All right. Is this working? All right. Well, just in the interest of keeping on time, we'll get this kicked off. I'm very excited to have Gal Krubiner, sorry, with me. Gal started Pagaya, I don't know, 2016, so 10 years ago. And I think, as many of us in the room probably know, this is an extraordinary idea, a big shift in the market for consumer lending. And real quick positioning is Pagaya is positioning itself to become a network of lending, inserting itself between businesses and consumers as a way to originate loans and distribute loans to the capital markets in an extraordinarily efficient manner, but that also benefits their business partners, benefits their customers, and obviously benefits them. And we'll get obviously a lot more into this over the course of this discussion. But just in terms of introducing Gal before he founded Pagaya, he did a lot in securitizations at UBS. So very, very deep background in understanding how funding markets work, how consumer-facing financial services work. And as a result of that experience, he's really trying to modernize the whole, again, lending network. So with that as an introduction, welcome. Thank you. And so first, we're going to just have, like you guys are accustomed to, a fireside chat here. We will try to leave a few minutes at the end for questions. But first question is kind of, we'll start a little bit more high level. What is your mission and where are you in the cycle of that mission? So thank you very much for having me on today. I think definitely Jefferies and yourself were one of the early ones to spot the uniqueness of the story and the impact that it could have. So delighted to be here today and to share a little bit more of how we think about not just today, but the next few years and how we think about the company progression and the mission that we have behind and what we're trying to achieve to your first question. So I think I will start with the very fundamental that all of us are fully understanding. The U.S. is a big place where consumers are driving most of the economy, 70%. Out of that, their biggest firepower is access to credit. Access to credit is really one of the things that is driving this country to the greatest that it's today. But still, even in the most developed financial services systems in the world, there are many people who are having a little bit harder time to access that capital in an efficient way. And when we thought about it, we actually believed that the better way to solve that problem and to inject more of a unique technology and capability to make this world more efficient doesn't go through the regular route of building another B2C lender. So many have done it and did it very well. And we actually thought more into the deep core of lending and really understood that lending is a tough business. And not just that it's a tough business, it has a lot of similarities in between different lenders that are trying to capture and to serve millions of customers in the U.S. by providing them the most ability to access to credit. So we thought of that and we said, what if instead of becoming a lender, we will become a service provider, a product company that is actually providing to the lending partners, which we view them as our customers, solutions to help them approve more customers and to be able to fund more loans through their systems, through their brands, through their ecosystems. By doing so, if you're actually successful of taking any brand in the U.S. that has a lending capacity and you help them to make themselves 10%, 20%, 25% more efficient, you actually solve the problem that has a magnitude and an impact on a full economy by doing a very unique thing that you can provide as a product and as a service to many lenders. That's really the vision and what we are thinking about ourselves as we are going to the next stages as we are providing these technology solutions that is embedded to your point with very strong and deep funding capabilities and solutions to help lenders across the country to be able to approve and fund more borrowers that actually have been left behind because they didn't have the capabilities because of our first point that lending is hard. So we have developed a company that in its core has an AI underwriting, machine learning, and different types of fundamental technology capabilities to be able to help these lenders approve more customers. And I want to take us 30,000-foot because I feel that at this point, many of us already know the Pagaya story. When we think about where we are in the journey and what we think about it, we're actually believing that we are creating a category. We believe that every balance sheet lender in the U.S. should have an extension of the ability to get access to capital and to provide to different types of customers that are coming through their door the ability to get financed even if the lender itself doesn't have that tech capability or funding capability and so on and so forth. So when we took all of that and we combined it as a standalone product, which we call now the extended platform, we are going into different lenders and asking them the question, hey, do you have your ability to actually service a 680 FICO personal loan borrower? Many of the times, the answer is no. And then we're saying, okay, we have the right solution for you because there are millions of customers that are coming through your door that don't get a service, but they should get a service from you as a lender. And we did that in personal loan, and we did that in auto loans, and we did that in point of sale. The holistic view of how we are thinking about it is actually building a platform, a network to your point, that could have actually a credit as a service to help different types of lenders to pick and choose what they didn't solve as of yet, and to be able with an API plug and play with our AI capabilities behind the ability to enable that lending in the tip of their fingers in their ecosystem under their brand. This is what we believe is going to be a major thing that is going to change the efficiency of the U.S. consumer credit space across many different markets and in very different lenders as much as fintech lenders and up until the big five biggest banks that one of them is our client like U.S. Bank. So that's the mission, that's the