WEBVTT - A Boston Fed Special

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<v Speaker 1>Bloomberg Audio Studios, podcasts, radio news.

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<v Speaker 2>This is the Bloomberg Surveillance Podcast. Catch us live weekdays

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<v Speaker 2>at seven am Eastern on Apple car Player, Android Auto

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<v Speaker 2>with the Bloomberg Business app. Listen on demand wherever you

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<v Speaker 2>get your podcasts, or watch us live on YouTube.

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<v Speaker 3>Now, are Michael McKee an important conversation with the President

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<v Speaker 3>of the Boston Fed, Susan Collins.

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<v Speaker 4>I'm Michael McKee, the international economics and Policy correspondent for Bloomberg,

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<v Speaker 4>and we are at the Boston Federal Reserve Bank today.

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<v Speaker 5>They're holding their sixty eighth.

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<v Speaker 4>Annual Economics conference, and we're joined by the President of

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<v Speaker 4>the Boston Fed, Susan Collins. Thank you very much for

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<v Speaker 4>being with us today.

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<v Speaker 6>It's delighted to be here. Thanks for being at the

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<v Speaker 6>Boston Fed.

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<v Speaker 5>It's great. We tell everybody. It's a beautiful day. But

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<v Speaker 5>it's thirty nine degrees so winter is finally hit here.

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<v Speaker 6>The seasons are wonderful.

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<v Speaker 4>Oh, speaking of winter, December eighteenth, you have another FED meeting,

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<v Speaker 4>and at this point there seem to be some questions

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<v Speaker 4>about whether or not the Fed will be cutting rates again,

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<v Speaker 4>because this week we got some firm inflation news retail

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<v Speaker 4>sales were okay, but not particularly strong at this point.

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<v Speaker 5>Are you thinking that.

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<v Speaker 4>We should see a cut or is it better to

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<v Speaker 4>pause and wait?

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<v Speaker 6>So I think it's important to say there's no preset path.

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<v Speaker 6>I do see rates as still in the restrictive range,

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<v Speaker 6>which means that over time some amount of easing will

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<v Speaker 6>be appropriate. But you know, the economy is in a

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<v Speaker 6>very good place right now, and inflation's coming back down

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<v Speaker 6>to target. The labor markets are healthy, we're seeing solid growth.

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<v Speaker 5>The goal of policies.

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<v Speaker 6>Really to sustain that healthy set of conditions, recognizing you know,

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<v Speaker 6>there are risks on both sides, and so I think

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<v Speaker 6>we're well positioned. I certainly wouldn't take another ease in

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<v Speaker 6>December off the table, But again we're not in a

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<v Speaker 6>preset path, and so we'll have to look carefully at

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<v Speaker 6>the data and see what makes sense when we get

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<v Speaker 6>to December eighteenth.

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<v Speaker 4>Well, the data this week showed inflation a little bit

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<v Speaker 4>stronger than it had been in the CPI and the PPI,

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<v Speaker 4>and those who do the nerdy calculations for the PCE

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<v Speaker 4>say we're going to see.

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<v Speaker 5>The same thing.

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<v Speaker 4>Should you keep your foot on the brake a little

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<v Speaker 4>more then because inflation is not back down to your target.

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<v Speaker 6>So you know, I don't focus too much on any

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<v Speaker 6>one data point. I think it's really important to look holistically.

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<v Speaker 6>And when I do that, what I see is that,

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<v Speaker 6>first of all, inflation has come down significantly. I focus

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<v Speaker 6>on the you know, a couple of month averages, and

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<v Speaker 6>if you take food, energy, and in particular shelter out,

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<v Speaker 6>the rest of inflation has actually been in the range

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<v Speaker 6>consistent with the two percent, exactly what we'd like to see.

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<v Speaker 6>What's really still elevated as shelter and that is taking

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<v Speaker 6>time to come back down, and a lot of that

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<v Speaker 6>really reflects shocks from the past. I'm not seeing evidence

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<v Speaker 6>of new price pressures, and so I think it's important

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<v Speaker 6>to stay the course. But that analysis of the data

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<v Speaker 6>is part of why I thought it was really appropriate

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<v Speaker 6>for us to begin easing in September, and to be

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<v Speaker 6>in an environment where we are really looking over time methodically,

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<v Speaker 6>perhaps patiently, to be normalizing policy, to maintain those healthy

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<v Speaker 6>conditions that I talked about a moment ago.

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<v Speaker 5>Well, let's look at the other side of the mandate. Employment.

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<v Speaker 4>We had a very strong employment report, and then we

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<v Speaker 4>had a very weak employment report, granted, affected by hurricanes

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<v Speaker 4>and strikes.

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<v Speaker 5>So what's your judgment of.

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<v Speaker 4>Where the labor market is when you look holistically at

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<v Speaker 4>all of the labor data and when I.

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<v Speaker 6>Look at all of the data, and you're absolutely right,

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<v Speaker 6>there have been some stronger readings, there have been some

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<v Speaker 6>readings over time that were a bit weaker, and there are.

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<v Speaker 5>A lot of special factors.

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<v Speaker 6>So looking at averages over time, looking at the range

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<v Speaker 6>of information, what I see is a labor market that

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<v Speaker 6>looks similar to conditions that we've considered full employment, so

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<v Speaker 6>in terms of job openings and quit rates, and the

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<v Speaker 6>fact that wage growth has been coming down and given

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<v Speaker 6>the high productivity we've seen is consistent with the move

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<v Speaker 6>back down to two percent inflation and staying there. And

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<v Speaker 6>unemployment has stayed in a range that is near four

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<v Speaker 6>percent low by historical standards, so yes, higher than a

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<v Speaker 6>year ago. So all of that, to me says healthy

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<v Speaker 6>labor market conditions. Things to watch carefully and don't focus

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<v Speaker 6>too much on any one piece of data.

