't think that's the case. I'd say on a scale of 1 to 10, there've been about 3. And I think if we can get to a 5 and a 7 and an 8 and a 9, there are tremendous organic growth opportunities with our top broker relationships for years to come. So I'm very confident about our ability to grow that space.

It's hard to give specific guidance on what we think the growth trajectory could be with adopting what we've outlined in quite a bit of detail here today. I think the Lexington example is a good one. We don't have to go back through that. But if you think about other scalable businesses where cycle time matters, you can point yourself to Japan. I mean we haven't fully started there, but the cycle time of getting quotes in a fraction of the time for personal insurance, small commercial, will have a dramatic impact on our ability to grow that business. And yes, you may be taking market share, but more importantly is you're probably getting more growth from additional product because you're able to actually quote that in more real time. And I'm talking about not like the example we gave before in Lexington, which could be days, or the one that we just did the pilot on was weeks and then you get it in hours. I'm talking about like getting it from an hour to like 12 minutes. I mean, like -- so if you can do that and you actually have the products, because it's more complicated in Japan, because every product is somewhat homogeneous and then there's like 50 riders that are heterogeneous and you have to build that out, but we do think that there's real opportunities in our scalable businesses where cycle time matters to have like multiple growth that we do today. What that looks like, what's the actual percentage is, I think that's what will evolve and take you through over time as we start to adopt this more broadly.

Great. And then my follow-up is back on the M&A framework. Just on the financial targets, the EPS and ROE accretion, is there a time frame that you think about to achieving accretion? Is it immediate? Is it 1 to 3 years? And should I think about that as impacting the $5 billion to $6 billion of share repurchases that you've outlined in 2025?

I think that was 3 questions, let me see.

I held back a little bit, too, so.\.

Which one do you want me to answer? No, it does not impact what we've given you guidance on for share repurchases. And look, our base case is that it's not going to be dilutive. Would it be -- if we found the right acquisition in a 1- to 3-year period, maybe. I mean -- but I would think about like we have capital to absorb risk. There's different ways in which to structure that. Driving more earnings is going to be accretive to ROE. And so like we're really focused on not coming back to this group and saying, "Oh, we just did a deal. And by the way, we're talking our guidance away and give us more time." I mean, I would not want to do that. But if there's something so compelling that it changes the organization forever, you'd want us to do that. If you look back at the AIG historically, and I'm not judging it, it's just math, that after it went public again, the money is spent on 3 buckets, which is reserve strengthening, raising debt, and then share repurchases was between $90 billion and $100 billion during that period of time to keep the stock flat. I mean, had they found something compelling -- and again, that was a point in time, I'm not judging it, I wasn't here, but you drive earnings, you drive more market cap, you drive more option value, you're able to today adopt LLM on a bigger platform, we want to do that. We want to be sitting here for whatever period of time as showing you that we have real potential for meaningful growth. This company is built and has capabilities to be bigger. It doesn't have to be. It has great size today, but we can be bigger. And also, we've shown through the operations that we have the muscle to transform. And so I think that we would be a good acquirer of businesses if it meets those thresholds.

Next question from Elyse Greenspan from Wells Fargo.

Elyse Greenspan, Wells Fargo. I wanted to come back to the reserve discussion earlier. Keith, you were talking about just the conservative nature of reserves. Within the guidance, the 20-plus percent EPS CAGR as well as ROE guide, are you guys assuming anything for reserve development? I'm thinking maybe just the ADC and then anything else on top of that could just be upside to guidance.

Yes. I love your questions and I get one-word answers, Elyse.

Well, I made that one easy. And then the second one takes the expense ratio comments and also just the last discussions on AI. Obviously, there's a cost there. So you guys have obviously been investing in AI, and it sounds like something that will continue. So how does that cost get factored into the desire to show a material improvement in your expense ratio?

Well, Claude, maybe just go a click down in terms of like how like the variable cost works. But we have a lot of initiatives in place. We talked about AIG next earning further into 2025, getting the businesses sort of set up to be leaner, other operations leaner. We have a path there, at least. And again, one of the things that I think we don't necessarily get full credit for is that even when we were giving guidance on some of the other operational programs that we were doing, we were investing all along. I mean, we were investing in people. When we started with the data, we had nobody. I mean, so like everything was additive in terms of how we are actually going to position the company for the future operations. But that's not this group's problem, that's our problem, is to be able to invest, reposition the business and still meet like guidance in terms of what we're going to do on the expense side. We need to be below 30%, and we're going to be all over getting that done while reinvesting for the future.

