Smarter Hedging, Loan Sales, and Margin Management With Rob Kessel | June 2025 Data

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Welcome to Market Advantage, the monthly podcast from Optimal Blue. Tune in for valuable insights from the Market Advantage Mortgage Data Report and in-depth conversations with industry experts. Stay competitive and optimize your advantage in the ever-evolving mortgage landscape.

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Welcome to the Market Advantage podcast. have Optimal Blue head of corporate strategy, Mike Vogue co-hosting with me. Our friend and data aficionado, Brennan O'Connell is actually away on paternity leave. Congrats, Brennan. We're really pumped for you and your family, but we're excited for you to come back as well. That's right. So Mike, I know you've joined us on the podcast before and you'll be joining us regularly now, but

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The timing today is especially prudent, I think, because last month we added a significant number of new data metrics to our monthly report, including an entire section dedicated to the secondary market, which is an area of expertise for you. So to kick us off, why don't you share some highlights from June's data findings? Thanks, Olivia. And I'm going to actually do counter to what people think I would do here. And I'm not going to start with the hedging data and the secondary data. I'm going come back to that.

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There are some big takeaways here that I wanted to start with. So first of all, overall volume increased almost 2 % this month. I think the biggest driver here is that we did see rates drop a fair amount going into the end of the month here. To build off that point, OBMMI declined to 6.67 to end the month, which is down 17 basis points from where we started. This is super interesting because it actually moved lockstep with the 10-year treasury. So a 10-year treasury was also down.

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17 basis points, which kept that spread between the two static at 2.43. That's a big one because that is the extra yield that investors require to buy a mortgage backed asset as opposed to a treasury slash risk-free asset. So the demand for that asset was basically flat month over month. And we've gotten out of a big period where that spread was very wide. So it's nice to at least see it be static.

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On an origination front, to just go a little bit deeper, our refinance share increased from 16 to 18%. And this is down from where it was beginning of the year, where we're in the mid twenties, but it did increase from last month, which was a nice sign. Purchase activity was flat month over month. And while that might seem kind of ho hum compared to how we looked at things historically, May to June usually has a drop anywhere from

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4 to 5 % in purchase activity as you see the spring buying season starts to slow as folks are going on summer vacations and things like that. So to see it kind of flat was actually, it's actually a good sign in this case. The next data point that I want to cover is percentage of arms originated. I want to give a shout out to Jim Glenn and Kevin Foley who in the great detail on this on the last podcast that they put out, we saw the arm population decrease from 9.1 to 8.81.

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This typically goes in lockstep of what we see in the industry as term premium. This is typically the extra yield that investors require for a longer dated debt obligation. So for example, typically an investor should require less interest rate for a two year than a 10 year, right? There's more risk with that 10 year paper than the two year paper. And right now we see that term premium as 52 basis points between a two and 10 year treasury.

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Last month it was 56 basis points and a year ago it was negative 30 basis points. That actually tracks really nicely with the uptick in arm originations that we've seen year to date and also just the conversations that we've had. We've had a lot of conversations on the trading desk about arms. We've had a whole podcast just dedicated to arms. So it's nice to see that increase but we did see that decrease this month. And now I'm do the typical Mike Vogt thing. I'm gonna jump right into the hedging stats. The big one that I wanna call it this month and this is the second month that we've been showing these stats.

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is what we call our hedge loan statistics. And this is the percentage of loans that are sold to a specific loan sale execution. We typically break this down between loans sold to the agency cash window, loans securitized as a Fannie or Freddie Mac back security, or Jenny Mae security. We have loans that are actually sold best efforts at the point of loan sale, which is kind of counterintuitive, but we do see that happen. And then loans sold to aggregators via a bulk execution.

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And the big kind of takeaway here is that we saw loans sold to aggregators down almost three points month over month. It was 38 % the previous month and 35 % this month. And it was actually completely countered by an increase in agency backed share. So it was either, it was up 2 % for loans sold to the cash window and then 2 % loans sold via MBS securitization. And that's really interesting given just a lot of the headlines out there. You see the agencies get back a little bit more of that share.

