Transcription:
Bonnie Sinnock: (
Hello, and welcome to our discussion on How Far Are We From Instant Mortgage Approvals? I'm Bonnie Sinnock, capital markets editor at National Mortgage News, and with me today is a team of experts our digital mortgage conference organizers have brought together to address this topic, including our sponsor, who we thank for backing our discussion. Each of our experts will be introducing themselves as they speak, so you'll hear more about who they are later, but before that happens, I'm going to give you a couple notes on how we're gonna play the How Far Are We from Instant Mortgage Approvals? game today, and one is that in this discussion, the audience is encouraged to ask relevant, articulate and constructive questions in the chat at any time. So you don't need to wait until the end to ask them. We will try to get to them as we go along, and while we may not get to every question, because we wanna keep the discussion moving, we will do our best. The other thing you need to know, and that you might suspect if you read the description of this panel, is that we're not going to talk about how far we are from instant mortgage approvals in general, or across the board, we're going to talk about how the answer to that question might differ depending on the customer's needs, what the particular product at hand is, and perhaps what loan channel is being used. On that note. I'd like to ask for someone from the panel who can talk about the different needs borrowers have and how you can address that with technology to talk about how that process works. Is there anyone who can address that question?
Nate Longfellow: (
Yeah, I'm, I'm happy to, to jump in, uh, uh, first on the topic. So I, I think there's a pretty substantial shift that we've all been going through for few years in mortgage lending, which is, um, sort of the realization that nobody wants a mortgage customers don't really want amortgage. What they're really trying to do is navigate life. And when we realize that we realize that our capabilities, we need to give them need to align with what they're trying to accomplish. So I think it all kind of relates very much well to, you know, into the decisions, but shifting that experience to more about what our customers are going through, uh, which is home ownership. In most cases, us usually using the home to achieve something relevant in their life, um, moving to, for, to, for their family for, for all sorts of good reasons.
Nate Longfellow: (
And so giving them capabilities that allow them to navigate their financial future is where we wanna continue to move to. And in doing it, doing that, we get this nice symbiotic relationship with our customer. We give them value to the things they're trying to accomplish in life and in doing so, they also give us access or permissible purpose to leverage their data in a meaningful way to give them insights on their spending habits, insights on what's going on in their community or their neighborhood insights on their, uh, equality and variety of other things. And in doing so, not only really helping the customer, um, along the journey that they're on, we're also helping, um, them and us through, you know, achieving more instant decisions because the more they allow us to leverage their data and understand them, the more we'll be able to, to, uh, you know, make that process more frictionless when they are ready for that transaction. It's much more to talk about there, but that's what the shift that I see that's, you know, I, I think a lot of people have been doing it for my customer experience perspective just to really align more closely with their customer, but there's there, it really ties deeply into instant decisions and how you automate processes for them as well.
Mohammad Rashid: (
Oh, go ahead. No, I actually wanted to add some color to what Nate said, which is basically that today, the paradigm is that we do a, a customer or a borrower comes to you and applies for a particular loan. Um, but we could turn out and we've spent actually millions of dollars, billions of dollars in changing that journey, right? The customer journey, the persona mappings, the application intake process, uh, we should turn it on its head and say, well, maybe the customer provides you with, with permissioning and there's data available for that per uh, for that borrower continuously for a, uh, continu is decisioning, right? A real time decision and a continuous decisioning depending on their life cycle. So bringing to bare technologies that are available today in the market, we can figure out where the borrower is in their financial journey and be able to inject, push rather than pull, um, the right product, the right, um, as set the right decisioning for their lifecycle.
Mohammad Rashid: (
And given that a lot of this data is available, rather data verified sources are available. It's a matter of integrating that data, um, decisioning on that data, profiling that data, it's a consider a financial DNA, right? Uh, for that borrower that's available and permissioned by the borrower or two particular lending institutions. And they continuously basically provide signals to the borrower saying, you have this available today. This opportunity is available today. A lot of borrowers don't even know that they can afford a home or afford some, any other type of loan right. Rather than apply for it and, and get a push, get a pull.