vision to the journey, I think, again, from reflecting on investor perspective. The biggest last two, we went public at not the greatest time, June 22nd. We could have picked a better time. So we were very successful in that. The last two years was really to solidify the unit economics, the business model, and to make people like yourself and others believe that that could be profitable, sustainable, and has a lot of impact that it could do over time. The next stage will be to make it standard, to make it that every lender in the U.S. will use it, and we are on that trajectory from here. So maybe talk about, call it the ecosystem, call it onboarding a partner, what those partners, is there any kind of characteristics about the partners? And then ramping up the partner and how everybody in the system benefits. Maybe talk about the supply-and-demand journey of one product through the system. So, lenders typically have types of products that they are strongest at and types of products that they are less strong at. And when we are thinking about who our lenders or our partners' potential, our customers, it can be anywhere from the fintech lenders, which many of them, I'm sure you're familiar with, SoFi, LendingClub, Prosper, Avant, many of the most lucrative personal loan fintech players that exist in the country and actually driving a lot of the volumes through the ecosystem to your point. And then on the other side, in between, you have what we would describe as the regional banks. Ally is the best example of a partner like that, but actually on the auto loan side. And then at the end, we have one of the bigger, largest banks in the U.S., which is U.S. Bank that is our customer. And in all of these cases, we are going after lenders and trying to share with them that their ability to service their customers in a B2B2C type of a business model is really driven by the ability to connect to Pagaya. So for example, if you have some kind of a hard FICO decline, from that you cannot serve your customers, we are actually connecting to your systems and allowing that FICO type of people to actually be approved. And you will be surprised sometimes a hard cut off of a bank could be a 700 FICO, which is a great customer that should get a loan. More likely than not, will get a loan from a fintech lender, but the capabilities and the technology and the agileness of being able to drive that through capital market didn't find its way to the banks as of yet. Pagaya is coming with a one-stop shop, the full network, the full credit capabilities and underwriting to be able to enable that capability in a bank. It's always starting from the sale, and we are in that sense, elephant hunting type of a thing or a whale hunting type of a thing. You have something like 100, 200 candidates in the U.S. We are speaking with the top part of them. That cycle could take six months, one year. You're spotting what are the areas of the most amount of lift that they could get that usually aligns with their three-year vision for the business of trying to provide more solutions for the PL business or for your auto business or whatever it is. And then you're starting to have an onboarding, which usually takes six months to a year, that is connecting the system, creating the legal framework, being able to understand deeply what the bank is solving for and therefore fitting the pieces to it. And then the third piece is the ramp up, which starts as low as a few million dollars or dozens of millions of dollars a month and could be ending up at a $2 billion a year as the models and the AI is learning a lot through the process. So you have the ability to approve many more customers and support the bank in many more parts. And then you have what we call a mature partner that's driving both for them a lot of value because they could serve their customers, to their customers a lot of value because they are now in a situation where they can get more credit. And for us, a lot of value because we are providing that through the investor network. The one piece I think that we were underappreciating when we went to this journey at the beginning and we are learning as we go by is the importance of not just the underwriting, but the operational savviness, but the marketing capabilities of what these actually marketing channels are bringing to the partners' doors. What we've been focusing on in the last few quarters is to embed more and more technology into the marketing engines, into the verification process, to be able to provide to the customers of our lenders the seamless, most easy way to actually apply for a loan and to be able to do it seamlessly. For example, a lot of the stipulation that is a major part with auto could be done now with technology and online, etc., that reduces the friction of the borrowers in the dealerships, which obviously increases the pie for everyone. The technology aspect here of the progression over time and embedding more and more quant, which is the basis of Pagaya, into different angles and not just the underwriting is really where we are taking that. We see a great amount of progress and growth that are being embedded from that unique tech capabilities that will drive future value to our customers. And so maybe dive a little bit deeper into the technology. You mentioned API and the ability to integrate with the major financial service companies, AI. Maybe talk about what are the key components as you see it on your technology platform and how are you differentiated in those? So from a tech stack perspective, I think this is one of the places, and again, I'm reflecting a little bit of how investors are thinking about it, that we look much more like a B2B service provider that is working with banks rather than a consumer lender. We are servicing them as clients. We have different parts of centralization from that perspective. And I will try to a little bit describe it in high level of what does it take to be able to support all of that in that velocity and in that depth. So the first piece is all the connectivity to the actual loan origination systems of the banks. The name of the game there is one word, seamless. You want the experience for the customers, for the dealership, for the merchant that is driving the flow to these types of lenders to feel that every customer that is going to be funded by