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<v Speaker 7>Have to look at the whole picture.

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<v Speaker 4>All right, healthy labor market. Inflation's coming down, even if

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<v Speaker 4>it's stalled a little bit, but it's in the twos

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<v Speaker 4>and the economy is stronger than people had forecasts. So

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<v Speaker 4>do you agree with Chairman Powell and saying there is

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<v Speaker 4>nothing telling you you have to cut rates very quickly?

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<v Speaker 6>So I think that I don't. I agree that I

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<v Speaker 6>don't see a big urgency. At the same time, I

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<v Speaker 6>do think that preserving those healthy conditions, right, I mean,

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<v Speaker 6>that's what our mandate really is from Congress. Price stability

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<v Speaker 6>and maximum employment sustained over time, not just at some

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<v Speaker 6>point in time. And so as I said before, I

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<v Speaker 6>do see financial the policy stances being in a restrictive

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<v Speaker 6>place and over time, normalizing that I think is going

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<v Speaker 6>to be important. But we're well positioned to be really

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<v Speaker 6>careful in assessing the data and making decisions about the pace,

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<v Speaker 6>about the timing, and so that you know, that's how

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<v Speaker 6>I think about that.

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<v Speaker 4>Let me ask about the elephant in the room, and

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<v Speaker 4>that is the new President elect of the United States.

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<v Speaker 4>His policies have not been fleshed out. Tremen Pol's made

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<v Speaker 4>it clear you don't know exactly what's going to happen.

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<v Speaker 4>But do you expect that something in whatever his fiscal

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<v Speaker 4>plans are will affect the economy and you will have

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<v Speaker 4>to take another look, say at what your economic projections

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<v Speaker 4>are and what the plot projections are for twenty twenty five.

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<v Speaker 6>Now, as we get information about the economy, certainly that

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<v Speaker 6>includes about fiscal policy. Of course, it's really important to

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<v Speaker 6>factor that in. And there are lots of things we

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<v Speaker 6>look at. Fiscal policies certainly one of them, but I

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<v Speaker 6>don't want to speculate on what policies that haven't been

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<v Speaker 6>enacted or implemented might look like.

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<v Speaker 4>Well, do you think that tariffs as an economic concept

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<v Speaker 4>add to inflation?

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<v Speaker 6>They can, And again we would have to see if

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<v Speaker 6>there are tariffs that are implemented, more about the specifics

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<v Speaker 6>and the dynamics for those.

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<v Speaker 4>Now, if there's a fiscal impulse in whatever the President

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<v Speaker 4>elect chooses to do, is the economy growing too fast

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<v Speaker 4>for that right now? Would that be a danger a worry?

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<v Speaker 6>So again, I think there are lots of things that

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<v Speaker 6>determine how the economy evolves and grows over time. Fiscal

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<v Speaker 6>policy is certainly one of them and certainly does have

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<v Speaker 6>an impact on that, and we'd have to factor that

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<v Speaker 6>in and look through that. You know, I do think,

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<v Speaker 6>and Chair Powell has also said this that you know,

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<v Speaker 6>fiscal policy at the moment is on a path that's

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<v Speaker 6>not sustainable. But again, we when we make our policy

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<v Speaker 6>decisions to focus on our mandate from Congress, it's really

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<v Speaker 6>based on the data that we have available and the

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<v Speaker 6>analysis and the assessments that we can do on that basis.

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<v Speaker 4>As far as I know, President like Trump has never

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<v Speaker 4>threatened to fire you.

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<v Speaker 5>But I wanted to ask.

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<v Speaker 4>What is in your mind the relationship between the Federal

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<v Speaker 4>Reserve and the executive branch.

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<v Speaker 6>So what I would say is that the FED is

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<v Speaker 6>structured by Congress as an independent body, and that that

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<v Speaker 6>is important in terms of the ability for us to

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<v Speaker 6>do our job well. There's a lot of analysis that

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<v Speaker 6>shows that independent central banks are more effective at keeping

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<v Speaker 6>inflation low and stable, and we have really seen how

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<v Speaker 6>important it is to keep inflation low and stable in

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<v Speaker 6>terms of the impact the higher prices past inflation have had.

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<v Speaker 6>And so I think that is a very good structure

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<v Speaker 6>to enable us to do our jobs well.

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<v Speaker 4>So the things that come across social media basically just

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<v Speaker 4>noise in the background to you as a policymaker.

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<v Speaker 6>I am very focused on doing my job and there

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<v Speaker 6>is more than enough to keep me very focused and

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<v Speaker 6>very busy now.

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<v Speaker 5>The people, well you can't see them.

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<v Speaker 4>I could see them out there, all the traders on

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<v Speaker 4>their knees going tell us when you're going to.

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<v Speaker 5>Do this sort of thing.

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<v Speaker 4>Can we basically say, because of the potential changes that

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<v Speaker 4>are coming and the data that we have seen, that

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<v Speaker 4>the dot plot for twenty twenty five and the SEP

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<v Speaker 4>for twenty twenty five, those are kind of out the

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<v Speaker 4>window now and we should really wait until December or

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<v Speaker 4>even later to get a good idea of where you

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<v Speaker 4>think you're going to be and the economy is going

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<v Speaker 4>to be.

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<v Speaker 6>All things I think always evolve, and so in about

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<v Speaker 6>a month or so, we will have a new SEP

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<v Speaker 6>and information from all of the policymakers about what they think.

