As higher interest rates force investors to focus on revenue, profits, and cash flow, Slok argues that the key question is no longer whether demand for AI exists, but whether companies can generate returns that justify the unprecedented capital being deployed.
Key topics include:
- Why AI exposure extends far beyond technology stocks, including into fixed income
- How higher-for-longer rates are complicating the AI trade
- Why the next AI winners may be adopters, not builders
- The bullish case for AI’s impact on jobs and entrepreneurship
- Why manager selection matters more than ever in private credit
His central message: as AI spending shapes changing interest rates, it is becoming one of the most important forces shaping markets and the broader economy.
The Bridge EP 23, Torsten Slok/Apollo – Transcript
COLD OPEN
Sonali Basak (00:00:00 -> 00:00:02)
Mr. Higher for longer, for a very long time,
Torsten Slok (00:00:02 -> 00:00:04)
. And he delivered on that promise.
Sonali Basak (00:00:05 -> 00:00:11)
Torsten Slok is one of the most highly watched economists on Wall Street, and he’s been saying for a while that interest rates would be higher, longer,
Torsten Slok (00:00:11 -> 00:00:11)
Probably
Sonali Basak (00:00:11 -> 00:00:21)
Stay higher for longer, longer. And now that’s certainly the case as the Fed starts a hiking cycle. So, what does that mean for some of the most critical parts of the economy, particularly artificial intelligence?
Torsten Slok (00:00:22 -> 00:00:27)
This AI thing better work out because otherwise we’ll have problems both in the economy and also in financial marketing.
Sonali Basak (00:00:44 -> 00:01:12)
Welcome to the Bridge by iCapital. I’m Sonali Basak the Chief Investment strategist at iCapital, and today I am joined by Torsten Slack, the chief economist at Apollo Global Management. He has been focusing a lot on artificial intelligence. And Torsten, thank you for joining because we’re in this moment where you’ve been talking about it a lot, this concentration of AI in portfolios. Here’s my question to you. We are in an era where borrowing costs have been rising. What does that mean for the AI trade?
Torsten Slok (00:01:13 -> 00:02:05)
Well, the risk when interest rates go up is that any business that has cash flows far out in the future is going to be more vulnerable because when the discount rate, meaning interest rate starts to go up, that means that cash flows have to be discounted in a way where they’re worth less. Because now I can take my money, put it into fixed income and get higher interest rate. So that raises the bar for cash flows, and especially for equity that pays off far out in the future. And that’s very important for AI because a lot of the investments in ai, especially AI and venture capital, are only cash flows that come far, far out in the future. So that’s why when interest rates go up, it does increase the bar for all other investments because suddenly I can get a risk-free interest rate on interest rate or yield in public credit, private credit, fixed income, which is higher, and therefore raises the bar for what I can get in other investments. So higher interest rates has been making it bit more difficult for the AI trade.
Sonali Basak (00:02:05 -> 00:02:13)
Well, it’s so interesting what you’re saying it sounds like is just credit is on average or on balance, rather, a little more attractive than equities in the scenario.
Torsten Slok (00:02:13 -> 00:02:50)
Yeah, and if you think about that from a Federal Reserve perspective, this is actually the whole idea with raising interest rates. If someone from the Fed were sitting here next to you and me, they would say, but the reason why we are raising interest rates is that we want to slow the economy down to get inflation to slowly come down.
Sonali:
Yeah.
Torsten:
So that’s why they’re raising small increments of 25 basis points because they want to do this very, very gradually. And when you think about that from a 60 40 asset allocation perspective, that means that the Fed is really saying, please take a little bit money out of public equities and put it instead into fixed income, higher quality credit, things that pay you a higher level of yield because that is now more attractive in relative terms.