Pagaya or not has zero difference. So a lot of the engineering is to make sure it's 100% working, zero downtime, very deeply integrated, the same user experience throughout the journey, replicating all the little nuances from the lending pages and up until to the verification process that will be replicated in Pagaya internally and augment the partner way of working. And that is the big thing, seamlessly integrated with the heavy technology capabilities to make it as agile as possible to solve for each lender nuances, if you will. The second piece, that's the very deep AI capabilities. So as long as we become bigger and better and collecting more data, the ability to use very strong AI tools to be able to price risk better is the name of the game. And what we're building from that perspective is think about it as a very gigantic one database that is collecting more and more information from the partners and using it for their benefit to approve more customers on their door. And the alignment of interest with our lenders is huge because when they are giving us more information, we can be more accurate and therefore we can approve more customers on their behalf. So there is a very strong flywheel here of provide more data, get a better accuracy, get a better approval rate, and drive that down to either a better interest rate for the customers or on the other side, higher approval rate. The name of the game for the second piece is accuracy. You want to do it very accurate. And there is an AI progression over, I would call it 10%-15% every year that your models are learning more new methods, better data, unique data that is becoming powering this very strong capability of that piece. And then the third piece, which is what we spoke about, the verification and the other pieces, that is always the analogy I have in my head is a little bit the Facebook piece, which is try to build not that much of an AI basis, but definitely try to build a connectivity in between the different operational points that there are on the partner side and build that in a framework of A/B testing and different types of quantification capabilities that over time, your ability to understand in between segment, in between operational differences is becoming very easy. So for example, how different segmentations are reacting to different pricing is something that you can do only if you build a very strong internal infrastructure that could support an A/B testing go live in the same channel, in the same time, in the same partners, and therefore to drive the conclusion from that. So the third piece, which is the infrastructure, I will call it the robustness. So we are trying to take very heavy operational world and to move them to a quant world, and that connectivity is going through infrastructure that is becoming more and more robust and becoming more and more generic. So three pieces, the seamless to the lenders, the accuracy and the importance of the data in the models, and the systematic approach of learning and being able to extract more value. These are the kind of like stack that you can see in companies like ourselves. That's very helpful. Thank you. So certainly consumer lending is subject to different economic cycles, both positive and challenging cycles. How do you see Pagaya's positioning for both or all types of cycles and how has that developed over the past couple of years? So the way we think about it, and by the way, this is the part of the business that we are more like a consumer credit lender, if you will. The way we think about it is the following. There have been a few very top capable organizations in the world that managed to run down consumer credit through cycles in a very efficient way. The way we think about it internally is be as good as Capital One. All of that in Capital One too is being driven by technology capabilities, prediction, etc. So we have all the right fundamentals, but it's all running around risk management. The way you need to run companies like that is to be able on the one hand side to push and push growth and progression as much as you need, but in the same time, always look for the downside risk. Many of the times in one-on-one investor meetings, we're getting the question, why don't you push the pedal more? Why don't you grow faster? You have all the capabilities. We have, because our vision and we are a founder-led company that we are looking on what we're trying to solve and achieve 10 years down the road, there is zero reason why to risk any of that in any occasion or any connectivity to any credit cycle. And therefore, we are fine leaving some money on the table. We are fine to not go to the edge of approving more to discover that it didn't work. And we have discovered that to do a little bit more conservatism in the way you operate, because of how much operational headache and risks it takes out of the system, it's actually becoming more efficient even. So when we think about it, it's risk management first. We are running the company to be profitable and meaningfully profitable. And I think the last piece we didn't talk about, the last question is about the operational leverage that all of that the tech drives. We'll talk about it later. But the important piece is that we are thinking about the downside as even if the downside is being met or hit, we are still, if not profitable, break even. Because you want to make sure you have a very strong defensible company that knows to operate through cycle and to continue to grow in the way it should, which is lending more partners, building more products, developing more technology, and not trying to squeeze the lemon more because there is a better environment right now. And therefore, you can either ramp up the ability to approve people, vice versa. Now, we are obviously in an ecosystem of economies, so we need to be reactive to that. But we are definitely considering ourselves as the more conservative part because there is no other way to do it. And risk management is. It's about diversification. It's about systemic risk. It's about the very good things that actually banks actually manifested to do a good job about. And we're trying to copy that internally to do the right balancing between risk-taking to the growth. So that's the way we think about it. And the last piece I would say that is driving a lot of that