WEBVTT - BI Weekend: Oracle, Macy’s Earnings 

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<v Speaker 1>This is Bloomberg Intelligence with Alex Steel and Paulsweenye.

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<v Speaker 2>The real app performance has been the US corporate high yield.

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<v Speaker 3>Are the companies lean enough? Have they trimmed all the fats?

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<v Speaker 2>The semiconductor business is a really cyclical business.

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<v Speaker 1>Breaking market headlines and corporate news from across the globe.

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<v Speaker 3>Do investors like the M and A that we've seen?

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<v Speaker 2>These are two big time blue chip companies.

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<v Speaker 3>Window between the peak and cut changing super fast Bloomberg.

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<v Speaker 1>Intelligence with Alex Steel and Paulsweenye on Bloomberg Radio.

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<v Speaker 2>On Today's Bloomberg Intelligence Show, we dig inside the big

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<v Speaker 2>business stories impacting Wall Street and the global markets.

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<v Speaker 3>Each and every week we provide in depth research and

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<v Speaker 3>data on some of the two thousand companies in one

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<v Speaker 3>hundred and thirty industries our analysts cover worldwide.

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<v Speaker 2>Today, we'll break down a merger between two of the

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<v Speaker 2>world's largest advertising groups PLAUS.

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<v Speaker 3>We'll discuss why shares of the computer tech company Oracle

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<v Speaker 3>fell by the most in a year.

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<v Speaker 2>But first we dive into how I planned US supermarket

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<v Speaker 2>merger between Kroger and Albertson's crumbled. And this came after

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<v Speaker 2>Albertson terminated their.

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<v Speaker 3>Packed Albertson's also set a file the lawsuit against Kroger,

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<v Speaker 3>claiming the company failed to exercise best efforts to secure

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<v Speaker 3>regulatory approval.

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<v Speaker 2>The lawsuit comes after our federal judge blocked the deal,

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<v Speaker 2>saying the merger with lesson competition and raise prices for

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<v Speaker 2>your shoppers. For more.

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<v Speaker 3>We are joined by Jen Ree Bloomberg Intelligence senior litigation analyst.

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<v Speaker 2>We first asked Jen if it's common for merger partners

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<v Speaker 2>on a broken deal to suit each other.

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<v Speaker 4>It happens once in a while. Well, I'll say it's

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<v Speaker 4>pretty rare, but it has happened. I mean, think about

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<v Speaker 4>Anthemin Signa. I don't know if you remember that deal

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<v Speaker 4>from back in twenty fifteen. It fell apart also, and

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<v Speaker 4>there was litigation for a couple of years after the

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<v Speaker 4>deal was terminated in Delaware. And you know, they both

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<v Speaker 4>came out with nothing. Spent a lot of money and

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<v Speaker 4>both came out with nothing.

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<v Speaker 3>Is it true that you think that Kroger didn't do

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<v Speaker 3>enough here? Like, do they have a leg to stand

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<v Speaker 3>on Alberson?

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<v Speaker 4>I think a breach of contract claim based on you know,

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<v Speaker 4>failing to abide by sufficiently defending against the antitrust claims

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<v Speaker 4>is very difficult because you know, this is really very

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<v Speaker 4>subjective and to some extent, when companies go to court

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<v Speaker 4>and they have a remedy, they're sort of rolling the dice.

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<v Speaker 4>They're hoping they'll convince the judge, even though they didn't

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<v Speaker 4>convince the FTC. And I'm not so sure that you

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<v Speaker 4>can think of that as a breach in this case though,

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<v Speaker 4>having meant a trial, the remedy really was deficient. I mean,

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<v Speaker 4>it was very difficult to understand how a judge, after

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<v Speaker 4>the FDC presented their case on how this deal could

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<v Speaker 4>cause harm in thousands of markets, how a judge could

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<v Speaker 4>accept the remedy that had been put forward by Kroger,

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<v Speaker 4>which was really very piecemeal, very complicated and difficult, and

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<v Speaker 4>didn't really have the best buyer. So you know, we're

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<v Speaker 4>gonna have to see what happens here with this.

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<v Speaker 2>I mean, so again, I kind of thought that's kind

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<v Speaker 2>of what a partially what a breakup fee kind of

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<v Speaker 2>covers there. I mean, if this deal doesn't go through

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<v Speaker 2>for whatever reason, you guys wanted to buyas you initiated

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<v Speaker 2>the deal, if it doesn't go through, right, you got

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<v Speaker 2>to compensate.

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<v Speaker 5>Me right, right, that's exactly right. The seller is really

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<v Speaker 5>has a.

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<v Speaker 4>Difficult time during that interim period, right, they lose employees.

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<v Speaker 4>They can always enter new supply contracts, So this is

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<v Speaker 4>really intended to make that seller whole, you know, in

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<v Speaker 4>this case, I think now Kroger's turned around and said, no,

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<v Speaker 4>it was it was Albertsons that breached the contract, you know,

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<v Speaker 4>And of course they're probably doing that to get a

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<v Speaker 4>little bit of leverage here. Maybe the hopes would be

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<v Speaker 4>that they could settle for something less than that six

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<v Speaker 4>hundred million breakup fee in order to make all the

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<v Speaker 4>litigation go away. Maybe maybe that's what's happening here, just

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<v Speaker 4>a little bit of leverage.

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<v Speaker 5>But you know, again, we'll have to see what happens.

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<v Speaker 4>It would be a shame if they continue to litigate

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<v Speaker 4>this and spend millions more dollars.

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<v Speaker 6>Good for the lawyers.

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<v Speaker 7>A deal, dumb question? Is a deal really done?

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<v Speaker 5>Oh?

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<v Speaker 7>Yes, they killed for sure, it's done.

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<v Speaker 4>So Albertson's is already terminated. They exercised their right under

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<v Speaker 4>the agreement to terminate, so it is done.

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<v Speaker 5>The deal.

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<v Speaker 4>Agreement is no longer good. So if they even wanted

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<v Speaker 4>to do another deal, they'd have to enter a new agreement.

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<v Speaker 4>And now obviously there's antagonism between the.

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<v Speaker 2>Companies, all right, in your world of antitrust, What is

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<v Speaker 2>the expectation of change given a new administration, given you

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<v Speaker 2>a Republican control House and Senate, is there any expectation

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<v Speaker 2>that things will get easier?

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<v Speaker 5>I think it get better.

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<v Speaker 4>I think some of the exuberance on Wall Street is

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<v Speaker 4>maybe a little overdone. These huge deals between competitors are

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<v Speaker 4>still going to get challenged. And we have to remember

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<v Speaker 4>that the two Republican FTC commissioners who will still be

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<v Speaker 4>there on the Commission both voted yes to sue the

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<v Speaker 4>Tapestry could pre deal and to sue the temper See

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<v Speaker 4>Le Mattress Firm deal. They both said yes we should sue,

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<v Speaker 4>so they are aligned in some restricts with suing the

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<v Speaker 4>deals that could cause harm. I do think what we're

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<v Speaker 4>going to see though, is an uptaking deals that can

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<v Speaker 4>close with settlements. We didn't have any of that in Biden.

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<v Speaker 4>The Biden enforcers did not want to settle deals if

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<v Speaker 4>the deal was bad. They wanted to challenge the deal,

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<v Speaker 4>and that's what they did. I think in this case,

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<v Speaker 4>once we have a majority of the FTC and new

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<v Speaker 4>people at the DOJ. We're going to see that list

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<v Speaker 4>of settled deals that then go on to close grow.

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<v Speaker 3>What do you make of the potential new FTC people

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<v Speaker 3>coming in, Well.

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<v Speaker 5>I'll just say this.

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<v Speaker 4>If Lenakon's mission was to stop consolidation and revitalize antitrust,

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<v Speaker 4>their mission is going to be to stop with they

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<v Speaker 4>perceive as censorship of conservative viewpoints by big tech platforms.

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<v Speaker 4>There has been a lot of talk about that, even

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<v Speaker 4>suggesting that there could be collusion amongst big tech platforms

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<v Speaker 4>to censor conservative viewpoints and that the FTC should be

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<v Speaker 4>going after these companies under the anti trust laws to

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<v Speaker 4>stop that. And I think that's going to be a

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<v Speaker 4>big focus.

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<v Speaker 2>So what's the timing there at the FTC and the DOJ.

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<v Speaker 2>When do the new sheriffs, if you will, kind of

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<v Speaker 2>get in town.

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<v Speaker 4>The FTC could be DOJ will be quick, these people

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<v Speaker 4>will leave. The appointees by Biden will leave in January,

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<v Speaker 4>and that is the expectation also that Lena Kon at

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<v Speaker 4>the FTC will leave in January. As soon as Trump

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<v Speaker 4>is inaugurated January twenty, then Andrew Ferguson will become the chair.