Sonali Basak (00:02:50 -> 00:03:05)
We’ll talk more about the Federal Reserve because to your credit, you’ve been talking about hire for longer, for a very long time, well before the market started even baking in interest rate hikes for example. But on AI what is at stake if this, if the trade really does slow down,
Torsten Slok (00:03:05 -> 00:04:32)
That’s a lot at stake. If the AI trade does slow down, first of all, a lot of GDP growth is driven by AI spending at the moment. We calculate that GDP growth, which is normally 2% today, roughly 1% is point of that naming. Half of that is because of ai. And it’s not only the building of data centers and energy associated with data centers, it’s also spending on tokens.
Sonali:
Mm-hmm .
Torsten:
It’s also spending on AI tools for consumers. It’s also spending on AI tools for businesses. And it’s also the wealth effect that has come along with ai naming home price in San Francisco have been going up because there’s a lot of wealth generated as a result of ai. So, the first answer to your question is if AI does begin to slow down, it would also slow down the economy. And most importantly, really is also that AI is absolutely also now everywhere in people’s asset allocation, the equity market, the 10 biggest stocks, they make up 40% of the index. And most of the returns in s and p 500 in the last several years has been driven by ai. Similarly, in fixed income, if you look at especially public credit, you also have that hyperscale’s have been issuing more debt. That is also now more ai. And finally, if you also own venture capital, venture capital used to be pharma, biotech, prescription drugs, but today 87% of venture capital is also ai. So, the answer to your question is, if AI does not work out, we will have some problems for the GDP outlook. We will also have some problems from an investing perspective. So, the conclusion is this AI thing better work out because otherwise we’ll have problems both in the economy and also in financial markets.
Sonali Basak (00:04:33 -> 00:05:04)
Let’s define workout, right? Because you’re saying there’s a slowdown. A slowdown is very different from a crash. I think a lot of people are very nervous out there about the worst scenarios that could happen in a slowdown here. And I think that’s the art of the moment that we’re in is crafting that landing. So, when you think about what a slowdown really means, you know, does it mean that, you know, we might see some companies fall into really meaningful distress. Does it mean that we’ll see even a probability of a recession start to rise? I mean, what does that actually mean to you?
Torsten Slok (00:05:04 -> 00:05:15)
Yeah, so there are four different buckets of investing in ai. One is of course the frontier labs and the models and those of course that are exposed directly to the consumer and the user of AI.
Sonali Basak (00:05:15 -> 00:05:16)
These are OpenAI, Anthropic
Torsten Slok (00:05:16 -> 00:06:12)
For example. They have negative profit margins at the moment because they’re developing the technology. And that of course is expensive. That’s why those that are facing the consumer, which is unusual, have negative profit margins. The next step in the value chain is the hyperscalers. Those who are building the data centers, they have positive profit margins, but they of course are also an important part of whether AI working out or not is going to be impacting them. The next step is energy and grit. So that means that this provides the energy to ai. They are of course also at risk to the upside and downside as a function of whether AI is succeeding or not. And finally, we have silicon and equipment, meaning those who built the chips and the semis, and they of course at the ultimate end because they’re the, the ones that all the models are running on, whether it’s closed source, open source, of course the chips are ultimately what is solving all the problems in AI. And the answer to your question is different parts of that value chain can absolutely get differently impacted as a result of what AI not working out exactly means.
Sonali Basak (00:06:12 -> 00:06:33)
Yeah, let’s talk about that a little more because you had mentioned that Frontier Labs typically have been losing money from a margin perspective, right? Um, hyperscalers though that that buffer is much thicker. Does that mean in an environment like this, there’s so many people worried about the free cash flow impacts the declines in free cash flow, but they’re relatively insulated actually. So are you actually really worried about them raising money in the market>
Torsten Slok (00:06:33 -> 00:07:37)
Yeah, this is a really important discussion because at the end of the day today, the demand for compute is really going up significantly. Not only because of all of us writing questions into ChatGPT and to Claude, but also because of agentic AI becoming much more pronounced. That means that demand for compute is rising very, very significantly. Meaning people want to run on chips in data centers, but at the same time, the competitive landscape is now also changing for the models. Namely open-source models are becoming much more used and much more pronounced in the landscape of those who use ai. Whereas closed-source models, of course are now getting more competitive pressure from the open-source models. This raises all kinds of questions about -what is the competitive edge for closed-source models for us to open-source models. But the answer to your question is this race is demand for compute is going up very, very rapidly, but at the same time, the price of that compute and the price of tokens and ultimately the competitive landscape for those who use it has actually been under more downward and more competitive pressure. And that’s the race in ai that is the most critical part of understanding whether it’s working out or not over the next several years.