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Another interesting tidbit from the capital market slash secondary market side was loan sale by price. And this is where we track where folks actually are selling their loans. It seems kind of counterintuitive, but there are instances where folks are not selling to the highest price. There's a number of reasons why that happens, whether that is things such as eligibility mix, things such as representative mix, which means, hey, you want to make sure that each investor has

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that specific slice of your loan population that corresponds with your overall, right? If you had a specific geo or credit exposure, you wouldn't want one investor to get all that paper because that could impact pricing that you get an ad group from that investor. So one of the things that we saw here is that folks actually sold to their rank one price or the highest price 69 % of the time, which is up from 68 % last month. And any execution sold to the fourth or worst price actually had the counter

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change. So it was 13 % last month and then 12 % this month. So we saw price be a bigger factor in like softer eligibility guidelines over the course of the month. Another interesting data point was servicing. So we saw servicing rights decrease in value by approximately two basis points over the course of the month. That makes sense because rates dropped. OVMI dropped 17 basis points over the course of the month. And when servicing rights

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decrease in value, typically means that expectations of prepays have gone up. And when rates drop like that, you are expecting to see some prepayment activity. We also saw the best efforts mandatory spread increase for conforming loans, conforming 30 year loans up four basis points while the government best effort mandatory spread remained flat at 13. We did see purchase pull through rates increase about 170 basis points to eight almost 85 % pull through.

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That's really interesting given the fact that rates dropped this month. So I think what we potentially could be seeing there is folks that are maybe locked into long-term rate obligations. Think of 120, 180 day, maybe even 360 days of a rate lock, especially if you're a builder. And you could be seeing folks take advantage of float downs. And so you don't see that come out as true fallout. Now, any good hedger or any good cap markets team is gonna probably still count that as a fallout in some ways.

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because that's a soft fallout. It doesn't really leave your position, but you do have to change your hedging strategy to account for that, right? Like getting out of a higher TBA coupon and moving into that lower TBA coupon does have a hedge cost associated with that. So you will see folks account for that. And we did see also refi pull through also increased to 62.6 % and that was of about 30 basis points. I'm gonna flip back over to the production side just to round this out here.

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You know, we saw conforming loans make up 53 % this month. That's up 110 basis points from last month. And so we could be seeing some of that flight to those more affordability focused programs. The last couple of months start to trend backwards. Now we did see decreases across FHA loans down about 80 basis points, VA loans down about basis point. And we saw non-conforming loans down about two basis points as well from a share percentage. We saw FICO on average.

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remained the same, it barely increased moving from 732 to 733. We saw the average loan amount basically flat as well, barely changing about $50 over the course of the month. And we saw first time homebuyer stats effectively flat throughout the course of the month. The last one I wanna hit is expanded guidelines. This is our non QM and kind of non agency catch all bucket. We saw that account for about 7.4 % of originations this month.

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basically flat month over month. this is basically just continuing that trend that I and others in the industry have been hammering is that we've seen this share increase a lot over the course of the last year, and it's not really going anywhere. We haven't seen any real decrease there at all. So lenders have to continue to make sure they have a strategy in place for the pricing originating and hedging and trading of that asset. All right. Thank you, Mike. And I think this is probably a good moment to remind folks that

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There's a lot more data available in our complete Market Advantage report and you can subscribe for free on our website. We will have that link in our show notes. It's time to welcome this month's guest. We have Rob Kessel joining us. He's founder of Panoramic Capital Advisory and Consulting. That's a professional development organization focused on capital markets training. Rob, welcome to the Market Advantage. Thank you very much for having me. So I know you might go way back.

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And I will turn it over to you two to have some secondary market banter here in a moment. But I thought maybe you could kick us off by telling us a funny anecdote or story about Mike when he was a little younger in his career. Oh, gee, we don't have that much time, do we? No, I've been super fortunate. Back when we worked at Compass Analytics together, we brought in a new team, some of the best and brightest. Mike is exhibit number one in that vein.

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It's been such a pleasure working with you through the years and how quickly you picked up stuff and excelled at it. It was just amazing and wonderful to watch. Rob, maybe a good place to start would be telling us a little bit more about Panoramic and what you and your team are doing over there. After selling Compass Analytics, I took some time off and ultimately decided that complete retirement just wasn't for me. And just wanted to be back in the industry and rekindle lot of relationships and looked where was a good fit.

