WEBVTT - AI Can Tell Us Something About Credit Market Weakness 0:00:02.720 --> 0:00:07.200 Bloomberg Audio Studios, Podcasts, radio News. 0:00:18.560 --> 0:00:21.640 Hello and welcome to another episode of The Odd Lots podcast. 0:00:21.720 --> 0:00:23.960 I'm Joe Wisenthal and I'm Tracy Alloway. 0:00:24.160 --> 0:00:26.960 Tracy, there are just so many credit related things to 0:00:27.000 --> 0:00:28.800 talk about right now, all things credit. 0:00:28.920 --> 0:00:29.400 I love it. 0:00:29.640 --> 0:00:30.200 I love it. 0:00:30.360 --> 0:00:31.840 Credit is interesting again. 0:00:31.960 --> 0:00:32.839 This might be one of the. 0:00:32.800 --> 0:00:35.320 Only credit episodes that we've ever done where like I 0:00:35.440 --> 0:00:37.720 found the guest because I feel like when I think 0:00:37.720 --> 0:00:39.800 about like a credit all the credit episodes, it's usually 0:00:39.800 --> 0:00:42.320 like someone you know. Randomly. I found someone who knows 0:00:42.360 --> 0:00:44.199 a little bit something about credit. She's like, oh, let 0:00:44.240 --> 0:00:44.479 me do it. 0:00:44.520 --> 0:00:45.640 Let me The stakes are high. 0:00:46.240 --> 0:00:48.479 I know I was thinking about there because you're like, how, Joe, 0:00:48.560 --> 0:00:50.560 you like pick someone who doesn't know anything. No, I 0:00:50.560 --> 0:00:52.840 don't think that. I think we have a very knowledgeable 0:00:52.920 --> 0:00:55.040 credit guest. But I'm a little stressed about this aspect. 0:00:55.120 --> 0:00:57.480 I believe in you, Joe, you do. I trust your judgment. 0:00:57.840 --> 0:01:00.080 But to your point, there's a lot going on. So 0:01:00.120 --> 0:01:03.520 obviously there are concerns around private credit. We've had some 0:01:03.920 --> 0:01:09.080 idiosyncratic defaults and frauds in the market, and each one 0:01:09.160 --> 0:01:11.840 is special in their own way. But I think the 0:01:11.880 --> 0:01:15.399 worrying aspect is that they keep coming to light. Yeah, right, 0:01:15.520 --> 0:01:18.160 And so you've seen people like Jamie Diamond using the 0:01:18.160 --> 0:01:22.280 cockroach analogy, which is now famous. And at the same 0:01:22.319 --> 0:01:25.720 time you have the connection with AI, right, which we 0:01:25.760 --> 0:01:28.039 have spoken about a little bit on the podcast with 0:01:28.080 --> 0:01:33.440 Paul Kadrowski. All these complex circular financing structures that are 0:01:33.520 --> 0:01:35.520 driving a lot of the credit boom, or have been 0:01:35.640 --> 0:01:39.000 driving a lot of the credit boom, and then at 0:01:39.000 --> 0:01:41.759 the same time you also have the impact of AI 0:01:42.240 --> 0:01:43.720 on credit itself. 0:01:43.840 --> 0:01:46.960 Yeah, that's right because in theory right, like we've talked 0:01:47.000 --> 0:01:49.520 about this. We did that episode with Joel Werthheimer that 0:01:49.600 --> 0:01:52.360 was in a slightly different context, but we've done these 0:01:52.400 --> 0:01:55.960 episodes about you know, just the incredible length of deal text, 0:01:56.200 --> 0:01:59.480 et cetera. And perhaps if there's one area where maybe 0:01:59.480 --> 0:02:02.240 we could say with some high degree of confidence that 0:02:02.680 --> 0:02:05.680 large language models could be useful, it is can we 0:02:05.760 --> 0:02:09.320 break down this multi hundred page agreement so that we 0:02:09.360 --> 0:02:12.360 don't have to have you know, junior associates or junior 0:02:12.440 --> 0:02:15.400 lawyers or junior bankers up till four in the morning 0:02:15.560 --> 0:02:17.800 making sure that every comma is in the right place, 0:02:17.880 --> 0:02:21.080 et cetera. In theory, this could be an area in 0:02:21.160 --> 0:02:23.600 which AI could be productively applied. 0:02:23.720 --> 0:02:27.280 You know, there was an actual case argued over a comma. 