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<v Speaker 4>If Lena Khan is still there, she'll then just become

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<v Speaker 4>a commissioner, but she will probably leave and then at

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<v Speaker 4>that point he just has to get his new appointment

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<v Speaker 4>mark meter through the Senate confirmation process. It could take

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<v Speaker 4>a few months. He has a majority in the Senate

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<v Speaker 4>in the House. I don't think it's going to be

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<v Speaker 4>too difficult. So it'll be a few months and in

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<v Speaker 4>the meantime it'll be a two to two FTC. Probably

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<v Speaker 4>the DJ will change over more quickly, probably in January.

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<v Speaker 3>So if I'm a company and I'm interested in buying

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<v Speaker 3>another company, do I get on the list now? Do

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<v Speaker 3>I wait until all this stuff is cleared and then

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<v Speaker 3>I get on the waiting list to get my deal done?

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<v Speaker 3>Like what's my strategy?

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<v Speaker 4>I think if you know that it has some issues,

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<v Speaker 4>if you know you're probably going to get investigated, you

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<v Speaker 4>can go ahead and file it now because you have

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<v Speaker 4>eight months ahead of you and the new people will

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<v Speaker 4>be the decision maker.

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<v Speaker 5>So if you have a deal you.

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<v Speaker 4>Think has no issues and could get through in thirty days,

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<v Speaker 4>maybe you wait right because you have a greater hope

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<v Speaker 4>of just getting get cleared in thirty days once the

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<v Speaker 4>new people are in all right.

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<v Speaker 3>Thanks to Jen Rey, Bloomberg Intelligence Senior Litigation analyst.

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<v Speaker 2>This week we focused on a Bloomberg Big Take story

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<v Speaker 2>entitled Jane Fraser stares down skeptics ahead of City's critical year.

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<v Speaker 3>You can find it on Bloomberg dot Com and the Terminal,

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<v Speaker 3>and the story looks at extensive reporting and an exclusive

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<v Speaker 3>interview with Citygroup CEO Jane Fraser, and it illustrates her

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<v Speaker 3>five year plan to turn the bank around.

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<v Speaker 8>For more.

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<v Speaker 2>We were joined by the story's author, Todd Gillespie, a

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<v Speaker 2>Bloomberg Finance reporter.

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<v Speaker 3>We first asked Todd to break down his reporting and

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<v Speaker 3>how Citygroup has done recently.

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<v Speaker 9>Thanks generally speaking as a sector have done really well

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<v Speaker 9>this year. You know, Citi's kind of sitting the middle

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<v Speaker 9>of the pack of the top six major US banks,

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<v Speaker 9>so they're doing okay.

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<v Speaker 8>You know.

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<v Speaker 9>Mark Mason, the CFO, said that the bank is set

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<v Speaker 9>to hit the top end of its revenue guidance for

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<v Speaker 9>the end of this year. So after years of disappointing people,

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<v Speaker 9>you know, investors, analysts, slowly maybe starting to think that

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<v Speaker 9>she can turn the ship around.

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<v Speaker 6>But it's a huge task.

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<v Speaker 3>Why is the ship so big and why is it

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<v Speaker 3>so hard to turn Well.

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<v Speaker 9>City Group is you know, was once before the financial crisis,

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<v Speaker 9>the world's largest financial company. It was the US's largest bank.

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<v Speaker 9>This is a company that is probably the most global

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<v Speaker 9>bank in the world. It's the only bank, for instance,

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<v Speaker 9>that has a significant presence in Lebanon, where it had

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<v Speaker 9>to evacuate staff earlier this year.

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<v Speaker 6>We reported that earlier this year.

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<v Speaker 9>And yeah, so you know, it's one of those banks

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<v Speaker 9>that is so sprawling, which is one of its advantages

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<v Speaker 9>because it gets, you know, it enables it to have

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<v Speaker 9>this incredible global network of payment systems and m and

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<v Speaker 9>a advice and you know X in all sorts of

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<v Speaker 9>different countries.

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<v Speaker 6>But it's also a big hindrance.

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<v Speaker 9>And one of the things that Jane Fraser has tried

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<v Speaker 9>to do is pull in exit you know, thirteen of

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<v Speaker 9>its retail markets where it has retail banking presence. It's

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<v Speaker 9>about IPO, it's retail business in Mexico by twenty twenty six.

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<v Speaker 9>So it's really kind of trying to straighten, you know,

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<v Speaker 9>downsize in the right ways she's saying, and also increase

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<v Speaker 9>its feed businesses like wealth management and banking as well.

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<v Speaker 2>What does City want to be when it grows up?

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<v Speaker 2>Does it want to be JP Morgan? Is that the

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<v Speaker 2>aspiration for City or they have a different strategy.

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<v Speaker 9>I mean, it's hard to com bear, but yeah, I

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<v Speaker 9>mean I probably say JP Morgan is a bank. I

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<v Speaker 9>mean i'd say small steps, you know, I think Bank

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<v Speaker 9>for America. The way that Bank of America came out

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<v Speaker 9>of the financial crisis was something that City could have

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<v Speaker 9>only hoped to emulate.

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<v Speaker 8>Right.

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<v Speaker 9>City has really been a laggard since the financial crisis

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<v Speaker 9>in a way that Bank of America was able to

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<v Speaker 9>suddenly turn that ship around fairly strongly. City is only

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<v Speaker 9>just managing to maybe start to start do that.

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<v Speaker 8>You know.

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<v Speaker 9>It has very large servicesiness payment system, just like JP Morgan.

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<v Speaker 9>It's obviously it's banking business has been traditionally one of

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<v Speaker 9>the smaller on the M and A side, but larger

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<v Speaker 9>on the DCM and ECM side. So it's trying to

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<v Speaker 9>trying to see if it can kind of even out

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<v Speaker 9>those businesses as well. So yeah, it's unclear. I mean, yeah,

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<v Speaker 9>maybe if Jamie Diamond had stayed at City Group back

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<v Speaker 9>in the day, it.

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<v Speaker 6>Would have had a very different trajectory In talking.

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<v Speaker 3>To shareholders and talking to analysts, what's the vibe on

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<v Speaker 3>Jane Fraser, like, is she doing a good job?

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<v Speaker 6>Is it?

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<v Speaker 3>I realize it's only halfway through, but what's the confidence level?

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<v Speaker 9>Yeah, well she's passed halfway through now. I mean she

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<v Speaker 9>set out these targets in March twenty twenty two. She

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<v Speaker 9>says that by the end of twenty twenty six she

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<v Speaker 9>can get to a return on tangible common equity of

0:09:44.720 --> 0:09:48.439
<v Speaker 9>eleven to twelve percent. They're sitting rather unhappily just under

0:09:48.520 --> 0:09:50.200
<v Speaker 9>seven percent right now, which is one of the key

0:09:50.240 --> 0:09:53.280
<v Speaker 9>metrics that investors an analyst, are quite unhappy with, to

0:09:53.280 --> 0:09:56.080
<v Speaker 9>be honest. But people like her as a CEO, you know,

0:09:56.120 --> 0:10:02.480
<v Speaker 9>people respect her. She's pretty forthright, she's got empathy, you know, regulators,

0:10:03.000 --> 0:10:05.000
<v Speaker 9>you know folks. I think people like dealing with her

0:10:05.160 --> 0:10:08.160
<v Speaker 9>as a person. But obviously, when you take a bank

0:10:08.200 --> 0:10:11.000
<v Speaker 9>through this massive change, you know, right, they announced twenty

0:10:11.040 --> 0:10:13.120
<v Speaker 9>thousand job cuts at the beginning of this year, nine

0:10:13.200 --> 0:10:15.720
<v Speaker 9>thousand of those still to go in the next two years.

0:10:16.760 --> 0:10:19.280
<v Speaker 9>It's it's, you know, you're obviously going to have enemies

0:10:19.400 --> 0:10:21.439
<v Speaker 9>and people who really don't like the way that you're

0:10:21.640 --> 0:10:23.199
<v Speaker 9>you're moving this thing around.

0:10:23.360 --> 0:10:25.840
<v Speaker 2>What's next for city in their turner REMP plant. Is

0:10:25.840 --> 0:10:28.240
<v Speaker 2>there a mile post that investors are saying for this

0:10:28.280 --> 0:10:29.520
<v Speaker 2>is the next thing we need to see.