Sonali Basak (00:07:37 -> 00:07:47)
So very simply, when you watch all these hyperscalers, the, you know, um, Amazons of the world go out and raise debt in markets, right? Uh, Alphabet, right? Do you, do you worry about it?
Torsten Slok (00:07:47 -> 00:08:52)
Well, markets are already voting with their feed on that question because CDS spreads on, uh, several of these names have been widening out. CDS spreads of course is measuring what is the probability that these companies might not be able to pay back their debt in the next five years. And that means that that premium meaning the price of insuring yourself against the risk that they will not be paying that debt, has been moving a little bit higher, which some people are beginning to look at, including me and say, well we need to understand better why that’s happening. Similarly, we’ve also seen spreads on hyperscale debt also widen out, which is also saying that the market has not much. But starters were a little bit more about what is the trajectory that we are on here? Are the revenues going to increase? And if you look at the consensus expectations from FactSet today, the operating cash flow in the five hyperscalers is about $600 billion. And the consensus is expecting that over the next several years will grow from $600 billion to about $2 trillion. In other words, a very dramatic increase in the revenues and the cash flows for the hyperscalers. And that is the question, if that revenue comes in faster, comes in slower, is the answer to the question. Namely, what is the scenario we have ahead of us for AI?
Sonali Basak (00:08:52 -> 00:09:10)
And it’s interesting because we are, were talking about this as it pertains to the hyperscalers, but the hyperscalers we just said have a bigger buffer. Right? But what about the frontier labs? At the end of the day, you saw something happen where you didn’t really see this happen in prior years where pre-IPO companies are actually raising fairly meaningful amounts of debt. Is that healthy?
Torsten Slok (00:09:11 -> 00:10:01)
Well, one first observation about this, that these companies are private. So, this tells you and me a very important conclusion that you and I have talked about for many years, Naomi, that a very significant part of the economy is outside the SA&P 500,
Sonali:
Right
Torsten:
And there are a lot of private companies that are wildly successful. In fact, if you look at businesses in the US that have revenue of more than a hundred million dollars, 90% of them are actually not public. So, there’s a different way of saying there’s a lot of private companies including an open philanthropic that are very successful at what they do and generate a lot of revenue. So, in that sense, they are not publishing the same way of course the companies in the S&P 500 are doing. But if they are about to do IPO, of course this will give much more insight, much more light and transparency in terms of where are they making money and how are they making money? And that will give the market a better idea about this competitive landscape that we are seeing between open-source models and closed-source models.
Sonali Basak (00:10:01 -> 00:10:20)
The reason I ask this also is because in private markets there’s the venture capital aspect, which we’ve talked about the, you know, the growth equity event, uh, private equity type aspect that we were talking about. But even data centers to a large degree are tied to the credit ratings of these firms and the credit health of these firms. And so, there’s a whole ecosystem that hinges on this question it feels like,
Torsten Slok (00:10:20 -> 00:11:18)
And, and that’s why ultimately, particularly from a GDP perspective, data center build out is absolutely critical for anyone’s forecast for GDP growth. So normally people would say, oh, CapEx and business spending, which data center, the data center build out is, is normally a smaller issue in my forecast. Normally it’s all about the consumer, but now your entire forecast depends almost completely on what is your view on the data center build out. And it’s very clear, yeah, that the data center builds out depends on whether the hyperscalers are going to generate all the revenue on the back of all the compute that’s being created. So yes, there’s unlimited demand for compute, but the question is over time whether the price of that compute is at risk potentially of eventually beginning to go down. Because if that begins to go down, then you will have two opposite forces. Yes, we all want to do more at Gen AI and use ai, but at the same time if the price of that usage, especially with the competition from open-source models starts to go down, then of course there will be some questions exactly about what does that then mean for the overall data center build out.