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turned out that there still wasn't good capital markets training out there in the industry. You know, so embarked upon the project of, you know, putting together what we never had at Compass. think largely the industry hasn't had until Panoramic and putting together all the content in the right order to provide the full context for training capital markets folks. We're two semesters in and we've had great feedback and great fun with it. And it's a joy, you know,

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being on this side, just on the education side of the business. Really fun. Rob, to build on that, I always tell folks that it took me, while you said, I'll pick it up quick, I think it took me at least two years to kind of put the pieces together. And you would learn maybe step three or step seven or step 10. And then you would figure out step one, like six months later. And then when you figured out that, all these things add together.

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to tell the full cohesive story of like how capital markets and the mortgage, you know, manufacturing process like tie together. I always told people it was like a light bulb. Like I almost feel like I was, that came to me when I was reviewing maybe some of your training material on like the Metro one day that it all snaps straight. So it's really, it's really awesome to see that the class is set up in a way where it's sequential to build up on top of it. I don't know if you've gotten any feedback that is similar to that or if you want to expand upon any of those thoughts there.

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Well, you know, it's, uh, and I appreciate those kind of words. There's so much jargon in our business and you know, there's this whole foundational approach to where understanding the participants in the industry and the roles they play, but you know, very importantly, the jargon that's used and then figuring out how to rewind all the way to the beginning and just lay down the necessary foundation so that when you need to reference something later on.

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there's an understanding of what it is you're referencing. And there's, as you know, a couple of my compadres, James Baublets and Gary Malis have participated in the sausage making of the class. And there's lots of arm wrestling around when we could introduce a topic and how deeply we could go on a topic. And I think it's been a pretty fruitful exercise in how we've put it together.

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Now that's awesome. I think that's probably a good segue maybe to some of the topics that we wanted to cover today. So we recently in our Market Advantage monthly report, we added some secondary marketing focused data points. And we thought there was nobody better out there to talk to about these data points than yourself. So the one of the first ones that we really wanted to bring more of a light to is the best effort mandatory spread.

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And I remember when I was first getting started, this concept was very foreign to me. I never heard of a concept like this before outside of mortgage banking. So I was wondering if you can kind of first give us your interpretation of that, of that spread and what that means. then, and then we'll dive a little bit deeper from there. Yeah. I mean, so the, the, the originators in the space today all learned through practical experience that they can't get competitive pricing until they increase their investor base, until they increase their capital, until.

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They start taking more risk on and you know, one milestone for many lenders is when they look at moving to be to closing their own loans and they get a warehouse bank. And the next milestone of course, is when do they look at starting to hedge their loans and instead of locking in every loan at origination time with a specific investor, you know, taking on the risk of fallout and market movement and hedging that through the close. When you go out and explain that kind of milestone to lenders,

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You know, they're always saying, what's in it? You know, why would I take on that risk? Right. And, certainly the best measure of that risk is what is the difference in price that you can receive selling a clothes loan versus selling a loan on a best effort basis when you, when you lock it in. And that of course is that mandatory best effort spread. And, know, there's, as you know, intimately, there's a lot of noise in that, you know, certainly.

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Locking a loan in for a 45 day lock when you accept the lock from the LO versus selling a closed loan on a mandatory seven day Delivery that you know that creates some noise in that number but that you know, that's generally you know There's a starting point that's that general value of that of that spread and it's moved in and out But I'll leave it at that. I know you've got some fine fine points to bring up about it Yeah, and you know, I think another way to think about it is that premium for like who's managing that risk, right? so

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In the best efforts world, the buyer or the investor of the loan is, they're susceptible to fallout, right? They're susceptible to interest rate risk on that loan post agreeing to a price, where the lender, then if they take that risk on, they're incentivized for it with that better price. And there's a variety of reasons why you touched upon a couple with the different delivery terms, but there's different things that kind of pop in and out of that best effort price that occasionally actually maybe sometimes maybe

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have it priced through mandatory. don't know if there's anything, any like tips or tricks that you've noticed over the years of like different scenarios where that happens. You know, there's a, there's a, I'll even say the word trope in our business, which is never be complacent. And that is, you know, the, that's the beauty of having a PPE, right? Because you can assume that the mandatory price is going to be better, but you just never know.

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You know, really best practices would be that you would look at every best effort execution the same time you're looking at your mandatory execution. I just different investors have different appetites, uh, axes for different products at different times and one shouldn't be complacent. to your point. Yeah. Uh, love that point. And that's something that we, really, really push on like our, uh, on our clients from a, you know, best X perspective and a hedging perspective is making sure you have every execution possible. I mean, sometimes when.

