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Speaker 1: Bloomberg Audio Studios. Podcasts. Radio.
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Speaker 2: News.
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Speaker 3: This is Bloomberg Businessweek Daily. Reporting from the magazine that helps global leaders stay ahead. With insight on the people, companies, and trends shaping today's complex economy. Plus, global business, finance, and tech news as it happens. The Bloomberg Businessweek Daily Podcast. With Carol Masser and Tim Stenebeck.
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Speaker 4: I'm Jess Minton with Alexis Christophorus, in for Carol Masser and Tim Stenevik, who will be back tomorrow at the Future Proof Conference in Huntington Beach, California. And Alexis, we've been talking so much about AI. I mean, we do pretty much every day, right? But just looking at today, the basket of Mag7 stocks that we have in the terminal, it's actually up slightly, up four-tenths of a percent, which might be a little bit of a surprise, but that, of course, houses those Mag7 stocks like NVIDIA and other companies. But still, if you look at a year-to-date basis, The NASDAQ 100's up about 16%, and that basket of MAG7 stocks trailing that, only up about 6%, 7% relative to that, just because a lot of the plays have been more in the memory space and other chip makers. But of course, we have that other impact we're talking about economically when it comes to how does this transition to jobs, and apparently, the fear of people worried about losing.
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Speaker 3: Their jobs to AI.
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Speaker 5: Everybody wants to know, okay, what is AI going to do to my life, to my pocketbook, to my job?
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Speaker 4: Right, and how that it affects your career, your families, your livelihood, and so who better to bring in than Tom Orlick, Bloomberg Economics Chief Economist, joining us from Washington, D.C., and you have a new report that you put out today. Walk us through this about this AI apocalypse, potentially for millions of workers, and you pose that as a question, and you're saying the reality, potentially, but maybe we're just not there just yet.
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Speaker 6: So great to be here, Jess. So the big question, there's so many big questions about AI. One big question is what does this mean for the economy? Is this going to be a boom for worker productivity and wages? Is it going to make us all smarter, all better at our jobs, all more valuable to our employees? Or is this going to be something more like factory automation, which put a bunch of blue collar workers out of a job in the 80s, 90s, and 2000s? Are we going to see a wave of white collar redundancies as Claude and other models put us out of a job? So at Bloomberg Economics, we've been making the calculations, running the models, and doing that for the US and a range of other countries. We don't have definitive answers, right? This technology is still evolving. But what we do have is a kind of a range for what the estimate might be. At the top end, if we look at AI hitting its full potential, we're looking at hundreds of millions of workers, perhaps as many as 380 million workers worldwide, who are going to see their jobs significantly impacted, significantly disrupted by this new technology.
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Speaker 5: When you say disrupted or impacted, does that mean they'll be using AI in some way in their jobs? Does that mean they will be displaced by AI? What can you tell us?
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Speaker 6: So the way these calculations work is the first step is to break down a job into a set of tasks, right? And then to think about which of those tasks AI could do and which of those tasks AI can't do, right? So maybe think about two stylized examples.
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Speaker 7: Right.
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Speaker 6: Think about a computer coder. Well, most of the tasks a computer coder does, AI can do. So computer coders are one of the jobs which has already been pretty significantly disrupted by AI. Well, I think about the other end of the spectrum. Think about perhaps a hairdresser. Well, could AI help with the bookings? Sure, a little bit. Could it help with keeping up with latest trends, latest styles? Yeah, a little bit. But most of it, AI is not going to be able to do, right? So that hairdresser, their job's pretty secure. So what we did was we looked at all of the jobs in the economy, and then we broke those jobs into tasks. And then we looked at which tasks AI is going to be able to do and which tasks AI is not going to be able to do. And for jobs where more than 50% of the tasks, more than 50% of what's done in that job, AI could have a significant impact. Well, those are the ones which we include in our calculation. And if you add that up across all the countries we look at worldwide, well, that's how you get to our 380 million number for the number of jobs that are going to be significantly impacted potentially by this new technology.
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Speaker 5: Well, Tom, I think we're all running out to be hairstylists now. What other jobs or industries, sectors were, I don't want to say AI proof, but may fare better, let's say, in terms of workers not being displaced?