0:10:29.720 --> 0:10:32.200
<v Speaker 9>The next thing everyone needs to see is positive operating

0:10:32.280 --> 0:10:35.440
<v Speaker 9>leverage that really consistently comes through. That's you know, that's

0:10:35.520 --> 0:10:39.679
<v Speaker 9>that's revenues outpacing growth and revenues outpacing expenses for them

0:10:39.720 --> 0:10:41.600
<v Speaker 9>in the next twelve months. And they also really want

0:10:41.600 --> 0:10:46.440
<v Speaker 9>to see strong growth towards that RTC that returns target

0:10:46.800 --> 0:10:49.200
<v Speaker 9>every quarter, quarter by quarter, and that's the kind of

0:10:49.240 --> 0:10:52.280
<v Speaker 9>consistency that city has lacked for the past decade that

0:10:52.400 --> 0:10:55.080
<v Speaker 9>Jane Fraser is really trying to bring back to the

0:10:55.120 --> 0:10:58.920
<v Speaker 9>business and show investors that they can believe the targets

0:10:59.120 --> 0:11:02.040
<v Speaker 9>that she and her CFO Mark Mason set out and

0:11:02.080 --> 0:11:06.000
<v Speaker 9>actually stick to those so that they have that confidence

0:11:06.040 --> 0:11:08.720
<v Speaker 9>in the market, they can get rid of those regulatory

0:11:09.000 --> 0:11:12.440
<v Speaker 9>burdens that have kneecapped them for so long, and that

0:11:12.520 --> 0:11:15.120
<v Speaker 9>city can really come out of this stronger, more streamlined,

0:11:15.160 --> 0:11:19.160
<v Speaker 9>and finally, you know, put behind it this bloat that

0:11:19.200 --> 0:11:20.200
<v Speaker 9>has really weighed it down.

0:11:20.520 --> 0:11:23.760
<v Speaker 3>You also mentioned in the piece, but how they do

0:11:23.840 --> 0:11:25.760
<v Speaker 3>good numbers, They deliver good numbers, they don't get the

0:11:25.760 --> 0:11:26.760
<v Speaker 3>credit for it and earnings.

0:11:26.760 --> 0:11:27.360
<v Speaker 7>What's up with that?

0:11:27.840 --> 0:11:28.160
<v Speaker 6>Totally?

0:11:28.240 --> 0:11:30.679
<v Speaker 9>I mean every you know, every quarter there. You know,

0:11:31.120 --> 0:11:33.920
<v Speaker 9>if they post strong revenues, it's the ROTC number that's

0:11:33.960 --> 0:11:36.319
<v Speaker 9>not quite right. If the ROTC number is good, it's

0:11:36.400 --> 0:11:38.560
<v Speaker 9>revenues that aren't quite right, or it's something like that.

0:11:39.280 --> 0:11:42.320
<v Speaker 9>And you know these are often battles really on earning schools.

0:11:42.320 --> 0:11:44.400
<v Speaker 9>These are longer arning schools than most banks have, and

0:11:44.440 --> 0:11:46.880
<v Speaker 9>you can really listen to those yourself. They do get

0:11:46.960 --> 0:11:49.240
<v Speaker 9>quite colorful and quite lengthy, so you know you need

0:11:49.280 --> 0:11:52.000
<v Speaker 9>to have an extra shot of espresso while they're going through.

0:11:52.840 --> 0:11:55.320
<v Speaker 2>Thanks to Todd Gillespie, Bloomberg Finance.

0:11:55.040 --> 0:11:57.760
<v Speaker 3>Reporter, coming up well, break down the carbon market and

0:11:57.760 --> 0:12:00.720
<v Speaker 3>why it's a key part to transforming the energy landscape.

0:12:00.760 --> 0:12:03.440
<v Speaker 2>You listening to Bloomberg Intelligence on Bloomberg Radio, providing in

0:12:03.480 --> 0:12:05.640
<v Speaker 2>depth research and data on two thousand companies in one

0:12:05.679 --> 0:12:08.600
<v Speaker 2>hundred and thirty industries. You can access Bloomberg Intelligence via

0:12:08.640 --> 0:12:09.600
<v Speaker 2>Bigo in the terminal.

0:12:09.640 --> 0:12:12.400
<v Speaker 3>I'm Paul Sweeney and a Malex Steel, and this is Bloomberg.

0:12:16.840 --> 0:12:20.720
<v Speaker 1>You're listening to the Bloomberg Intelligence podcast. Catch us live

0:12:20.800 --> 0:12:24.120
<v Speaker 1>weekdays at ten am Eastern on Afocarplay and Android Auto

0:12:24.240 --> 0:12:27.120
<v Speaker 1>with the Bloomberg Business app, Listen on demand wherever you

0:12:27.200 --> 0:12:31.360
<v Speaker 1>get your podcasts, or watch us live on YouTube.

0:12:31.800 --> 0:12:34.200
<v Speaker 7>We move next to a big deal in the media space.

0:12:34.240 --> 0:12:36.959
<v Speaker 3>This week we heard that Onakrom Group is acquiring inner

0:12:36.960 --> 0:12:40.000
<v Speaker 3>Public Group to create the world's largest advertising company.

0:12:40.280 --> 0:12:43.240
<v Speaker 2>The deal values into Public at thirteen point three billion

0:12:43.320 --> 0:12:45.240
<v Speaker 2>dollars and the merger has seen as a response to

0:12:45.280 --> 0:12:46.960
<v Speaker 2>the changing advertising landscape.

0:12:47.000 --> 0:12:47.319
<v Speaker 8>For more.

0:12:47.320 --> 0:12:50.080
<v Speaker 3>We are joined by Githermongana than Bloomberg intelligence analysts on

0:12:50.160 --> 0:12:50.760
<v Speaker 3>US Media.

0:12:51.160 --> 0:12:54.079
<v Speaker 2>We first asked Githa exactly why this deal happened.

0:12:54.640 --> 0:12:57.400
<v Speaker 10>Over the past ten to fifteen years, advertising has been

0:12:57.440 --> 0:13:01.120
<v Speaker 10>completely disrupted by the likes of you know, Google and

0:13:01.200 --> 0:13:04.120
<v Speaker 10>Meta where we've seen a complete shift of ad budgets

0:13:04.160 --> 0:13:07.360
<v Speaker 10>from traditional mediums like you know, TV and radio and

0:13:07.400 --> 0:13:11.439
<v Speaker 10>newspaper to really all digital forms of advertising to the Internet.

0:13:12.080 --> 0:13:15.280
<v Speaker 10>And so there has been a lot of disintermediation with

0:13:15.400 --> 0:13:18.720
<v Speaker 10>the ad agency holding companies all of these you know

0:13:18.800 --> 0:13:22.480
<v Speaker 10>Madison Avenue type of agency companies that are only really

0:13:22.520 --> 0:13:24.920
<v Speaker 10>a handful of them left. So you have the big

0:13:24.960 --> 0:13:28.560
<v Speaker 10>four omnicommon Interpublic are of course two US based agencies,

0:13:28.600 --> 0:13:32.240
<v Speaker 10>but the bigger ones are their European rivals, Publicies and WPP.

0:13:32.840 --> 0:13:35.000
<v Speaker 10>And really what we're trying, what they're trying to do

0:13:35.080 --> 0:13:38.480
<v Speaker 10>here is, you know, it's become such a data driven business.

0:13:38.480 --> 0:13:41.520
<v Speaker 10>There is so much competition from big tech and now

0:13:41.520 --> 0:13:44.000
<v Speaker 10>of course with the advent of AI, you know, this

0:13:44.120 --> 0:13:47.480
<v Speaker 10>threat of disintermediation is only growing more and more. And

0:13:47.520 --> 0:13:49.960
<v Speaker 10>I think this is absolutely the right time for consolidation.

0:13:50.000 --> 0:13:52.480
<v Speaker 10>And this really just tells us about the amount of

0:13:52.520 --> 0:13:55.760
<v Speaker 10>secular pressures in this industry, very very similar to the

0:13:56.080 --> 0:13:57.480
<v Speaker 10>linear TV model in a way.

0:13:57.840 --> 0:14:00.880
<v Speaker 6>How cost intensive is this business? How much do they

0:14:00.920 --> 0:14:01.640
<v Speaker 6>spend on labor?