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<v Speaker 6>And so I think it's always true that you know,

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<v Speaker 6>in the middle of the SEP information you don't want

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<v Speaker 6>to take too much from what might have been written down,

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<v Speaker 6>penciled in. I would say a number of weeks earlier,

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<v Speaker 6>a lot of the data evolves.

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<v Speaker 4>What are the people in these tall buildings around us,

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<v Speaker 4>all the corporate leaders in your district telling you about

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<v Speaker 4>how they see the economy going forward and their plans.

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<v Speaker 6>Yeah, and I appreciate you asking about that. I think

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<v Speaker 6>one of the really important things that I do, that

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<v Speaker 6>my colleagues do is talk to people across the economy

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<v Speaker 6>in lots of different sectors. So being out and about

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<v Speaker 6>throughout New England and what I'm hearing is pretty consistent

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<v Speaker 6>with what I said at the outset that people are

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<v Speaker 6>cautiously optimistic. They see an economy that seems resilient. Labor

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<v Speaker 6>markets have moved into much more normal conditions relative to

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<v Speaker 6>the unsustainable, more overheated conditions from a year or more ago,

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<v Speaker 6>and the price pressures really have abated considerably. So that's

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<v Speaker 6>all very consistent. But of course, you know, the aggregate

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<v Speaker 6>data masks a range of different specifis across individual firms

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<v Speaker 6>and sectors and regions, and it's really I think helpful

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<v Speaker 6>to hear all of that and pull the qualitative information

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<v Speaker 6>together with the statistics.

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<v Speaker 4>One last question at your conference. It's on financial technology

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<v Speaker 4>this year and the Boston Fed's been in the middle

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<v Speaker 4>of financial technology and just coincidentally, coming up at the

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<v Speaker 4>top of the hour, we have our Bloomberg Technology Show.

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<v Speaker 5>So let me ask you.

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<v Speaker 4>A lot of tech talk over the last five, six,

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<v Speaker 4>seven years has been tech talk.

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<v Speaker 5>How fast are we going to see some.

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<v Speaker 4>Sort of impact on the average person from new payment systems.

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<v Speaker 4>I realize you have fed now in place, but how

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<v Speaker 4>fast are people going to say, hey, this is something different?

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<v Speaker 5>And are we going to.

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<v Speaker 4>See any kind of digital currency adoption, whether it's private

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<v Speaker 4>or government in the next few years.

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<v Speaker 6>So, you know, the impacts of technology have many, many dimensions,

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<v Speaker 6>and I think we're already seeing some impacts in terms

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<v Speaker 6>of the roles that fintech are playing across our economy

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<v Speaker 6>in different ways. And the conference today and tomorrow is

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<v Speaker 6>intended to really bring experts together who have knowledge and

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<v Speaker 6>done analysis from different vantage points to see as we

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<v Speaker 6>put together the things we know, what are some of

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<v Speaker 6>the things we don't know and need to know better.

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<v Speaker 6>And so what we're really focusing on is a number

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<v Speaker 6>of different themes, including financial inclusion, what are some of

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<v Speaker 6>the implications of the innovations for access to financial services?

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<v Speaker 6>And then also what are some of the implications of

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<v Speaker 6>technological innovation for the transmission of monetary policy, for our

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<v Speaker 6>supervision and regulation of financial institutions, and also for financial stability.

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<v Speaker 6>So thinking about both the opportunities and the risks, and

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<v Speaker 6>I think we are already seeing some of those implications,

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<v Speaker 6>but it's still unfolding. It's complicated, and it's moving pretty quickly.

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<v Speaker 6>So that's what we're trying to better understand. And again

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<v Speaker 6>we're delighted that you're all here while we're in the

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<v Speaker 6>midst of a conference on an important topic.

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<v Speaker 5>Well, thank you for having us.

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<v Speaker 4>Susan Collins, the President of the Federal Reserve Bank of Boston.

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<v Speaker 5>We'll send it back to you now.

0:13:21.200 --> 0:13:23.679
<v Speaker 8>Hi, Michael McKee, thank you very much. Bloomberg's Michael McKey

0:13:23.679 --> 0:13:27.760
<v Speaker 8>speaking with Boston FED President Susan Collins here in Boston.

0:13:34.400 --> 0:13:38.240
<v Speaker 2>You're listening to the Bloomberg Surveillance podcast. Catch us Live

0:13:38.320 --> 0:13:41.640
<v Speaker 2>weekday afternoons from seven to ten am. Easter Listen on

0:13:41.679 --> 0:13:44.920
<v Speaker 2>Apple car Play and Android Auto with a Bloomberg Business app,

0:13:45.040 --> 0:13:47.360
<v Speaker 2>or watch us live on YouTube.

0:13:47.000 --> 0:13:48.360
<v Speaker 9>And commute this morning.

0:13:49.080 --> 0:13:52.040
<v Speaker 3>It's very important on radio on Apple car Play and

0:13:52.040 --> 0:13:54.920
<v Speaker 3>Andrew Auto to talk to the number one chart guy

0:13:54.920 --> 0:13:55.360
<v Speaker 3>in the world.

0:13:55.440 --> 0:13:57.640
<v Speaker 9>It really works on radio, maybe works better.

0:13:57.480 --> 0:13:59.760
<v Speaker 3>On YouTube, but we're going to be chart free this

0:13:59.840 --> 0:14:03.760
<v Speaker 3>morn with Uri and Timmer. The title is Director Global

0:14:03.840 --> 0:14:08.000
<v Speaker 3>Macro at Fidelity Management, and you can see the miracle

0:14:08.080 --> 0:14:11.280
<v Speaker 3>of this work on LinkedIn, where he's very very visible.