risk is the funding risk. What we have did in the last few years is reducing the funding risk massively, both by doing forward flow agreements, which are now accounted for 30-30-plus% of our production. The second piece is that we have a very unique structure that is my background in the structured products, which is a pre-funding models. We have the money before we are actually lending. These very important features on the funding side is making sure that even if a risk arises, we have time to fix it. We're never being rushed to making the wrong decision because we don't have the time. The right way to think about it and just having patience as we are growing the company to where it needs to be rather than rushing it because the environment is pushing us to do so. All right. I like that perspective. But I guess the funding model, so obviously the audience understands they're helping their partners originate more loans, but they also help their partners fund those loans. And the funding side, you just referred to it, forward flows, ABS structures and so forth, but it has evolved a lot over the past couple of years. Maybe explain to the audience where the channels were two years ago, where they are now. Do you have a mix over the long term that you aspire to have, or will it be fluctuating depending on where the capital markets are? So we started very much as a capital market shop. We are today the biggest ABS personal loan securitizer in the U.S. We're driving $5-$7 billion of capital market paper, as we call it, to the market. And you will be actually surprised that most of those investors are actually very institutional investors by their nature. We have many of the investors who have participated in our transactions for more than 40, 50 times. So it's a very repeatable process. So I think there is a very big distinction between what we call as a repeatable scalable issuer like the Fords of the world or the JPs, etc., that Pagaya is actually starting to be in that category versus a first-time issuer that markets are opening or closing more quickly on them as they come fit. And we never had any single day that we didn't have capital at hand to provide loans. Having said that, pricing is definitely fluctuating over cycles. So you can have a higher or lower pricing relatively on the capital markets as cycles come and go, while outside of the capital market, this nature of this pricing tends to be stabler. Not that it doesn't have any fluctuation, but it tends to be stabler. The big theme, and it's a very strong tailwind that we are experiencing in the last, I'll call it, two years, is the private credit. The private credit is a formation of many big alternative asset managers that are thinking of themselves as smart enough to be able to interact with companies not through pricing discovery of the capital market, but directionally aligned. And we have very much enjoyed working with the most important ones, Castlelake and Blue Owl and many others to drive that production through the Pagaya network and up to them. To put things in perspective, we have today 135 different investors on our investor network, which is one of the largest, if not the largest in these ABS markets. And I'm seeing now Josh is telling me now that it's higher than 135, so maybe it's even higher than that. And the other piece to that is that part of the private side, which we are trying to keep balancing between 30 to 40, sub 50%, I think is a good mix. And as we think about that, we are, to your point, trying to have a balanced approach, but in the same time diversified that we can ramp up or ramp down as we think market cycles that are relevant for the pricing efficiency of the different parts. So both parts, private markets, public markets, more like 50/50 or 70/30 towards public versus private. And even in the private, very repeatable type of transactions and processes to be able to do that. I guess that's probably a good segue into talking about the balance sheet. As a result of becoming more, I guess, diversified from a funding perspective, I think in a sense, your capital requirements have come down over the past. It's becoming more optimal, more efficient. Maybe take the audience through that journey of what the balance sheet risk retention looks like now versus a few years ago. Yeah, and I want to put it in the context of the conversation we had in the beginning, so there are two parts for the business. There is the B2B network that is connecting lenders with a very strong technology, and technology is the driver for the margin and for the ability to connect and to have a stable business, and then there is the other side, which is the Capital Engine, which we believe that even that you are a technology company and definitely being driven by tech and the operational leverage is definitely tech-oriented, the most efficient way to actually generate revenues and profits, etc., in the financial industry is through participation in the financial assets creation and sale, and that makes us to have another piece to the business, which is what we call the Capital Engine, and that Capital Engine has two characteristics. One is how much of the thing that you are actually producing, you're keeping on your balance sheet over time for risk retention purposes and actually other purposes to enjoy from the things you are generating and the ability to show to investors that you have a skin in the game, which is a very important practice for the risk management too. And the other piece of it is how efficient your balance sheet is to be able to support that type of activities. So to the first point, I think we did a tremendous amount of work in the last two years, and we're now at a so-called very low single-digit percentage point of efficiency of how much we actually need to retain on our balance sheet. It is now as low as 1%-2% on the full production and to your point, becoming much more efficient. Over time, as we see a little bit more opportunity to increase our profitability in a bigger stack or a smaller stack, we're playing with that along the way as we think about the earning power that we want to create versus the liquidity and the other pieces that we have on the balance sheet. The second piece to it, which we had just concluded two months ago, a high-yield bond offering that was B-rated by three of the