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Speaker 6: So I think the way to think about this is really, to put it crudely, white collar, blue collar, right? 1980s, 1990s, 2000s, Blue-collar workers faced two massive disruptions. First, from factory automation, the arrival of robots on the factory floor. And secondly, if you were a worker in the US or Europe, from the rise of the rest, right? The rise of China, globalization and your job being outsourced. But white-collar workers, they were pretty secure, right? The AI revolution is gonna be hitting the white-collar workers hard, right? you're an accountant, you're a computer coder, you're a trader, you're an economist, unfortunately, AI is going to bring some pretty significant disruption. If you're in the blue collar world, if you're working in a factory, if you're working in, I guess what you might call the sort of the human touch services professions, you're a hairdresser, you're a sports coach, well, AI ain't coming
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for you. That's where the greatest security is gonna be.
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Speaker 4: So tell me, what exactly are AI skills in the sense of, is that something like you're getting a STEM related degree, those types of industries? How do you acquire those types of skills?
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Speaker 6: Oh, that's a really interesting question. And I think one of the sort of funny facets of this kind of dynamic is, is AI gonna have a huge impact on the labor market?
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Speaker 1: Yes.
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Speaker 6: Could that impact be significantly negative? Could we see a wave of unemployment?
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Speaker 7: Yes.
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Speaker 6: Anthropic just put out a report saying that potentially unemployment in the United States could move above 10% as AI displaces knowledge workers. But right now, if we look at the impact of AI on the labor market, well, first, it's difficult to see much evidence of significant displacement, not many people losing their jobs because of AI right now. And in fact, it's a little bit the reverse, right? Huge demand for people at the really, really top end of the job spectrum to build the models, demand for people to help train the models, right? You're a specialist in a particular sector. Well, right now, there's demand to help train AI models to make people in that sector smarter perhaps in the long run to replace some of those workers and of course demand for all of those construction workers to build the data centers the kind of the brains of the ai universe so one of the interesting findings from our research was if you look you know not too far into the future three four years into the future scope for huge disruption right more productivity if we want to be positive about it more unemployment if we want to be negative about it But right now, we don't see so much of that downside. But in some parts of the world, where we're building the models, where we're building the data centers, actually, we are seeing a boost to employment.
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Speaker 1: Interesting.
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Speaker 5: But Tom, what about new grads, those people who are in college right now? We're hearing a lot about people who went in getting one degree, maybe in computer programming or in finance. They're coming out, they're having a hard time finding jobs because AI is being used by so many companies for sort of that low and, you know, those entry level positions. Are you finding that that's the case?
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Speaker 1: You know, it's funny.
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Speaker 6: I was having a chat with a friend of mine over the weekend, a young guy who's just graduating in computer engineering. And I said, you know, are you worried about this? And, you know, this is just one anecdote, but he said, everything I read in the newspapers, everything I read online tells me I have no career. I have no future. Everything I see in my email as I apply for jobs, as I apply for internships, tells me I'm going to get a job next week. Right. So just one example. Certainly a lot of news out there about young grads finding it harder to get that first step on the jobs ladder. Are we seeing that so much in the data yet? Well, something to pay close attention to.
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Speaker 4: What are your thoughts on the AI boom and bust here? What are the risks and what do you think are the potential optimistic signs there that people might be overlooking?
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Speaker 6: So if we think about the history of technology, game-changing technologies like railways, like the internet, what we see very often is a pattern where there's huge enthusiasm for the new technology, capital piles in, valuations go sky high, But then the profits, they're not so quick to materialize. And there's a moment of pessimism and there's a crash, right? And then people work out what's really going on and we see the benefits, right? We saw that most vividly with the dot-com boom bust cycle in the late 90s, early 2000s, right? The market roared, the market crashed. Did that mean it was the end of the dot-com story? No, in some ways it was just the beginning. and the internet revolution was very much the story of the 2000s. Well, I think the concern with AI is that we see something similar, right? This does turn out to be a game-changing technology for good or ill, but before we get to that broad application, right, before we get to that world where AI is kind of part of our lives, making us all more productive, we have that boom-bust cycle in the markets. And with valuations for AI companies in the U.S. extremely high, well, some people think that that boom-bust cycle is actually something that we're looking at right now.
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Speaker 1: Stay with us.
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Speaker 8: More from Bloomberg Businessweek Daily coming up after this.
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Speaker 5: Chipmakers today dragging down stocks as leaders of AI giants propose slowing the technology's development. And there's just been so much activity. I just want to run down what some of these CEOs are saying. So Anthropic CEO Dario Amodi proposing slowing development of the most advanced systems to prevent AI slipping beyond human control, he says.