0:02:27.400 --> 0:02:29.639 I can't remember exactly what it was, but like, you're 0:02:29.680 --> 0:02:33.240 absolutely right, the grammar, the specific words clearly matter in 0:02:33.320 --> 0:02:36.000 legal language. I would just add one of the things 0:02:36.000 --> 0:02:39.800 that's been driving arguably driving private credit is the booming 0:02:39.919 --> 0:02:43.400 creditor on credit or violence in public deals. So it 0:02:43.440 --> 0:02:45.680 was this idea that you could avoid that by having 0:02:45.800 --> 0:02:49.840 you know, this private close relationship with your borrower where 0:02:49.880 --> 0:02:50.840 you are higher up. 0:02:50.760 --> 0:02:53.960 In the waterfall of payment. So this is important. 0:02:54.000 --> 0:02:56.079 It would be really nice if you could upload a 0:02:56.120 --> 0:02:59.320 credit agreement to chat GPT and just say, make sure 0:02:59.360 --> 0:03:01.200 there's nothing in that would get me in trouble. Make 0:03:01.240 --> 0:03:03.680 sure there's nothing in here that five years later I 0:03:03.720 --> 0:03:05.080 will regret the placement of a. 0:03:05.080 --> 0:03:07.680 Certain Make sure I don't lose money, make sure. 0:03:07.520 --> 0:03:10.600 I don't lose money in some technical way anyway. So 0:03:10.639 --> 0:03:12.639 there's just a lot going on. I feel like there's 0:03:12.680 --> 0:03:15.359 plenty of episodes to do on this, but we really 0:03:15.400 --> 0:03:18.160 do have the perfect guest, someone who literally sort of 0:03:18.200 --> 0:03:20.639 sits in the intersection of I think we identified three 0:03:20.720 --> 0:03:22.920 distinct trends. Here we are going to be speaking with 0:03:23.000 --> 0:03:25.360 Dan Wortman. He is the co founder of a company 0:03:25.440 --> 0:03:29.760 called Nohica AI, and it does exactly this. It sort 0:03:29.760 --> 0:03:32.160 of attempts to use AI to understand credits. There's a 0:03:32.200 --> 0:03:35.400 lot of understanding about deals and the text in them. 0:03:35.600 --> 0:03:38.119 He also just has a lot of understanding about AI, etcetera. 0:03:38.240 --> 0:03:40.200 So we can talk about all of these things. Dan, 0:03:40.320 --> 0:03:42.560 thank you so much for coming on the podcast. 0:03:42.760 --> 0:03:44.960 Thanks so much for having me. I'm a fan of 0:03:45.000 --> 0:03:46.920 the show. Love to hear it you guys. It kind 0:03:46.920 --> 0:03:50.640 of like celebrities for me. So it's kind of fitting 0:03:51.120 --> 0:03:54.200 that I'm here because at least with folks of Bloomberg, 0:03:54.280 --> 0:03:57.200 because many people think about us and Oedica like the 0:03:57.200 --> 0:03:58.280 Bloomberg for deal terms. 0:03:58.280 --> 0:04:00.720 Okay, well let's see. Let's see if you actually live 0:04:00.800 --> 0:04:01.120 up to that. 0:04:01.280 --> 0:04:01.360 No. 0:04:01.480 --> 0:04:04.760 But so since I said I'm stressed that, oh this time, 0:04:04.800 --> 0:04:07.080 we're doing a credit episode and I've found the guest 0:04:07.320 --> 0:04:10.200 give us the quick version of like your career and 0:04:10.240 --> 0:04:11.120 what no Edica is. 0:04:11.680 --> 0:04:14.480 Yeah, so let's start with Oedica. What we build at 0:04:14.560 --> 0:04:18.800 no Edica is a power software for benchmarking real time 0:04:18.880 --> 0:04:22.600 data on what's market in credit m and a capital 0:04:22.600 --> 0:04:26.000 markets deal terms. Okay, so said another way, we help 0:04:26.080 --> 0:04:30.279 folks like transactional attorneys, credit managers, bankers. We help them 0:04:30.320 --> 0:04:34.159 figure out whether the terms of their transactional agreements like 0:04:34.440 --> 0:04:39.680 think financing agreements, murder agreements, perspectuses, and really all other 0:04:39.720 --> 0:04:43.200 corporate transactions are on or off market by benchmarking them 0:04:43.240 --> 0:04:46.000 to market comps. So as far as the genesis of oedica, 0:04:46.400 --> 0:04:48.520 it was kind of born out of my own experience 0:04:48.920 --> 0:04:50.839 in my career. So I started my career at Blackrock. 