Latest / Chrisman Commentary - Daily Mortgage News / 6.17.26 Servicing Treasure Trove; Addy AI’s Michael Vandi on Productivity; Rate Swap Markets

Transcript

6.17.26 Servicing Treasure Trove; Addy AI’s Michael Vandi on Productivity; Rate Swap Markets · Chrisman Commentary - Daily Mortgage News

• 0:02
  Speaker 1: Welcome to the Chrisman Commentary, Daily Mortgage News podcast.
• 0:06
  Speaker 1: I'm your host, Robbie Chrisman.
• 0:08
  Speaker 1: Topics on today's episode include how servicing is a treasure trove for some, an in-depth look at Fed Chair Warsh's first meeting in charge of the FOMC, and my interview with Addy AI's Michael Vandy on the importance of AI and improving efficiency and competitiveness, especially as a productivity tool for originators.
• 0:29
  Speaker 1: Here, take a listen to a little preview.
• 0:31
  Speaker 1: Can you talk a little bit about AI as it relates to being a productivity tool for originators?
• 0:40
  Speaker 1: Because, in my opinion, we see the running of the gamut from way overuse, blind overuse, and people are getting turned off by it to selective use or even underuse, and now you're getting bypassed by the competition.
• 0:55
  Speaker 1: Just thoughts in general on AI as a productivity tool for originators.
• 0:59
  Speaker: I think the industry has changed a lot since we started building it in mortgage.
• 1:04
  Speaker: A lot of these paradigms uh we we started with like invented uh in the industry, I would say, from like bringing AI inside of the live loan.
• 1:14
  Speaker: Right now, where we're seeing the most pull is in loan setup processing, pre-underwriting, that's core like packaging uh of the loan.
• 1:24
  Speaker: And last month, I will tell you, we processed about 19,000 loans.
• 1:29
  Speaker: And that's a lot of people are saying that the calculations that ADAI is doing is around a tenth of a percent as what the underwriter would give back.
• 1:40
  Speaker: So we've crossed the chasm of like this being like a one-time tool or like they're just like trying it out.
• 1:47
  Speaker: And the models have gotten so good that these things are actually taking on responsibilities and like doing tasks.
• 1:54
  Speaker: And some of the larger enterprises are just like waking up to that right now.
• 1:59
  Speaker: And organizations that already have an existing platform, people like to call them six systems of records, they probably sit at an interesting position right now where they have all of this like customer attention.
• 2:10
  Speaker: And by plugging into some of these like agentic tools like us, uh, it's really helping them.
• 2:14
  Speaker: So I mean, I say we're seeing a lot of productivity in the loan setup phase and in the processing and the pre-underwriting phase.
• 2:20
  Speaker: And right now, these tools have moved away from like doing one-time tasks to like just taking responsibilities.
• 2:31
  Speaker 1: Thank you to TrueWork for sponsoring this week's podcast.
• 2:33
  Speaker 1: TrueWork is the one verification solution to replace in-house waterfalls.
• 2:38
  Speaker 1: Verify any borrower with a VOIE solution that automates the entire process to quickly deliver the most accurate and complete reports with broad GSE coverage.
• 2:47
  Speaker 1: To learn more, visit Truework.com.
• 2:51
  Speaker 1: Here in Honolulu, as it is in places like Florida and New York, the condo market and HOA fees are of paramount importance, as are the affordability impact of special assessment fees.
• 3:04
  Speaker 1: Even though the inventory of houses for sale has steadily increased in many areas, some people want more.
• 3:10
  Speaker 1: One idea being bantered about is changing or eliminating the capital gains tax on the sale of primary residences.
• 3:17
  Speaker 1: Money talks and a housing crash won't necessarily fix affordability.
• 3:22
  Speaker 1: A crackdown on H1B visas is causing Indian buyers to leave the Dallas housing market, meaning skilled professionals who transformed the region now face exile.