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Speaker 4: And then even just seeing overall in the market, seeing Samsung as well as SK Hynix under pressure. But then the opposite side of that AI play, you're seeing cybersecurity shares higher today as well as software basically benefiting from the opposite side of that spectrum there. So it's a very large dynamic when you're thinking about who's winning, who's losing in this dynamic when you get a headline like this.
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Speaker 9: For sure.
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Speaker 5: Let's dig into it now with Mike Shepard, Bloomberg News Senior Editor of Technology and Strategic Industries, joining us. from our Washington bureau. Mike, great to see you. I know that these AI bosses are now clashing with our very own president who came out on social media today criticizing them for wanting to put guardrails up on AI development. How much of this is really about AI and the race with China for
the US?
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Speaker 7: Well, from the president's standpoint, it's everything. He is saying that whoever wins in AI wins. And that was a statement he made while in Ireland for the Irish Open. And he told reporters that when asked about AI guardrails and whether there needed to be more restrictions on the technology, he brushed off the idea and said that this whole question about safety really takes a backseat to the need to stay ahead of China in the competition to develop the most advanced AI. You also have to remember that Trump and his administration have made AI development a centerpiece of their economic agenda. They see it as an engine of job growth, and they really don't want to see any move whatsoever to upset the apple cart. In another social media post, he also questioned why anyone would want to kill, as he put it, the golden goose. And that is language he has used to defend the rollout of data centers across the country that many in America have started to take exception to. And it's something that's even emerged as a political issue in the midterm elections.
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Speaker 4: Hey, Mike, so Chinese officials obviously rejecting those calls to slow AI for safety reasons and also criticizing those claims by some American tech leaders that the progress by China posed a global security threat. So what ends up happening to the data center boom and also those valuations when you're thinking about a lot of those chip makers and other companies that are housed in that?
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Speaker 7: You know, that is one of the big questions out there. What does this slowdown mean actually in terms of all the hundreds of billions of dollars in investments that are either planned or underway. And the two leaders of OpenAI and Anthropic made clear, hey, look, we do not intend to slow down overall our plans to grow our business or to make these investments. It's really just slowing our development of the most advanced models. Yet that wasn't as comforting as they thought it might have been to Wall Street investors who are really trading in the opposite direction. We see the Philadelphia Semiconductor Index, which is a benchmark of investment in AI infrastructure. That's down by almost 5% today, and we're seeing losses in key chip makers on the day from Micron Technologies, which specializes in memory components for AI processors. And then, of course, NVIDIA, the world's most valuable company, which has really built an industry-defining business in making those GPUs that power data centers.
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Speaker 5: Mike, today Microsoft came out with this manifesto, I guess we can call it, talking about what needs to be done in efforts to slow the development of AI.
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Speaker 9: Can you tell us a little bit more about what's in that manifesto?
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Speaker 7: Well, what they are trying to do is also make sure that Their point of view as a stakeholder in all of this, they are not only a backer of open AI, but they do a lot of business with them.
And they also agree that, hey, look, we need to make sure that humans stay in the loop, mostly in the development of AI. But it's a long manifesto, all 15,000 words of it. Whether it actually has that kind of concrete impact, though, Alexis, remains to be seen. And that is true also with the essay that Dario Amadei published on Saturday. In it, Amadei promised to have outside evaluators, third-party evaluators, come into the company to get a firsthand look with.
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Speaker 3: Badges and all.
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Speaker 7: At how these models are being developed even before their release. But that's a big promise. And there are many on Wall Street who looked at those pledges and started to wonder, are they really going to follow through with all of this? And there is a question about whether some of it is marketing. And Jess brought up earlier the question of the Chinese government. They have accused the AI leaders here in the U.S., of fear-mongering, using the word from the Chinese foreign ministry earlier today. And they say that these companies are using it as a pretext to goad the government here in Washington into imposing restrictions that would undercut China's efforts to develop AI on its own.
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Speaker 1: Stay with us.
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Speaker 8: More from Bloomberg Businessweek Daily coming up after this.
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Speaker 4: Let's go to the Barclays Global Financial Service Conference in New York where Bloomberg TV's Danny Berger is sitting down with Bank of America CEO Brian Moynihan.
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Speaker 9: Jess, thank you so much. That's right. I am here with Brian Moynihan. Brian, thank you so much for joining. Great to see you today.