0:04:51.040 --> 0:04:53.480 I was on a team responsible for coming up with 0:04:53.560 --> 0:04:57.080 new financial products and fixing and markets, and we were 0:04:57.080 --> 0:05:01.679 developing these new interesting innovative structure and I just learned 0:05:01.720 --> 0:05:05.040 a ton about the capital markets ecosystem, and in particular 0:05:06.040 --> 0:05:09.280 just this is a fifty trillion dollar global market and 0:05:09.360 --> 0:05:13.960 it runs on phone calls and relationships and it's unbelievably antiquated. 0:05:14.320 --> 0:05:16.320 Then fast forward, I went back to get my GD 0:05:16.400 --> 0:05:19.200 I joined WALKT toall Lipton, where I did corporate transactions. 0:05:19.200 --> 0:05:21.400 This was twenty seventeen to twenty twenty two. So if 0:05:21.680 --> 0:05:23.839 if you guys remember that time, it was heyday of 0:05:23.960 --> 0:05:27.359 merger activity. So I worked on you know, T Mobiles, 0:05:27.400 --> 0:05:30.640 Bioto Sprint, the biggest thirty billion dollar commitment at the time, 0:05:31.040 --> 0:05:35.880 Algon ave to see raytheon and I distinctly remember sitting 0:05:35.920 --> 0:05:38.120 down at my desk. I was looking at a transactional 0:05:38.160 --> 0:05:40.960 grip and a multi billion dollar merger, and I was 0:05:40.960 --> 0:05:42.960 looking at a term, and I was trying to figure 0:05:42.960 --> 0:05:46.159 out whether I should help my client accept term A 0:05:46.600 --> 0:05:48.920 or term B in this context. And I was stuck. 0:05:49.080 --> 0:05:51.000 So I called the seenor partner on the deal. I said, hey, 0:05:51.160 --> 0:05:54.520 where's the database of information where I could see exactly 0:05:54.560 --> 0:05:56.640 how this term should come out and quantify it for 0:05:56.760 --> 0:06:00.680 my client? And you know, the answer was that doesn't exist. 0:06:01.800 --> 0:06:04.039 Now that was two and a half plus years ago. 0:06:04.080 --> 0:06:05.760 Now I left walked out to start no edico with 0:06:05.760 --> 0:06:10.200 a fairly simple idea, which is AI enables us to 0:06:10.320 --> 0:06:14.039 finally quantify what market agreement terms should look like in 0:06:14.080 --> 0:06:17.480 these markets. You know, now we work with almost all 0:06:17.520 --> 0:06:19.120 the top twenty law firms on the street, but helping 0:06:19.120 --> 0:06:21.920 them advise their clients on these deals. And this here 0:06:22.080 --> 0:06:23.479 on track to do about a trillion dollars or of 0:06:23.480 --> 0:06:25.080 transactions through the platform. 0:06:25.000 --> 0:06:26.080 And you get one percent of that. 0:06:26.200 --> 0:06:29.200 So that's great, Well, talk to us about what these 0:06:29.240 --> 0:06:33.720 financing agreements actually look like and how traditionally they're sort 0:06:33.720 --> 0:06:36.080 of judged by both the investors and the lawyers who 0:06:36.120 --> 0:06:36.960 are looking at them. 0:06:37.160 --> 0:06:41.600 Yeah, I mean so when I say deal terms, what 0:06:41.640 --> 0:06:44.039 I mean is deal terms are really the underpinning of 0:06:44.080 --> 0:06:47.680 the entire transactional system, the rules of the road. You 0:06:47.680 --> 0:06:50.719 could think about them like speed limits, double yellow lines, 0:06:50.800 --> 0:06:53.599 street lights. They're kind of the plumbing that goes into 0:06:53.640 --> 0:06:57.839 the transactions, putting in a way that people can understand. Imagine, 0:06:57.880 --> 0:07:01.200 I go sign of lease. Most people are very familiar 0:07:01.200 --> 0:07:05.400 with certain things, right, like the rent price, the how 0:07:05.440 --> 0:07:06.159 long the lease. 0:07:06.040 --> 0:07:08.520 Is, subletting policy exactly. 0:07:08.600 --> 0:07:11.480 But if deep in that twenty page lease the least 0:07:11.480 --> 0:07:15.240 says if the weather gets under thirty degrees at any time, 0:07:15.280 --> 0:07:17.720 you forfeit your right to the apartment, Well, that's a 0:07:17.760 --> 0:07:21.680 deal term, and that affects whether you want to accept 0:07:21.680 --> 0:07:23.920 that lease or not. And so it's the same in 0:07:23.960 --> 0:07:27.160 capital market terms. To give you a more tangible example, Yeah, 0:07:27.440 --> 0:07:31.240 are you guys fast food people? Yes? Yes, Okay, So 0:07:31.320 --> 0:07:33.960 I'm like a McDonald's guy. Yea, And whenever I go 0:07:34.040 --> 0:07:36.960 to McDonald's, I always ordered the tempiece chicken McNugget. I've 0:07:37.080 --> 0:07:40.560 ordered the ten piece hundreds of times. There's exactly three 0:07:40.560 --> 0:07:42.360 things that happened to you order a tenpiece, you open 0:07:42.400 --> 0:07:44.840 the box, you have nine pieces. You open the box 0:07:44.880 --> 0:07:47.200 you have exactly ten pieces. Or you open the box 0:07:47.440 --> 0:07:50.600 and you have eleven pieces. Now, if you have nine pieces, 0:07:50.840 --> 0:07:53.239 you go to the counter, you say, hey, I'm missing 0:07:53.240 --> 0:07:55.640 a piece. They give you a piece. You get the 0:07:55.640 --> 0:07:58.200 benefit of your morgan. If you get ten, you enjoy 0:07:58.280 --> 0:08:01.280 your McNuggets. If you get eleven, what do you do? 0:08:01.320 --> 0:08:02.200 You stay quiet? 0:08:03.120 --> 0:08:07.120 Exactly so you had the jaguar right now. There's this 0:08:07.240 --> 0:08:10.240 kind of unwritten rule in American consumerism, which is that 0:08:10.960 --> 0:08:13.840 if a company that's bigger than you gives you something 0:08:13.920 --> 0:08:17.560 by accident, then you get the benefit of that as 0:08:17.560 --> 0:08:21.200 a consumer. Well, in twenty twenty, the exact kind of 0:08:21.200 --> 0:08:24.480 thing happened in the credit markets, but it ended very differently. 0:08:25.080 --> 0:08:28.600 City Bank sent nine hundred million dollars to lenders in 0:08:28.680 --> 0:08:32.040 full prepayment of a loan for Revlon, and they did 0:08:32.040 --> 0:08:34.160 so accidentally. Now, they were supposed to just send an 0:08:34.160 --> 0:08:36.760 interest payment. At the time, the terms of the credit 0:08:36.840 --> 0:08:40.920 agreement were silent. The governing documentation, especially with this loan, 0:08:40.960 --> 0:08:44.320 didn't say what happens in that scenario. Long story short, 0:08:44.440 --> 0:08:47.680 many funds did not give back that hundreds of millions 0:08:47.679 --> 0:08:52.000 of dollars and litigation ensued. But a deal term in 0:08:52.040 --> 0:08:57.200 credit deals called erroneous payment. Deal terms started popping up 0:08:57.200 --> 0:08:59.760 in the market. No Whatadka's data last clocked that deal 0:09:00.320 --> 0:09:02.560 as a last quarter ninety percent of deals. So if 0:09:02.600 --> 0:09:04.560 you don't have that term now in your deal, you're 0:09:04.679 --> 0:09:06.480 way off market in terms of the way the market 0:09:06.520 --> 0:09:08.960 actually operates. This is why deal terms are important. These 0:09:08.960 --> 0:09:11.320 are hundreds of millions of dollars at stake. In the 0:09:11.320 --> 0:09:13.800 context of all these deals. 0:09:13.400 --> 0:09:16.120 There's something very loyally but like I have to say, 0:09:16.160 --> 0:09:18.720 I've never counted the McNuggets. I really get it, so 0:09:18.840 --> 0:09:20.959 just I would this example would have never occurred to 0:09:21.000 --> 0:09:22.839 me because I'm not the type of person that opens 0:09:22.840 --> 0:09:24.320 a box of McNuggets and start. 0:09:24.240 --> 0:09:26.600 Clearly, you don't value McNuggets. 0:09:26.080 --> 0:09:28.640 Not evidently not. What are some other deal terms? So 0:09:28.679 --> 0:09:32.360 that's a great example that. Okay, now, after that incident, 0:09:32.440 --> 0:09:36.160 which is infamous, language about this start popping up. What 0:09:36.200 --> 0:09:38.280 are some other sort of classic and I'm sure they 0:09:38.360 --> 0:09:40.520 get much much more esoteric than that. But what are 0:09:40.559 --> 0:09:44.440 some other like interesting deal terms that trend over time. 0:09:45.000 --> 0:09:48.040 Yeah, so it's really interesting. So there's a whole host 0:09:48.040 --> 0:09:50.240 of what it would call structural protections in a lot 0:09:50.240 --> 0:09:52.600 of these deals. These come in a lot of different vivors. 0:09:52.640 --> 0:09:55.160 Many people talk about them as things like anti pet 0:09:55.200 --> 0:09:58.960 smart terms, things like j crue blockers, things like sert 0:09:59.040 --> 0:10:01.600 of protections. Let's talk about some of the Yeah, let's 0:10:01.600 --> 0:10:04.320 talk about some of these, so anti pet smart terms. 