Good morning and welcome to the Beforepay Full Year 2025 Investor Webinar. My name is Danny Younis, and I help with investor relations for Beforepay. With me this morning, we have the CEO of Beforepay, Jamie Twiss, the CFO, Laavanya Pari, and the Head of Finance, Shreya Prakash. Before I hand over to Jamie, just to note that we will be having a Q&A session at the end. If you have any questions, please type them into the Q&A box that you see on the bottom of your screen. I would now like to hand the webinar over to Jamie. Please go ahead. Thank you, Danny, and good morning, everybody. Thank you all for joining us as we release our full-year results. I'm delighted to be introducing Laavanya Pari, our new Chief Financial Officer, and, as Danny noted, also joined by Shreya Prakash, our Head of Finance, who was previously our interim CFO and helped produce these numbers. I'll cover off a few of the highlights to start, and there are a few highlights to cover off. Laavanya and Shreya will then go through some of the more detailed numbers, and then I'll wrap up as we head into questions. As Danny noted, you can ask questions at any time during the webinar. Just to start off, this was a very, very strong year for us. I am really pleased with how FY2025 finished up. I think, obviously, we'll work through the numbers, and you'll see some very, very strong outcomes there. I think what we saw over the course of the past year was all the work that has been occurring over the last six years really falling into place, and I think pieces of work that got started quite some time ago in terms of how we think about the risk modeling in terms of the product, all that grind and effort and all that attention to detail, we're really seeing that come good and drive the business forward, so really pleased with these results, and even more so, I'm pleased that they rest on a very solid foundation of the capabilities that we have, and I think we are very, very well set up for the future, so really pleased with where we ended up overall. I think just to kind of recap for anyone who's new in terms of who we are and what we do, so as many of you already know, our business has two sides to it. The overall company is Beforepay Group, and within that we have Beforepay, and that's our mission-driven lending business in Australia, and then we have Carrington Labs, which is our enterprise risk analytics business, which operates globally. Again, as many of you know, Beforepay, our lending business, that's the heritage of the company. That's still very much the core in terms of what's driving the financials today. The original vision behind the lending business, which continues to be the vision today, is to provide a safe and affordable alternative to high-cost or unsafe lending practices with a Pay Advance product, our flagship product, that is safe and affordable for customers, priced in a way that is both helpful for them and also protects them. We also offer the Tax Refund Advance product through our partner, H&R Block, and we have our larger and longer duration personal loans as well. The core of this business is, of course, that very strong risk management capability, which is also what drives Carrington Labs, as well as that very high level of automation that comes because we are a genuine digital-first cloud-native business. We write tens of thousands of loans every week with a very small team because the vast majority of our loans go through no human intervention. So that's our lending business. And again, that continues to be at the core of the financial numbers you're about to see today. We're also, as many of you know, extremely excited about our Carrington Labs business as our enterprise risk analytics business. And what that does is that takes that core IP around risk management, it puts it in a product wrapper, and it offers it to other lenders to take advantage of that pretty distinctive capability that we've got, primarily overseas. The client base is very heavily weighted toward the United States. You can see here on this page the core offerings that we have. And essentially, the way to think about these is these range from very deep, bespoke, customized models for lenders with significant scale and large data sets so they can get some of that same pretty distinctive predictive power that was built for the Beforepay business, but bespoke to their market, their lending experience, their product economics for customers, through to lighter touch scores that can be quickly stood up, especially for smaller lenders or those with less data. And I'll talk a bit more about Carrington Labs, but it's been a very transformative year for Carrington Labs, and we are really excited about where that business is going. To briefly cover off just a few highlights, and I would love to run through all of these, but I want to steal a thunder from Laavanya and Shreya. I'll start by just covering up a couple of things on this page. The first and most obvious one is the very strong profit outcome. So AUD 6.7 million in net profit after tax, that's up 74% year on year. Really, everything contributed to that. Obviously, top-line growth, but as well, very strong margin outcomes driven by a really step change, I think, in our risk management capabilities and the way that we do that heavy data-driven analytics around credit and around loan and limit configuration. So the profit outcome was a really remarkable one. And again, I think I'm most pleased that that sits on a very solid foundation of capabilities and assets in terms of the customer base that we've got, the position that we've got in Australia. I won't speak to the other numbers at this point, so