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we're working with different lenders, they might have a mandatory execution and a best effort execution for the same lender that they're using throughout the life cycle of the loan, whether it's that front end pricing all the way to loan sale, because sometimes you see things where maybe there's a better spec pay up in a best effort price, or maybe there are some lenders who have different pay ups for things such as like a CRAX that comes in through the best effort rate sheet. One of the things that we've actually started tracking is the split of

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the split of loans that are actually sold best efforts at the point of loan sale. And we see that number in that 2 % 4 % range, which is enough that everyone should be including that in their best X, even if it's a 1Z or 2Z there, if it's additional basis points, everybody needs that right now. Rob, is there any type of magic number out there for a best effort mandatory spread that is like, this is the screaming hot time to do this if you're not doing it?

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Anything that, any rules of thumb there from your perspective? I think the long standing 30 some year assumption generally still is relevant, 25 to 40 basis points. But it's the improvement in technology and all the things that have happened in our business, including loan level, valuation and bidding and to your point, CRA being passed through, maybe in some cases through best effort.

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Those are all things that kind of throw that assumption on its head, right? And so lenders still have to look at, you know, what is their cost to hedge? It's going to be at some level of volume play because that cost will be spread out over the loans. And then, you know, work through this 30, 40 basis point kind of number. you know, as we know, it's not, you can't guarantee what that spread is going to be. And there certainly are conditions where it's much better.

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and their conditions were it's much less. And I'd say the last point I'd make is the move of the industry towards the whole-loan bidding format has taken some of that best effort mandatory spread transparency out because there are many investors that maybe only buy through just that bidding process. it's added some challenges as well as opportunities, Yeah, definitely. has backed up a couple of years. Every investor had their

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their rate sheet that was out there that you could, I remember one of the first things that that compass was build our standardized, you know, LOP template for all the different investors. You know, that was, you know, every investor had their own grid or their own type of an adjustment for MSRs or spec payups or things like that. And it's moved now to a world where they have like these living, breathing, dynamic models that are moving with the market every day. And every time you send out a loan sale, they're getting different pricing there. And so the technology there has been, it's really improved at the point of loan sale.

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I think you're starting to see people start to move that further up in the manufacturing process. So you see some investors who are using those models for mark to market bidding. And I think you'll continue to see that kind of move more towards the front of the origination process to put that best foot forward for folks. You've almost seen some of that best effort mandatory spread, maybe move to secondary GL in some cases, because there's not enough price discovery for that front end origination.

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Yeah, it's one of those rare things where the GNL moves to secondary and not to the loan officers and the branches. Yeah, I mean, it's still, I think you still have that risk. let's say you're just doing best efforts and your strategy is to give loan officers the best of the best efforts. I mean, I know as hedge advisors, this is something that gives us indigestion when our clients want to do this kind of thing.

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Because you know what happens that that know that lender on that day might be priced very aggressively. But you know if you're hedging that wrong over the next you know 45 60 days then who knows if they're going to back out. So there's always this kind of like how far through is the best price compared to the second best price. And then you you want to do right by your L.L.Os and give them the most competitive price so they get the business. But if it's too far through it's not in anyone's best interest for secondary to lose money by giving too much away right.

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And I know that you, know, that intimately and I'm sure you guys have pretty cool technology to help manage that. Yeah. It's, one of those things where, know, the ability to kind of take a little bit of the guy who's sticking out, also kind of grounding yourself to like where the majority of your pricing lives. It is really important to Rob's point there. Like the certainty of what you price on day one and your expected profitability is, it's all, it's all correlated, right? It's,

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I've said this on the Honest Podcast before, it's like an X minus Y equals Z, right? And so if your X is very, very high and your Y is stable, well then your profitability or your Z is going to go up or down based upon that. So if you have this starting point that's kind of sticking out, it's very difficult to make sure that your Z is predictable. And with things that we do on rate sheet tools and different things with blending of pricing, we have a lot of interesting options there. But to your point, pricing best efforts, there's a lot of

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kind of like murkiness there in terms of like what is going into that price and how you track it and how you pull it apart. And it makes that, that GL attribution very difficult because the best efforts for a changes every day. So it's a, it's a big, it's a big hurdle for folks. Uh, you know, on that point, you know, I think we mentioned this a little bit during the conversation already, but another kind of like, you know, uh, data point that we've started looking at is pull through. So.