• 3:31
  Speaker 1: That story and the following ones offer a look into the challenges facing homeowners and renters around the world from San Francisco to the United Kingdom.
• 3:39
  Speaker 1: For links to those, visit CrismanCommentary.com.
• 3:43
  Speaker 1: I want to spend some time today talking about servicing.
• 3:47
  Speaker 1: Why do some companies try to keep their servicing rights and at the same time buy yours?
• 3:51
  Speaker 1: Advances in data infrastructure and artificial intelligence are making it economically feasible to extract meaningful insights from millions of borrower interactions, transforming servicing from a back office function into the industry's most persistent customer touch point.
• 4:04
  Speaker 1: The strategic value of a servicing portfolio increasingly lies in understanding homeowners, identifying emerging needs, financial stress, renovation plans, insurance concerns, or future borrowing opportunities long before they appear in traditional data sets.
• 4:18
  Speaker 1: Recent consolidation across the servicing landscape reflects this shift.
• 4:22
  Speaker 1: Institutions are not simply buying cash flows, they are buying access to customer relationships and the intelligence embedded within them.
• 4:29
  Speaker 1: Servicing is evolving into the operating system of a housing finance.
• 4:33
  Speaker 1: Historically, servicing organizations relied on reports, analysts, and manual processes to identify risks and opportunities after they emerged.
• 4:42
  Speaker 1: Today, intelligent systems can continuously monitor portfolios, service patterns, and provide decision-ready insights in real time.
• 4:50
  Speaker 1: The competitive advantage will not come from deploying AI itself, as those tools will become ubiquitous, but from building the infrastructure and context that allow those systems to produce meaningful outcomes.
• 5:01
  Speaker 1: Servicing will cease to be a downstream administrative function and become the command center through which lenders understand, anticipate, and respond to homeowner needs.
• 5:09
  Speaker 1: The firms that win are unlikely to be those that process payments most efficiently.
• 5:13
  Speaker 1: They'll be the ones that turn servicing into a source of continuous customer intelligence.
• 5:17
  Speaker 1: And not only does the value of servicing go up and down, but so do interest rates, which are often moved by inflation moves.
• 5:25
  Speaker 1: Oil prices fell below eighty dollars per barrel yesterday on continued optimism surrounding a potential US-Iran agreement, but the broader market response was muted as stocks stalled and treasury yields declined only modestly, reflecting lingering skepticism about the durability of any deal.
• 5:40
  Speaker 1: Agency MBS performed well in the middle of the coupon stack with spreads tightening slightly, while higher and lower coupon sectors lagged amid a bull flattening treasury curve and settlement-related positioning in Ginny May securities.
• 5:51
  Speaker 1: Investors appear to be in wait and see mode ahead of key catalysts this week, including retail sales, housing data, and the Federal Open Market Committee's decision, and Chair Warsh's first press conference, while benchmark treasury yields edged two to three basis points lower, and MBS prices gained roughly a quarter point yesterday.
• 6:08
  Speaker 1: As investors look ahead to the expected US Iran ceasefire signing and wonder what has changed in four months, focus has shifted from overall geopolitical risk to the economic implications of rapidly falling energy prices.
• 6:20
  Speaker 1: Oil has retraced sharply on expectations that the Strait of Horror moves will reopen and regional supply disruptions will ease, though production capacity damage and how quickly output can normalize are both anyone's guess.
• 6:31
  Speaker 1: The decline in energy prices is raising the possibility that headline inflation could begin moderating after months of upward pressure, even as central banks remain cautious.
• 6:41
  Speaker 1: For today's interview, I wanted to welcome to the show Addy AI's Michael Bandy to talk about the importance of AI in improving efficiency and competitiveness, especially as a productivity tool for originators.
• 6:53
  Speaker 1: He's the founder and CEO of Addy AI, which helps mortgage professionals close more loans.
• 6:59
  Speaker 1: Let's hear how.