we're about to go through them in more detail. The other thing I would mention in terms of a highlight from this year, which isn't on the page, is the progress of Carrington Labs. So as those of you that have followed our story know, there's been a flurry of announcements of new clients and partners in recent months. I think the growth in that commercial activity, of course, speaks for itself. And as I've said before, that rests on quite a strong pipeline and a high level of interest. I think we continue to find that the Carrington Labs capability is globally distinctive. What we do is difficult, and we do it well. And while we're never complacent about competition, we see very few other businesses even trying to build that capability. And I think we genuinely have quite a bit of white space in that market right now. It's been a tremendously strong year commercially for Carrington Labs in terms of growth, in terms of the pipeline. Then the other thing, which is probably less visible from the outside, is I think we've really sharpened up the proposition as to exactly what that product is and how we've taken that pretty significant capability and placed that out to the market and offered it to clients. We've really kind of sharpened that up. I think we've got a very clear go-to-market strategy at this point. Then just building the underlying infrastructure and assets from our side so that clients can easily integrate with us, work with us, and we can train models for them in a bespoke way in a highly automated fashion. So there's been a lot of progress both in that kind of top-line commercial momentum side, but also in terms of the product, the product capability, how we define that, and then how we've delivered that as well. It's been really transformative over FY25 as well. That'll hand over to Laavanya to talk through some numbers. Absolutely. So what we can see is that our total advances have actually increased by 14%, with our default rate decreasing to 1.1%. And what that's translated to is a net transaction margin, which has continued to improve over the half years. So we're seeing that improvement. If we jump into the next one, we see that improvement resulting in the margin continuing to increase while our operating expenses have flattened over time. So we've really been able to optimize the business, improve, and continue to grow without having that impact our operating expenses and really sharpening that net profit that Jamie talked about earlier. So all of this is translated to that improved net profit number. So with our total advances going up by 17%, and really, it's a seasonal business, so the half year that you're comparing to is H2 FY2024. You can see that 17% improvement in total advances. However, our actual average advance has stayed pretty flat, so a 3.4% increase, which is quite small. So really, what that's telling us is that the volume of our advances have really increased. So if we jump into the next one, so you can see our active users. So that's really translated into an increase in our active users. So that's gone up by 12% compared to H2 2024. So that's really where a lot of the improvement in the revenue has come from. So the increase in the active users rather than actually an increasing average advance going out to customers. At the same time, as you saw in that first slide, our loan defaults continue to flatten. We're down to 1.1% for FY2025, which is down from 1.4% in FY2024. You can see that line just continuing to flatten out both from a gross defaults and a net default perspective. Of course, it's a seasonal business, so that obviously continues to flatten. We continue to optimize our models. I'll just hand it over to Shreya. Thanks, Laavanya, and hello, everyone. Just to continue what Laavanya was saying as well, other contributors to net transaction margin include funding costs as well as direct service costs. I'll talk through funding costs first. Assuming 26 days as our average loan duration, which is typically where it tends to be, as well as a 15.31% in cost of external debt facility and a maximum loan-to-value ratio of 80%, our effective third-party funding cost is around 87 basis points. Now, our actual cost is, in fact, a lot lower, and that's really a function of how we utilize the debt facility. What this shows is our cost of funding is, in fact, quite efficient relative to the size and nature of our product. And in addition to this, we also paid down a portion of our debt and set up a AUD 7.5 million revolving supplement within our existing facility. That really gives us more flexibility with our funding, allowing us to deploy excess cash when available to grow the loan. Moving on to direct service costs. What we see here is our direct service costs have really cost to facilitate a Pay Advance, including things like KYC checks, bank transaction scraping, direct debits and credits, etc. And over the past three years, we've seen a consistent decline in these costs, going from about AUD 1.80 in the first half of FY2022 all the way to just AUD 0.73 in 1H FY2025. So what we see is that with increasing volumes, we've, in fact, been able to spread our fixed costs instead of having them increase. In the next couple of slides, I'll keep it quite brief, just focusing on the key metrics. So as Laavanya and Jamie mentioned, our net transaction margin for the year was AUD 25 million. Looking at that a different way, the group charges 5% for our advances, and that's our revenue. When we deduct our net defaults of 1.1%, our funding costs of 0.6%, and direct costs of 0.2%, that gives us a net transaction margin percentage of 3.1%. Once we deduct our operating expenses, we