Sonali Basak (00:11:19 -> 00:11:20)
Bullish or bearish?
Torsten Slok (00:11:20 -> 00:12:13)
I am still bullish on the economic output because I still think that the most important impact of AI is also on the labor market. That yes, there will be some people that likely will lose their jobs, but I think that a much more important effect on the labor market is that the moment today in the census data, we are seeing the most businesses created in US economy ever in US history. In other words, the business dynamics that have appeared because of AI have just been incredible. People are leaving finance to open their own business. They’re leaving consulting, they’re leaving media, they’re leading or leaving of course legal services, and they go home to their basement, and they basically start a solo founder firm. There are many more solo founder firms now than multi founder. And that is of course if some of these businesses, it’s just a fraction of the many business that are created at the moment end up creating some success, they will also create more jobs. And I think when we put that up on the scale, that will be positive for employment.
Sonali Basak (00:12:13 -> 00:12:14)
And you think that sticks – lasts?
Torsten Slok (00:12:14 -> 00:12:34)
I truly think AI is a miracle drug that will both create higher productivity and also higher employment. And that’s by the way also what the data is showing so far. The employment report, as you and I have talked about, continues to be strong, has been strong for the last six months so far at this point, there is no effect of the labor displacement effect, meaning the effect that people are losing their jobs because of AI being particularly significant.
Sonali Basak (00:12:34 -> 00:13:02)
Okay, one more, one more question on AI before we move to the macro. We’ll put some AI in there too because it’s so related. But a tough question I had gotten this week from a large investor in your space was what happens? You have multiple companies now, three of them at least, that have surged past a trillion dollars in value in a timeframe we have never seen before reaching almost $2 trillion in some of those cases. What happens if one of those companies doesn’t exist in the next five years?
Torsten Slok (00:13:02 -> 00:15:29)
Yeah, this is really, really important. So that’s also why the famous discussion at the moment is about the moat. What is really the moat that different businesses, especially in the tech world have? Because if the tech companies that broadly speaking the magnificent seven and the hyperscalers, if they do not have a moat where they can protect themselves, then of course they will ultimately begin to shrink and they will be more at risk. So, the question of course to ask will all the hyperscalers survive? Are some of them at risk of going down because they might not have the right mode or are we seeing all of them surviving and growing into even much bigger companies? And that becomes hugely a function of this question around is it open-source models that are winning? Is it closed-source models that are winning? What is regulation going to look like? Are we going to see regulation? There’s a lot of talk at the moment about human extinction, maybe everyone losing their jobs. I mean all these impacts of AI on the economy ultimately will be very critical for the answer to the question of -who are the winners and who are the losers. So, another way of saying this is many in Silicon Valley talk about technology as an S-curve; first we invented the technology and now we’re trying to figure out how do we use this technology? How do we implement it? If that implementation phase takes six months, well then, we’re certainly off to the races and saying this is how the technology should be used, this is going to pay off. But if that implementation phase takes like 2, 3, 4 years, then we have a risk that the takeoff is only going to come later. And if there is an S-curve in implementation, maybe to your question, there’s also an S-curve in valuations. And if that’s the case, maybe the companies that invented the technology are not the ones that ultimately will be winning once the technology is used. So that’s a different way of saying the Magnificent Seven and hyperscalers did very well initially, but maybe what we’re waiting for now is the S&P 493, meaning the rest of the economy that now needs to take off and show the returns of AI adoption in healthcare, in airlines, in consumer products. Because if that takeoff takes a longer time, then of course we will not get the payoff from all the investments that were done to develop the technology.
Sonali:
Yeah, absolutely.
Torsten:
So let me say with a very slightly different words, let’s think about the invention of Ozempic. Ozempic was invented and therefore there was several years where those who invented Ozempic were able to generate higher profits because this was the only GLP-1 in the market. Then later on other GLP-1s came to the market. But that long period generated a situation where you could create some pricing power to pay back your development cost. But today the difference between the closed-source models and the open-source models is only like three, four months in terms of capability.