0:10:04.400 --> 0:10:09.480 These are protections that prevent guarantor releases when subsidiaries of 0:10:09.520 --> 0:10:13.000 the credit group become non wholly owned. In other words, 0:10:13.040 --> 0:10:16.400 it prevents value from being transferred away from the loan 0:10:17.000 --> 0:10:20.800 into some other structure which doesn't provide credits for it. 0:10:20.840 --> 0:10:22.200 Let me put this in a way that most people 0:10:22.200 --> 0:10:25.079 don't understand. If you were getting a mortgage on your house, 0:10:25.800 --> 0:10:28.280 pretty simple framework. You take out the debt, you pay 0:10:28.440 --> 0:10:31.679 your mortgage payments, you pay a packfal loan. Bank can 0:10:31.720 --> 0:10:34.280 foreclose in your house if you stop paying a mortgage. 0:10:34.480 --> 0:10:38.000 But in the mortgage if it said something like well, 0:10:38.080 --> 0:10:41.240 if you sell any part of your home front door, 0:10:41.640 --> 0:10:45.280 a window, a shingle, the bank loses the ability to 0:10:45.320 --> 0:10:47.600 foreclose in the house fully. Well, then what would you do. 0:10:47.880 --> 0:10:50.760 You'd sell a single shingle, you would stop paying your 0:10:50.800 --> 0:10:53.400 mortgage and you get to keep your house and you 0:10:53.440 --> 0:10:56.720 get the benefit of that. That's what anti pest smart 0:10:56.800 --> 0:11:01.520 terms actually prevent. They prevent the ability for credit groups 0:11:01.840 --> 0:11:05.160 to actually sell a single equity and actually lose the 0:11:05.160 --> 0:11:07.800 credit support from that particular equity. So it's kind of 0:11:07.800 --> 0:11:09.840 interesting what we're seeing in the market right now. We 0:11:09.920 --> 0:11:13.040 have this really unique vantage point from the point of 0:11:13.120 --> 0:11:16.720 view of our software where we quantify trends in deal 0:11:16.800 --> 0:11:19.280 terms over time, and so we can actually very precisely 0:11:19.320 --> 0:11:22.160 tell you the percentages of deals that are actually getting 0:11:22.160 --> 0:11:24.120 a lot of these structural protections and actually gives us 0:11:24.120 --> 0:11:28.199 this really unique window into the anxieties and the optimisms 0:11:28.200 --> 0:11:31.160 that are currently happening in the market. Some people think 0:11:31.160 --> 0:11:33.440 about this as kind of an early signal of something 0:11:33.559 --> 0:11:36.400 likely to come. So what are we seeing, Well, we're 0:11:36.440 --> 0:11:40.680 calling it a flight to fortification, and it's really happening 0:11:40.720 --> 0:11:42.920 on both issuers and barbers. And I'll explain what I mean. 0:11:42.960 --> 0:11:47.800 We're seeing massive increases in lenders getting structural protections in 0:11:47.880 --> 0:11:50.440 these deals. Basically, these are protections that help make sure 0:11:50.440 --> 0:11:53.400 they're collateral is locked, things like the anti pet smart terms. 0:11:53.600 --> 0:11:57.560 In return, borrowers are getting the same fortification. In fact, 0:11:57.640 --> 0:12:00.920 they're getting more economic flexibility. You could think about it 0:12:00.920 --> 0:12:03.040 as a way for them to weather the storm. This 0:12:03.120 --> 0:12:05.880 is how we're seeing it. So things like add backs 0:12:05.880 --> 0:12:09.599 to eve, you know, more ability to send money to shareholders, 0:12:09.880 --> 0:12:12.640 more ability to make long term events bins. Let's talk 0:12:12.640 --> 0:12:14.920 about the actual specifics of what we're seeing. Antipasmart terms, 0:12:14.920 --> 0:12:16.880 the one I just talked about, we clocked out at 0:12:16.920 --> 0:12:19.920 twenty eight percent of deals in Q three. That was 0:12:19.960 --> 0:12:23.000 at four percent in twenty twenty three, and Q two 0:12:23.080 --> 0:12:25.480 is at twenty five percent, is the highest we've ever recorded. 