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Speaker 1: It's great to see you again, Danny.
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Speaker 9: And I want to start just because you did make a little bit of news just moments ago speaking at this conference saying that you expect trading to be flat. for this current quarter. And I wonder just what has changed in the environment? Because we obviously saw just such a big second quarter in this high watermark. What has sort of changed in the overall trading landscape?
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Speaker 1: So I think just to keep a perspective, if we end up with a quarter of what we just said flat, it'll be one of the best third quarters that we've ever had in the trading history of the company. But what happened is it changed. So last year's second quarter was Liberation Day 25. This year's second quarter compared to that was up a lot in trading and investment banking, things like that. Last year's third quarter was a recovery quarter from Liberation Day quarter and the tariffs coming in. I know it's hard to remember that far away, but all of us are running around saying, oh my gosh, the economy's going to stop cold. Third quarter, oh, it got understandable, easier, everything kicked back in. So now you're comparing that quarter with this year's third quarter. This year, then the AI trade came in, and you guys report about Korea and the leverage and all that stuff, and a lot of it's come out of the system because people brought the risk down. And when you put that together, just the sheer volume of activities. Now, equities is up more, and fixed income is bouncing around a little bit down, and that ends up to flattish. But the team, and Dennis and Sufian and Jimmy's leadership, the team is doing a great job. It's just sometimes the market quits doing things, and that's one of these times. Now, the pipeline investment banking's full. The activity level is strong, but with rates moving up 100 basis points over a short period of time, people pause a little bit, and leverage coming out of the system for a while.
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Speaker 9: Do you think that that pause in a more, again, relatively flat environment extends through the end of the year as well into Q4?
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Speaker 1: I think as soon as we get some stability around the rate structure, I mean, they got the Fed meeting this week, and sort of what people get a common view of that, then the rates will settle at some point, and I think that'll help. some of the trading activity. We've got a lot of pipeline IPOs, secondary offerings, things coming on that we know will go through. But on the debt financing side, which is a big part of the activity, the issue is that you've got to have a rate structure that's not bouncing around so people can feel comfortable they can commit the issue into an issue a week later a few days later. So it's good. But Yemeni activity is strong. The conversations are strong. And we're, you know, flattish. You know, it's $ 5 billion plus of revenue. It's good. Now the West Mellon's revenue will be up 10% to 15%. So you're trying to say to people, you know, we're 60% core net interest income. That's fine. It's doing everything we thought we'd do. We are managing expenses well. The credit quality of the firm is good. The consumers are spending well. It's just that the trading activity was such explosive in the second quarter. Of course, when it mitigates, it feels a little bit strange, but then it'll get back and grow from here.
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Speaker 9: It's maybe a good problem to have, Brian, when you set the high watermark that high that you can't get back there. So fair to say ramps back up fourth quarter. That's kind of what I'm hearing from you.
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Speaker 1: Yeah, we'd expect the activity will settle in. And you've got the summer's a summer, and we lose a lot of activity in August anyway. And it's always traditional the second or third quarter comes down. It's a comparison last year that's kind of got to be.
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Speaker 9: So part of what we saw in the second quarter of this trading bloat was around the AI trade and situational awareness. And I wonder how you've rethought things. Obviously, Bank of America acting as a prime brokerage for situational awareness. Has anything changed post that whole blow up?
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Speaker 1: We always look back at everything and without getting any clients. But you should
assume that we have good risk manager practices then and now. We've made a lot of money in the second quarter. We've made money every day this thing. The team does a very good thing. But that doesn't mean it won't change the environment pretty quickly when the world changes around it.
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Speaker 9: I mean, the world is changing around us every day, Brian, and just sort of on a bigger scale, the concerns around AI have reached a fever pitch. I mean, you have not been shy about expressing your own concerns. I know you were on Bloomberg in July saying, I'm worried about structurally the impact AI could have. Now we're talking about humanity itself. Brian, as a corporate leader, as someone who is helping to implement AI in both your company and fund the trade more broadly, are you worried about the path that we're headed down right now?