have a profit for the year of AUD 6.7 million, and that compares to 3.9 in the previous year, which is a 74% increase. The business continues to rest on a strong balance sheet. We had assets of AUD 76 million and an equity position of AUD 39.3 million. On the debt facility, as of 30th of June, we had drawn AUD 30.9 million and had an undrawn balance of AUD 24.1 million. Moving on to cash flows, we had positive net operating cash flows of AUD 4.9 million for the year compared to negative 4 in the previous year. We ended the year with a cash at bank balance of AUD 14 million. That excludes AUD 5.2 million in our third-party settlement accounts as well. The total cash balance for FY2025 was, in fact, AUD 19.2 million. It's worth noting that the decrease in cash from FY2024 to FY2025 reflects the repayment of AUD 7.5 million in debts with the injection of that revolving supplement. So thank you, Shreya. Thank you, Laavanya. So coming back to where to from here. So we've had a really remarkable and very strong year. And when we close the books on the year, we high-five, we go out for drinks, and then we think, okay, how do we deliver an even better FY2026 and where to from here? So looking forward, I think if I look at our business across the three different things that we do, Pay Advance, including Tax Refund Advance, Personal Loans, and then Carrington Labs. On the Pay Advance side, that business is working well. I think we understand how to deliver that product in a responsible and positive unit economics way. We will continue to optimize it. There is always so much more that we can do. We look forward to continuing to grow that. We look forward to continuing to invest in the risk models in particular. We are still finding so many things we can do to get better at risk. I think that's something I think is really baked into the DNA of our company, and doing that in a very cost-efficient way. As you've seen, we genuinely deliver the pay advances with a fixed cost model, and as a result, we think that while we will continue to invest in the overall business, particularly the new initiatives, we can continue to get good, very strong unit economics out of pay advance while we look to continue to grow it. I think just to put a bit of an advanced notice on this. I think as we think more about the economics of the pay advance business, we do talk about that active user number. What we're finding is the economics are really driven by sort of the upper third or so of that user base. So one of the things we're thinking about more is that value per user number. And so we're probably less focused on the smaller dollar end of that base, the active user number, which is heavily influenced by that as well. So we are thinking about that whole of value approach for the pay advance business and probably less about that headline user number over time. On the personal loan side, so we launched this last year, and we've had a period where we've tested it and gotten it operationally robust and worked through the risk, collecting data on performance. I think FY2026 is going to be our year for personal loans. We think that we're going to shortly be in a position to start growing that business more. And I think when we look at the size and scale of the personal loan business in Australia, that's a very significant market. It's got attractive economics. And we think we have a very strong right to play and win in that space. We know a very large portion of people taking out personal loans in Australia already. As you would have seen on that highlight slide, we have more than 1.7 million registered accounts. We see a significant portion of this volume already through the transaction data that we collect. We think that we have good access to that market. We are very strong at risk. We think that we are in an excellent position to put in place compelling offers based on our sharp understanding of customer risk behaviors. Personal loans, I think FY2026 is absolutely going to be our year. Carrington Labs continues to go from strength to strength. The challenge that we've had, as I've said a number of times, is the pipeline is, if anything, almost too full. The thing that holds us back there is mostly just the decision-making and documentation timelines of our prospective clients, which can be lengthy, especially for banking clients and other heavily regulated lenders. That pipeline looks very strong. Again, I never want to. It's hard to predict when any particular opportunity will come out the other end. Some of the opportunities may be announceable and some may not. We continue to feel very, very confident about this business. I think we will continue to see good momentum there. I think the heavy lifting that we've done on the delivery of the product and that kind of sharp product proposition, and of course, there will always be more work to do, but I think we have set ourselves up well on that product as well. If I think about the year we had in FY2025, I mean, that was self-evidently a fantastic year for us, and I'm really pleased with that. We are now very focused on FY2026 and delivering a fantastic outcome there. I think across all three lines of our business, we are well set up to do that. So thank you very much. And with that, we're happy to move to your questions. Thank you, Jamie. We will now move to the Q&A session. Once again, if you have any questions, please type them into the Q&A box at the bottom of your screen. Okay. We've got a couple of questions from Larry Gandler at Shaw and Partners. They're both financial questions. The first question is maybe a little bit of clarity around the movement in the other receivables, please. Yeah. So