0:14:11.840 --> 0:14:14.720
<v Speaker 3>Urine Timmer joins us now as he gets ready for

0:14:14.760 --> 0:14:18.320
<v Speaker 3>the charts of the weekend. How do you amend your charts?

0:14:19.000 --> 0:14:22.800
<v Speaker 3>When there was a news bulletin yesterday, the Bloomberg headline

0:14:23.240 --> 0:14:28.280
<v Speaker 3>that there's seven trillion dollars in cash laying out there,

0:14:28.440 --> 0:14:30.960
<v Speaker 3>how does that affect Will dan Off? How does that

0:14:31.000 --> 0:14:32.240
<v Speaker 3>affect Uri and Timmer?

0:14:33.120 --> 0:14:36.960
<v Speaker 10>Well, so that's that's cash shitting in money market accounts.

0:14:36.960 --> 0:14:39.960
<v Speaker 10>Of course, we are the leading provider of money market

0:14:40.040 --> 0:14:43.720
<v Speaker 10>so we're intimately involved with that with that cash. But

0:14:44.120 --> 0:14:46.720
<v Speaker 10>my sense always has been that a lot of that

0:14:46.800 --> 0:14:51.040
<v Speaker 10>cash did not flee the stock market in a flight

0:14:51.080 --> 0:14:53.760
<v Speaker 10>to quality, which is kind of typically what you would expect,

0:14:53.840 --> 0:14:57.400
<v Speaker 10>and then when when people feel more comfortable, they bring

0:14:57.400 --> 0:14:59.760
<v Speaker 10>the cash back in. In this case, the cash came

0:14:59.800 --> 0:15:04.280
<v Speaker 10>out of the banks during the regional bank crisis, you

0:15:04.320 --> 0:15:07.680
<v Speaker 10>know a few years ago, when banks, you know, still

0:15:07.720 --> 0:15:10.320
<v Speaker 10>are paying half a percent on deposits, and they were then,

0:15:10.720 --> 0:15:14.280
<v Speaker 10>and the Fed was raising rates and providing alternatives. So

0:15:14.680 --> 0:15:17.760
<v Speaker 10>I don't quite see this as a powder keg of

0:15:17.800 --> 0:15:21.480
<v Speaker 10>cash waiting to chase stocks. And the metric I look

0:15:21.520 --> 0:15:24.920
<v Speaker 10>at is money market fund access assets as a percentage

0:15:24.960 --> 0:15:28.120
<v Speaker 10>of the market cap in the stock market, and there

0:15:28.240 --> 0:15:31.480
<v Speaker 10>it's more it's more normal, it's more normal. So that

0:15:31.760 --> 0:15:34.200
<v Speaker 10>money came out of the banks, my senses eventually will

0:15:34.200 --> 0:15:36.080
<v Speaker 10>go back into banks, but not necessarily stock.

0:15:36.240 --> 0:15:38.840
<v Speaker 3>We need to go into the crown jewel secrets of fidelity.

0:15:39.000 --> 0:15:41.680
<v Speaker 3>And Abby, thank you so much for listening this morning

0:15:41.680 --> 0:15:44.520
<v Speaker 3>and giving us access to mister Timmer.

0:15:45.040 --> 0:15:46.400
<v Speaker 9>I'm going to cut to the chase.

0:15:46.440 --> 0:15:51.240
<v Speaker 3>What's the elasticity I've yield in money market flows? If

0:15:51.320 --> 0:15:54.800
<v Speaker 3>yields come down two decimal points or one decimal point

0:15:55.000 --> 0:15:57.720
<v Speaker 3>or a big figure, when does Paul get out of

0:15:57.800 --> 0:15:58.880
<v Speaker 3>his money market funds?

0:15:59.800 --> 0:16:03.160
<v Speaker 10>Well, I think the FED is not going to cut

0:16:03.200 --> 0:16:07.040
<v Speaker 10>as much as many people have thought and continue to think.

0:16:07.080 --> 0:16:10.280
<v Speaker 10>So maybe it goes to four, it's at four and

0:16:10.360 --> 0:16:12.680
<v Speaker 10>five eighths. If that's the case, money market yields stay

0:16:12.760 --> 0:16:15.600
<v Speaker 10>around four or so, and I don't think that is

0:16:15.640 --> 0:16:18.520
<v Speaker 10>going to create a tsunami, you know, out of cash

0:16:18.560 --> 0:16:23.760
<v Speaker 10>into other assets, whether it's bombs or equities. So I

0:16:24.040 --> 0:16:25.920
<v Speaker 10>don't think we're going to have another sort of zerb

0:16:26.040 --> 0:16:30.240
<v Speaker 10>era where we go to zero or one and risk

0:16:30.280 --> 0:16:32.960
<v Speaker 10>premia in the bond market. Gets suppressed and then that

0:16:33.040 --> 0:16:37.000
<v Speaker 10>money flees into the risk market. So I don't think

0:16:37.000 --> 0:16:39.320
<v Speaker 10>we're going to get there, but it would be, it

0:16:39.400 --> 0:16:41.600
<v Speaker 10>would It would take you know, more than what we've

0:16:41.640 --> 0:16:42.920
<v Speaker 10>seen so far, for sure.

0:16:42.800 --> 0:16:44.360
<v Speaker 8>You're in What do you make of the move we've

0:16:44.360 --> 0:16:48.200
<v Speaker 8>seen in financial markets since the election, big move of stocks,

0:16:48.600 --> 0:16:53.240
<v Speaker 8>yields pushing higher, dollars, stronger, Bitcoin at ninety thousand per token,

0:16:54.120 --> 0:16:54.920
<v Speaker 8>What do you make of all that?