Dani Hernandez: (
Yeah. And I think also, um, like the amount of data that we've got now, I think one of the things, when you say instant approval, um, or, um, we talk about, uh, like, you know, dockless approvals or these kind of things is that people look and they think, oh, what's gonna happen. Are we going back to 2008? And I think today, um, being able to utilize that data, to make these decisions, um, quickly, um, and sometimes without, uh, human and involved, I think that there's actually far less risk because this third party data, um, is not coming from someone who's an interested party. And then at the same time, um, if you can remove, uh, human error or from this, the entire process, I think that's very important as well. Um, and I think the part that we've kind of stalled at, um, in our industry is that we have focused a lot on the upfront borrower experience, but then the back end, a lot of mortgage companies, like you basically have a digital application, but you don't have an actual digital origination process the whole way through. And so I think, um, that in order to get to this instant approval piece, it's, you have to, um, automate the backend processes as well,
Josh Hager: (
Just to, if I could just piggyback off of, of what everyone has spoke about. I think also, you know, where a day and age where the consumer or the borrower is looking for authenticity in their experience and from the lender that they're coming to, and really looking for the transparency, whether it be the education on the product they're signing up for, and them being able to provide everything up when they need to, to get that instant approval or that pre-decision, um, it, it's gonna be very important to allow us to continue to leverage and continue moving all of those technologies that we need to seek permissions from the borrower to give us to move closer and more forward towards that instant approval.
Bonnie Sinnock: (
Can you talk a little bit about, uh, how that plays out at your company, Josh, you focus on a particular product, right? You focus on home equity products and where do you think they're farther along than other products in this quest for instant mortgage approvals?
Josh Hager: (
I, I do think that, you know, when you speak about an instant mortgage approval or, you know, I know Nate likes to call it the pre-decision, um, you know, I, I think we are a little further along than the first mortgage world, so to speak in the fact that, you know, the GSE, um, are pushing lenders towards this incident approval, to where on the home equity side, we're not so much leveraged by the GSE. We don't always, we can use more technology by going AVM route. You know, so where we do a button is once the consumer of the borrower completes the application, we, the machine starts pulling data, whether we have the work number available, we are pulling all kinds of, you know, third party information for ourselves, um, and appraisal models to be able to really turn an, a decision over to underwrite the underwriter to really then give the, the, the final decision so to speak right the approval. So how far are we from an instant approval at button we're not too far off, we are continuing to leverage our technology, um, to really be able to get towards an instant approval. I'm pretty fast, uh, looking at like around Q2 Q3 of next year to have a,
Bonnie Sinnock: (
The other loan product I was wondering about is, you know, given the housing market, we have recently, there's been the rise in the cash offer loans, if you will. And those by nature are supposed to be very instant. Right. Uh, can anyone talk about how instant those really are now and how that plays into this question of how we are to instant mortgage approvals?
Dani Hernandez: (
Yeah. So, oh, go ahead.
Josh Hager: (
No, go ahead, Danny. And then I'll follow.
Dani Hernandez: (
Uh, so, um, at up equity, our signature product is our all cash offer. And, um, what we do essentially is, and we, first of all, we don't charge fees for this. Like this is service that we, um, use to allow borrowers to compete with, uh, all cash offers. And so, um, in order for us to give that guarantee and sign that contract with the borrower to guarantee that we underwrite our borrowers up front. So, um, we have a system, we pull the work number, we have their credit, we get a VOA, um, and we verify the income asset and credit of that borrower. Um, and that is all done instantly without any, uh, human, like actually verifying these things, our, our computer or our APIs pull this stuff, um, and then run Aus. Um, and then we have an, a writer review and look at that, but I mean, our, uh, SLAs on that are usually 24 hours or less.
Dani Hernandez: (
Um, and then, um, once that part is done, essentially, all we have to do then is underwrite the property once our borrower finds, uh, property that they wanna buy. Um, and really, I think the part that is, is the hold up for us is the appraisal process right now, appraisals take so long. Um, we would love to be able to do a 10 day close, no problem, except that we have to get this appraisal. And, um, we're based out of Austin, which is a crazy housing market right now. And so I would love to see, um, the GSCs, um, or some more, uh, innovation around that. Uh, the part of the process
Bonnie Sinnock: (
Are other folks also finding that, that the appraisal is one of the sort of me pieces of the puzzle, if you will.
Nate Longfellow: (
Yeah. I think, I think to Danny's Danny said a few things, things earlier, too, that I think are worth re revisiting as well. I, I think when we talk about instant, uh, you know, instant approvals, we really have to think about what that really means. Right. And what does it mean for the customer? Um, so, so when you think about it, I, I think everyone appreciates that given today's, you know, process and mandates, um, that, uh, you know, the credit decision, if you will, they cut customer's ability to pay and their credit worthiness is the more upfront part of that. Right? So for, for, for us, we, we like to break it into, and Danny's sort of touched on this there's segments of innovation that we need to go after to really make this thing real for the customer. And it could be the product is one example there, the financial instrument, I should say, uh, is one dimension, can you create products and be able to take them to market?