0:14:01.679 --> 0:14:05.360
<v Speaker 10>For instance, sixty percent, sixty percent of all of their

0:14:05.400 --> 0:14:08.760
<v Speaker 10>costs are are on labor. So really, this merger, in

0:14:08.840 --> 0:14:11.720
<v Speaker 10>so many ways, John is really about saving costs. They

0:14:11.720 --> 0:14:15.199
<v Speaker 10>already outlined about seven hundred and fifty million dollars in

0:14:15.600 --> 0:14:17.600
<v Speaker 10>cost energies, and of course that is likely to go

0:14:17.720 --> 0:14:21.040
<v Speaker 10>up as they kind of eliminate redundancies. And if you

0:14:21.120 --> 0:14:22.640
<v Speaker 10>just kind of look at it over the course of

0:14:22.680 --> 0:14:24.480
<v Speaker 10>the next ten years, I mean there have been multiple

0:14:24.520 --> 0:14:27.040
<v Speaker 10>studies that have been conducted that have said that you know,

0:14:27.080 --> 0:14:30.560
<v Speaker 10>with AI being able to create campaigns. Being able to

0:14:30.600 --> 0:14:34.040
<v Speaker 10>create all of these the creative elements of what an

0:14:34.080 --> 0:14:38.480
<v Speaker 10>ad agency does, almost thirty three thousand jobs or post

0:14:38.480 --> 0:14:42.080
<v Speaker 10>to almost forty percent of the ad agency sector's jobs

0:14:42.280 --> 0:14:45.160
<v Speaker 10>would have anyway been eliminated. So it is really going

0:14:45.200 --> 0:14:46.920
<v Speaker 10>to come down to saving on on labor.

0:14:47.320 --> 0:14:47.640
<v Speaker 1>Wow.

0:14:48.000 --> 0:14:52.640
<v Speaker 2>So in this world where it's it's Facebook and it's YouTube,

0:14:52.680 --> 0:14:55.240
<v Speaker 2>and if I'm Coca Cola and I'm Ford Motor Company

0:14:55.280 --> 0:14:57.440
<v Speaker 2>and I'm going to do a big advertising buy on

0:14:57.440 --> 0:15:00.400
<v Speaker 2>one of these digital platforms, how different is is than

0:15:01.080 --> 0:15:04.120
<v Speaker 2>forty years ago when I was just advertising on network television.

0:15:04.400 --> 0:15:07.680
<v Speaker 10>Yeah, it's really different now because all of these small

0:15:08.040 --> 0:15:11.760
<v Speaker 10>businesses actually now just go directly to Google and Meta.

0:15:11.920 --> 0:15:13.880
<v Speaker 10>So the way that it is now working is all

0:15:13.920 --> 0:15:17.040
<v Speaker 10>of the small mom and pop stores, medium sized businesses

0:15:17.480 --> 0:15:20.000
<v Speaker 10>are not going to these ad agency networks anymore. So

0:15:20.040 --> 0:15:23.640
<v Speaker 10>it's really only a handful of these big brands that

0:15:23.720 --> 0:15:26.920
<v Speaker 10>are really still you know, having their campaigns kind of

0:15:27.000 --> 0:15:30.640
<v Speaker 10>designed by the big you know, ad agency networks. And

0:15:30.680 --> 0:15:33.600
<v Speaker 10>even in those big brands, even brands like p ANDNG,

0:15:33.720 --> 0:15:37.200
<v Speaker 10>even brands like Apple are really kind of going more

0:15:37.280 --> 0:15:40.080
<v Speaker 10>and more in house. So it has become really difficult

0:15:40.240 --> 0:15:43.880
<v Speaker 10>for the ad agency companies to kind of survive in

0:15:43.920 --> 0:15:46.040
<v Speaker 10>this changing world, and they have to keep adapting, and

0:15:46.080 --> 0:15:49.280
<v Speaker 10>they have to keep acquiring more data centric businesses. They

0:15:49.320 --> 0:15:53.160
<v Speaker 10>have to keep investing more in AI really and in data.

0:15:53.200 --> 0:15:55.320
<v Speaker 10>And if you kind of just look at omnicommon Interpublic

0:15:55.440 --> 0:15:58.760
<v Speaker 10>versus their European rivals, they're actually lagging behind a little

0:15:58.800 --> 0:16:01.320
<v Speaker 10>bit in terms of AI and tech investments. And I

0:16:01.400 --> 0:16:04.000
<v Speaker 10>think this deal was kind of prompted a little bit

0:16:04.040 --> 0:16:04.880
<v Speaker 10>by that as well.

0:16:05.080 --> 0:16:09.840
<v Speaker 6>Can AI really deliver a creative execution for these firms?

0:16:10.240 --> 0:16:14.720
<v Speaker 10>Yes, it can, maybe not at the highest level, but

0:16:14.760 --> 0:16:17.480
<v Speaker 10>I think as you know, the algorithms kind of keep

0:16:17.520 --> 0:16:20.680
<v Speaker 10>getting refined, we are definitely going to see a huge

0:16:20.760 --> 0:16:26.000
<v Speaker 10>level of disintermediation. And even today, you know, we talk about,

0:16:26.200 --> 0:16:28.720
<v Speaker 10>you know, these companies talk about how AI is helping

0:16:28.760 --> 0:16:32.280
<v Speaker 10>them kind of refine their campaigns, kind of refine the messaging,

0:16:32.880 --> 0:16:35.320
<v Speaker 10>get to better targeting. So AI is definitely a very

0:16:35.400 --> 0:16:37.000
<v Speaker 10>very useful tool. And if you just kind of look

0:16:37.040 --> 0:16:40.120
<v Speaker 10>at even Omnicom and Interpublic over the past year, one

0:16:40.120 --> 0:16:42.760
<v Speaker 10>of the reasons why Interpublic has kind of been so

0:16:43.480 --> 0:16:46.080
<v Speaker 10>keen to for the sale is because it has been

0:16:46.160 --> 0:16:49.240
<v Speaker 10>losing so many clients. They lost a very very important

0:16:49.280 --> 0:16:53.560
<v Speaker 10>client with Amazon, and really a whole string of account

0:16:53.720 --> 0:16:57.640
<v Speaker 10>losses kind of precipitated this whole sale process. And on

0:16:57.680 --> 0:16:59.600
<v Speaker 10>the other hand, if you look at Omnicom, they've actually

0:16:59.640 --> 0:17:03.760
<v Speaker 10>have an AI assist tool called Omni which has helped

0:17:03.800 --> 0:17:06.520
<v Speaker 10>them kind of really win a lot of clients. So

0:17:06.560 --> 0:17:09.400
<v Speaker 10>we've kind of seen the two agency groups have very

0:17:09.520 --> 0:17:11.159
<v Speaker 10>differing performances all right.

0:17:11.160 --> 0:17:14.679
<v Speaker 3>Thanks to Keith Raganath and Bloomberg Intelligence Analysts on US media,

0:17:14.800 --> 0:17:15.320
<v Speaker 3>each week.

0:17:15.200 --> 0:17:18.160
<v Speaker 2>We look at research from Bloomberg and EF previously known

0:17:18.200 --> 0:17:19.439
<v Speaker 2>as New Energy Finance.

0:17:19.600 --> 0:17:21.760
<v Speaker 3>They're the team at Bloomberg that tracks and analyzes the

0:17:21.880 --> 0:17:25.840
<v Speaker 3>energy transition from commodities to power, transport, industries, buildings, and

0:17:25.920 --> 0:17:27.040
<v Speaker 3>agricultural sectors.

0:17:27.200 --> 0:17:29.440
<v Speaker 2>This week, we took a look at the carbon market,

0:17:29.520 --> 0:17:32.679
<v Speaker 2>a key part of transforming the energy landscape for more.

0:17:32.880 --> 0:17:35.880
<v Speaker 2>We were joined by bo Chin b n EF, head

0:17:35.880 --> 0:17:38.240
<v Speaker 2>of America's Environmental Markets and Weather analysts.

0:17:38.280 --> 0:17:40.400
<v Speaker 3>We first asked bo to discuss what she's currently seeing

0:17:40.440 --> 0:17:42.480
<v Speaker 3>in the US carbon market and what she expects in

0:17:42.520 --> 0:17:43.159
<v Speaker 3>the year ahead.

0:17:43.480 --> 0:17:47.320
<v Speaker 11>The US carbon market is now going through ups and downs,

0:17:47.359 --> 0:17:50.200
<v Speaker 11>so this year has been super exciting year for US

0:17:50.280 --> 0:17:54.480
<v Speaker 11>carbon markets. We have hit record highs. The most interesting

0:17:54.520 --> 0:17:57.560
<v Speaker 11>carbon markets in US are on the coasts, so we

0:17:57.640 --> 0:18:01.440
<v Speaker 11>have on the West coast California linked with Quebec, and

0:18:01.480 --> 0:18:04.720
<v Speaker 11>then on the East Coast we have Regional Greenhouse Gas Initiative,

0:18:04.800 --> 0:18:08.960
<v Speaker 11>which is a power sector specific carbon market focused on

0:18:09.040 --> 0:18:14.480
<v Speaker 11>ten states. Both of these markets have seen price records.

0:18:14.920 --> 0:18:19.159
<v Speaker 11>So looking at just West Coast, the California carbon price

0:18:19.320 --> 0:18:22.760
<v Speaker 11>went up forty percent since twenty twenty three, hitting a

0:18:22.920 --> 0:18:26.800
<v Speaker 11>record forty four dollars per ton, and we have seen

0:18:26.880 --> 0:18:30.320
<v Speaker 11>this price is actually, unfortunately this year, come down thirty

0:18:30.320 --> 0:18:35.200
<v Speaker 11>percent this year, and this is because of the reforms

0:18:35.200 --> 0:18:38.960
<v Speaker 11>that have been proposed and also the delays of these reforms.