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was kind of hoping we would go through kind of a little bit same exercise if you can kind of give us your opinion on what pull through is and then you and can kind of go down memory lane of some of the things that we've worked on over the years on pull through. Well, you know, clearly if you try and simplify the hedging proposition, you know, not 100 % of every loan is going to close and you need to back off your hedge enough to where you're not over hedging and

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and certainly not flip side either under hedging the loan. And of course that pull through is the assessment of the behavior of the borrower or the probability it will close, right? And to the extent you misspecify that, to the extent you fail to keep it updated, then you end up with, you know, hedge mismatch, right? And sometimes if the market sells off that could be a win, but no one wants that win, right? They want a predictability of performance. They want to, you know, be on top of a pull through.

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And so, know, that's obviously the objective and the concept. You know, I think one of the things that not everyone in the industry agrees on is that, you know, what is the flip side of poll do? What is fallout? And, you know, so the, one of the things that I think, you know, and certainly in early days, you know, you and I spent a lot of time talking about is that, you Hey, there's a type of fallout when there's a long renegotiation, right? That, you know, if fallout, if

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Pull through models to prevent hedging losses. even if a loan closes, if it renegotiated, there was a hedging loss, right? Your loss on the hedge stayed the same, but if you renegotiate down in rate, your loan gain has evaporated or largely evaporated, right? That was an important distinction in pull through saying, differentiating those loans that renegotiated as a type of fallout. And then,

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being able to use that as an input variable to the pull-through analysis. Certainly that was the one, I think an important area of pull-through analysis and clearly the sky's limit these days as people pay more attention to a lot more data and AI writ large, right? Yeah, and I think it all goes back to that predictability of profitability, right? So, kind of the summarize a couple of things you said there, like, there's not...

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Every application that you take in and load into your LOS isn't going to close, right? And so the hedger's job or capital markets team is say, okay, well, how many of those applications that came in today and were locked are actually going to close? Like a simplistic example is like, Hey, we have a million dollars of new locks today. And then I want to hedge that basically at the same level as my pull through. So if my pull through is 70%, then I don't need a full million dollar hedge to hedge that loan. need $700,000.

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And that changes as rates go up and down, as you move through the manufacturing process. And to Rob's like first point, if the pull through changes, well then you're adding or subtracting to your hedge. And every time you do that, there's a transaction cost, right? And to Rob's second point, which I can't agree with enough, and we've worked over the years and some of these reports still live and breathe with some added data points that we've added over the years. But the whole like, almost like originator behavior or borrower behavior part, it's not always.

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just interest rate. A lot of it is behavioral. And so, you know, some of these things that we look at can actually cause you to take on a hedge loss, even though the loan's still in the pipeline. So think about something like an extension, right? It might extend the loan longer than you initially expected. It's not just the amount of hedge you put on, but it's also the coupon slotting and then the settlement slotting of the loan. So if you extend the loan and it goes, it then is better matched with

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the July versus the June TVA, well, then you have to you have to actually roll your coverage and take on transaction costs. If you switch products, if you switch rates and it changes you drop coupon, that's gonna that's gonna change your hedge and you have to incur that hedge cost sooner than maybe you expected. From like going through your class, like were there any other like interesting operational, you know, things that came to light that maybe maybe some of the secondary marketing folks aren't thinking about with your like broader perspective here?

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You know, I think, I think the one thing that we try and work through in the class is making sure that there's perspective about why, you know, pricing strategies and how competitive, especially today's plays, it has to be, and maybe why that leads to concessions. And it's kind of the margin journey, right? It's a margin journey from what maybe the management thinks is the margin, to what shows up on the rate sheet that gets adjusted to then maybe suffers from

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concession to then maybe suffers from an extension to your point or renegotiation later on. I think that to protect the back of secondary or the secondary vendor, is to just provide more transparency to where that P &L goes. And the fact that yes, a concession comes right out of margin typically, or that a renegotiation, yes, you can calculate a P &L impact and it comes right out of your margin, your corporate margin. And, you know, through

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You know, sunlight's the greatest disinfectant, right? Just by educating everyone and having everyone understand each other's perspectives, the hope is that people get to the right spot with how they approach things. Yeah. I think your point on sunlight is spot on. Being able to show folks that, hey, this is where you fit from a pull-through perspective, but then also not just what we would call your top line, right? What is just, did the loan close?