0:12:25.480 --> 0:12:28.439 That term J crew blockers, which prevent issuers from moving 0:12:28.520 --> 0:12:30.720 material ip out ofside the credit group. That's at forty 0:12:30.720 --> 0:12:33.440 five percent of deals now the baseline from twenty twenty 0:12:33.480 --> 0:12:35.559 three to fifteen percent, and last quarter it was thirty 0:12:35.559 --> 0:12:39.320 eight percent. Anti SERTI protections, which are leansbordination protections. They 0:12:39.360 --> 0:12:42.800 actually helped secure your place in line if and when 0:12:42.880 --> 0:12:45.720 some sort of distress activity happens. That's at eighty four 0:12:45.760 --> 0:12:47.520 percent of deals. That's the highest jump we've ever seen. 0:12:47.559 --> 0:12:50.679 Quarter quarter it went up from sixty one percent to 0:12:50.800 --> 0:12:53.400 twenty three point jump, and the baseline is thirty nine 0:12:53.400 --> 0:12:58.880 percent twenty twenty three. That's pretty significant for a quarterly jump, 0:12:59.600 --> 0:13:02.079 and it really signals something about the market. On the 0:13:02.160 --> 0:13:06.000 quantitative side, we track a lot of stuff too, including 0:13:06.640 --> 0:13:12.000 the ratios under which borrowers need to maintain specific types 0:13:12.000 --> 0:13:15.360 of leverage. We saw that at three point nine times 0:13:15.600 --> 0:13:18.440 EBITDA in Q two and it went down to three 0:13:18.440 --> 0:13:22.160 and a half times, But again that's signaling some sort 0:13:22.160 --> 0:13:25.199 of anxiety among the lender group that we wouldn't normally see. 0:13:25.880 --> 0:13:28.640 Now you may ask what a borrower is getting for this, Again, 0:13:28.679 --> 0:13:32.160 they're getting more fortification. One of the ways this is 0:13:32.160 --> 0:13:36.560 coming up is in EBITDA adbacks, so EBADA add backs. Basically, 0:13:36.640 --> 0:13:41.079 there's a very long and complicated calculation of cash flow 0:13:41.120 --> 0:13:44.000 and a lot of these deals and the adbacks to 0:13:44.000 --> 0:13:48.200 EBADA basically allow bars and issuers to add back certain 0:13:48.320 --> 0:13:50.800 things to count them as cash flows. 0:13:50.640 --> 0:13:53.880 To flatter their balance sheet basically correct correct. 0:13:54.320 --> 0:13:57.520 One of the more interesting adbacks that we track is 0:13:57.520 --> 0:14:01.880 what's called a cost saving satback. So imagine a borrower 0:14:02.040 --> 0:14:06.720 knows it's gonna optimize some cost in the future. If 0:14:06.760 --> 0:14:09.840 it can reasonably predict that cost, it can add that 0:14:09.880 --> 0:14:13.520 back to today's cash flow. That cost savings atback, whether 0:14:13.640 --> 0:14:17.640 materializes or not, is added back to today's cashflow. Sixty 0:14:17.679 --> 0:14:21.240 four percent of deals now have cost savings atbacks in them. 0:14:21.280 --> 0:14:24.360 That's the highest we've ever recorded for deals, with those 0:14:24.400 --> 0:14:27.560 adbacks being above twenty percent of EBITDA that came in 0:14:28.120 --> 0:14:30.160 fifty one percent, which is also the highest we've ever 0:14:30.400 --> 0:14:34.480 tracked on the platform. They're also getting things like excluding 0:14:35.360 --> 0:14:38.600 lenders that are short in their debt. So, for instance, 0:14:38.800 --> 0:14:42.920 folks may be familiar with what happened with the Windstream 0:14:43.000 --> 0:14:45.720 case a few years ago. What happened in that case 0:14:45.800 --> 0:14:51.640 is certain hedge funds were actually short the debt the 0:14:51.760 --> 0:14:55.800 loan that was in default, and that makes them not 0:14:55.960 --> 0:14:59.920 exactly aligned with the company that has the debt outstand. 0:15:00.560 --> 0:15:02.520 Terms started popping up in the market which we've tracked, 0:15:02.520 --> 0:15:06.160 which are called net short lender terms, which allow bars 0:15:06.160 --> 0:15:08.280 to exclude those lenders from voting. That is now in 0:15:08.320 --> 0:15:10.440 thirteen percent of deals, which is the highest we've ever tracked. 