• 7:00
  Speaker 1: To start, I hear about these AI agents for email.
• 7:18
  Speaker 1: I've been I'm so behind on emails, and I'm like, I should do an AI agent, but I don't know if I trust it.
• 7:23
  Speaker 1: And I'm sure that that's a common feeling out there.
• 7:26
  Speaker 1: Thoughts on on maybe this is a too narrow of a scope for where I should start the interview, but thoughts on where to first start deploying AI before we get into all what they can do and the full capability, just for somebody who wants to dip their toes in the water a little bit and not let things pass them by, the best places to deploy AI agents as it pertains to personal tasks or the blown origination process, and kind of how we can start buying in more and more to the capabilities.
• 7:53
  Speaker: For me, I am using AI to automate my entire email setup.
• 7:58
  Speaker: So I have an agent that runs every now and then, reads my inbox, and then contextually can see all of the conversations that I've had with somebody and can respond contextually for me.
• 8:09
  Speaker: And I go in and makes make some edits.
• 8:11
  Speaker: I run a podcast.
• 8:12
  Speaker: I have an agent that's like automating podcast guest scouting.
• 8:15
  Speaker: So it would reach out to the guests, scout them on LinkedIn, and then sort of like maintain its own CRM.
• 8:20
  Speaker: This is like pretty uh like advanced stuff.
• 8:22
  Speaker: And even for coding as well, we have agents that we were using, we we have them running in a loop where they would look at the logs that um we have, and then they would just figure out customer errors.
• 8:32
  Speaker: And we even have agents that are looking at how customers are using the product.
• 8:36
  Speaker: Like after like uh we would do these like customer interviews and customer sessions where we'd bring an agent in um to sort of like look at how they're using it and then take those transcripts and those video recordings, give it to the agent, and then eventually sort of like improve the platform.
• 8:49
  Speaker: So these are like really advanced things, but but for like an originator, the simplest thing that you can use AI for right now is income.
• 8:56
  Speaker: You can just get out of the box and say, hey, income is the most important thing in the loan.
• 9:01
  Speaker: Like 90% of the reasons why a loan gets rejected is because of income, right?
• 9:05
  Speaker: So you can just say, hey, I'm gonna use AI for income.
• 9:07
  Speaker: This is like, and it's also quite deterministic because you can sort of verify what the underwriter came up with and what the AI came up with.
• 9:15
  Speaker: And we found that as like a way to have people buy in and all the other stuff, like identifying large deposits, all that stuff, those things are like much more subjective and much more like guideline driven.
• 9:24
  Speaker: But something that is as deterministic as just like income, just use AI for it.
• 9:29
  Speaker 1: Well, now that I realize my podcast is light years behind yours, let's talk about Addy and Ernest a little bit.
• 9:34
  Speaker 1: One of the taglines is that you can originate loans 90% faster.
• 9:38
  Speaker 1: And I I would love for you to give an overview of Addy, certainly, but also where you see the improvements to be made in the mortgage process.
• 9:48
  Speaker 1: Because I I will talk to people that are in the underwriting space, and I'm going, what does it matter if underwriting can be done in three minutes if the appraisal is still taking seven days?
• 9:57
  Speaker 1: So just your thoughts.
• 9:58
  Speaker 1: First off, what does Addy do in earnest?
• 10:00
  Speaker 1: And also, where do you see easy improvements?
• 10:03
  Speaker 1: And then we can get into kind of longer term, you know, a nirvana mortgage process.
• 10:08
  Speaker: Yeah.
• 10:08
  Speaker: In short, ADI AI is an AI brain for mortgages.
• 10:12
  Speaker: So it will connect to all of your mortgage tools, and it has AI agents that it would build for you to help you pre-underwrite loans faster, uh, to help you process and set up the loan, calculate income, large large large deposits, all of the mundane stuff that loan officers and processors are already doing today.