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Did it close with the renegotiation? And maybe there are things that you can like tighten up operationally. So being able to show different originators, hey, your branch or your channel or your LO sits here and he compares to the rest of your peers. This is a report that we use at Compass and we still use today at Opel Blue, the originator scorecards, but it just is such a powerful concept, that idea of sunlight on that. From your perspective, any interesting like...

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Trends or rules of thumb on different on different channels versus different products from you know Interesting pull through trends you've noticed. You know, I think there's a lot I I think people are gonna put more and more energy into that with AI and I'm sure you guys are all about that because you know There's a lot of the behavioral stuff that you know, there's probably related to the processing alone So there's you know, there's I'm sure that's gonna be a trend, you know, I think that you know that

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whole how you get pricing to rate sheet and what you know more this is more of a margin concept but you know the the big aggregators that are buying it's as you've experienced super interesting just how differently they value MSRs same loan but two investors might have you know two corresponding investors might have 75 basis points different price that you can only relate to the servicing asset I mean you know and of course maybe is a recapture play but

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That's like a very, you know, big window to drive a truck, you know, you can drive a truck through that makes it hard to kind of figure this stuff out. And that's back to the whole transparency, right? Why, why, why can they do that? How do they do that? What are their assumptions and what does it lender do to, to protect yourself? Yeah. And I think you had a really good point there in terms of pull through and just general, like speeds or prepay are kind of related in terms of the, impact of interest rates.

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Now I do think that there is differences on pull through from the standpoint of all these different things that are happening during the origination part of the loan. And, know, just generally like we see, you know, pull through on like purchase loans typically closer to like 80 % and then refi is closer to like the 65 ish range. I think that makes a ton of sense just based upon, know, hey, you start working with a real estate agent to go buy at first home. You're maybe you are a first time home buyer. Maybe not at you haven't gone through the process yet. You're more likely maybe not to shop.

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Um, but then on refi, you've, you've at least been through it one time already. You know, you could see some of the differences of rate and some of those intangible things that I think might be gained during the home buying process. It becomes more commoditized, I think, during that refi piece. So it's, it's, it's more about like dollars and cents than it is a relationship, in my opinion. So I think that that's some things that we've noticed there. And, you know, it's, you alluded to this too. It's, it's a ripe spot for automation and some of the new technologies that are out there.

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we just got have our hackathon. There was another podcast from Alpha Blue that just talked about that. And it was a was a ripe, ripe subject of our hackathon of like what we could do with AI and large language models and machine learning models to figure out how to crack that nut because

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It drives such a huge piece of profitability, but it's still one of those dark arts, feel like, in a certain extent. It's one of those, hey, you think it's a science, it really should be a science, but it does take a capital markets professional to kind of look at previous data and be like, oh, okay, this makes sense because rates have trended up and we haven't seen down rate shocks, or I don't have enough sample size and certain moves.

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There's a lot of human intuition still in pull-through modeling, but I think that we wake up in two or three years, maybe even sooner. And I think it's going to be a very different state of the world there. think the, I mean, the funny thing is, the, the whole stone of a purchase and refi pull through has largely been those numbers for 30 years. You know, so one, think the, the benefit of transparency is going to provide.

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data and information, which I think will actually be implemented as workflow changes, that's going to start to impact that pull through. Like if you have events, you can identify, you know, what can you put into your LOS? What can you feed your LO that can now start to actually change the outcome of that pull through? And I think that that's, know, once there's more transparency and discovery of what's actually impacting pull through, the next wave will be, okay, now we're going to do something about

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Yeah. And I wish I could give more detail, but you like highlighted the number one winner of the hackathon there. So you're going to see something from Alphamold Blue more on this to come here. But just using that as our segue here to the next topic, before I give away any company secrets on the podcast, I wanted to touch upon loan sales. So when we talked about the best efforts to mandatory spread conversation, it kind of culminates with this decision that a lender has to make.

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the lender has to make a decision on how to get rid of that loan. Like a lot of these lenders, especially IMBs, they borrow from warehouse banks overnight to fund the loan, and then they need to go out and sell the loan to actually pay down the warehouse banks and then do that a thousand more times. Depositories have a little bit more wiggle room there, but the choice of how lenders sell loans and the different delivery methods is a really important strategic conversation and decision lenders have to make. So Rob, I was wondering if you can give us some insight into just

33:39

some of the different delivery methods and how lenders sell loans today. Well, I think just kind of comparing against 15 years ago, it used to be easier for a lender at a smaller size to both be able to securitize and to sell cash. And you've seen a lot of that, a lot of the agencies have pushed a lot of lenders into selling cash. And it's just the bigger lenders that had the securitization option.