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Speaker 1: Well, last week I was on one of your competitor shows, and they asked me the question, should I slow down? And I said, I think they should slow down, but I'm not the person running these companies. They have now said they should slow down. So I think that's interesting. You basically had the analogy I said to somebody, we were talking to somebody today, was you have the NASCAR drivers saying, please slow down the cars. And the question is, who's going to decide how you slow them down? Should it be the governing body, Congress in this case, the administration? Should it be the private sector saying, wait a second, you've got to slow this down, because if you're selling this product that has these impacts, we can't use it. Or whether it's society writ large. But the good news is, everybody sees that the pace of this change has to be absorbed, and I think that's what you heard from the leaders that are just unbelievable companies, unbelievable at this, said the pace has to slow down, and that we have to make sure that we don't put an agent out there that can act on its own. That's far different than using AI in a controlled environment. When you put a completely autonomous agent out there, that's the big concern. Can it cause problems in hacking? That's sort of the questions of mythos and things like that. Or can it cause questions by ganging up other people? That's what you've been reading about in the papers. So I think they're wiser saying, hey, we have a great product here. Let's not gum it up by having to do some things that cause an over-regulation.
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Speaker 9: I wonder, though, how you see your own role in this and your peers, because you might not be building the things, but you're helping finance build things. the AI ecosystem. So does the financial services industry have a role here too to make sure this is developed in an ethical way?
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Speaker 1: Well, you've got the other thing is we're a major user of it. So if there's going to be a revenue stream, these companies are going to come from companies like ours. So we deployed $ 400 million plus in AI capabilities this year. We're going to deploy more than that next year. It works. Our Erica we developed 10 years ago. So we believe in the power of digital manipulation of data and information and process. Believe it to our core. And that's not a question. The question is, we believe as a company we have to give the right answer. If you went into Erica and used it and we gave you the wrong answer, not a great client experience. So we are careful that we deploy it with the controls, the people in the loop and things like that. That is a responsibility we have as a user to make sure the people are given as products we can use. As a financer, we have to worry about what's the liability. So you hear a lot of talk about product liability from different types of people saying, oh, the product liability that might be incurred. Well, we have to think about that as a lender and the markets have to think about that as a funder. So those are the issues. That's not new issues. Those are being raised as we speak. But just the maturity cycle, like everything, it goes so fast now that we have to think that through. And product liability around products from cars and things took years to develop, so the question is how you do it. And on the other hand, we have a competitive race between us and other parts of the world. We're not on our own, so that adds a complexity. But yes, we as a bank have to help think this through, and we work with these companies regularly. a lot of different ways in what it can do for hacking, cybersecurity. We work with them in terms of applying it and how it works. And our job is just to bring our perspective and help them think about it, along with governments and others.
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Speaker 9: To the point about risk, because all these companies with the aid of Bank of America are prepping for IPOs, are these a significant enough risk, for example, that they should make it into an S1? Is that the kind of level we're talking about?
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Speaker 1: I think the question would be the regulatory aspects, because if.
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Speaker 1: If the issues got bad and they over-regulate, the revenue stream may come slower and things like that. But those are the, I don't, I haven't read the S ones of the most recent one, but I, I, I'm sure that smart lawyers, I was a lawyer at one point in my life, smart lawyers are thinking through all those risk factors. But the real question is, you know, can we get this right? We have a meeting this week that's been written about that's going on with a group of them and, and, uh, some under the King's leadership over in Scotland to talk about this. And, you know, this was pre-scheduled, obviously a long time before, but the, You know, the Pope's written on it, the King has convened people to talk about it, you've had the companies themselves, the administration has thought about it, you've seen stuff, so it's not people aren't thinking about it. Now it's the question of what should we, what's the wisest thing to do, and what
pace you should do it at to not just hurt innovation, at the same time have the controls around it that we can make it work. As a company, we have to be very careful with that. That's, frankly, wouldn't let us deploy autonomous agents and things in our company. We said, we can't see how we could actually control this thing because it's doing what it's supposed to do, which is go figure out problems over and over again. But on the other hand, with AI, applied AI, and some of the work around semi-autonomous agents, pretty interesting stuff.
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Speaker 9: So you, of course, are referring to the King's meeting next week in Scotland. I know Jensen Huang is going to be there. Are any other of your banking peers attending for you? Are you leading the charge in financial services? And if so, what's your message?
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Speaker 1: I'm there in my role for the Sustainable Markets Initiative that I've been working on with His Majesty for seven, eight years now. And we have some CEOs that participate in this. It's being set up through a group over there, so I don't have the list of people going, but it'll be a good representation of Compass, I'm sure, because his convening power on all matters is really unbelievable. And so he'll bring them together, have people talk and learn from each other. And I've seen it happen with New Energy Transition, with other types of activities. He's quite something, how he can bring people together and get them to think about things.