by other receivables, Larry, I assume you mean the non-customer receivables. So in the receivables line, we have—I want to say it's 58, of which 53 is the gross customer advance book and 48 is the net. And then there's about five and change of other receivables. That's mostly our cash that sits in a third-party account that, from an accounting standpoint of view, we don't count as cash, but we do include it in total cash. So when you hear us talk about that total cash number, it's a non-GAAP, non-IFRS term. Usually, the difference between that and cash at bank will be that other receivables. It mostly sits in that third-party settlement account, which is the account that we use. That's where money is sitting, waiting to go out to customers when we generate a payment instruction upon a new Personal Loan or Pay Advance being issued. And we also do have some in a separate bank account, which is used to true up the net balances we have with our lenders, reflecting the advance rate of that facility as well. Thank you. The next question from Larry is a... Move around at any given point in time. This is just what happens to be going on at that moment and when we take that snapshot for quarter-end or year-end. Yep. Thank you, Jamie. The next question from Larry is around how you calculate Cash NPAT. So there's a little few moving parts here. So the Cash NPAT of AUD 12.2 million is it as follows. You take the AUD 44.1 million in receipts from income. You subtract payments to suppliers of AUD 18 million. You subtract net interest of AUD 4.7 million. And you subtract loans written off of AUD 9.2 million to get to that 12.2. Can you maybe clarify that, please? So do we publish the 12.2 or is that the EBITDA number? Yeah. Yeah. Okay. That's it. Yeah. Shreya, do you have any comment on that? No. I think Larry's on the right track in that, yes, it is indeed receipts, less operating expenses, so that includes paying to our suppliers, employee costs, etc., as well as other non-operating expenses, and that really gives us that 12 million in EBITDA. Great. Okay. The next question is around Carrington Labs. Can you maybe talk to Carrington Labs' revenue profile in the future and what the pipeline looks like? Yeah, so let me just start by talking a little bit about how we charge clients, and of course, these can be quite large enterprise contracts, so things may vary, and often there's a negotiation at the end of this, but this is a software as a service, a SaaS product, so we primarily charge off the back of usage, and again, there may be custom setups for various reasons, but essentially, your client, we have trained a model on your data. We then are hosting that model in the cloud, and when you say you're using this for a loan application for recommendation, you will call our API, you will send data to us, we will run that and then send that back, and essentially, the pricing model is we will charge you a certain amount of money for each one of those decisions. There are other uses, so we may do ongoing portfolio monitoring that's charged more on a per user per month kind of basis. We do often charge implementation fees. We may charge proof of concept fees depending on the nature of that relationship. We generally look to have some sort of monthly minimum in place reflecting what we think the volume will be, but just to make sure that actually the usage levels land where we think they will be. But essentially, it's that volume-based charging. I think in terms of the revenue profile, so it's always going to look quite sort of, it's going to be quite lumpy or maybe a bit of a staircase look because these are individual clients. And some will be mid-sized, some could be very large indeed. And so it's a bit hard. I think with the Pay Advance business, you look at the revenue over time, it's a very smooth straight line, and this will be more of that staircase pattern, and so it's a bit when clients sign and when clients then in turn go live, which again is more a reflection of their internal documentation processes and approvals and technical implementation. That's a bit unpredictable, but we do expect that based on the health of the pipeline, we do expect that there will be more continued good news in terms of, again, some will announce, some we won't, but that will flow through, obviously, to the revenue profile as those clients go live. Okay. The next question is around the personal loans product. So can you maybe provide a little bit more clarity around the existing users and the volumes? Yeah. So the existing users are current Beforepay Pay Advance customers or, sorry, people who have already taken out a Pay Advance Beforepay and then repaid. And the reason we do that is we just understand those customers, their data and their risk very well. So we haven't yet opened it up externally. We haven't yet even indeed opened it up to everybody internally. We're still looking at a subset of our user base. But I think in terms of volumes and numbers, the way we think about that to this point has been more along the lines of what's the number of loans that we should be issuing in order to get a better sense of the credit performance and to the extent to which elements and variables that are predictive for the Pay Advance are also predictive for the Personal Loan. Obviously, we would like to really get that credit right before we start scaling, so the number is not especially high to date, but in large part, that's because we haven't been driving personal loans with that direct commercial outcome in mind. We've been driving it with much more of a data collection outcome in mind. We'll see what happens when we turn it on