34:09

That kind of options taken away a little bit in that old school AOT 10 plus years ago has been replaced now with know, bid loan individual loan bid tapes with hybrid AOT, right? And so, you know, the, it's certainly in the interest of the lender, given their capital and strategic decisions to figure out what are their investors and which delivery options they'll, they'll allow, right? And, know, and co-issues another flavor of that if they're, if they're selling to the agency and

34:38

It's the, I think that the flip side of don't be complacent, always do the work to figure out best execution is also getting into the relationship with the investor a little bit and your own operations. Like the best price for a single loan isn't always the very best execution, right?

34:58

If it involves operational expense, certainly if you're optimizing pools and you can move loans around, then you maybe lose best execution on one loan to enable best execution across a broader set of loans. And there is the importance of the investor relationship. If you listen to the aggregators out there, they certainly represent themselves in the value of a good relationship where it's not always everything price.

35:24

And I think the more mature lenders increasingly explore and deepen their relationships with the aggregators to deliver loans to them in a way that works for both of them and is appropriate. Those would be kind of the add-ons I'd consider. No, definitely. That makes a ton of sense. when we sit back and look at the data that we see,

35:48

We approximately cover about 40 odd percent of all the loans hedged in trade in the secondary market. You know, I mentioned before we see best efforts execution somewhere in that two to 4 % range. You know, we see folks who sell to the, to the bulk loan sale piece about 30, 32 to 35 % of the time. That's where loans are sold today. And then Rob mentioned this earlier as well. Like that's when you're selling the whole loan, you know, principal interest and servicing to a investor. And they sometimes will also.

36:16

let you sell the hedge to them as well. So you can get that risk neutral transaction. And then we see the rest of it kind of going to the agency side, whether it's a mix of cash or MBS. We saw, you know, just last month, for example, about 36 % of our loans sold through an MBS securitization. Now that's skewed towards some of the bigger folks who have the economies of scale there to do that. And they might have more robust teams. There's a little bit more of a reporting kind of aspect there to handle.

36:45

on the cash side, about 27%. know, Rob, just from your perspective, any of those numbers stand out to you as interesting. And then if not, like, what are some of the distinctions and the considerations for folks to, at least on the agency side, think about going cash versus MBS? It seems to me, just from what I hear, that it's the agency's kind of predilection to encourage

37:11

lenders or maybe limit lenders to one or the other. And it seems that it's increasingly been lent, uh, restricting them to cash. Uh, and you know, so compared to 15 years ago, whether you could do both, right, but they just didn't want you to best X each other. So I think that's kind of given to the lender these days. You're certainly lenders that delivered to agencies now have much more coal issue opportunities. They don't have to invest in the servicing asset. They don't need the capital or take that risk on. And so, you know, I think that's.

37:40

made agency cash sales more available to more and the technology that's been brought to that realm moves that execution into more of a real time kind of proposition that could be, you know, tailed right into, you know, against the totally released bid tape executions. know, and so the technology has picked up such that, you know, the capital markets folks can make a true best execution that's timely. you know, those numbers don't surprise me. I'm sure there's big

38:09

big, big delivers that are selling on the MBS side. You know, last bastion is the, how prevalent the suspect pay ups and story bonds had become. you know, clearly the agencies try and pass a fair amount of that through and their cash pricing, but you know, the, still probably, you know, non-trivial stuff left that if you were a securitizer, you might capture. And certainly they're doing that on the Gini side, right? Where they don't have that cash option. And I think a lot of it has to do with like some of the,

38:39

minimums and some of the smaller spec stories like that folks can really only sell cash right now. So you do see some of those, maybe some of the mission score specs and maybe some of the home possible home readies that we want to incentivize from an affordability perspective, the admission perspective, but they may not be enough to securitize. So I think there are a couple of folks who are maybe have a maybe a half foot in some of them to keep up with some of those goals. But yeah, it definitely seems like it's a pick your own lane.