0:16:55.160 --> 0:16:58.800
<v Speaker 10>Yeah, so the markets are always in price discovery mode. Right,

0:16:58.840 --> 0:17:03.360
<v Speaker 10>Sometimes the new information comes in gradually, slowly, a company

0:17:03.440 --> 0:17:08.560
<v Speaker 10>reports earnings, the stock price adjusts, and sometimes the information

0:17:08.720 --> 0:17:11.240
<v Speaker 10>comes in all at once, as we had with the election. Right,

0:17:11.280 --> 0:17:13.760
<v Speaker 10>you can tell that people were sitting on their hands,

0:17:13.840 --> 0:17:16.240
<v Speaker 10>you know, it was supposedly too close to call, so

0:17:16.400 --> 0:17:20.439
<v Speaker 10>nothing really got done. And the market's brutally efficient in

0:17:20.640 --> 0:17:24.880
<v Speaker 10>discounting new information, and so on November sixth, it had

0:17:25.000 --> 0:17:28.840
<v Speaker 10>a lot of new information to discount, and that's what

0:17:28.840 --> 0:17:31.560
<v Speaker 10>it did. And that's what price discovery is. And so

0:17:32.200 --> 0:17:36.959
<v Speaker 10>the red wave trade right, small caps, less fed cuts

0:17:37.119 --> 0:17:42.280
<v Speaker 10>return of the term premium rotation into financials, energy industrial,

0:17:42.400 --> 0:17:43.960
<v Speaker 10>so broadening.

0:17:44.359 --> 0:17:46.280
<v Speaker 9>That is the trade.

0:17:46.320 --> 0:17:50.000
<v Speaker 10>And I think in twenty sixteen that trade was pretty

0:17:50.040 --> 0:17:53.479
<v Speaker 10>much sort of done by December, right, So it happens

0:17:53.560 --> 0:17:56.639
<v Speaker 10>very quickly. It's not like this is like the first

0:17:56.760 --> 0:18:00.560
<v Speaker 10>bat of the first inning, like it's done instantaneously.

0:18:00.640 --> 0:18:04.240
<v Speaker 3>You have portfolios of Fidelity that are over fifty percent

0:18:04.320 --> 0:18:07.520
<v Speaker 3>in their top ten stocks and they're very mag seventy.

0:18:07.200 --> 0:18:09.880
<v Speaker 9>Et cetera, et cetera. What do you see in your

0:18:10.000 --> 0:18:13.160
<v Speaker 9>chart work on the flows?

0:18:13.560 --> 0:18:17.280
<v Speaker 3>Luisja Motto would say, the distributions in and out of

0:18:17.359 --> 0:18:20.520
<v Speaker 3>MEG seven right now? Are we selling? Are we buying?

0:18:20.800 --> 0:18:22.280
<v Speaker 3>What are we doing well?

0:18:22.320 --> 0:18:25.199
<v Speaker 10>I think the good news for the MAG seven is

0:18:25.200 --> 0:18:28.040
<v Speaker 10>that they're not that expensive, right. I think I take

0:18:28.080 --> 0:18:30.000
<v Speaker 10>a broader brush. I look at the nifty to fifty,

0:18:30.080 --> 0:18:32.720
<v Speaker 10>the top fifty stocks, just because I have a data

0:18:32.720 --> 0:18:35.719
<v Speaker 10>sets all the way back to the sixties and eighteen

0:18:35.840 --> 0:18:39.240
<v Speaker 10>sixty and during the early seventies the original nifty to

0:18:39.240 --> 0:18:42.880
<v Speaker 10>fifty and the late nineties, the dot com era, those

0:18:42.920 --> 0:18:46.440
<v Speaker 10>fifty stocks were trading at twice the valuation multiple as

0:18:46.480 --> 0:18:49.840
<v Speaker 10>the bottom four fifty. Today, the top fifty are trading

0:18:49.840 --> 0:18:53.080
<v Speaker 10>at a twenty five percent premium. So you can't call

0:18:53.119 --> 0:18:55.359
<v Speaker 10>it a bubble if the valuation is not extreme. The

0:18:55.400 --> 0:18:58.080
<v Speaker 10>price movements have been extreme, but not the valuation. So

0:18:58.760 --> 0:19:01.000
<v Speaker 10>what we've seen over the past few months really since

0:19:01.040 --> 0:19:03.919
<v Speaker 10>the FED started cutting rates, is that this has been

0:19:03.920 --> 0:19:07.680
<v Speaker 10>a bullish broadening. So the market has broadened eighty percent

0:19:07.720 --> 0:19:09.960
<v Speaker 10>of stocks are above the two hundred moving average, but

0:19:10.000 --> 0:19:14.760
<v Speaker 10>it's not happening at the expense of the mega growers,

0:19:14.840 --> 0:19:17.400
<v Speaker 10>and in that sense, this cycle in a way has

0:19:17.520 --> 0:19:20.520
<v Speaker 10>kind of gone in reverse. It's like a Benjamin Button cycle,

0:19:20.560 --> 0:19:24.160
<v Speaker 10>where you know, usually a bull market starts very broad right,

0:19:24.160 --> 0:19:28.679
<v Speaker 10>because the junkie low price stocks that are obliterated in

0:19:28.720 --> 0:19:31.720
<v Speaker 10>the bear market come bouncing back, and then as the

0:19:31.760 --> 0:19:34.840
<v Speaker 10>cycle matures, it gets more narrow and the blue chips

0:19:34.840 --> 0:19:36.760
<v Speaker 10>are left standing at the end and you get those

0:19:36.800 --> 0:19:40.760
<v Speaker 10>breath divergences. This time, it's been the opposite. It started

0:19:40.760 --> 0:19:43.400
<v Speaker 10>with the Mac seven and then even during the rate

0:19:43.480 --> 0:19:46.720
<v Speaker 10>hiking cycle, those were the safe stocks to be in

0:19:46.760 --> 0:19:48.800
<v Speaker 10>because they were immune to the FED because they had

0:19:48.840 --> 0:19:53.720
<v Speaker 10>so much cash. And now they're holding their absolute performance.