• 10:34
  Speaker: ADI AI is going to do that for you.
• 10:36
  Speaker: And the biggest thing is because it is already partnered with a lot of the tools in our space, like Encompass and Meridian Link, we plug in directly into those tools.
• 10:46
  Speaker: You don't have to change your current tools.
• 10:48
  Speaker: A lot of the people that use Addy AI just use the agents that work inside of those tools and they don't have to relearn uh newer tools.
• 10:55
  Speaker: So we can get a customer stood up like in minutes, pretty much.
• 10:58
  Speaker: To your question, I think it is much more helpful if the tools work directly inside of the customer space.
• 11:06
  Speaker: And then you can have like these agents um pretty much deployed and can perform actions as a human is performing an action.
• 11:12
  Speaker: We try to do a lot of work with like the the product experience and just say, well, uh, how do humans sort of like process the loan today?
• 11:20
  Speaker: When you said something about, well, what does it matter if I can pre-underwrite in five minutes, but the appraisal is not going to be done in seven days?
• 11:26
  Speaker: The AI is getting there.
• 11:28
  Speaker: There are some parts of the process where if you are, say, like um, you know, you're a chief lending officer, well, you have some offshore operation and you have, let's say, 50 processors offshore and all leaders just scrub files.
• 11:40
  Speaker: You can start to say, well, I can use AI to automate, say, 90% of that work and just have those people go focus on other parts of the inefficiencies of the business.
• 11:51
  Speaker: So now you start to shift the business priorities where you are you had like human talent that was elsewhere, that now that human talent can be directed to other things, let's say, like appraisal ordering and other stuff.
• 12:03
  Speaker: But like some of the other stuff in the industry, like we have we have TRID, um, things that literally prevent you from closing the loan in in hours, right?
• 12:12
  Speaker: Like you have like regular regulatory things that's like you know, that present prevent you from doing things faster.
• 12:18
  Speaker: So I think right now in the industry is like you have to look at say, well, what are the things that I can do today that has no bottleneck in like some sort of physical work, and then that also has no bottleneck in regulatory work, and then just like implement those things.
• 12:32
  Speaker: And you know, if you can't help, let's say, an appraisal coming back in 24 hours, there's some companies that can give you like a 24-hour appraisal.
• 12:39
  Speaker: And those companies say you can go work with those companies and just help the process move move a lot faster.
• 12:44
  Speaker: But maybe we'll eventually we'll have like uh those uh robots that will go out and like appraise the property and then do all that stuff.
• 12:51
  Speaker: Uh, but right now the things that are within your control are things that you can help AI and direct some resources inside of the business to like other things that AI cannot help with.
• 13:02
  Speaker 1: There's different cohorts or subsets of people out there when it comes to AI.
• 13:06
  Speaker 1: There's the people that are trying to get it as much in their processes as possible.
• 13:11
  Speaker 1: Let let's let AI do everything for me as or as much as it can.
• 13:14
  Speaker 1: There's the people that are saying, I'm going to be left behind if I don't use it.
• 13:18
  Speaker 1: So let me try to integrate it into what I'm doing.
• 13:21
  Speaker 1: And there's the people that are saying, I'm not doing it, you know, or what sorry for the southern accent.
• 13:27
  Speaker 1: But you know, to hell with that.
• 13:29
  Speaker 1: I'm I'm sticking in my ways and and so I wonder, in a in a purely practical sense, at what point people are left behind from a I am no longer closing loans, I am clearly losing competition to the point that I need to exit this industry?
• 13:45
  Speaker 1: When does the and maybe you can throw out milestones, but when do the people that are vehemently against AI start start being incapable of competing in a true sense?
• 13:56
  Speaker 1: When do the people that are are kind of adopting but but not really getting it, when do they become obsolete?
• 14:02
  Speaker 1: What when do we actually what what are the the milestones or the markers for for obsolescence for those groups?