I would just add to that, Peter. This effort up until now, it's been an end-to-end transformation. I talked about optimizing the process. So it's people, it's process and technology as an accelerator and enabler. We've been able to offset the cost of implementing what you saw today through optimizing the process. And so today -- so that's all captured today in our numbers, and we'll continue to do that. We'll get leaner, we'll get smarter, we get faster, and we figure out how to take the waste out of the system while we're implementing the new solutions that we're building. And again, we're doing it in a cost-efficient way by the RAG framework and making sure we're only sending what's necessary to the models, which is what's driving the token cost. And that's really what the cost drivers are for a solution like this.

Brian Meredith from UBS.

Yes. Going back to the AI discussion, you're doing a lot of stuff. It looks great. As an outsider, what are the things we should be looking for to kind of grade you on whether this is successful or not? I mean the 13% ROE target, that's terrific, but I look at other companies that you compete against, they have much higher ROEs. Do you anticipate this will take you to an ROE that will be best-in-class or best-in-class combined ratios growth? How should we measure this as outsiders? It's difficult to.

Quentin, you never give Brian the last question. How many times have I -- Brian always tries to get a double or triple guidance. Other companies -- here's where I'll start, with the other company comparison. Nobody has had a start where we started. So if you look at ROEs of different companies, that doesn't mean we're not going to have aspirations to get there. They're coming back to the average, we're moving up. I mean, certainly, with the scalability, again, there's no time frame for this, Brian. I said like this is from 2025 to 2030. But certainly, being able to grow in a way that we have not seen in the past will give us opportunities for ROE to be more accretive, for sure. So I mean the 10% to 13% does not contemplate large language models or what we've outlined today of hitting that out of the park. That would be in addition to. And we're very focused on making sure that we're driving those outcomes and investing for the future. And you should measure us based on the progress that we're making, not too tight of time frames, but like how are we rolling it out to businesses, how are we actually effectively changing the way in which we can ingest data submission activity, how do we grow and how are we driving this across the enterprise. Or if you want to do it easier, just compare us to our competitors, and I think you'll be happy with the progress that we're making because I don't think anyone else is doing the end-to-end.

And then one other just quick one here. Obviously, it's a change right now. AIG now is more about growth and not fixing. Any changes to incentive compensation that we should be or you've been thinking about and making changes at all looking forward versus what it's been over the last couple of years?

Not particularly. I think one of the changes, like when -- you can imagine when you're first bringing in people who were going to be critical to the turnaround, that getting people convinced on the calendar year compensation wasn't easy. And so those are some of the changes that we've done with our Board of Directors to really drive all of the incentives to be aligned with every aspect of financial performance in the company. And so now it's ROE. It's making sure -- as a matter of fact, we took out -- because we had a 2-year commitment on getting other operations down to this optimal $350 million for parent, and we got there sort of 12 months ahead of where we thought we would, we took it out like because there's a new metric. And now we're driving things that are aligned with all of our shareholders and making sure that we're driving EPS, ROE, calendar year and accident year combined ratios. And so everybody has the same incentive. And it's not different for underwriters than it is for functions. It's not different for corporate than it is for the business. I mean it's all aligned, and people get paid if we drive value aligned with our investors.

Thank you all for the questions. And I think with that, I'll turn it back over to the Chairman and CEO, Peter Zaffino.

Thanks for -- it's been a great day, and I really appreciate all of your attention to our story. I'm going to say one sort of quote, which many have said before that, "One's grasp should always exceed its reach," meaning your goal should always be greater than what you're actually capable of achieving. But for AIG, our reach is our grasp. I mean we've shown that we've had enormous aspirations. And what we've accomplished, we tried to outline this morning, has been nothing short of extraordinary. And I've been told it ain't bragging if it's true. So what things -- you've been overwhelmed with information and a bunch of data. What would I take away from today? The past is in the past. We've taken no shortcuts. We've worked at massive pace. We've run the problems and have worked through all the real critical issues to make sure we position ourselves for the future. I would say the best predictor of future performance is past performance. And today, we've demonstrated that we always deliver, and we want you to really bet on this team. The next -- the third one would be the company has enormous strategic and financial flexibility. We're going to be very disciplined with every decision as we always have been, but we feel like the industry is facing headwinds, and we've never had more momentum as we enter 2025. And the last piece I want to leave you with, we went through it a lot today, but AI is real, and it's not a cost-cutting exercise. It's an end-to-end exercise. You need scale, expertise and a strategy that will propel you into the future. And we have that. We've accomplished a significant amount, and we think the best days are ahead. So again, we really appreciate your time today. Hopefully, it was informative and look forward to spending time with you at lunch. Thank you very much.