Nate Longfellow: (
Do you have the portfolio or secondary market that could do that, that allow you to, uh, make decisions with, with reasonable, the right appropriate levels of risk for the investor that might take a lot of friction outta the process for the customer. So that's one area of innovation and the rest is in, you know, in, in various segments when around a borrower's, you know, customer's, you know, credit, worthiness and their ability to pay and then, uh, the collateral. But I think it also begs the question, what are we really going after here? What problem are we really trying to solve? Are we really trying to solve a time problem maybe? Or is the time just a, just a byproduct of the real experience we're trying to give what I mean by that is customers in my opinion, and we don't have to debate things that we can, we can go past, but, um, is, is it's really about certainty the customer.
Nate Longfellow: (
They're looking for that. What I would always refer to and we always refer to, and we use it at various companies too speed to certainty, right? How quick can we give the customer comfort that I can afford this type of money? And I've substantiated my, my income to know, I, I can get this amount of money. And then the other dimension, when it comes to the collateral is what kind of comfort can we give them in transparency? And that we can give them into the collateral and what the cloud value may or may not be. We can, you know, the way it stands today. There's not really, obviously there's waivers. We can, uh, collateral waivers we can pursue, which are awesome from an experience perspective, but not every customer gets that. So what transparency can you give them that lets them build their own level of comfort into, oh, the appraisals likely gonna come back are not gonna come back.
Nate Longfellow: (
Not that we would realistically ever tell them what it might be, but you can give it a transparency for them to build their own comfort, their own level of certainty. And that's what I think we're really going after. It does translate into days because speed to certainty is days. Um, but it's really, that's what we're going after is can I afford this transaction? I wanna do, uh, do I have the means to do it? Is it, am I, am I, to a point in, in the engagement with my lender where I know that's taken care of whether that's before the transaction for shopping or, or daring. And I think the more we can do that, the more we're really going to be helping the customer out because, you know, instant decisions, you know, may or may not be the destination. It may be just the byproduct of giving that speed to certainty for our customer.
Mohammad Rashid: (
So I may, um, just speak of back on what Nate said and add some color to the production side of the manufacturing side of the pipeline. And so we talked a little bit about how the customer experience may be the push, uh, versus pull the subscription versus an application. Um, when, when we are talking about the backend production is more like li lipstick on a pig. What we are coming to the table with is more of a streamlined kind of a touchless lending approach. Um, and what we mean by that is basically, if you look at the statistics in the market today, the underwriting and processing is pretty much of the bottleneck in the, in the manufacturing pipeline, there's 114 hundred 13,925 underwriters in the us and 4 trillion worth of mortgages go through that pool, that underwriter pool. And so there is a, a rarity in that resource.
Mohammad Rashid: (
And so how do I take a lot of the load, the stairs and compares the manual updates, the comparison of documents off of the table of an underwriter. Uh, they literally spend 80% of their time there, by the way, 20%, they look at assessment of risk. How do I increase that 20% to make it the larger, the 80%, uh, right. Of the work that they do. And so what we've done is basically look at the components of underwriting credit asset income from the borrower perspective, collateral from the property perspective and extend out to title as well as fraud overall, right? Individually the components may look really good and all our green lights and no red flags, but once you've put the puzzle together, there are fishers there's fault lines in the overall underwriting process. That's where the fraud comes into play. And underwriters are detectives, they're financial detectives. You basically have to give them the tools that allow them to tease out the clues, right. Um, and that's where, um, uh, bringing in AI and machine learning and data analytics capabilities to these component pieces is what Mels them together and provides the underwriter with a, an ability to decision faster, right? With validated verified sources of data.
Nate Longfellow: (
And, and Danny, you said something earlier too, that I, I, I think it's, it's aligns to what Muhammad said, which is, which is really the back office is really, you know, you could argue the place to start when, when it comes to this, that's not the word to use, but that's, that's the kind of, you know, my, my rehash of those words. And I think that's, that's true. I think the, the, the interesting thing that we still deal with is we still treat this process. Many of us do as is this, this experience as this three stage experience, I'm going to, you know, take an application from you. I'm going to do due diligence on, on your ability to pay and all sorts of dimensions of risk. And then I'm gonna make an underwriting decision. And we still see those as three stages of a process, even with some really great advents of really great technology out there, as far as digital engagement, all that fun stuff.