• 14:11
  Speaker: Oh man, you you're asking me to be like Dr.
• 14:13
  Speaker: Dr.
• 14:14
  Speaker: Doom right now.
• 14:15
  Speaker: When are you gonna be obsolete?
• 14:19
  Speaker 1: Because I would say that these people are people that haven't really embraced AI are still able to compete and make decent livings right here in the middle of 2026.
• 14:27
  Speaker: Yeah, and hey man, the the the thing about AI is like a lot of people like to FOMO it and be like super hype driven and say, hey, if you don't use the current the the next best model, like you're gonna be left behind.
• 14:40
  Speaker: If you don't use this, you're gonna be left behind.
• 14:42
  Speaker: Like Anthropic just dropped mythos, which is an incredibly good model.
• 14:47
  Speaker: And over this week, I've just had this like existential thing where I'm like, holy shit, like we're crossing some sort of like chasm in AI right now where I like personally feel it.
• 14:57
  Speaker: And I made a post on Instagram the other day.
• 14:59
  Speaker: I never really make posts on Instagram.
• 15:00
  Speaker: It's like 99% of the world does not understand the chasms that we have crossed with AI.
• 15:06
  Speaker: In San Francisco, you have these labs that are paying expert humans to like perform a task and have the AI record the task and then use something called reinforcement learning to go replicate that task.
• 15:20
  Speaker: I would argue that coding is largely solved, which is like one of the tasks that humans do.
• 15:26
  Speaker: And financial services, underwriting mortgages is like the next thing.
• 15:28
  Speaker: So if you've seen that meme where it's like the Dark Angel of Death, they're going door to door, just like now we've crossed the coding, uh, the coding door, the next door is the financial services door.
• 15:38
  Speaker: So the obsolescence is coming, but it's not going to be immediate.
• 15:42
  Speaker: Like there's not going to be like a wand that you wave and then everybody is as obsolete.
• 15:48
  Speaker: One of my mentors that I look up to, Dan Sugg, uh, in Michigan here, uh, he usually tells me the printing press was developed in 1440 and it took decades or centuries for it to be fully adopted.
• 16:00
  Speaker: So like I don't like to be like the uh Dr.
• 16:02
  Speaker: Doom thing and say you're gonna be obsolete, but I really think there are some things as minor as say, like, if you're not using AI for income, you're truly just like hurting your business.
• 16:11
  Speaker: Because like if you can't get income same day or like same minute, or like just at the time of submitting an application, you're just getting left behind on those places.
• 16:20
  Speaker: So while you may not be fully obsolete and wiped out of the market, but there are some things like competitive edge where somebody can beat you to a deal five minutes before you even get there.
• 16:30
  Speaker: So you're slowly gonna be left out, so it's not gonna be like a one-time process, like you might be left out over like a 10-year time span instead of like a 10-minute time span.
• 16:39
  Speaker 1: Yeah, I do remember when uh Ten Cent came out, C Dance came out, and I went, we have reached this point where, and and these are those are video soft for making videos, fake videos out there.
• 16:50
  Speaker 1: I went, we have reached the end of true reality because who knows what's real anymore, and who knows.
• 16:56
  Speaker 1: So it's it's weird new, it's a weird new frontier that we're living in in terms of crossing these chasms, and and we can't go, you know, the genie's out of the bottle, the toothpaste is out of the tube, whatever, whatever phrase you want to use.
• 17:07
  Speaker 1: I want to focus, I want to focus on Addy AI though, yeah a little bit.
• 17:10
  Speaker 1: And and obviously, one of the selling points is that this can be rolled out in minutes without a complex setup.
• 17:17
  Speaker 1: But I would argue people in general, and certainly this industry, are reluctant toward change.
• 17:24
  Speaker 1: And so you could argue that the rollout of a technology is as important as what the technology actually does.
• 17:31
  Speaker 1: If a company botches the rollout process or the implementation, people are never going to buy into it.