0:19:54.160 --> 0:19:57.159
<v Speaker 10>But the market has broadened really since a year ago,

0:19:57.960 --> 0:20:00.360
<v Speaker 10>and so it's kind of the best that you can

0:20:00.520 --> 0:20:04.160
<v Speaker 10>hope for. Like are a more disorderly version of that

0:20:04.359 --> 0:20:07.000
<v Speaker 10>would be that the mag seven or the nifty to

0:20:07.040 --> 0:20:11.840
<v Speaker 10>fifty decline because money is moving from those stocks to

0:20:12.400 --> 0:20:14.720
<v Speaker 10>the broader market. Then the index, the S and P

0:20:15.280 --> 0:20:18.040
<v Speaker 10>would have trouble staying up just because of the weight

0:20:18.119 --> 0:20:20.840
<v Speaker 10>of those seven stocks. But we're not seeing that yet.

0:20:21.200 --> 0:20:25.040
<v Speaker 8>Your titles director of Global Macro. Where do you see

0:20:25.080 --> 0:20:27.160
<v Speaker 8>the US versus non US right now?

0:20:27.400 --> 0:20:31.000
<v Speaker 10>Well, so US, you know, excellence, you know has been

0:20:31.000 --> 0:20:34.480
<v Speaker 10>in place for a decade. And it's interesting, you know,

0:20:34.480 --> 0:20:37.120
<v Speaker 10>because we're always debating, you know, do we go outside

0:20:37.119 --> 0:20:40.080
<v Speaker 10>the US? I mean the US trading at twenty two x,

0:20:40.240 --> 0:20:43.560
<v Speaker 10>US is trading at fifteen PE, So the US is

0:20:43.600 --> 0:20:46.840
<v Speaker 10>sixty percent more expensive than the rest of the world,

0:20:46.880 --> 0:20:50.840
<v Speaker 10>whether it's em or EFA, you know, Japan, Europe. But

0:20:50.920 --> 0:20:53.879
<v Speaker 10>you need a catalyst, right, Evaluation is not alone. You

0:20:53.960 --> 0:20:56.919
<v Speaker 10>need relative earnings. Like if you go across the street

0:20:57.280 --> 0:21:00.960
<v Speaker 10>and you're in the halls of fidelity, there is price

0:21:01.000 --> 0:21:06.160
<v Speaker 10>follows earnings and relative price or relative performance follows relative earnings.

0:21:06.560 --> 0:21:09.080
<v Speaker 10>And so that is missing with between the US and

0:21:09.119 --> 0:21:11.680
<v Speaker 10>the rest of the world because US earnings continue to dominate.

0:21:11.800 --> 0:21:15.320
<v Speaker 3>Price follows earning. Sounds like Bettina Dalton nineteen eighty. Okay,

0:21:15.760 --> 0:21:19.439
<v Speaker 3>let's go there. I got an election. I got a

0:21:19.480 --> 0:21:23.480
<v Speaker 3>belief nominal GDP's gonna pop. Do you, within the research

0:21:23.480 --> 0:21:26.520
<v Speaker 3>of the fundamental animals at Fidelity and what you're doing

0:21:26.560 --> 0:21:30.840
<v Speaker 3>with charts, agree that nominal is gonna pop. Revenues are

0:21:30.840 --> 0:21:33.200
<v Speaker 3>gonna pop, and that's earnings will sustain.

0:21:33.720 --> 0:21:36.200
<v Speaker 10>Yes, So we are one year into an earning cycle.

0:21:36.520 --> 0:21:39.119
<v Speaker 10>Trailer earnings are up eight percent this year. Forward earnings

0:21:39.119 --> 0:21:42.760
<v Speaker 10>are off about twelve or so. The expectation is that

0:21:42.880 --> 0:21:45.000
<v Speaker 10>earnings will continue to grow next year. And if we

0:21:45.040 --> 0:21:47.560
<v Speaker 10>do get this nominal GDP pop and earnings are a

0:21:47.640 --> 0:21:50.760
<v Speaker 10>nominal thing, the earning cycle can continue. But the thing

0:21:50.800 --> 0:21:53.840
<v Speaker 10>I worry about is the return of the of the

0:21:53.880 --> 0:21:56.040
<v Speaker 10>fed model, you know, back in the green span in

0:21:56.160 --> 0:21:59.879
<v Speaker 10>days of the eighties. Bond yields kind of you know,

0:22:00.080 --> 0:22:04.600
<v Speaker 10>are causing indigestion again the rockvigilantes, And we've seen that

0:22:04.680 --> 0:22:07.120
<v Speaker 10>now repeatedly over the last few years, and I think

0:22:07.200 --> 0:22:09.240
<v Speaker 10>that is a risk for twenty twenty five.

0:22:09.359 --> 0:22:11.960
<v Speaker 9>You gonna be in New York soon, I will be please.

0:22:12.119 --> 0:22:14.040
<v Speaker 3>You got to come in because we got to talk

0:22:14.040 --> 0:22:16.560
<v Speaker 3>about Babson the global ranking.