different agencies, and you can see more online on these pieces, is that we have tapped into the public market to be able to fund our balance sheet. We have closed a high-yield offering that has given us a very strong, robust capability to be able to actually continue to fund that through cycles. As you can imagine, again, I'm using a lot of analogies from other companies. I think the one who controlled that the most and did the most amazing work in the last few years is actually OneMain. So they have a very strong, steady ability to access the public markets on the high-yield side. They have a very strong access to the ability to have that on the ABS side. So from a funding perspective, definitely the OneMain concept of diversification, balance sheet strength, and the ability to build equity buffers, and therefore much higher ability to utilize leverage in their smart way is how we're thinking about it. And today we are having a very light balance sheet business model with a very strong support from capital markets' ability to make it more and more efficient as we think about the Capital Engine from a KPI perspective. Okay. I do have a couple more questions, but we have a handful of minutes left. Does anybody in the audience have a question that they'd like to pose? Okay. So we'll keep going then. So we've only got a few minutes left, and I do want to talk about the financial performance a little bit. And there's a lot to probably talk about there, but maybe for context, the company's goal was to become cash flow positive and GAAP earnings positive this year. We expected it to be toward the latter end of the year, but they've already achieved that milestone. But so maybe talk, maybe highlight your KPIs, like your FRLPC margins, fee revenue minus production costs. It's basically like a gross margin or take rate. Talk about those KPIs around that. Now that you are GAAP earnings positive and cash flow positive, what does that mean for the strategic decision-making? Yeah. And I will try again to put it in a framework that will be easy for investors to think how we think about it. Obviously, none of that is any projection or anything else. It's just illustrative. So don't hang on the numbers specifically. The way we think about it from there is the growth of the network, which again, I don't know if the network is the best perfect fit for it, but the growth of the economy value that we create. And then there is the FRLPC, which has that embedded in it and the pricing power. And then you have the so-called adjusted EBITDA or GAAP net income into taking into consideration the operational leverage. And then you have earning power and ability to create equity value or shareholder value over time. That's the framework of how we think about it. And there are three components that are very unique to us that I think is very interesting in the context of the financials. Number one is the growth that is being driven through the creation of more value through lending more partners and creating more technology. Full stop. Not by doing more marketing budgets, not by increasing the opening the credit box, just by doing a SaaS B2B enterprise sales lending. Fundamentally different. How you model, how you think about it should be completely different. The second piece is how much of that is actually going to Pagaya as a net margin. The biggest piece that people are missing here, that is this piece is being driven not just by spreads and capital markets, but by the service we provide for the lenders and by the unique technology capabilities that are actually keeping the margin strong. Pricing power, that's what we're talking about in FRLPC, is coming from the question: could anyone replace you in the partner's eyes? The answer to that right now is no. There is no number two. There is no number three. It's very complex to build it. It takes years. Hopefully, we're going to be a category leader that takes most of it, but the real question about FRLPC, and we are thinking about that to stay as such for the long run, is really driving from what is the ability for someone to replace you, and the answer is once you're getting injected into a partner, very, very, very low, so the margin compression over time should be very low in Pagaya terms, as much as you see in any other SaaS, very strong B2B businesses with unique products. Then you're going to the question of efficiency or EBITDA or GAAP net income, and that is really driving where we see a lot of the AI progression that is driving very strong operational leverage. We don't have any manual works in Pagaya, not even a single person. It's only very high-educated physics, statistics, quant, and strong financial people. Not many, not that many people. We are like on the core company without the daughter companies, only three or 400 people that are driving something like $10-$12 billion of production. John, now you need to ask me, Gal, how many more people you think you need to do when you're going to get to a $25 billion? Gal, how many people do you think you're going to need to get to $25 billion? The same. The same. Now, do we need to pay a little bit more because of inflation and performance of people and what we are building? Yes, of course. But that has nothing to do with the growth of the business. So operational leverage is almost not 100, but like very high. And then the last piece is the compounding power of earning power that we easily could see how this company in that trajectory, with the uniqueness of the Extended Platform as a place where every lender in the U.S. should have some kind of version of that. Us taking hopefully 70+% of that market share, we could actually see how this company could create hundreds of millions of dollars of GAAP net income, if not even on the long run of the billions, by driving all of that that is strongly embedded by the technology unique capability that is keeping the margin and the service quality to our most important customers over time. That's how you should think about lending and the GAAP net income and the growth and how we think about over a cycle in Pagaya. That concludes the session. Very interesting. Always fun to catch up and hear about the business. Thank everybody in the room for participating and have a great day. Thank you very much, everyone. Thank you very much, everyone. Thank you so much.