Nate Longfellow: (
That's fundamentally the, the paradigm that we still work with them. And I think to really go after this space, um, and really achieve what we're looking to all achieve. I think you have to converge all three of those things. You really have to combine the back office, the automation of decisions, you know, the due diligence of work and the sales experience, if you will. And even the pre-engagement the sales experience into really one set of capabilities in one at, of, uh, of processes. Otherwise we're just gonna keep propagating the same, that same fundamental structure of let's go apply. Let's go do due diligence. And, uh, let's go do underwriting. And I used to say this, so some of you probably heard say this before, but our process still in some respects, in fact, many respects still is the same way it was decades ago, where it is. The difference is thank you customer for spending 25 minutes with us telling us all about your needs and what you want. Um, but we don't believe a word you just told us now let's go do, do some due diligence to see if we can help. And that just needs to change. Cause that's fundamentally still what, what we're working under and we're making some great, great improvements on certain aspects of those decisions, but it's not really all tied together very well with the, with the technology that supports its industry.
Dani Hernandez: (
Yeah. And I think, um, one of the things too, is that the workflow, um, I think a lot of companies, you're still all of those documents and that application information, it's, they're going from an Ello to a processor then to an underwriter and you're get waiting, you know, for weeks before an underwriter sees it. And that just makes absolutely zero sense. Um, when the underwriter is really the only person you can actually give approval of this loan to begin with. And so, um, one of the things, you know, that we've done, and I think that everyone should do honestly, is really get that underwriter involved upfront, um, but also leveraging different, uh, providers and different services or even proprietary stuff, um, to make that underwriter's job easier where they are, it is more of just a, let me review this versus let me do all these calculations, verify these different things.
Dani Hernandez: (
And I think a lot of, uh, times that underwriter spends is actually conditioning out of file and knowing which conditions or what they should condition for, and I think that's where you also have a lot of frustration with your LO, with your sales team and your borrowers is, I'm getting all of these random different conditions, or you have underwriter discretion that's built in. And so one underwriter looks at a file and says, oh, you know, a and the other one looks at it and says, no, it's actually B. Um, and so if you can codify, um, all of that and you can, uh, to take loan characteristics and then build out a, you know, set of conditions that apply, like, if this then, um, kind of things which we're doing in our equity, like that will, that substantially increases your speed and it makes things more uniform. So that borrowers and loan officers know what to expect.
Josh Hager: (
I I'd like to add you. I think the thing is that the consumer, the borrower really regarding the experience wants to know what additional stuff do you need from me, right. They they're wanting to provide, provide. And I think it's about making the machine smart enough from taking from an underwriter's perspective, taking map, plugging in an address and, and measuring distances to say, oh, I need now, can you provide me this in a split of a second, right. Your job so far, what's going on. And I think that as far as like the borrower consumer borrower experience, it's about how, like quick do you want the documentation additional more and more and more right. That mortgage process has been known for more documentation, more documentation, more documentation, but how fast can you get new the decision to tell me what additional documentation I need, not so much clothes, not so much, you know, but how much do you need and how fast,
Bonnie Sinnock: (
How much does that dynamic encourage consumers to provide the permissions they need to provide to provide that instantaneous data, if you will. And how often is that data there when they do?
Josh Hager: (
Yeah. I think that, um, you know, borrowers are at a point where they want to finish a process as soon as possible. They don't want to be barraged by the lender coming back 10 to 15 times over the, the five days. And so the response rate, you know, we have seen from the, you know, from a model like that is, is rather rapid. You alert the, you know, when the borrower's in the, the application process, you alert them at the end that this could be an issue, let's address it. You know, one of the things through the digital experience, right? Every question we do have, we have the opportunity to potentially lose somebody, but the faster you can have them address the issue, the more they're gonna like gain trust in your process and your system, and really see that you have that transparent experience to provide.
Mohammad Rashid: (
I think there's a, there's also an aspect of gamification that you can apply to that customer journey to be able to tell them, or encourage them to follow the digital pathway. Unfortunately, you know, not a lot of consumers provide that digital kind of, um, you know, verification of asset or income or employment they're going through, uh, scan the PDF and they feel, they actually think they're doing the work for you. They're doing the scanning, they're doing the imaging, they're uploading it through the document center. You just received it. You should be able to decision me right away. The fact that this, um, is going to cause another person on the back to validate that you've not uploaded a Chinese menu and you've actually uploaded a W2 for yourself and not for somebody else. And in the timeframe that is required requires a lot of manual, uh, workflow in the back, right?