0:18:39.359 --> 0:18:41.640
<v Speaker 11>On the East Coast we have a similar story. So

0:18:42.000 --> 0:18:45.159
<v Speaker 11>it was a very polish story up till September with

0:18:45.320 --> 0:18:48.280
<v Speaker 11>prices moving up seventy percent to twenty eight dollars per

0:18:48.320 --> 0:18:51.320
<v Speaker 11>short ton, and then prices have since also come down

0:18:51.440 --> 0:18:53.600
<v Speaker 11>twenty five percent because of their reforms.

0:18:54.000 --> 0:18:55.680
<v Speaker 7>But we do expect next.

0:18:55.480 --> 0:18:59.440
<v Speaker 11>Year to be a very exciting year as these reforms

0:18:59.480 --> 0:19:06.000
<v Speaker 11>get concluded and we see more policy certainty within these markets.

0:19:06.480 --> 0:19:08.040
<v Speaker 2>Explain it to me like I'm a five year old.

0:19:08.160 --> 0:19:10.040
<v Speaker 2>What drives the price of carbon?

0:19:10.200 --> 0:19:13.000
<v Speaker 7>I was going to ask that to you. Actually, yeah,

0:19:13.119 --> 0:19:15.520
<v Speaker 7>carbon markets really is like commodity.

0:19:15.960 --> 0:19:19.879
<v Speaker 2>Yeah, commodity, so demand, Yeah, it's demand.

0:19:20.000 --> 0:19:23.879
<v Speaker 11>It's basically think it as a farmer's market where polluters

0:19:23.920 --> 0:19:27.120
<v Speaker 11>go to buy permits and then abaters go to sell

0:19:27.200 --> 0:19:30.719
<v Speaker 11>their permits. It depends how big family are feeding, how

0:19:30.800 --> 0:19:35.480
<v Speaker 11>much demand is for that abatement, then that drives the price.

0:19:36.320 --> 0:19:39.320
<v Speaker 11>In our world, we call that demand, and the price

0:19:39.400 --> 0:19:42.000
<v Speaker 11>is a marginal abatement cost curve. So if you have

0:19:42.119 --> 0:19:46.760
<v Speaker 11>a strong demand or a strong climate ambition and a

0:19:47.680 --> 0:19:51.080
<v Speaker 11>very limited marginal abayment cost curve, that would lead to

0:19:51.280 --> 0:19:54.359
<v Speaker 11>a high carbon price. And then vice versa. If you

0:19:54.480 --> 0:19:57.639
<v Speaker 11>have low demand or low climate action and a very

0:19:58.200 --> 0:20:03.040
<v Speaker 11>significant marginalbayment cost curve, meaning that you have cheap abatement

0:20:03.520 --> 0:20:06.160
<v Speaker 11>and a vast amount of it, then you would have

0:20:06.359 --> 0:20:08.000
<v Speaker 11>typically a lower carbon price.

0:20:08.200 --> 0:20:10.960
<v Speaker 3>So to me, also the idea what the carbon price is,

0:20:12.040 --> 0:20:14.560
<v Speaker 3>If you get it high enough, then companies are going

0:20:14.600 --> 0:20:18.080
<v Speaker 3>to want to store their carbon because they're going to

0:20:18.119 --> 0:20:20.359
<v Speaker 3>be able to then trade that credit and get money

0:20:20.400 --> 0:20:22.720
<v Speaker 3>for it. Right, So the higher it is, the better

0:20:22.800 --> 0:20:24.919
<v Speaker 3>it is for the environment because companies will be more

0:20:25.000 --> 0:20:28.199
<v Speaker 3>incentivized to store their carbon or not produce it or

0:20:28.240 --> 0:20:28.720
<v Speaker 3>to sell it.

0:20:28.800 --> 0:20:31.760
<v Speaker 7>Right, Yeah, but what is that price?

0:20:32.840 --> 0:20:36.520
<v Speaker 11>It really depends on the supply and demand assets a commodity.

0:20:37.000 --> 0:20:39.560
<v Speaker 3>But like every talking about like eighty dollars, would it

0:20:39.600 --> 0:20:40.800
<v Speaker 3>really be a good incentive?

0:20:40.880 --> 0:20:41.600
<v Speaker 7>Is it one hundred?

0:20:41.640 --> 0:20:44.439
<v Speaker 3>I mean any commodity is going to have that incentive price?

0:20:45.040 --> 0:20:48.240
<v Speaker 11>Yeah, exactly. It depends on what technology you're looking at.

0:20:48.280 --> 0:20:51.040
<v Speaker 11>What is the trigger point for a trigger price? So

0:20:51.160 --> 0:20:54.040
<v Speaker 11>if you're like we typically say that the cheapest is

0:20:54.080 --> 0:20:57.200
<v Speaker 11>the call to gas field switch in, and that also

0:20:57.280 --> 0:21:00.720
<v Speaker 11>depends on the market, So in a Europe that typically

0:21:00.800 --> 0:21:04.480
<v Speaker 11>is higher than US where gas is already very low.

0:21:05.280 --> 0:21:08.680
<v Speaker 11>We also looked into this that not only a power

0:21:08.720 --> 0:21:10.960
<v Speaker 11>sector now is the ones that are being trigger but

0:21:11.000 --> 0:21:17.159
<v Speaker 11>also transport where you tilt from ice vehicle to a

0:21:17.200 --> 0:21:20.159
<v Speaker 11>EV and a carbon price can help you to do that.

0:21:20.760 --> 0:21:23.439
<v Speaker 11>And also carbon price doesn't work alone, so there's a

0:21:23.440 --> 0:21:26.520
<v Speaker 11>lot of complementary policies. We are pretty much the yeah,

0:21:27.160 --> 0:21:31.080
<v Speaker 11>final defense. So if other complementary policies didn't deliver the

0:21:31.240 --> 0:21:34.080
<v Speaker 11>results we wanted to see, then carbon price can do

0:21:34.200 --> 0:21:34.960
<v Speaker 11>the final lift.

0:21:35.080 --> 0:21:39.919
<v Speaker 2>Hopefully interesting, So real quickly change in administrations coming up.

0:21:39.920 --> 0:21:41.639
<v Speaker 2>What does that mean for your world?

0:21:41.960 --> 0:21:45.199
<v Speaker 11>Yeah, it's really exciting actually for US. Maybe for the

0:21:45.400 --> 0:21:49.320
<v Speaker 11>clean energy sector it's maybe not such positive news as

0:21:49.640 --> 0:21:55.360
<v Speaker 11>potentially some subsidies like Inflation Reduction Act and other complementary

0:21:55.359 --> 0:22:00.000
<v Speaker 11>policies for renewables and clean transport will be now reduced

0:22:00.480 --> 0:22:04.360
<v Speaker 11>and there will be more support for oil and gas industry.

0:22:04.400 --> 0:22:06.320
<v Speaker 11>But for carbon market this could be a good thing

0:22:06.440 --> 0:22:10.560
<v Speaker 11>because we would have more emissions that would support carbon prices.

0:22:10.840 --> 0:22:13.520
<v Speaker 11>But also a lot of states could now really double

0:22:13.600 --> 0:22:18.879
<v Speaker 11>down on carbon market as a policy tool to support prices. Also,

0:22:18.920 --> 0:22:22.639
<v Speaker 11>for investors, carbon price could become an attractive tool to

0:22:23.119 --> 0:22:28.680
<v Speaker 11>invest because carbon markets, particularly those compliance carbon markets, can

0:22:28.840 --> 0:22:32.720
<v Speaker 11>hedge inflation, which could become a topic now with the

0:22:32.800 --> 0:22:36.919
<v Speaker 11>immigration rules and twists being changed with the new admin quickly.

0:22:37.000 --> 0:22:38.719
<v Speaker 3>Is it a bad thing that it's so fragmented?

0:22:40.480 --> 0:22:40.840
<v Speaker 6>Yes?

0:22:41.840 --> 0:22:43.719
<v Speaker 3>Do we ever get to a place where there's like

0:22:43.800 --> 0:22:45.040
<v Speaker 3>a US carbon price?

0:22:45.720 --> 0:22:46.560
<v Speaker 6>We do hope.

0:22:46.640 --> 0:22:47.400
<v Speaker 10>So for.