more fully and start to scale that, and indeed, when we start to look at longer durations and larger limits, we do expect it will be material to the overall group at full strength once it gets its momentum going. Okay. A reminder, if you have any questions, please type them into the bottom of your screen. We've got two further questions. The first one is around the net default. So how do you balance the very low default rate against customer growth? Yeah. So I'm going to interpret this question as an excuse for me to go down a little bit of a data science rabbit hole, which is something I look for in every results announcement. So I'd like to thank whoever asked that and apologize to everybody else. So I'd answer that question in two parts. The first one is we try to say yes as much as we can to both existing and new users. So we are a very much mission-driven organization, and the goal of having this lending product out there is to give people a better alternative. So whenever we can issue an advance to somebody in a way that feels aligned with our values, which ultimately means it has to be helpful to them. So it has to be something we think is going to leave them in a better place than if they aren't at it. And of course, it's sustainable for us. So if the expected value of that is hopefully positive and if not tolerably small, we would like to do so. Now, in order to be able to do that, we vary the size of those advances quite dramatically. So as many of you know, the maximum advance size is AUD 2,000. The minimum is 50. So we will absolutely advance somebody AUD 50. They will pay a flat fee of AUD 2.50 for that. And I think that's, again, very much aligned with our mission, but also aligned with getting people on the door. And if they can demonstrate good repayment behaviors on that and perhaps some others, then that limit may go up over time. So the reason I mention that is when we think about the default rate and customer growth, we generally find we don't turn away that many customers off the back of risk considerations. We turn a lot away from on an eligibility basis. So either, I mean, first of all, if you haven't completed the process, you haven't synced it to your bank account, been through KYC, and so on, obviously, you won't be able to use the product. We do have some eligibility around you have to be employed. The majority of your income has to come from employment. You have to be in Australia over 18, all those sorts of things. We also do have some values-based eligibility rules as well around levels of gambling and levels of debt to make sure, again, that this product is healthy. Many people get screened out in that eligibility stage, but the significant majority of people, if they are eligible, will receive something, even if it's only that minimum AUD 50 advance. I don't think kind of risk settings have a huge impact on that customer growth number. Kind of, as I said a little while ago, when we think about kind of the economics of the business and the momentum of the business, I think that overall customer growth number, that active user number, that feels less important actually than kind of that core of how many of those less risky customers who have the AUD 500 and AUD 1,000 and AUD 1,500 advances. That's actually what really drives the economics of the business. There we think very explicitly about the trade-off between credit risk and essentially average advance size and revenue growth, net transaction margin growth in particular. The way that we do that is we do a lot of quite sophisticated modeling around for each customer who's in front of us at this point in time, whether it's because they're coming in as a new customer or for existing customers, we'll just rescore them in the background every week for the most part and recalculate a limit so that they come back in with our limits ready to go. We will look at their expected elasticity of default, by which I mean if we give them a small advance of AUD 50, what we expect their default rate would be based on this statistical modeling that we do, or all the way through kind of the other end, those very large advances, and generally, we find that that's monotonically increasing, so the larger the advance, the higher the default rate. Then when we map the marginal unit economics on top of that, the variable contribution, we usually find sort of kind of an arc like this where at the small end, low default rates, but not very much revenue. At the big end, lots of revenue, but high default rates. And somewhere in the middle will be that global maximum. And subject to kind of our values constraints, some of our servicing rules and other things, that's the limit they will get. In general, as the model becomes more powerful, we should take some of that benefit in the form of lower defaults and some of it in the form of higher limits. I think if you look back over the last year, I think our risk modeling has significantly outperformed our expectations in terms of the quality of its power. And so as you can see from what Laavanya was saying earlier, the net default rate fell quite substantially, and the average advance size stayed roughly constant. So if I look forward, I would say we probably actually performed better than we thought we would. And as a result, we probably underloaned to many of those customers. If you look forward to FY2026, that's something we'll be taking a look at is what is that balance between not so much customer numbers, but more kind of that average advance size for those customers against net default rate. And we don't have a target in mind for either of those numbers. We target the highest possible variable contribution