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Speaker 9: Just given what you've learned about that, again, you've advocated for other initiatives, too. Is it the role of regulators? Because this president, President Donald Trump, was saying earlier, we don't need regulation. We don't need AI guardrails. Should regulators be stepping in? Or is this a self-regulatory moment for these companies?
00:27:07
Speaker 1: Well, I think it's always a self-regulatory moment. Because in the end of the day, you shouldn't require, just like with us regulation as a bank, we regulate ourselves tighter than the regulators do. Because in the end of the day, we think it's the right thing to do for the customer, right thing to do for the future. Here we are. really on the anniversary of Lehman failing and us buying Merrill Lynch at Bank of America in just a hugely disastrous time for the financial services industry, from which we recovered and done a great job. That was a lot of self-regulation, honestly, and that's important. So it's encouraging to hear the leaders of these companies say, hey, We've got to take it seriously. That's first order. Brian, just jump in.
00:27:45
Speaker 9: Does that mean that if these companies don't self-regulate, of course it's apples to oranges to compare the two, but they could go to a moment where their businesses face a risk of that type of blowup, but something more catastrophic if they don't.
00:27:56
Speaker 1: Start to self-regulate. There's a plaintiff's bar, there's a state attorney general's, there's a state legislature's. What we advocate for is, wait, if you have everybody regulated, then you have a patchwork of stuff that's hard to figure out. So can we operate with our tools and capabilities in California, same way you can operate in Nevada, same way you operate in Texas and in North Carolina. That's not good for any industry to have multiple regulations and then to operate as a provider of the service is even tougher for us even to use them. So I think the idea is a federal regulation, but your base point is it's interesting and important that these companies said, we're going to do this on our own because they're saying we are balancing long-term health and structure of our companies in what we do for a living. That's encouraging. I think we should heavily encourage that. What else comes out of the regulation stuff? We have to see what that is. You can't reflect in the theory. But it's good news that the NASCAR drivers are saying, let's slow down the engines and make sure we can be safer.
00:28:51
Speaker 9: More broadly, the banking sector has done extremely well because of AI. I mean, whether it be because of trading, which we discussed, M & A, these IPOs, which we also discussed. If there is a meaningful slowdown, how does it impact Bank of America and this industry more broadly?
00:29:05
Speaker 1: I think So where the theory would come is that the revenue streams would slow down, therefore the build-out would... The models we're using now to get all the value we're getting at Bank of America and other companies are not these models. These are the frontier. These are the most advanced. The models we're using are versions before that. These models haven't even been deployed yet. This is in a test. So I think the idea of us getting value and the idea of society getting value and the idea of society deploying this, the idea of the data centers to actually run them, is going to be there. It may be growth curve X or growth curve Y, up or down. There's a lot of debate about can it get built as fast as you want.
00:29:42
Speaker 9: Well, also just the CapEx issuance and what that has.
00:29:45
Speaker 1: Meant for banks. It'll be a super cycle, I'm fairly convinced, because we see the value. It means we're willing to pay something for it. And when we're willing to pay something for it, we're not different than any company. That provides a revenue stream that will build. It's a build or 75% X or 50% X, it's still a lot of X. to get to.
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Speaker 9: Just on that, so M & A obviously has been quite robust for Bank of America, and you mentioned some of the M & A cycle, you maybe not being as heavily invested or as concentrated where some of that is taking place. How much of that is around AI? Because you've obviously been participating in these big blockbuster IPOs, but things like SpaceX, for example, maybe not necessarily top billing. What does it take to get top billing on these?
00:30:25
Speaker 1: It's a complex thing of how long the
relationship, and SpaceX, we participate in that, especially What we have at Unique at Bank of America is we have the retail capability to distribute retail. A lot of these companies want to get out to the broad base for two reasons. One is a good shareholder base, but secondly, it's also a good user base. They are the people who keep the product knowledge out there and stuff. So we have that. We have good underwriters, good coverage bankers. The issue is we'll have a transaction pushed off a quarter. This is fairly sensitive, especially when these larger fees come in, to if something happened when you think you do it, because this is the amount of cash you received. not the transactions announced. So we're fine with it. The team's doing a good job, Matthew Coder and the team. It's just sometimes you're a little luckier and sometimes you're not so lucky. But the underlying flow of business, 1.6 to 1.8 billion, which is what we told people, that's a good strong quarter. We haven't had a lot of two billion quarters. We had one last quarter, last year this quarter. So that was an even better quarter. So we're fine. We want to integrate a corporate investment banking business, and that's part of a huge business which makes a couple billion dollars a quarter.