0:22:49.200 --> 0:22:52.840
<v Speaker 11>National level carbon price, it will most likely not become

0:22:52.960 --> 0:22:55.679
<v Speaker 11>a realistic thing in the next few years, but we

0:22:55.720 --> 0:23:00.320
<v Speaker 11>could see more states linking like even right now we

0:23:00.400 --> 0:23:05.560
<v Speaker 11>are seeing that Washington, which survived the repeal actually.

0:23:05.320 --> 0:23:06.200
<v Speaker 7>In November as well.

0:23:06.280 --> 0:23:08.960
<v Speaker 11>So now there's more opportunity for Washington state to be

0:23:09.000 --> 0:23:10.080
<v Speaker 11>linked with a California.

0:23:10.520 --> 0:23:12.000
<v Speaker 7>There are also other states that.

0:23:12.000 --> 0:23:16.640
<v Speaker 11>Are talking about having a compliance carbon market. Actually right

0:23:16.640 --> 0:23:20.680
<v Speaker 11>here in New York, very excited about Niki. I'm excited

0:23:20.720 --> 0:23:24.280
<v Speaker 11>to make the sun O Mikid become a Hey Nikki.

0:23:25.520 --> 0:23:27.200
<v Speaker 7>So New York is going to.

0:23:27.119 --> 0:23:28.680
<v Speaker 11>Be a economy wide and it's going to be a

0:23:28.680 --> 0:23:32.520
<v Speaker 11>similar size to California. So if these all get linked,

0:23:32.560 --> 0:23:35.040
<v Speaker 11>then we could have a like maybe not an official

0:23:35.720 --> 0:23:38.000
<v Speaker 11>national but a benchmark price our.

0:23:37.960 --> 0:23:40.480
<v Speaker 2>Thanks to bo Chin b n Ef, head of America's

0:23:40.560 --> 0:23:42.280
<v Speaker 2>Environmental Markets and weather analysts.

0:23:42.480 --> 0:23:44.520
<v Speaker 3>Coming up on the program, we'll discuss why the department

0:23:44.520 --> 0:23:46.600
<v Speaker 3>store chain may See has trimmed its profit outlook for

0:23:46.680 --> 0:23:46.960
<v Speaker 3>the year.

0:23:47.200 --> 0:23:50.000
<v Speaker 2>You're listening to Bloomberg Intelligence on Bloomberg Radio, providing in

0:23:50.080 --> 0:23:52.159
<v Speaker 2>depth research and data on two thousand companies from one

0:23:52.200 --> 0:23:55.200
<v Speaker 2>hundred and thirty industries. You can access Bloomberg Intelligence via

0:23:55.240 --> 0:23:57.480
<v Speaker 2>bi go on the terminal, Paul Swinging and am Alex

0:23:57.520 --> 0:23:59.119
<v Speaker 2>Steel and this is Bloomberg.

0:24:05.440 --> 0:24:09.320
<v Speaker 1>You're listening to the Bloomberg Intelligence podcast. Catch us live

0:24:09.400 --> 0:24:12.920
<v Speaker 1>weekdays at ten am Eastern on Applecar Play and Android

0:24:12.960 --> 0:24:15.720
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0:24:15.840 --> 0:24:18.960
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0:24:19.320 --> 0:24:21.320
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0:24:21.359 --> 0:24:24.600
<v Speaker 3>Eleven thirty We moved next to the computer tech company Oracle.

0:24:24.640 --> 0:24:26.399
<v Speaker 7>This week's shares of Oracle fell by the most in

0:24:26.440 --> 0:24:26.760
<v Speaker 7>a year.

0:24:27.040 --> 0:24:29.480
<v Speaker 2>That's after the company reported second quarter profit and revenue

0:24:29.520 --> 0:24:31.240
<v Speaker 2>that missed analysts expectations from more.

0:24:31.280 --> 0:24:34.360
<v Speaker 3>We are joined by anaag Rana, Bloomberg Intelligence technology analyst.

0:24:34.680 --> 0:24:37.600
<v Speaker 2>First, ask on Arov what Oracle's results say about its business.

0:24:37.880 --> 0:24:39.960
<v Speaker 8>See, when you look at the constant currency growth for

0:24:40.040 --> 0:24:43.360
<v Speaker 8>a cloud infrastructure, it was fifty two percent. I think

0:24:43.359 --> 0:24:46.200
<v Speaker 8>consensus was fifty one, so a slight beat, but the

0:24:46.280 --> 0:24:49.760
<v Speaker 8>reaction tells me it was not good enough for byside investors.

0:24:50.400 --> 0:24:53.760
<v Speaker 8>You know, from our side, there's no problem in terms

0:24:53.800 --> 0:24:57.639
<v Speaker 8>of future growth prospects for that business because backlock's very strong.

0:24:57.960 --> 0:25:01.320
<v Speaker 8>The demand is there. And for Oracle, they're actually getting

0:25:01.359 --> 0:25:04.680
<v Speaker 8>work from Microsoft because Microsoft is leasing their data centers

0:25:05.359 --> 0:25:08.040
<v Speaker 8>because it is having a huge backlog of work on

0:25:08.080 --> 0:25:08.520
<v Speaker 8>their end.

0:25:08.800 --> 0:25:10.560
<v Speaker 3>So does that mean this is just a Hey, the

0:25:10.600 --> 0:25:13.639
<v Speaker 3>stock could run up really fast. Therefore, the expectator, just

0:25:13.640 --> 0:25:15.480
<v Speaker 3>the expectation game, is that what I can read into

0:25:15.480 --> 0:25:16.280
<v Speaker 3>the equity.

0:25:16.320 --> 0:25:19.440
<v Speaker 8>I would absolutely say that because right now this has

0:25:19.520 --> 0:25:23.280
<v Speaker 8>been the trade for twenty twenty four has been the

0:25:23.280 --> 0:25:27.159
<v Speaker 8>infrastructure that's related to AI, so whether that's the chips,

0:25:27.200 --> 0:25:30.080
<v Speaker 8>even the numbers were pretty good, and twenty twenty five

0:25:30.119 --> 0:25:32.400
<v Speaker 8>could be a year where you will see the downstream

0:25:32.440 --> 0:25:36.320
<v Speaker 8>impact of some of these AI infrastructures, which is cloud

0:25:36.400 --> 0:25:40.000
<v Speaker 8>companies or other software companies coming up with applications that

0:25:40.040 --> 0:25:43.240
<v Speaker 8>are based on some of these AI infrastructures. So we

0:25:43.320 --> 0:25:45.920
<v Speaker 8>have a long way to go before we realize the

0:25:45.960 --> 0:25:49.320
<v Speaker 8>true value of AI spending across the entire value chain.

0:25:50.119 --> 0:25:52.280
<v Speaker 8>For this year, we just saw it in the you know,

0:25:52.320 --> 0:25:54.240
<v Speaker 8>the cloud and the chips part of it.

0:25:54.560 --> 0:25:57.360
<v Speaker 2>The demand is so robust on a rock that I've

0:25:57.359 --> 0:26:01.000
<v Speaker 2>heard companies talk about maybe even some shortage of some

0:26:01.160 --> 0:26:03.600
<v Speaker 2>components of some of the things they want to buy.

0:26:03.720 --> 0:26:05.280
<v Speaker 2>Talk to us about that. What did Oracle say?

0:26:05.720 --> 0:26:09.480
<v Speaker 8>Yeah, Oracle is no different than other companies because even

0:26:09.480 --> 0:26:12.240
<v Speaker 8>for Microsoft, they cannot get up data centers at the

0:26:12.240 --> 0:26:15.320
<v Speaker 8>same rate as they're seeing demand coming from open AI.

0:26:15.480 --> 0:26:19.200
<v Speaker 8>They are not They are everybody's having struggled to procure

0:26:19.760 --> 0:26:22.639
<v Speaker 8>in video GPUs to train some of these models. And

0:26:22.680 --> 0:26:26.040
<v Speaker 8>that's the case. Oracle's backlock is so strong. But you

0:26:26.080 --> 0:26:28.520
<v Speaker 8>know there has been supply challenges. They are spending a

0:26:28.520 --> 0:26:32.479
<v Speaker 8>lot of money on capital expenditure. Last year approximately, they

0:26:32.520 --> 0:26:35.879
<v Speaker 8>spent about seven billion dollars in capex. This year is

0:26:35.920 --> 0:26:39.400
<v Speaker 8>going to be double of that fourteen billion dollars. So

0:26:39.480 --> 0:26:43.200
<v Speaker 8>I mean it we see that when these companies spend

0:26:43.200 --> 0:26:46.320
<v Speaker 8>money to expand their capacity, we know that demand is

0:26:46.359 --> 0:26:46.880
<v Speaker 8>behind it.

0:26:47.280 --> 0:26:49.520
<v Speaker 7>So this is like the software stuff.