0:22:16.600 --> 0:22:19.840
<v Speaker 10>They just got yes, And while while you have me

0:22:19.920 --> 0:22:22.240
<v Speaker 10>on the air, I don't know what your schedule is,

0:22:22.240 --> 0:22:24.560
<v Speaker 10>but I would be like to invite you to come

0:22:24.880 --> 0:22:26.880
<v Speaker 10>look at our chart room after the show.

0:22:26.960 --> 0:22:30.680
<v Speaker 9>Or it's like the Vatican, folks. You've got the golf

0:22:30.680 --> 0:22:33.439
<v Speaker 9>stream right, Oh, sure you can go over you're in.

0:22:33.600 --> 0:22:35.119
<v Speaker 9>I don't think I can do it. I think I

0:22:35.160 --> 0:22:36.320
<v Speaker 9>have to race to the airport.

0:22:36.400 --> 0:22:39.760
<v Speaker 3>Okay, I'm sorry, but Paul's got the golf stone, so

0:22:39.800 --> 0:22:40.520
<v Speaker 3>we'll do it next time.

0:22:40.640 --> 0:22:40.919
<v Speaker 11>You're in.

0:22:40.960 --> 0:22:43.800
<v Speaker 3>Timmor, thank you so much with Fidelity there, and we're

0:22:43.800 --> 0:22:46.480
<v Speaker 3>efforting a number of their managers as well to talk

0:22:46.520 --> 0:22:50.040
<v Speaker 3>about this spectacular year we've seen in the markets world.

0:22:50.080 --> 0:22:54.320
<v Speaker 2>This is the Bloomberg Surveillance Podcast. Listen live each weekday

0:22:54.440 --> 0:22:57.600
<v Speaker 2>starting at seven am Eastern on applecar Play and Android

0:22:57.640 --> 0:23:00.159
<v Speaker 2>Auto with the Bloomberg Business app. You can all so

0:23:00.240 --> 0:23:03.400
<v Speaker 2>listen live on Amazon Alexa from our flagship New York

0:23:03.480 --> 0:23:06.760
<v Speaker 2>station just Say Alexa playing Bloomberg eleven.

0:23:07.000 --> 0:23:11.320
<v Speaker 3>Joining us now Gotamcunda Yale University with other parchment along

0:23:11.359 --> 0:23:14.240
<v Speaker 3>the Charles River as well. He's given us such good

0:23:14.240 --> 0:23:18.119
<v Speaker 3>help here with the election. I want to talk and

0:23:18.160 --> 0:23:22.160
<v Speaker 3>this is a fancy technology seminary. Everybody here knows how

0:23:22.160 --> 0:23:24.840
<v Speaker 3>to use a cell phone a computer.

0:23:25.200 --> 0:23:27.520
<v Speaker 9>They're back. They're using Fortran here at the boss.

0:23:28.200 --> 0:23:32.399
<v Speaker 3>Okah, gout them as simple as this is a ludite

0:23:32.440 --> 0:23:37.199
<v Speaker 3>America where there's a huge in our polarization. There's a

0:23:37.280 --> 0:23:40.600
<v Speaker 3>huge body of people that just aren't in taking advantage

0:23:40.640 --> 0:23:43.720
<v Speaker 3>of technology and are almost anti technology.

0:23:44.240 --> 0:23:48.800
<v Speaker 11>I mean, I think certainly there's a huge anti technology push,

0:23:49.119 --> 0:23:51.200
<v Speaker 11>but it's striking that some of the most deleite protect

0:23:51.200 --> 0:23:52.000
<v Speaker 11>people in the world.

0:23:52.359 --> 0:23:56.960
<v Speaker 3>That's my second question. I got Elon Musk. As part

0:23:57.000 --> 0:24:03.159
<v Speaker 3>of the new administration, he defines entrepreneurship in technology, and

0:24:03.200 --> 0:24:05.640
<v Speaker 3>you got it. I got partially a ludeied America.

0:24:05.720 --> 0:24:05.920
<v Speaker 9>Yeah.

0:24:05.960 --> 0:24:08.320
<v Speaker 11>So you have sort of this icon of entrepretion technology

0:24:08.320 --> 0:24:10.520
<v Speaker 11>on the Musk, and you also have RFA Junior, possibly

0:24:10.560 --> 0:24:13.160
<v Speaker 11>the most anti science person in America, and apparently they're

0:24:13.200 --> 0:24:14.960
<v Speaker 11>going to be serving in the same administration. So it's

0:24:15.040 --> 0:24:19.800
<v Speaker 11>quite a contrast. And technology shocks, like China shocks, have

0:24:19.880 --> 0:24:22.560
<v Speaker 11>had big impacts on the labor market. We know that

0:24:22.560 --> 0:24:24.880
<v Speaker 11>they seem to be affecting people in lots of different ways.