Sonali Basak (00:15:29 -> 00:15:31)
It’s like generic drugs versus premium
Torsten Slok (00:15:31 -> 00:15:56)
Exactly. That’s why there is a risk that we don’t have a long period where you can squeeze out high, high pricing power because they’re just right behind you, the open-source models. And that creates all kinds of corporate finance questions around, normally our textbook would say, we invent you and I a new product, therefore we have that on the market for a period. But that period becomes really, really important for what would the revenue and the profitability be of our business in particular if that period is at risk of being relatively short.
Sonali Basak (00:15:56 -> 00:16:29)
Okay. So, I could be completely off on this, but I do want to kind of give you the victory lap here on the higher for longer thing because when the feds, uh, summary of economic projections came out and I saw that higher neutral rate baked in, I just wanted to sign your name at the bottom of it, . And so, what does this all mean at the end when the Federal Reserve unanimously voted for a higher interest rate in the most recent FOMC, um, they’re projecting another rate hike for the rest of the year at least one. Um, and they’re looking at longer term rates being higher. What does that amount to in the end?
Torsten Slok (00:16:29 -> 00:18:09)
Yeah, this is really important because the economy is doing well because of AI spending and they want to be bill of a bill, but that’s another part of the economy that is not doing well. And that’s the part that’s sensitive to interest rates and that part that’s sensory to interest rates is housing is not doing well. Mortgage rates during the pandemic where 2.7 normally mortgage rates are at a level of around three and four, but today mortgage rates are now seven. So that means we’ve seen a very significant increase in mortgage rates that is weighing dramatically on the housing market at the moment. Similarly, the auto sector and car sales have also been dragged down by interest rates going up because signing a lease to buy a car, the monthly payment has just gone up because interest rates have gone up. So, we have a bifurcated economy where the boom is happening in AI spending and in the one Big Beautiful Bill the fiscal expansion. But we have another part of the economy that is dragging things down, namely housing and autos. The good news from a macroeconomic perspective is that the Fed still is experiencing that the tailwind coming from AI spending is so strong that they still see more hikes coming along because the economy still does well. But that just gets back to the discussion around, well, if AI does not continue to do well, if there is any type of slowdown, either because the models are dangerous or because there’s risk to the models in terms of security and safety or if that’s the case, that may also mean that the tailwind to the economy from AI would also be weaker and that could potentially begin to ultimately slow the economy down maybe sometime in our view, sometimes in the middle of 2027. But at this point where we’re sitting here still in 2026, we still have strong growth from AI coming and that is the reason why the Fed is seeing higher inflation combined also with higher oil prices and combined with some delayed effects of tariffs. But all that is arguing for still a strong economy, at least for the next six to nine months.
Sonali Basak (00:18:09 -> 00:18:18)
Right, the, the job market seemed to have kept enough room for a rate hike to happen, but do you ultimately agree that a hiking cycle is warranted? Well,
Torsten Slok (00:18:18 -> 00:19:18)
Well, the risk of course with beginning to raise rates because markets, as you said, are now pricing a hike this year and then two more hikes next year.
Sonali:
Yeah.
Torsten:
The risk is of course that the interest rate sensitive parts of the economy begins to slow down even more. And if that’s the case, then of course is it warranted. Well, you are going to still continue to see a significant drag downwards in housing and autos because those sectors are sensitive to interest rates. So that’s why it’s a very difficult balance that the FOMC is striking here.
Sonali:
Right.
Torsten:
The main thing that they are telling us at the last meeting is that, well, we still have inflation today, which is in round number three and a half at the peak during the pandemic it was nine, now it’s three and a half. But we still have the last mile of getting inflation down to 2% and that’s still turning out to be a lot harder. And that’s why Kevin Warsh, and the FOMC voted for unanimously, we need to do more to get inflation down and importantly to raise interest rates to slow the interest rates census and parts of the economy down in a very, very gradual and hopefully controlled way. And that’s why of course the economy is as we look into next year, expected to begin to moderate in terms of growth.