0:26:49.520 --> 0:26:53.240
<v Speaker 3>So Nvidia supplies the chips for Oracle, who then uses

0:26:53.440 --> 0:26:57.280
<v Speaker 3>builds the software stuff for companies like Eccentric or Amazon

0:26:57.320 --> 0:26:58.840
<v Speaker 3>AM I is that correct?

0:26:59.480 --> 0:27:02.280
<v Speaker 8>Yeah, it's you got it right. In this case, what's

0:27:02.280 --> 0:27:07.920
<v Speaker 8>happening is companies like Microsoft, Google, AWS, and Oracle are

0:27:07.920 --> 0:27:12.000
<v Speaker 8>building an infrastructure on which companies can build applications. So

0:27:12.080 --> 0:27:14.760
<v Speaker 8>these companies could be accentual, it could be JP Morgan,

0:27:15.040 --> 0:27:18.320
<v Speaker 8>it could be Citybank, et cetera. These companies will go

0:27:18.400 --> 0:27:21.640
<v Speaker 8>out and create their own AI apps that can then

0:27:21.680 --> 0:27:24.639
<v Speaker 8>be used internally by the companies. And I mean you

0:27:24.680 --> 0:27:27.400
<v Speaker 8>can do this in house also by buying AI servers

0:27:27.680 --> 0:27:30.040
<v Speaker 8>but cloud is usually a better and each cheaper way

0:27:30.080 --> 0:27:31.560
<v Speaker 8>to go because you can turn it off if you

0:27:31.600 --> 0:27:34.200
<v Speaker 8>don't like it. So that's what we are seeing right.

0:27:34.119 --> 0:27:38.000
<v Speaker 2>Now is peak AI anywhere on the horizon there on

0:27:38.119 --> 0:27:38.440
<v Speaker 2>a rug.

0:27:39.400 --> 0:27:42.080
<v Speaker 8>That's a very very good and tough question, frankly, because

0:27:42.320 --> 0:27:44.840
<v Speaker 8>the question is going to be will people get bored

0:27:44.880 --> 0:27:47.479
<v Speaker 8>in the AI infrastructure space, and they will will they

0:27:47.520 --> 0:27:50.080
<v Speaker 8>move to somewhere else? We saw that in the last

0:27:50.119 --> 0:27:53.719
<v Speaker 8>three months suddenly the interest in Salesforce, for example, and

0:27:53.760 --> 0:27:56.880
<v Speaker 8>that is because Salesforce is the second leg of this equation.

0:27:57.200 --> 0:27:59.960
<v Speaker 8>One is the infrastructure we talked about. Second is the application.

0:28:00.760 --> 0:28:04.359
<v Speaker 8>Salesforce created some AI application that can help you do

0:28:04.720 --> 0:28:10.680
<v Speaker 8>you know, fix your online orders, automatically, do some referns,

0:28:10.720 --> 0:28:13.359
<v Speaker 8>et cetera. So that's the application part of it. We

0:28:13.520 --> 0:28:16.200
<v Speaker 8>think next yer is going to be a lot of

0:28:16.520 --> 0:28:20.040
<v Speaker 8>Salesforce like applications that will come to the market by

0:28:20.080 --> 0:28:23.440
<v Speaker 8>different software companies that will help people be more productive.

0:28:23.720 --> 0:28:25.479
<v Speaker 8>And then the third and the final layer would be

0:28:25.680 --> 0:28:28.879
<v Speaker 8>the consulting companies that are helping in the implementation of

0:28:28.880 --> 0:28:32.480
<v Speaker 8>that that goes in tandem with software companies. But we

0:28:32.560 --> 0:28:34.960
<v Speaker 8>think there are multiple years before we see the true

0:28:35.000 --> 0:28:37.640
<v Speaker 8>realization of the funding that's happening right now.

0:28:37.760 --> 0:28:38.800
<v Speaker 7>All right, quickly on a rag.

0:28:39.120 --> 0:28:41.720
<v Speaker 3>Adobe is a competitor Oracle and what do we learn

0:28:41.760 --> 0:28:43.680
<v Speaker 3>from Oracle as relates to Adobe.

0:28:43.880 --> 0:28:48.120
<v Speaker 8>Yeah, from a from Wells. They're both software companies, but

0:28:48.160 --> 0:28:51.240
<v Speaker 8>they do slightly different things. For Adobe, the big question

0:28:51.360 --> 0:28:54.560
<v Speaker 8>is going to be is their business being cannibalized by

0:28:54.880 --> 0:28:58.080
<v Speaker 8>open source AI tools. We don't think that's the case

0:28:58.160 --> 0:29:00.320
<v Speaker 8>right now, but that's a big argument in this space.

0:29:00.600 --> 0:29:03.080
<v Speaker 8>If you look at the entire software space right now,

0:29:03.520 --> 0:29:06.280
<v Speaker 8>Adobe's probably the one where do you have the biggest

0:29:06.400 --> 0:29:09.000
<v Speaker 8>argument whether they're going to be the net beneficiaries of

0:29:09.040 --> 0:29:11.160
<v Speaker 8>AI or whether they're going to get hurt by I.

0:29:11.640 --> 0:29:14.160
<v Speaker 8>For Adobe, we expect them to go out and come

0:29:14.160 --> 0:29:16.600
<v Speaker 8>out and say that the adoption rate of their own

0:29:16.640 --> 0:29:19.120
<v Speaker 8>AI tools is picking up, and that's really what we

0:29:19.160 --> 0:29:20.400
<v Speaker 8>are looking for. All right.

0:29:20.400 --> 0:29:23.520
<v Speaker 3>Thanks to Anna Agrana Bloomberg Intelligence and your technology analyst.

0:29:23.800 --> 0:29:26.760
<v Speaker 2>We move next to the retail space and Macy's. This week,

0:29:26.840 --> 0:29:29.240
<v Speaker 2>the department store chain said it had trimmed its profit

0:29:29.320 --> 0:29:30.120
<v Speaker 2>outlook for the year.

0:29:30.440 --> 0:29:33.600
<v Speaker 3>This comes after Macy's concluded its investigation into an employee

0:29:33.600 --> 0:29:36.240
<v Speaker 3>that hid millions of dollars and expenses. The discovery of

0:29:36.240 --> 0:29:38.800
<v Speaker 3>the accounting eras led Macy's to delay its full earnings

0:29:38.840 --> 0:29:39.920
<v Speaker 3>report back in November.

0:29:40.160 --> 0:29:42.280
<v Speaker 2>For more, we were joined by Mary Ross Gilbert Bloomberg

0:29:42.320 --> 0:29:45.120
<v Speaker 2>Intelligence senior Ecuadanalysts. We first asked Mary to walk us

0:29:45.160 --> 0:29:46.719
<v Speaker 2>through Macy's recent investigation.

0:29:47.160 --> 0:29:50.640
<v Speaker 12>What happened here is that they had a single employee

0:29:50.960 --> 0:29:55.000
<v Speaker 12>who basically hid small package delivery expenses of about one

0:29:55.080 --> 0:29:58.200
<v Speaker 12>hundred and fifty one million. That was over a three

0:29:58.320 --> 0:30:01.680
<v Speaker 12>year period, so were the year to date. I think

0:30:01.720 --> 0:30:04.560
<v Speaker 12>it was about nine million is the effect in the

0:30:05.640 --> 0:30:08.600
<v Speaker 12>for that period. So the company, of course had to

0:30:08.640 --> 0:30:13.360
<v Speaker 12>lower their guidance, and the gross margin figures anyps of

0:30:13.400 --> 0:30:15.920
<v Speaker 12>course because it drops all the way down there, but

0:30:16.240 --> 0:30:20.080
<v Speaker 12>it doesn't affect cash. So that's the good news and

0:30:20.120 --> 0:30:23.920
<v Speaker 12>it's put behind him. What they have done is they've

0:30:23.920 --> 0:30:28.640
<v Speaker 12>improved their financial controls. They've added some additional checks and

0:30:28.720 --> 0:30:31.880
<v Speaker 12>balances there. So I think this is now behind them,

0:30:32.280 --> 0:30:35.320
<v Speaker 12>and I think the real focus here is on the

0:30:35.360 --> 0:30:39.040
<v Speaker 12>go forward operations. And I say go forward meaning let's

0:30:39.120 --> 0:30:41.440
<v Speaker 12>exclude the one hundred and fifty stores that they're going

0:30:41.520 --> 0:30:44.680
<v Speaker 12>to close. Sixty five of those stores will close in

0:30:44.720 --> 0:30:47.959
<v Speaker 12>the fourth quarter. That's ahead of the original fifty they

0:30:48.000 --> 0:30:51.400
<v Speaker 12>slated to close, and then the other eighty five maybe

0:30:51.400 --> 0:30:53.840
<v Speaker 12>that'll get done by next year instead of the next

0:30:53.880 --> 0:30:57.040
<v Speaker 12>two years. Nonetheless, if you put those aside and you

0:30:57.080 --> 0:30:59.760
<v Speaker 12>look at what's going on with the go forward business,

0:31:00.160 --> 0:31:05.440
<v Speaker 12>we're seeing sequentially sequential improvement with the first fifty stores

0:31:05.480 --> 0:31:10.440
<v Speaker 12>that they've completely revamped actually posting a positive increase. They

0:31:10.440 --> 0:31:12.719
<v Speaker 12>were up one point nine percent in the third quarter,

0:31:13.000 --> 0:31:16.520
<v Speaker 12>and that's the third quarter of positive comp improven there.