0:15:11.000 --> 0:15:13.120 So you could see the fortification actually on both sides 0:15:13.160 --> 0:15:16.360 of the market, and it really signals, I think, to 0:15:16.480 --> 0:15:19.480 us that there's a risk allocation happening with a lot 0:15:19.560 --> 0:15:20.480 of these anxieties. 0:15:36.360 --> 0:15:38.920 Joe, First of all, you know, my husband was a corporate. 0:15:38.640 --> 0:15:39.880 Lawyer at one point. 0:15:39.960 --> 0:15:40.760 Yeah, okay. 0:15:40.800 --> 0:15:42.840 So one of the things he's most proud of is 0:15:42.920 --> 0:15:45.640 he came up with some language in a deal shortly 0:15:45.720 --> 0:15:48.040 after the two thousand and eight financial crisis, and it 0:15:48.160 --> 0:15:51.080 was he sent it to me just now a significant 0:15:51.120 --> 0:15:55.200 dislocation in financial markets. That was him, and that became 0:15:55.360 --> 0:15:59.200 like standard language in risk factors, at least in a 0:15:59.200 --> 0:16:01.479 bunch of that's a contribution. 0:16:01.720 --> 0:16:05.160 I'm the inventor of this deal, so and so the inventor. 0:16:05.320 --> 0:16:09.040 Some people invent great medicine, some people invent some new technology, 0:16:09.080 --> 0:16:11.600 and someone invents a new deal term that gets propagated 0:16:11.600 --> 0:16:14.480 across that's right documents for years thereon after. 0:16:14.680 --> 0:16:15.440 That's how it works. 0:16:15.480 --> 0:16:17.360 But Dan, I wanted to ask you something. Okay, So 0:16:17.400 --> 0:16:21.480 you say there's more fortification in a lot of deal terms, 0:16:21.600 --> 0:16:25.000 more protections perhaps for both investors and lenders. 0:16:25.040 --> 0:16:27.040 I guess one of the things we. 0:16:27.080 --> 0:16:30.480 Heard prior to twenty twenty in them for some years 0:16:30.520 --> 0:16:34.200 after it was we had this explosion in CoV light deals, right, 0:16:34.440 --> 0:16:39.880 fewer protections for investors because everyone was so desperate supposedly 0:16:39.960 --> 0:16:42.600 for yield for that particular paper, So the balance of 0:16:42.640 --> 0:16:46.400 power shifted to the borrowers they were able to dictate 0:16:46.480 --> 0:16:51.800 the terms. How are investors getting better protections now? With 0:16:52.160 --> 0:16:55.640 you know, credit spreads still at basically multi decade lows, 0:16:55.680 --> 0:16:57.960 which suggests that there's still a lot of demand and 0:16:58.040 --> 0:17:01.280 that they don't hold all the power in the market. 0:17:01.440 --> 0:17:04.200 Yeah, I think about it, and what the data supports 0:17:04.480 --> 0:17:06.720 that we see on the platform is. I think about 0:17:06.720 --> 0:17:09.639 it less so as what they're getting, but more about 0:17:09.640 --> 0:17:12.439 what the terms actually reflect in terms of the macro 0:17:12.560 --> 0:17:16.160 environment that they're operating in. So, for instance, right now, 0:17:16.200 --> 0:17:20.120 we're seeing this flight to fortification in part largely due 0:17:20.119 --> 0:17:23.240 to probably a few things. Number one being some of 0:17:23.240 --> 0:17:25.600 these headline risks that folks have been talking about, and well, 0:17:25.600 --> 0:17:27.280 I'm sure we'll get into some of what's going on 0:17:27.240 --> 0:17:30.520 in the private credit market today. So people flooding into 0:17:30.600 --> 0:17:32.760 more structural protections because they're worried about their place in 0:17:32.800 --> 0:17:35.240 line if there is distress. I think number two is 0:17:35.840 --> 0:17:37.600 just mac or wise if you think about it. In 0:17:37.640 --> 0:17:40.160 the credit markets, there was a ton of debt taken 0:17:40.200 --> 0:17:43.000 out in twenty twenty, twenty twenty one, twenty twenty, early 0:17:43.000 --> 0:17:45.680 part of twenty twenty two. This leads to a lot 0:17:45.680 --> 0:17:49.080 of maturity walls upcoming, especially in twenty twenty seven twenty. 0:17:49.160 --> 0:17:52.440 We don't say upcoming on the show, we say looming. 