Sonali Basak (00:19:18 -> 00:19:45)
Right. I mean it just seems to me like it risks a little bit more of a K-shaped hap economy headed into the midterms at a time where their monetary policy as a blunt instrument can’t fix that K shape. And if you had to fix it, it would really be the fiscal, but now you have a fiscal where if you added more to the pain, you’re, you’re also adding more pain to the higher cost of interest. So how do you think about that burden?
Torsten Slok (00:19:45 -> 00:21:08)
Yeah, the real challenge is the Federal Reserve cannot do anything else, rather other than raise interest rates or lower interest rates. And as you say, exactly, that’s a very blunt tool compared to a lot of the other things that are going on. So that’s why fiscal policy is of course, in many cases a way to try to address some of the challenges, everything from the k-shaped economy, everything from what you might want to do on taxes, what you want to do on expenditures. But the problem is, as we all know that it’s becoming more and more complicated to see any major national compromise on a fiscal deal. The challenge is that debt levels are just going to go up. And as we know at the moment, a lot of the spending by the government is just really, really significant. And an important statistic is that roughly two thirds of government spending is discretionary spending on entitlements. Entitlements meaning spending on Medicare, Medicaid, and social security. And one very simple problem is that about 75 million people today get social security. So, it’s become very, very difficult politically to solve this problem. And you and we and us, everyone has now to deal with the cards that we’ve been dealt and say, well, there’s not a great hand we have, but at the moment, well if interest rates are going to stay higher because the fiscal situation is going to continue to be bad, I just need to plan accordingly as an investor. And that just means cutting coupons in fixed income, benefiting from higher quality credit, still paying you will continues to be a good strategy. Because this is ultimately what is the consequence, both of short-term interest rates going up and long-term interest rates going up.
Sonali Basak (00:21:08 -> 00:21:11)
How much do you think it encourages saving versus investing?
Torsten Slok (00:21:11 -> 00:21:43)
I think this is very important because a lot of money has gone into money market funds and you and I spoke about this also several years ago, that money market funds have seen a very significant increase. Interestingly enough, if you look at the ETF flows, households are very, very eager to buy short-term government debt, cheap bills, meaning money market funds because that has also gone up in yield. But households are actually selling over the last several years long-term government debt. So, there are really not many households who are willing to lend money to the US government for the next 30 years. So that has meant that interest rates have gone up, but most of this has gone through the front end of the yield curve.
Sonali Basak (00:21:43 -> 00:21:45)
Does that create a financial stability issue?
Torsten Slok (00:21:46 -> 00:22:49)
I still think that we are okay. And I still think that because we have an AI boom and we still have a significant tailwind in growth, that the fiscal issues are still helped by significant tax payments, of course significant growth that will help ultimately still provide some more tax revenue on the fiscal side. But the problem is that if the economy does enter a recession for whatever reason, then you normally see the public deficit go from at the moment around 5% and you normally add about 4% is points. So that means that we would get from basically having a 5% deficit for the government to basically a 10% deficit. And that’s a very dramatic need to raise more money because if you have a recession, you need to pay more in unemployment benefits and of course you get less tax revenue. So therefore, the deterioration will come along in the government finances. So, the problem today is that we have a really good economy, and we still have a significant deficit. So, I don’t think that will create fiscal and financial instability problems, but I’m still, of course, we are watching very carefully what the consequences are and especially if we have an environment where rates are higher for longer because then the debt servicing costs for the government will also be higher for longer.
Sonali Basak (00:22:49 -> 00:22:55)
So, what do you make of the treasuries moves in relation to what’s happening at the Federal Reserve?