0:31:16.800 --> 0:31:21.520
<v Speaker 12>So we're actually seeing signs that the plans, the initiatives

0:31:21.520 --> 0:31:25.920
<v Speaker 12>that they're employing are working. So we see some green

0:31:25.960 --> 0:31:27.880
<v Speaker 12>shoots in there. What does it let me think this

0:31:28.160 --> 0:31:30.320
<v Speaker 12>accounting issue is behind them all right?

0:31:30.480 --> 0:31:33.840
<v Speaker 2>What does a revamped store look like? What's the strategy

0:31:33.960 --> 0:31:35.720
<v Speaker 2>behind a revamped store?

0:31:36.840 --> 0:31:38.160
<v Speaker 5>Paul, That's a good question.

0:31:38.640 --> 0:31:41.160
<v Speaker 12>So what that means is is they've really up their

0:31:41.200 --> 0:31:44.520
<v Speaker 12>game in terms of merchandising. They brought in new brands

0:31:44.600 --> 0:31:51.560
<v Speaker 12>like Lafitte, La Levec Fee, Donna, Karen, Carl Lagerfeld, Steve Madden.

0:31:51.920 --> 0:31:56.800
<v Speaker 12>These brands offer great style and value to the company.

0:31:57.240 --> 0:32:01.280
<v Speaker 12>Their private label program has been completely revamped. Now that's

0:32:01.320 --> 0:32:04.040
<v Speaker 12>only about fifteen percent of sales. So the biggest part

0:32:04.120 --> 0:32:07.040
<v Speaker 12>is really bringing me in these other brands. But not

0:32:07.120 --> 0:32:09.920
<v Speaker 12>only that, they've uped their game in terms of service.

0:32:10.240 --> 0:32:13.560
<v Speaker 12>They now have salespeople in the shoe department and then

0:32:13.600 --> 0:32:16.800
<v Speaker 12>they have runners. So what happens is a salesperson will

0:32:16.800 --> 0:32:19.480
<v Speaker 12>be working directly with a client and they'll say, hey,

0:32:19.560 --> 0:32:22.920
<v Speaker 12>I need size eight, size eight and a half in this,

0:32:23.240 --> 0:32:25.640
<v Speaker 12>and then they run and go get them. And then

0:32:25.680 --> 0:32:29.840
<v Speaker 12>also they have service in handbags and in women's ready

0:32:29.880 --> 0:32:34.720
<v Speaker 12>to wear. So having boosted the service levels also improving

0:32:34.760 --> 0:32:38.320
<v Speaker 12>the overall appearance throughout the stores. We've been in our

0:32:38.400 --> 0:32:42.080
<v Speaker 12>channel checks watching this happen, and we see the improvement.

0:32:42.160 --> 0:32:44.160
<v Speaker 12>We see how that they got rid of some brands

0:32:44.160 --> 0:32:47.440
<v Speaker 12>that were less relevant, brought in these newer ones. And

0:32:47.760 --> 0:32:52.520
<v Speaker 12>we also saw during that Black Friday, we saw this

0:32:52.640 --> 0:32:55.840
<v Speaker 12>year more traffic in the stores than we saw in the.

0:32:55.840 --> 0:32:56.960
<v Speaker 5>Prior two years.

0:32:57.400 --> 0:33:00.240
<v Speaker 12>And of course when you look at the data, their

0:33:00.280 --> 0:33:03.200
<v Speaker 12>sales were better this year. They saw an increase in

0:33:03.280 --> 0:33:06.720
<v Speaker 12>the Black Friday through Cyber Monday and the consumer transaction data,

0:33:07.120 --> 0:33:10.280
<v Speaker 12>and that's something the company mentioned on the call today

0:33:10.320 --> 0:33:13.520
<v Speaker 12>that yes, they're seeing strong you know, or sort of

0:33:13.560 --> 0:33:16.959
<v Speaker 12>sequential improvement versus the third quarter into the fourth quarter.

0:33:17.720 --> 0:33:20.560
<v Speaker 5>So I think those are some of the part.

0:33:20.520 --> 0:33:23.760
<v Speaker 3>You're describing Mary. The revamped stores. It sounds a little

0:33:23.760 --> 0:33:25.200
<v Speaker 3>bit like Bloomingdale's Light.

0:33:27.320 --> 0:33:27.800
<v Speaker 5>You know what.

0:33:28.040 --> 0:33:31.640
<v Speaker 12>That's exactly if you look at a let's say, one

0:33:31.640 --> 0:33:34.600
<v Speaker 12>of their better what what they would call that, one

0:33:34.600 --> 0:33:37.000
<v Speaker 12>of their flagships. So we have one here right next

0:33:37.000 --> 0:33:41.080
<v Speaker 12>door in Century City, it does very much look like

0:33:41.320 --> 0:33:42.240
<v Speaker 12>a Bloomingdale's.

0:33:42.280 --> 0:33:44.440
<v Speaker 5>The store is interesting. It's brand new.

0:33:44.560 --> 0:33:47.000
<v Speaker 12>I mean they've remodeled it four or five times within

0:33:47.040 --> 0:33:49.360
<v Speaker 12>the last few years. What I mean by that is

0:33:49.400 --> 0:33:52.800
<v Speaker 12>they've expanded beauty. So you walk in, it's an incredible

0:33:52.840 --> 0:33:54.000
<v Speaker 12>showcase of beauty.

0:33:54.320 --> 0:33:56.680
<v Speaker 5>Also includes Blue Mercury, of course.

0:33:56.880 --> 0:34:00.880
<v Speaker 12>So we we've seen just and the stores so much brighter.

0:34:00.920 --> 0:34:04.640
<v Speaker 12>But even in a tired old mall down in southern

0:34:04.720 --> 0:34:08.720
<v Speaker 12>California that I will go to, even that store looks

0:34:08.800 --> 0:34:13.120
<v Speaker 12>much better, even though it's sort of a tired location.

0:34:14.200 --> 0:34:15.640
<v Speaker 5>They've really improved it.

0:34:16.200 --> 0:34:20.320
<v Speaker 12>The better brands that they've incorporated, making these little Calvin

0:34:20.400 --> 0:34:24.560
<v Speaker 12>Klein they look like little boutique shops, Michael Core's, Calvin Kleine,

0:34:25.080 --> 0:34:29.960
<v Speaker 12>Tommy Hillfigure those are all in there and beautifully appointed.

0:34:30.000 --> 0:34:34.360
<v Speaker 12>It's much more open. There's not just a sea of merchandise.

0:34:34.560 --> 0:34:38.600
<v Speaker 12>It just makes more sense. So that's been extended across

0:34:38.640 --> 0:34:41.279
<v Speaker 12>another hundred stores, so not just a fifty, but another

0:34:41.280 --> 0:34:41.720
<v Speaker 12>one hundred.

0:34:41.880 --> 0:34:45.960
<v Speaker 2>All right, So what's the company saying just about holiday

0:34:46.080 --> 0:34:49.279
<v Speaker 2>sales so far? It is kind of confirmed what you've seen.

0:34:50.320 --> 0:34:51.560
<v Speaker 5>Yes, they did.

0:34:51.600 --> 0:34:54.000
<v Speaker 12>They said that they saw a good start to the

0:34:54.000 --> 0:34:56.839
<v Speaker 12>holiday season, but of course we still have more to go.

0:34:57.520 --> 0:35:02.160
<v Speaker 12>So no, and they act actually raised their guidance ATAD

0:35:03.520 --> 0:35:07.640
<v Speaker 12>so I thought that was also an indication of what

0:35:07.680 --> 0:35:10.360
<v Speaker 12>they're seeing, and so they could potentially beat the guidance

0:35:10.400 --> 0:35:13.720
<v Speaker 12>because when they put things the guidance out, they really

0:35:14.160 --> 0:35:17.120
<v Speaker 12>attempt to exceed those figures.

0:35:17.600 --> 0:35:21.080
<v Speaker 3>Right. Thanks to Mary Ross Gilbert, Bloomberg Intelligence Senior Equity Analyst.

0:35:21.160 --> 0:35:25.680
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