Mohammad Rashid: (
So obvious that need is one of the goals that we should be always looking for. The underwriter seems to be the kind of locked in the OS. And I think that we consumers have been out loan officers have been taken out from the LS constraints. Underwriters should have better tools, should have more, um, modern tools, right? Uh, equip them with AI and machine learning. Have them look at, uh, comparables through an analytics, not have to measure. As Josh mentioned, measure distance on Google map, um, provide those assisted tools to them so that they can kinda quickly go through the loan. If it's all green. If we have, if I've done an analytics on a, a collateral or an asset or a credit or an income it's green, it should just go through the green zone and be clear to close. They just provide the over, over oversee oversight.
Mohammad Rashid: (
If there's some red flags bubble up those red flags for them and give them a directed underwrite, right? Why have them review the low end to end, give them where the hotspots are, the heat zone, the heat map, and let them focus on those and then get to a clear to close faster. I think the focus should now from all this money and, and time and investment spend on the consumer side, we, the consumer side is I think, you know, taking a lot of that traction. Now we really need to focus on the manufacturing pipeline, to the processor, underwriter, the closing funding. And how do you get to a close, funded loan faster?
Bonnie Sinnock: (
How much of the do you think is close to being in the green zone? If you will, you know, people talk about the GSE being sort of, you know, perhaps with some exceptions, like home equity, as we mentioned, um, maybe the GSE market to kind of technologically advanced comparatively, relatively plain vanilla loans. Like, are we pretty close to getting something close to instant mortgage approvals depending on how you define that, uh, for the GSE market and how different does the rest of the market look compared to that?
Nate Longfellow: (
Yeah, I can, yeah. I can just give you a little bit of, um, for me it depends, right. And I think that's a horrible answer for you. So I acknowledge that, but, um, but, but it does depend because you, you know, Moham just brought something up, uh, a minute ago too, about customers still uploading documents and that's in for some customers a preferred way of engagement. And I think that's, there's an underlying issue. There's like the underlying barriers to answer that question, right? The barriers are access to the data. Like you can't provide instant decisions unless you are leveraging data and, and not people. Right. And so I think that's, that's kind of the resounding fact that I think we're all talking about. And then it turns into a couple different things. Do, does the customer, do you have a relationship deep enough with the customer where they trust you with a broader set of data?
Nate Longfellow: (
Um, and that's, and I've been around a few different shops and I've seen a BR a massively different, um, engagement pattern with customers, um, that are engaged made with a model line lender versus customers that are engaging with a, with an institution as a broader set of financial relationships. It's very different. So the, the question then turns in, well, how do I build that trust with the customer? How do I build that real relationship with them, where we have this symbiotic relationship of us sharing value with them, and in return them letting us have broader access to the data to serve them in a better way. And so I think that's the, that's the tough part. And then what comes with that, which we, you know, which isn't sexy, which isn't fun is a massive and really relevant, important da amount of data governance, right?
Nate Longfellow: (
And that's, it doesn't sound fun. It's not the part that people want to probably subscribe to, you know, sessions about, but this, this really, really hums when you manage your data really, really well, and a highly controlled way, a highly consistent way with high levels of quality, you can't automate anything unless you trust your data, um, fully. And so you can just imagine what that's required. So I, I say all that to answer your question, because it it's really about it's, that's the distance we are from the goal. It is building those deeper relationships, building that trust, building those symbiotic. So they're allowing, um, a broader access to data, um, providing better governance and understanding of our data through not just the governance mechanisms, but the technology to do it that way. Then those are just dials to turn, how do I improve the ingestion of data and improve the quality of it?
Nate Longfellow: (
How do I give customers more value that lets them, lets us have more access to about them to pre-decision them? So I would to give you a punchline, I think we're still in the, you know, single digit to, I would say low double digit, um, really, really practical at this hour on pre decisions. But, but it also means what it also has to answer the question of what does that really mean? What does instance decisions really really mean? Um, and I'm gonna say, I think the credit to pay is really the, the initial part that can be done in a broad sense, um, more quickly than others. And I think that one's in a, in a much higher level of opportunity than other segments, just because of the depth of relationship of data. And I think, you know, those, those who really can foster a great relationship or those are the ones that are gonna really win in this space early.