Torsten Slok (00:22:55 -> 00:23:00)
Yeah, I have seen that like, and you and I also talk about this, it’s a very important move because it is telling you that this
Sonali Basak (00:23:00 -> 00:23:03)
To buy back long bonds
Torsten:
Absolutely
Sonali:
using T-bills,
Torsten Slok (00:23:03 -> 00:24:00)
And the Treasury was trying to say, well, we are worried about long-term interest rates, so let’s instead take from $2 billion in buybacks to now $6 billion buybacks. And this is really putting a cloud over the rates market and saying there is a chance we could do something, but $2 billion, $6 billion are very, very small numbers when total government debt is $40 trillion. So that’s a different way of saying it’s not so much the numbers that have had an impact. It’s really more the threatening of hanging a cloud over rates market is that we could suddenly come with some headline on your Bloomberg screen that will say, well we are doing this now, and it can, if that happens, then you want to be prepared that, well if that risk certainly will come out of the blue, well maybe then I should be a little bit more worried about betting on, on rates continues to going up. But nevertheless, we’ve still seen interest rates going up and we have now seen the Fed also raise interest rates. So, the direction of travel for interest rates both in the front end because of inflation is higher and in the long end also because of the fiscal problems is also higher. And there is really, unfortunately not much the treasury Department can do about that.
Sonali Basak (00:24:01 -> 00:24:16)
You don’t need to have a view on this I guess, but do you have a feeling about where that ceiling is on rates on the long end? Because I think that that’s what’s kept a lot of people away this idea that why would I buy a 10-year at 4.8 or 4.9 if I think it’s it’ll go to 5.5.
Torsten Slok (00:24:16 -> 00:25:29)
Exactly, so that’s a, from an investing perspective, also extremely important because now it becomes important question, namely, when are rates peaking? When do we get to a point where it is optimal for you and me to take a hundred dollars and put into interest rates because now, they begin to go down?
Sonali:
Right.
Torsten:
I still think at this point, given the AI growth story is so strong that it’s a little bit too early to do that, but it’s very clear to watch the other parts of the economy; housing, autos, other things that are interest rate sensitive, because they continue to be dragged down if interest rates continue to go up. So, if that’s the case, it becomes a race where on the one, side, hand you have both AI doing well, but on the other hand you have other parts of the economy naming housing and autos doing less well. So, in that race we are watching very carefully not only AI, which has had a lot of hooray, hooray for a long time, but also watching the parts that are not doing well. Namely what are they saying, what are they doing, and if it gets worse, how big weight should we give to those parts that are dragging down in my GDP forecast? And therefore, ultimately the answer to your question is those things that are interest rates sensitive, will they become so big that it will begin to ultimately become a problem for the overall economy? That’s not what we’re seeing at the moment, but if you have a combination both of interest rates going up and AI slowing down at the same time, then you could have both the interest rate sensitive path pulling lower and also AI beginning to pull lower.
Sonali Basak (00:25:29 -> 00:25:48)
So, what does this mean for one of the most highly talked about areas of the market this year are private credit? On one hand, as a floating rate asset class on balance, it actually kind of becomes more attractive it feels like. But on the other hand, you have a whole host of borrowers that will be beholden to higher debt servicing costs.
Torsten Slok (00:25:48 -> 00:28:06)
Yes, and there it becomes extremely important therefore to look under the hood and say, what are different types of credit doing in this environment when we have interest rates higher for longer? And the simple answer to that is that businesses in private credit that have been lent to that are very, very sensitive to interest rates higher for longer is in particular software. Software makes up 25% of all direct lending outstanding. It’s an asset class direct lending that is about $2 trillion and roughly $500 billion of that $2 trillion is lending to software companies. In particular lending to application software companies and less lending to infrastructure and less lending to cybersecurity. The problem with this is that AI is now a threat in terms of disrupting the business model for a lot of software companies. Because if I want to learn a language, I would used to download an app, but now I can learn the language also of course on Claude or ChatGPT. If I have to take the ACT, the SAT or A test, now I can also just use Claude, or of course ChatGPT for that. So that means there’s an AI disruption risk, which is threatening, especially applications. But there’s also the higher of a longer risk because software companies generally are characterized by two things. They generally have a lot of leverage, and they generally have very low coverage ratios. Covers ratio measures, my earnings divided by my debt servicing cost, and the software sector stands out dramatically from everything else in private credit because the other parts of credit that are in the private markets is hotels, restaurants, machinery, construction. They generally have much less leverage and they generally have much higher coverage ratio, much better ability to service that debt. So that’s a different way of saying inside credit when you look under the hood in private credit, different managers have different strategies and managers that have strategies that are more vulnerable to interest rates higher for longer are going to have more headwinds. Because these strategies, especially in software that have high levels of debt and very little ability to service that debt, they of course will have more problems with servicing that debt servicing cost when interest rates are high. Whereas again, for example, hotels, restaurants, they have revenue, they have earning, they have customers, whereas software is waiting to development, they only get customers down the road. So that means that those types of loans in private credit are actually going to do relatively better. So that’s why it is not about private credit as an asset class, it’s really about what did different private credit managers actually lent money to? Which type of businesses was it and were those businesses sensitive to interest rates high?