• 17:37
  Speaker 1: So I'm hoping you can speak a little bit to designing technology for where it meets users in the sense that it's easy for people to use, easy for them to buy into, and it's easy for them to create lasting and meaningful changes to the way they go about their business.
• 17:51
  Speaker: I would say I've been in the industry a little bit now that I've seen both both sides of the coin where you'd have really great implementations, and sometimes you wouldn't have really, really great implementations, and uh every company is different.
• 18:04
  Speaker: I like to be vulnerable in these conversations, and you know, a lot of people are like, oh hey, like implementation's great.
• 18:10
  Speaker: It's like five minutes and everything works.
• 18:11
  Speaker: Where where is we we can deploy a tech in five minutes?
• 18:16
  Speaker: Um, even when we're connecting Encompass to Adi AI, there's this like 30-page setup that we made.
• 18:23
  Speaker: It's like you have to go to the services page, click this button, like import these rules, do all of that stuff.
• 18:28
  Speaker: And then we just looked at it and we're like, well, why does a human have to click all this like nonsense, right?
• 18:33
  Speaker: And we've just built an agent that will do the setup for you.
• 18:36
  Speaker: So the technical part of doing the setup is pretty much done.
• 18:40
  Speaker: Like a human can go in adding, like turn it, and then they have agents that can do the connection.
• 18:44
  Speaker: But the human elements to training the humans, that still needs a lot of direction from the team.
• 18:50
  Speaker: So I'll give you two examples of um of an implementation that we had the other day.
• 18:55
  Speaker: There was one that I didn't like the way it went because they said to us, just give us access to the platform, we'll invite our underwriters, we'll invite our team, we'll get our team trained, and then you guys can just be like in the sidelines.
• 19:08
  Speaker: And we're like, okay, if you want things to go that way, sure you will let you handle the rollout.
• 19:14
  Speaker: It didn't go out well because while you're an IMB and then you're great at closing loans, like you're great at being like the number one lender in like Makato, Texas.
• 19:25
  Speaker: Um, we are great at building software, we're great at implementing and being the product people.
• 19:30
  Speaker: So I like for us to handle the rollout for you, like have that sort of like wet gloved service.
• 19:36
  Speaker: And the opposite to that was another rollout where we came in, we had our setup people um set up training sessions for the team.
• 19:44
  Speaker: We identified like who's the best processor here, who's the best underwriter here, and then we actually built this thing.
• 19:49
  Speaker: It's like a it's like a gamification thing where we had told the team, hey, you're gonna spend uh a little bit on DoorDash credits.
• 19:57
  Speaker: And what we're gonna build is a leaderboard of how many people are using it and what's their streak looks like.
• 20:02
  Speaker: If you use Duolingo, we literally built Duolingo for a mortgage just for that one company.
• 20:07
  Speaker 1: That owl, that owl haunts my dreams, man.
• 20:09
  Speaker 1: The Duolingo owl.
• 20:12
  Speaker: Yeah.
• 20:13
  Speaker: And so that's what happens when you bring in experts in.
• 20:15
  Speaker: And then once we identify the landscape in the company and we say, well, we have to build a leaderboard, we have to identify some of these people, we have somebody right now who has like an 11-day streak on Addy.
• 20:24
  Speaker: And this is something that we had just launched um, let's say two or three weeks ago.
• 20:29
  Speaker 1: What have the biggest points of reluctance been or objection been when you are are potentially pitching your product or bringing your product into a company and how have you overcome those?
• 20:41
  Speaker: Man, people have been burnt, burnt out.
• 20:43
  Speaker: Like they don't, it's trust.
• 20:45
  Speaker: They don't like quite trust that it could do what it says it could do.
• 20:50
  Speaker: Because, you know, we've had AI in the industry for like so long, and sometimes it breaks my heart because I'm talking to somebody, you know, I don't know those quotes.