00:31:29
Speaker 9: Right. In the final minute we have left, we have a rate decision coming this Wednesday as U.S. 10-year yields reached 5% for the first time since 2023. How are you thinking about this moment as we feel the stress of higher yields?
00:31:42
Speaker 1: Well, I think the long-term yields and short-term yields are two different questions. And I think the short-term yields, the Fed raising rates, our team has had the Fed doing three rate increases for a long time now. We were kind of out of, you know, Candace and the team said it earlier, people didn't It looks now we may be closer to being right. But the point is three rate rises. If they do it this year or two this year and early next year, the idea is getting back, sort of putting back in the interest rate cuts that were made and get the inflation to come down. We don't think inflation, even with three rate rises, would get down to where the target would be until the end of 27 and 28. The Fed has to keep inflation because that will help with a real growth rate in wages and also economy. And the economy is robust. Our consumers spent 4% more money in August than they did last August. Their credit quality is very strong. The small, medium-sized businesses are borrowing money. Interestingly enough, short-term rate moves affect the small, medium-sized line of credit users faster than they do the consumer because mortgages are fixed, cars are fixed, and credit cards, the rate move doesn't mean as much. So as we look at it, that's where we've got to watch if it causes any stress. We don't think it has because 12 months ago the 18 months ago there at the levels we're talking about, and they were fine. So it's all is the underlying economy growing, and that's more the important question. And then the rate structure can be more normal. Everybody says higher. It's actually more normal. And then that will then grow us through that. That's actually a good place for the U.S. to be, and that helps the whole world get more normalized in terms. It was not normal from 2009 to 2019 to have zero rates. That is not normal.
00:33:21
Speaker 8: Stay with us. More from Bloomberg Businessweek Daily coming up after this.
00:33:33
Speaker 4: Jess Minton here with Alexis Christophorus in for Carol Master and Tim Stenevik, who will be back tomorrow at the Future Proof Conference in Huntington Beach, California. Fascinating story here, though, Alexis, on the Bloomberg Terminal about how patients often win if they actually fight insurance denials. But there's so much that goes in. It's so complex and it feels like it constantly people are running into this. And what an issue that is.
00:33:58
Speaker 9: But it can pay off.
00:34:00
Speaker 1: It can.
00:34:00
Speaker 5: If you go through the effort.
00:34:01
Speaker 9: The loopholes. Exactly.
00:34:02
Speaker 4: And the type of work that goes into it. So who better than to walk us through all this? John Tozzi, healthcare reporter at Bloomberg News, joining us here in studio. And walk us through the dynamic here because it's such a tough prospect of when you go through this and you might not realize you could appeal something and then end up getting something approved. So talk to us about that.
00:34:23
Speaker 2: Yeah, so what happens, I mean, we're talking about a process here called prior authorization that people are probably familiar with. Yes. Your health plan says you kind of need to get approval before getting a treatment or a medication, right? And when that happens, there's basically, if it's denied, people have a chance to appeal, and they have multiple rounds of appeals. The details... differ depending on the product, but what happens is most people don't appeal denials, but we analyze some new data from the insurance companies that show when they do, they often win about half the time, according to the data we found from large insurance companies. In some plans, they win nine out of 10 times or more. And this is an analysis that myself and colleagues here did based on new data that the companies were required to disclose under federal regulations.
00:35:24
Speaker 5: So in this article here on the Bloomberg Terminal, it says five large publicly traded insurers denied more than 10% of standard prior authorization requests last year for most Medicare, Medicaid, and Affordable Care Act plans. And as you said, patients winning about half of the time on appeal Who are they appealing to?
00:35:43
Speaker 2: Well, they're appealing to the insurance company, right? So the insurance company is the one who's saying, you know, this service or medication is approved or it's denied, and it could be denied for different reasons. It could be denied
because they think it's not medically necessary. It could be denied because the doctor hasn't submitted the right documentation needed to approve it. But it is generally the insurance company making that decision. Sometimes on an appeal, it goes to an external third-party reviewer at a certain point, but it's the insurance company's decision.