39:07

And, some of the technology to your point, some of the servicing release execution, know, improvements that both agencies have made to bring the co-issue bid in one kind of fell swoop to this execution has really helped, has really helped them bring more liquidity there in my opinion, because that was something that like humans have to have, you used have to manage, right? We used have to manage, so-and-so co-issue guy has changed their bid. Let's go have a human look at an Excel spreadsheet and then.

39:35

put those adjusters into a model as opposed to just flowing through into the decision making process. Exactly. And pivoting off that, think another topic I wanted to hit was you talked about the concept of things being not always price driven. And so I wanted to get your reaction on a number that we track in our report. So in our report today, we track how much of the low sales are actually done at the best price.

40:05

with the idea here that some of the things that you mentioned on a relationship standpoint do impact things. So last month, we had this quoted at 70 % as actually sold to rank one. And then it actually was basically eight and then 9 % and two and three. And then the rest of it was actually in rank four. So rank four or lower being the second highest kind of like grouping from a reporting standpoint. I was interested in your perspective on that. And if there were other things that maybe

40:35

outside just relationship that could potentially be impacting this trend that we've seen. It surprised me that it's 70%. I I think that I would almost expect it to be higher just because of how tough it is right now to compete. I think that this is another ring out for complacency, that there's a lot of assumptions that are made. I think that you can, I think if I recall correctly, you can actually with your rankings monetize that.

41:03

that difference exactly, like it's back 17 basis points, right? First thing I'd be thinking of if I'm in that stat where my department's selling at 70%, now I'm looking at that 30 and saying, what is that in dollars and cents and why? And what is the logic behind that? And chances are it makes perfect sense, but it's also possible that there's some complacency setting in where for whatever reason it's easier to do this and maybe they're not looking at the magnitude of dollars.

41:31

Your five basis points isn't that much unless it's on a billion dollars, right? And then it's a lot. And especially if our corporate margins are, you know, hopefully 50 basis points, right? So it's 10%. So, you know, it's, always, always get into the data if you've got it and monetize it and, know, make it transparent and then tell that into your strategy decision. Yeah. And to wrap up on this, on that point here, like.

41:57

you know, lot of the technology that's out there lets you take some of these like what are called like softer guidelines and have it have them automated, right? So you might be, Oh, I know that this this type of loan takes x more days at this investor, so I'm gonna sell someplace else and move it away from the best X. A lot of those things are can be easily programmed or configured in technology out there. Optimal blue is included, especially compass edge. So that like you're like, you don't have to do that manual thing, it will slot there based upon

42:27

your eligibility criteria or your operational process or managing something like a representative mix, making sure you're not delivering too much of a certain cohort to a certain investor. Back to that relationship point, right? You wanna give them a full view of your entire business and origination process. So there's things there that make that easier. And then another thing to consider too here is if you're moving that loan away at the point of loan sale, that probably means that you're marking it to market and maybe even

42:56

come up with pricing for it at the point of origination, that was not as accurate as it could have been. So it could have made your X and that formula I talked about earlier higher than you really should have offered previously. And it could look like a secondary loss. We talked about secondary gains earlier, but nobody wants secondary loss either. So making sure that everything is aligned between the loan sale to origination is a really important point. Absolutely. And your point about representative mix, I just want to emphasize that there is

43:26

You don't want to, know, quote Arb, an investor by dumping stuff on them that, you know, ultimately leads them to think that you're delivering poor credit or just poor performing to take advantage of a short-term price. And I think your point about representative mix and having the analytics and as you do your loan sales is a very critical piece to, to long-term profitability, but as well with relationships with the investors. Yeah.

43:52

Nobody wants to get armed if someone thinks they're getting are they're going to probably decrease your pricing. So it's yeah, you don't want to let the short term dollar signs impact long term viability.

44:04

So I have the unfortunate job of keeping an eye on the clock. As much as I hate interrupting you two, I think, Rob, it's probably safe to say we would love to have you back again in the future because I know there's so much more you and Mike could chat about. But I do want to end by asking one more question of you, Rob. So we ask every guest what we call our bonus question. So that is, what is one thing in your opinion that you think lenders should be doing today to maximize profitability? 100 % honest.

44:34

completely transparent, beginning to end margin, actual realized margin tracking. Short and sweet. I like it. So Rob, thank you so much for joining us, spending time here, sharing your knowledge. And to our listeners, if you'd like to learn more about what Rob and his team are doing at Panoramic Capital, we will be sure to put a link to their website in our show notes so you can learn more. But in the meantime, take care.