on each loan based on default elasticity. Very comprehensive, Jamie, and thank you for that. There's actually been a follow-up question on that default rate, and I think you've answered the first part of the question around do you think the 1.1% default rate is too low, but the follow-up question is, can you amend the Carrington Labs program to increase this? Sorry, can we amend the Carrington Labs program to increase? Increase the default rate. So I might be misunderstanding what the question means around NTM, but I will say so Carrington Labs and Beforepay use essentially the same technology and that same sort of underlying analytic capability, just obviously deployed in different ways for different products and different customer segments and so on. I think, yeah, again, we never target a specific default rate, and I think the 1.1% is remarkably low and, yeah, arguably too low. So again, we're not looking for a specific number, but we will kind of work through that balancing routine to optimize our Net Transaction Margin subject to kind of all of our values and other rules. And as a result, you might well see it go up in FY2026. If it does go up in FY2026, it will be off the back of a revenue increase that on a net basis means we are better on the scores. Okay. The next question seems to be pointing to the future, if I understand it correctly. So have there been discussions around separating Carrington Labs from the core Beforepay business? So I'm presuming that's in the future when Carrington Labs scales up. Oh, look, I think the group is working pretty well as it stands. I think, obviously, Carrington Labs and Beforepay rest on a very kind of similar technology stack capability. I mean, of course, as I always say with any kind of large strategic activity, we'll always look at the opportunities in front of us and make the decision that creates the most value and is most appropriate at the time. But that's probably all I have to say on that. Yep. Probably another one for you, Jamie. So are there any lenders in the U.S. offering a similar lending model to Beforepay that would benefit from Carrington Labs' offering? Yes. Yes. This is something we think about quite a bit. So I'll answer it in two parts. So one is absolutely there are a number of short-term lenders in the U.S., and I should say non-predatory short-term lenders. So Carrington Labs doesn't work with kind of a traditional predatory payday lender or anything like that. But there are folks doing similar things, often quite digitally. Some of them are sometimes embedded in other financial institutions. Some of the large neobanks will have a similar lending product. And yes, that's something we think about quite a bit because obviously we know that kind of credit, I mean, I think we know that kind of credit better than anyone in the world. I've talked to everybody in the world, but we spend a lot of time looking at that. Now, I will also say that the Carrington Labs product, one of the things that's really powerful about it is so what we're offering lenders is not, "Here's the risk model that Beforepay uses. You can use it too." What we are offering them in our flagship kind of product on the Carrington Labs side is, "Here is the intellectual property, the code base, the feature library, the training pipeline, the limit-setting algorithms, the default elasticity." Here's all of that stuff that you can see is working because we lend our own money with it every day over Beforepay. But we will take all of that, and we will run your data, your product economics through that entire process and pipeline. At the end of that, you will have a model that reflects your particular lending experience, customer segments, product setup, and so on. And so it is a broadly applicable product really across the lending spectrum anywhere where you have a meaningful number of loans. So anything in consumer, I think you can add a lot of value, small business lending up through probably about mid-corporate lending. And then loans are too big and too bespoke, and there aren't enough of them, and it sort of trickles out from there. But I think in that sort of mid-sized business lending all the way down to every piece of consumer, we can add quite a bit of value to a lender. Okay. There's a couple of follow-ups on Carrington Labs as we expected. So I think the first one is, what results or improvements are U.S. lenders seeing since using the Carrington Labs platform? Yeah. So I think we'd love to do sort of a full case study write-up of one of our clients. That's not something that's been appropriate up to this point. I think I would say that the live clients, we are seeing things work as we would hope and expect. And lenders are coming at this from all sorts of different directions, different things they're looking to do. And one of the great things about Carrington Labs is you can take the benefit really kind of any way that you want. We shift that efficient frontier outwards. And then if you want to take that through lower defaults or kind of higher approval rates or higher average balance or some mix of those, you can. But yeah, I think of all the things that I kind of think about and worry about, the possibility that the Carrington Labs product doesn't work and isn't a significant uplift, that is not on that list. I think we feel very confident in the quality of that product. And I think the live experience that we've had with our clients to date fully lines up with that view. Yeah. The next question, I think you've just answered it, Jamie, but I'll ask it anyway, and you can pass on it if you like. Can you outline the biggest risks Carrington Labs faces, and what