• 20:58
  Speaker: Like I think it was one of the US presidents.
• 21:01
  Speaker: Uh, you know, every politician comes in and says, uh, you know, I'm gonna do things different.
• 21:05
  Speaker: And like after every term, it's like the same thing.
• 21:07
  Speaker: And then I don't know which which uh politician on I'm gonna butcher that's like the eight worst words you can hear from a politician is like, I'm from the government and I'm here to help.
• 21:15
  Speaker: So that might not be eight words, but it's like, okay, I'm an AI company and I'm here to help.
• 21:21
  Speaker: The listeners are gonna like start counting their their fingers.
• 21:25
  Speaker: It's like uh it's like the AI wiz doesn't know how to how to count.
• 21:29
  Speaker: But so the worst words you can say is like, I'm an AI company and I'm here to help, because they've heard that so many times, like for years and years.
• 21:39
  Speaker: And so trust has been one of the things.
• 21:41
  Speaker: And so one of the ways we can overcome that is like, you know, hey man, just try this thing out, do a pilot with your team.
• 21:48
  Speaker: Like, you don't have to roll it out to the entire team.
• 21:50
  Speaker: Get a couple of underwriters, and then we would compare what your underwriters have with what the AI does.
• 21:56
  Speaker: And then we would have those transcripts and then show you the different uh sort of like responsibilities.
• 21:59
  Speaker: And then once people see that, we try to also get people into their own loans.
• 22:05
  Speaker: Sometimes when like vendors come in, they would have a test loan.
• 22:08
  Speaker: Like they would have a test uh environment.
• 22:10
  Speaker: It's like, oh, it's working so well in this test loan.
• 22:13
  Speaker: We just do things live.
• 22:15
  Speaker: We go in, we just do things live and see how it performs in your organization.
• 22:18
  Speaker: So trust has been the biggest barrier.
• 22:20
  Speaker: And the way we overcome that, just like doing things live and then moving fast with these pilots.
• 22:25
  Speaker 1: So people can't see this, but I'm going to count on my fingers to three here.
• 22:29
  Speaker 1: We're going to close with a three-part question.
• 22:31
  Speaker 1: Give us the latest and greatest from Addy.
• 22:34
  Speaker 1: And then maybe just a sales pitch in general.
• 22:37
  Speaker 1: You know, I like you so much.
• 22:38
  Speaker 1: I'm going to open it up to do that.
• 22:40
  Speaker 1: Then best next steps for people.
• 22:42
  Speaker 1: One, two, three.
• 22:44
  Speaker: Letters and greatest from us.
• 22:45
  Speaker: Uh it depends on when this is coming out.
• 22:47
  Speaker: But we actually just closed a top five uh lender.
• 22:51
  Speaker: That's you know, super cool.
• 22:52
  Speaker: And another thing is uh we crossed uh 20,000 loans processed per month on Addy AI, growing you know 10x uh month over month.
• 23:00
  Speaker: Uh that's uh super super cool.
• 23:02
  Speaker: And a lot of the growth has come in the last year since we have all of these like integrations and and and what we're doing with some of our partners.
• 23:10
  Speaker: We have incredible partners, and then you gotta know from Addy, we've been working on this tech before going to market for a really long time.
• 23:16
  Speaker: Like we were all grad students at CMU, just like building berates to train models.
• 23:20
  Speaker: So it's not like we're coming into the industry from hype where they're sort of working on this thing, like pre-chat GPT, and we're not even in the market.
• 23:27
  Speaker: So it's it's pretty cool to see like a top five uh IMB has just like signed up with us.
• 23:32
  Speaker: And then a sales pitch.
• 23:34
  Speaker: Man, I hate those.
• 23:35
  Speaker: I don't have to go like a good good salesperson.
• 23:38
  Speaker: Uh a sales pitch from Addy is that you know, if you're an IMB, you don't have to think about changing your current tools.