00:36:15
Speaker 4: How long on average do you think it ends up taking to try to go through an appeal process?
00:36:21
Speaker 2: That's a good question. I don't know the data offhand. You know, the health insurers point out that, you know, they make decisions on these prior authorization requests quickly within a day. On average, they say, and they say that's faster than the federal requirements. We hear from doctors and patients sometimes that that doesn't always line up with their experience, and it can be much longer for some people, particularly with complicated cases.
00:36:50
Speaker 5: If so many patients who appeal actually win the appeal, it sort of begs the question, why were they dinged in the first place, right? And do insurance companies need to take a good hard look at how they assess the situation?
00:37:03
Speaker 2: Yeah, it's a good question. So just to set the stage a little bit, there's been a lot of attention on this practice over many years. The insurance industry has been under pressure from the public, under pressure from regulators who say these prior authorizations are too burdensome. They have committed to voluntary actions to sort of simplify and automate the process and reduce the number of services that require prior authorization. So they say they're doing that. But it is a broader conversation around, you know, if you're an insurance plan and you're approving 98% of prior authorization requests for a particular service, why is it subject to prior authorization, right? That's a question that some people are asking. If your denials are being overturned nine out of ten times, why are you denying those patients? So those are all kind of part of the conversation around this, that this data helps us understand better.
00:37:58
Speaker 4: Is there a type of care that ends up getting denied more than others when you think about either terminal illnesses or chronic illnesses that are different than something else that might be a little bit more manageable?
00:38:09
Speaker 2: Yeah, I don't know that we have any data on that right now. I think one of the sort of blind spots in the data that the government required companies to disclose is we sort of know at a high level, you know, this percentage was denied, this percentage was approved, this percentage was overturned, but we don't know, well, were all those denials for, you know, particular types of disease or particular types of conditions. So there is still a lot of, a lot we don't know about how this process works in practice.
00:38:42
Speaker 4: How much, when you think about insurers potentially getting it wrong the first time as far as just not understanding what was in the type of guidelines for that particular patient?
00:38:52
Speaker 2: Yeah, I mean, this, I think, is a point of disagreement. You know, I think clinicians will often say, you know, that insurers are not up to date on the guidelines. And, you know, particularly with cutting edge, you know, advanced cancer treatments, we hear sometimes that insurance companies are relying on, you know, out of date guidelines, or they just disagree with the clinical judgment of, you know, a physician. And, you know, I think it's hard to speak in generalities around this, but this is a real source of tension in the health care system, right, where the company that is deciding whether or not it will pay for your care says, you know, no, this is not warranted based on X, Y, Z evidence. And the doctor who's actually in front of you treating you says, yes, it is, and here's why.
00:39:39
Speaker 1: Yeah.
00:39:40
Speaker 5: And the burden really does fall on the patient. If we dig deep into this article, UnitedHealthcare in the 1990s abolished prior authorization, just to bring it back, I guess, a decade later.
00:39:52
Speaker 2: Yeah, I mean, it's a really interesting history, and I think a lot of people don't know this. In the late 90s, when there was sort of really widespread backlash to managed care and to all these sorts of cost control measures from HMOs and insurance companies, The company did do away with this practice, and they did revive it then again in the 2000s after medical costs went up. We actually interviewed a former executive from UnitedHealth, a woman named Arkelle Georgiou, who was chief medical officer at the time when they did this, and she is now, has left the company. She's a strategic advisor to healthcare companies, but she's looking at all this data and advising people writing about how the industry could improve this practice by making it more targeted and by making it less burdensome on patients.
00:40:48
Speaker 9: All right.
00:40:49
Speaker 4: We're going to have to leave it there.
00:40:51
Speaker 5: We can go on and on.
00:40:51
Speaker 1: This is fascinating. We're going to have to bring you back to talk more about this.
00:40:54
Speaker 5: Very encouraging that if you have the time, which some patients don't, and the wherewithal to fight the appeal, it could be in your favor.
00:41:03
Speaker 9: Yeah.
00:41:05
Speaker 3: This is the Bloomberg Businessweek Daily Podcast. Available on Apple, Spotify, and anywhere else you get your podcasts. Listen live weekday afternoons from 2 to 5 p.m. Eastern on Bloomberg.com, the iHeartRadio app, TuneIn, and the Bloomberg Business app. You can also watch us live every weekday on YouTube and always on the Bloomberg Terminal.