keeps you up at night with this part of the business? Yeah. Well, I think I sort of answered what doesn't keep me up at night. I think with Carrington Labs, the biggest challenge for us there is the process of helping a client go through that first conversation all the way through to ink on paper. I don't worry about, can we actually build the model? Will the model work? That stuff, I mean, of course, we're very focused on it, but that is, I think, pretty well demonstrated. But these are large organizations. They have kind of lots of stakeholders. We're a small company. So just kind of moving people through that phase, negotiating contracts and things like that, I think that will probably always be our biggest challenge. Right now, we are also still in that early boost phase where we are still doing work on the product and the pipeline and the API kind of sandbox and all those sorts of things. So there's still work to do there. But yeah, I think that work, I think we've made great headway, and we'll continue to get through that. The biggest one is just that actual sort of non-analytic, non-technical side. It is always going to be just potentially a fair bit of time and work to get clients up and running. Okay. We've just got another follow-up that's just been received on Carrington Labs. So is it possible a large customer win for Carrington Labs could significantly increase the profitability of Beforepay? Yes. Okay. Moving away from Carrington Labs then. So the next one, this is an interesting question about customer acquisition cost. So you've previously disclosed customer acquisition cost numbers. Can you maybe provide some updated values for the past two quarters and fiscal year? So, I don't think we will put out a number that we haven't put out separately publicly. There's no particular reason, and we should probably do that for future releases. I'd say it's not, to the best of my knowledge, I don't think it's materially different from the sorts of things we've published before. Again, we don't target a specific acquisition cost. And of course, we do have a marketing budget because that's the way companies run. But the way we really think about this is we want to acquire any customer where the expected marginal cost to acquire them is below their expected marginal lifetime value. And then the acquisition cost and indeed the marketing spend is essentially a byproduct of that. If you look at marketing spend FY24 to FY25, it went up because we were better able to acquire customers at that value-creating level. From our point of view, that's good news. That's obviously what's powered a lot of the growth. I guess the thing I would say is as our customer base continues to become more affluent, as we continue to kind of really understand and focus on those pockets of value more, and of course, as our higher value personal loan product starts to grow and scale, you might see that number come up, but it would come up off the back of each individual customer still being demonstrably value-adding to us on an expected value basis. Okay. We're on to the final question. Let me just double-check. Yep. The final question. That's a good way to finish too. So can you maybe just provide an update on the July-August six, seven week period year-to-date trading? Yeah. So I think it's in line with expectations. No particular surprises. I think those of you that have been following the story for a while would have a bit of a feel for our seasonality, which is Q1, the July, August, September quarter, tends to be a bit slow in terms of particularly new user acquisition and maybe a little bit slow in usage overall. And that's mostly off the back of winters getting quieter, but also particularly people are getting their tax refunds. And so we just see kind of less of that new user growth in general. And I'd say, again, no surprises this year in terms of what we expected. On the flip side is Q1 is also very strong from a credit outcomes point of view. Because people are getting their tax refunds, we see a lot of kind of recoveries of previous defaults where people have a bit of spare cash and settle up there, and again, I'd say everything we're seeing is broadly in line with expectations there. Excellent. So that concludes the Q&A session. I will now hand back over to Jamie for any closing remarks. So again, to finish where I started, we were really, really pleased with the progress the business made in FY2025, both in terms of the outcomes and obviously the numbers and the profit growth and figures speak for themselves, but also the fact that that's built on a very solid foundation and sets us up really well for FY2026. As I mentioned, we do feel very good about what the next year is going to bring us. In part, that's the core business continuing to perform well, but I do think both personal loans and Carrington Labs really are in good position to hit their stride over the coming 12 months. So I want to finish by thanking Shreya for the work she did as Interim CFO before Lavanya arrived, and she and the team have worked very hard to get these numbers together, so thank you, Shreya. Of course, thank you all for being on the journey with us. I know many of you have been shareholders for quite some time, and we're really pleased that we've been able to really get the company in the position that we want it to be and setting up well for future success. Again, I feel very confident that we are well set up for the future and that we have a good several years ahead of us. Thank you all for being with us, and enjoy the rest of your day. Thank you, Jamie. Thank you, Beforepay, and thank you to all the participants. You may now disconnect.