• 23:46
  Speaker: It it's not a capital-intensive expense to adopt AI.
• 23:51
  Speaker: You can literally be in your current tools and use agents that can work inside of the current tools to then adopt AI.
• 23:59
  Speaker: You can have like an agentic brain because if you want to change every single tool that you use, you're gonna take years because you have all of that experience and stuff.
• 24:09
  Speaker: So why not get an experienced team that can bring in these agentic brains and then have it work with your team and also just train your team.
• 24:20
  Speaker: So that's so so that's that's gonna be my soul's pitch to folks is that hey, don't change your current tools, bring in agents into your current tools tools and see how they perform.
• 24:29
  Speaker: Um, and then the last question go to addy.com, baby.
• 24:34
  Speaker: Go to Addy.com, try it out for yourself, with a demo.
• 24:37
  Speaker 1: All right, Mr.
• 24:37
  Speaker 1: 10x per month.
• 24:38
  Speaker 1: I look forward to you doing 200,000 loans in July, and I look forward to having you back on the show.
• 24:43
  Speaker 1: Always a pleasure.
• 24:44
  Speaker 1: Thank you very much.
• 24:44
  Speaker 1: Take care, Robbie.
• 24:47
  Speaker 1: Investipedia tells us that a swap is a derivative instrument allowing counterparties to exchange or swap a series of cash flows based on a specified time horizon.
• 24:57
  Speaker 1: Typically, one series of cash flows is considered the fixed leg of the agreement, while the less predictable floating leg includes cash flows based on interest rate benchmarks or foreign exchange rates.
• 25:07
  Speaker 1: The swap contract, which is agreed on by both parties, specifies the terms of the swap, including the underlying values of the legs, plus payment frequency, and dates.
• 25:16
  Speaker 1: People typically enter swaps either to hedge against other positions or to speculate on the future value of the floating legs underlying index currency, etc.
• 25:26
  Speaker 1: Today the swaps market is pricing in with near certainty that the central bank will hold rates steady at the conclusion of its meeting.
• 25:33
  Speaker 1: But the eyes are on chairman and relative stranger to the market, Kevin Walsh's first press conference for clues on the future.
• 25:41
  Speaker 1: Signals on the Fed's policy bias, communication strategy, and inflation outlook will be closely watched.
• 25:48
  Speaker 1: With treasury yields already reflecting expectations for a more balanced or slightly hawkish stance, the combination of easing energy concerns and lingering skepticism about the durability of any peace agreement has left rates near the lower end of the recent range, while investors wait clearer direction from both policymakers and the Middle East.
• 26:04
  Speaker 1: Today's economic calendar kicked off with mortgage applications from MBA, which decreased 3.8% from one week earlier.
• 26:10
  Speaker 1: Later today brings May retail sales, April business inventories, May pending home sales, weekly crude inventories for oil, and the aforementioned June FOMC rate decision.
• 26:20
  Speaker 1: We begin hump day with agency MBS prices roughly unchanged from yesterday's close, the two-year yielding 4.05%, and the 10-year yielding 4.44% after closing yesterday at 4.43%.
• 26:32
  Speaker 1: Let's wrap up with the joke and some housekeeping.
• 26:37
  Speaker 1: Two men debate whether Hawaii is pronounced Hawai'i or Hawai'i.
• 26:42
  Speaker 1: They ask a passerby who answers Hawaii.
• 26:45
  Speaker 1: Thank you, says the satisfied first man.
• 26:48
  Speaker 1: You're welcome, replies the passerby.
• 26:50
  Speaker 1: Thanks again to this week's podcast sponsor, TrueWork, the one verification solution to replace in house waterfalls.
• 27:04
  Speaker 1: Verify any borrower with a VOIE solution that automates the entire process to quickly deliver the most accurate and complete reports with ProGSE coverage.
• 27:13
  Speaker 1: To learn more, visit Truework.com.