Sonali Basak (00:28:06 -> 00:28:20)
It’s been hard for people to understand what’s been going on under the hood. There was this great story by my former colleagues over at Bloomberg, private credit defaults are 1%, 6% or 19% depending on who you ask.
Torsten:
Yeah.
Sonali:
So, what is your view on where they’re headed?
Torsten Slok (00:28:21 -> 00:29:33)
Yeah. This is important because this is exactly a matter of where do I measure if I lend to a software company? Default rates of course have been higher if I lend to hotels and restaurants, default rates have been lower. So that’s why if you measure in certain parts of the leverage spectrum, in some parts of the leverage spectrum, there’s been more vulnerability In other parts of the leverage spectrum, there’s been lower vulnerability. So, this is a very difficult issue because it becomes a matter of discussion around what type of industries are we talking about or what areas of the economy are doing well, what areas of the economy are doing not so well? And in this case, for the rates higher for longer discussion, what areas of the economy is it that are more sensitive to interest rates and what areas of the economy is it that are less sensitive to interest rates? So put in different words, the vintages that were underwritten in 2021 and ‘22, for a lot of private credit.
Sonali:
Mm-hmm .
Torsten:
Those who underwrote vintages with a seven-year bullet, meaning a seven-year fixed interest rate, they need to reset now as we get to 2028 and ‘29 and those private credit managers and those parts of credit that did do vintages in those years under the assumption that interest rates would never go up, those are the areas where we have seen higher default rates. Whereas those that were underwritten with their assumption that maybe interest rates could go up, then they of course are less vulnerable. And that’s why default rates have been lower in those parts of the economy.
Sonali Basak (00:29:34 -> 00:29:44)
Same question applies to private equity.
Torsten:
Absolutely.
Sonali:
That backs a lot of this. Last question for you. What do higher interest rates mean for private equity, especially when there’s still a number of deals that were written in those vintages?
Torsten Slok (00:29:44 -> 00:30:42)
Yeah, because those vintages that were underwritten also in 2020 and ‘21 and ‘22, of course they were likely underwritten with the idea that interest rates are not going to go up. And raising the bar for private equity also means that companies that have cash flows far, far out in the future are now going to be more vulnerable, both in public markets and also in private markets. That means in private equity, it really is very essential to ask the question if the debt servicing costs are high, are the companies that I’m investing in in private equity, are they able to pay the higher debt servicing costs? In other words, this is all about growth versus value. Value means that our companies today that you invest in is companies that have higher ability to pay for the higher debt servicing cost that comes along when interest rates are higher for longer. So, the short answer to your question is in private equity, what has been outperforming is high-quality companies that have, of course, ability to pay their debt servicing cost. Whereas companies that do not have much earnings and have cashflows in the future, they have been struggling more.
Sonali Basak (00:30:42 -> 00:30:58)
Yeah. It’s time to pull out the AI tools with all of those DCF capabilities.
Torsten:
Exactly.
Sonali:
Torsten, thank you for joining. That is Torsten Slok. He is the chief economist at Apollo Global Management at a critical inflection point in the macro and for artificial intelligence. And you’ve been watching The Bridge by iCapital.
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