0:17:52.880 --> 0:17:56.520 Yeah, exactly. There are a lot of looming maturity walls 0:17:56.640 --> 0:17:58.639 in twenty twenty eight, twenty twenty nine vintage. And you 0:17:58.640 --> 0:18:01.479 can think about it as well. That's a macro factor 0:18:01.520 --> 0:18:04.280 that people are thinking about when they underwrite alone, because 0:18:04.320 --> 0:18:08.280 many of these deals actually have five year tenor you know, 0:18:08.359 --> 0:18:10.359 seven year ten or eight year tenor in some cases 0:18:10.560 --> 0:18:12.600 thirty year tenor, and so they're thinking about all these 0:18:12.640 --> 0:18:15.920 protections in the context of that market. I also think 0:18:16.040 --> 0:18:18.720 it's really interesting, aside from the credit context, right now, 0:18:19.560 --> 0:18:22.919 we're seeing a lot of structuring in terms happening in 0:18:23.040 --> 0:18:28.080 M and A markets, So things like regulatory uncertainty, things 0:18:28.200 --> 0:18:32.200 like tariffs, things like libildy management, as we talked about, 0:18:32.480 --> 0:18:35.200 things like tax uncertainty. I'm happy to go into these, 0:18:35.200 --> 0:18:37.240 but we're seeing a lot of things in this area. 0:18:37.920 --> 0:18:42.240 One kind of small example of this in situations where 0:18:42.800 --> 0:18:47.280 a buyer and a seller have regulatory uncertainty, which you 0:18:47.320 --> 0:18:49.520 know a lot of folks think about the administration and 0:18:49.520 --> 0:18:52.000 they're not sure exactly how things are going to play out. 0:18:52.680 --> 0:18:56.320 You actually see regulatory review in deals get hyper focused 0:18:56.320 --> 0:18:59.439 on and it actually precipitated a new deal term this 0:18:59.520 --> 0:19:01.960 year which we tracked in the market. We had an 0:19:02.000 --> 0:19:04.159 almost term detection of the platform. We sent out a 0:19:04.160 --> 0:19:06.560 note to all of our clients and it's called a 0:19:06.600 --> 0:19:10.040 new outside date structure term. Basically, what it does is 0:19:10.080 --> 0:19:14.880 it allows buyers of acquirees. It allows them to lock 0:19:14.960 --> 0:19:18.600 in their financing for longer and actually stand their financing 0:19:19.040 --> 0:19:22.879 in the case scenario regulatory review les. And that's just 0:19:22.920 --> 0:19:25.159 an example of the kind of innovation that's happening in 0:19:25.200 --> 0:19:28.560 the merger markets. In terms of tariffs, we picked up 0:19:28.600 --> 0:19:31.399 the first tariff event of default in a credit deal. Ever, 0:19:31.840 --> 0:19:34.360 it happened in a Superior industries deal over the summer, 0:19:34.680 --> 0:19:37.440 which probably isn't surprising to use an auto manufacturer deal. 0:19:37.480 --> 0:19:39.639 I've made a lot of parts in Mexico. That's not 0:19:39.840 --> 0:19:42.560 five percent of MNA deals for tariff based m and 0:19:42.600 --> 0:19:44.600 A carve outs and railie respect clauses. 0:19:44.720 --> 0:19:46.400 Can we talk a little bit about you know, you're 0:19:46.440 --> 0:19:50.920 scanning these documents. Google's ingram has existed for a long time. 0:19:51.040 --> 0:19:56.320 Tracking the prevalence of a term is not novel technology 0:19:56.359 --> 0:19:59.720 that control EF right control f Yeah, this is sort 0:19:59.720 --> 0:20:03.800 of like very barely even councils technology at that point. 0:20:03.840 --> 0:20:05.640 What is it that you you know, when you're talking 0:20:05.640 --> 0:20:09.560 about the changing prevalence of these terms, what is the 0:20:09.560 --> 0:20:13.920 actual novelty here that isn't just sort of yeah, document 0:20:13.960 --> 0:20:14.760 search over time. 0:20:15.040 --> 0:20:19.240 Yeah. So, Tracy, your husband's a former corporate lawyer. You know, 0:20:19.280 --> 0:20:22.000 he would tell covering corporate lawyer or covering corporate layer exactly. 0:20:22.040 --> 0:20:23.800 I am myself as well. One of the things he 0:20:23.840 --> 0:20:27.800 would tell you is that there's constant innovation in these markets. 0:20:28.000 --> 0:20:32.800 These agreements are highly complicated, there very long. They have 0:20:32.880 --> 0:20:35.480 a lot of what's called long range dependencies, which is 0:20:35.960 --> 0:20:38.399 that you may be used to seeing something in a 0:20:38.400 --> 0:20:42.080