Dani Hernandez: (
Yeah. And I'll say too, I think that, um, like for me, uh, I think it's not just about, um, there's that aspect of building trust, right? And then there are a set of borrowers who it's not so much about trust, but it's about convenience. Um, and so like for me personally, I will never buy another car from anywhere but carbon because it was the easiest process ever. Everything is right there. It's transparent. And honestly, I don't care if I have to pay a little bit more for the convenience. And I feel like a lot of millennials, uh, we are a convenience generation. Um, and I think that we also are more, um, we understand technology, um, better. And I mean, and so I think that, um, that segment is ready and would be willing to, uh, say, okay, if you can give, if I can complete this application and get an approval in the middle of the night, um, you know, and all I have to do is link my bank account from plaid and let you pull a VOE or a, let you pull some other, um, data from, you know, ADP or whoever it might be.
Dani Hernandez: (
Sure. I'll give you access to that data as long as I don't have to talk to somebody, but you also have to give them the transparency and make it easy for them to see their choices of products. What happens if I want a 15 year or a 30 year, or is, you know, and what are the fees associated with this? What does it look like if I escrow, if I don't escrow, um, I think you have to make it easy for them, uh, to under and mortgages. I think as an industry, we have made mortgages so complicated to that. It's not necessary. It does not need to be that necessary. I used to, uh, work at Freddy Mac and our CMO knew nothing about mortgages. Like that was not her job. She was our marketing person. Right. Like it, it, and she was like, I didn't don't even understand this.
Dani Hernandez: (
And so, um, one of the things you need to do is educate borrowers, make it easy for them to understand, be transparent so they can see it. And then I think that helps build that trust. But it also, if they know that, Hey, if I allow you to have this data, I'm going to have a convenience of, you know, getting this approved very quickly and, or not ever having to talk to a person like I'm in. I, I think that's another route that you go in order to, um, get that people to buy into the whole, let me use your data.
Mohammad Rashid: (
And just, uh, if, if it's okay, uh, Bonnie, I'll add one more color to this. Um, the, the customer side is an adoption problem, right? So, uh, we've given them a lot of road, you know, persona mappings journeys. There's definitely a lot of work that can happen on the hyperpersonalization of the, the customer, where they are at the financial life and journey and so forth so that you give the appropriate asset product at the right time on the, on the back end. Um, going back to your question around agencies and Fannie and Freddie and, uh, kind of the market, right? So you have the largest share of the market at Fannie Freddy, and they have said guidelines, right? So that is set in stone. They, you have to follow those guidelines, but what can be done is you bring to bear where it comes to following those guidelines in those areas of credit asset income collateral, right?
Mohammad Rashid: (
Um, so there is no reason why a human has to go through the images attached to an appraisal, to look at defects, look at, uh, comparables, whether the comparables are the right property size type, um, look at you is mold, uh, uh, in the house or paint peelings or foundation cracks. Those can be done with computer vision and you bubble up those findings to the underwriter and say, Hey, I found something, you know, look, take a look at this. And that allows that standardization. I think Danny, you mentioned about standardization to the process that brings standardization to the process. It helps the under, gonna follow in a more streamlined fashion that work rather than having to do this manually. Um, the, the joke in the industry, uh, I think Garth from staff Morris says this O often is the, the greatest progress for, is the dual monitors on the desk, right? Because it allows them to bring multiple docs up and to do it, their stare and compare and their manual updates. I think it's time to bring, take away one of the monitors and give them more advanced tools that use today's technologies. Right? So they do 2.2 underwrites per loan per day. Um, let's take it up to 10. Like, let's take it up to north of 10, right. Giving them the right, right tools and, um, uh, toolkits.
Josh Hager: (
I could add something to that as well. I think like, you know, that's what we were doing here at button for on the second lean home equity side is really identifying the red flag. And that's what we're bringing in to the underwriter, as opposed to calculate all these numbers, do all this, like review the document, does the addresses match and all that added on due diligence that's, you know, makes someone's job harder than what it needs to be when we have technology that can do that for us. It's something that we're leveraging on our end in the home equity to just improve. It improves the borrower experience overall, because we're able to then bring the empathetic side of a human in and say, well, I understand this and I can write around it and protect the risk decision of a lender to the GSE or to the, the private investor that's buying the instrument.
Bonnie Sinnock: (
All right. Well, we are just about at a time. Um, if you have a time to do it before we go people, there's one question about, on a scale of one to 10, uh, how close are we to instant mortgage approvals where 10 would be we're right there. Um, but otherwise you everybody for your time, we're gonna close out with that question and we'll probably thank you everybody for coming.
Mohammad Rashid: (
Thank you.