0:24:24.920 --> 0:24:28.320
<v Speaker 11>We've seen the decrease in manufacturing employment at times, and

0:24:28.440 --> 0:24:30.320
<v Speaker 11>all of these things added up to create a level

0:24:30.320 --> 0:24:33.639
<v Speaker 11>of social ferment in this country that we're just starting

0:24:33.640 --> 0:24:36.439
<v Speaker 11>to see the implications of. But the flip side of

0:24:36.440 --> 0:24:39.640
<v Speaker 11>that is a lot of parties that have won landslide

0:24:39.760 --> 0:24:42.240
<v Speaker 11>that will won big election. So this was a decisive

0:24:42.280 --> 0:24:44.280
<v Speaker 11>victory by the Repobulmans, but not a landslide. I didn't

0:24:44.280 --> 0:24:45.960
<v Speaker 11>look anything on like two thousand and eight, for example,

0:24:47.520 --> 0:24:50.359
<v Speaker 11>had interpreted that as gigantic sweeping mandates for all of

0:24:50.400 --> 0:24:53.040
<v Speaker 11>their policies and found out that actually people were voting

0:24:53.040 --> 0:24:55.119
<v Speaker 11>on one issue and that was and in this case

0:24:55.200 --> 0:24:59.600
<v Speaker 11>almost certainly inflation. And they've then sort of leaned into

0:24:59.680 --> 0:25:03.760
<v Speaker 11>the overinterpreted their victory. How much of this anti technology

0:25:03.760 --> 0:25:05.640
<v Speaker 11>thing that you're talking about is a product of people

0:25:05.680 --> 0:25:09.840
<v Speaker 11>starting to overinterpret the victory And we don't know yet,

0:25:09.880 --> 0:25:12.960
<v Speaker 11>but it's pretty striking when we see this, and Paul.

0:25:12.840 --> 0:25:15.560
<v Speaker 3>You see this with the technology reports we see like

0:25:15.640 --> 0:25:19.320
<v Speaker 3>Apple or Microsoft or in the video, it's like two

0:25:19.359 --> 0:25:20.280
<v Speaker 3>planets it is.

0:25:20.480 --> 0:25:24.800
<v Speaker 8>It's just extraordinary. Galtem, I mean, we're these cabinet picture

0:25:24.800 --> 0:25:28.880
<v Speaker 8>coming fast and furious from President elect Trump and his campaign.

0:25:29.440 --> 0:25:30.600
<v Speaker 8>What's your takeaway so far?

0:25:30.920 --> 0:25:34.439
<v Speaker 11>So in the first century AD, the mad Roman emperor

0:25:34.480 --> 0:25:39.320
<v Speaker 11>Caligulam decided to make his horse encinitatis a console of Rome.

0:25:40.520 --> 0:25:42.680
<v Speaker 11>That horse was still a better pick than Matt Gates

0:25:42.720 --> 0:25:48.000
<v Speaker 11>Attorney general. You know, you sort of see Republicans Democrats

0:25:48.040 --> 0:25:50.960
<v Speaker 11>we expect recall, but you can see Republicans recoiling that

0:25:51.400 --> 0:25:54.080
<v Speaker 11>in general. What does not expect that the Attorney general's

0:25:54.119 --> 0:25:56.840
<v Speaker 11>closest contact with the Justice Department before they get the

0:25:56.920 --> 0:25:59.960
<v Speaker 11>job is being investigated by the Justice Department for sexual

0:26:00.480 --> 0:26:02.080
<v Speaker 11>like that. That seems out of the ordinary.

0:26:02.200 --> 0:26:04.640
<v Speaker 8>So it talk to us the role that Congress will

0:26:04.680 --> 0:26:09.760
<v Speaker 8>play in the confirmation process for some of these appointees.

0:26:09.560 --> 0:26:12.440
<v Speaker 11>As large as they choose it to be. I think

0:26:12.800 --> 0:26:14.840
<v Speaker 11>of the set of appointees, they're the sort of the

0:26:14.840 --> 0:26:18.479
<v Speaker 11>normal appointees Burtom, Marco Rubio, who are going to get

0:26:18.760 --> 0:26:20.680
<v Speaker 11>the most Democrats will vote just you know, say thank

0:26:20.720 --> 0:26:24.920
<v Speaker 11>god we got him in fine. Stephanic at the UN

0:26:24.960 --> 0:26:27.760
<v Speaker 11>will probably get something some a little like that. But

0:26:27.920 --> 0:26:30.520
<v Speaker 11>the flip side is clearly Democrats are going to go

0:26:30.560 --> 0:26:35.320
<v Speaker 11>insane over the idea of the sort of Hegseth Tulsie

0:26:35.320 --> 0:26:37.280
<v Speaker 11>Gabbard at d and I that's the one that people

0:26:37.280 --> 0:26:39.320
<v Speaker 11>in the internet, and I'll say in the in the

0:26:39.400 --> 0:26:41.720
<v Speaker 11>in the National security community. People are simply going in

0:26:41.960 --> 0:26:44.080
<v Speaker 11>like that. They don't even know how to process that prospect,

0:26:45.600 --> 0:26:48.840
<v Speaker 11>you know, or if k Junior or at HHS, I don't.

0:26:48.840 --> 0:26:51.760
<v Speaker 11>I think people don't quite realize you. HHS has a

0:26:51.960 --> 0:26:55.000
<v Speaker 11>budget of almost two trillion dollars. So the scale of

0:26:55.000 --> 0:26:58.159
<v Speaker 11>what we're talking about wowing him there is just unimaginable.

0:26:59.000 --> 0:27:00.879
<v Speaker 11>And this is someone who, when he is running for president,

0:27:00.960 --> 0:27:02.840
<v Speaker 11>proposed that one of the things he wanted to do

0:27:02.960 --> 0:27:05.919
<v Speaker 11>was just stop all research and development on you drugs. So,

0:27:05.960 --> 0:27:07.840
<v Speaker 11>I mean, you know, four years no R and D

0:27:07.920 --> 0:27:11.800
<v Speaker 11>in the life sciences. I think people could probably object

0:27:11.800 --> 0:27:12.000
<v Speaker 11>to that.

0:27:12.080 --> 0:27:15.919
<v Speaker 8>So what's the realistic of you in Washington? Just about

0:27:16.080 --> 0:27:19.600
<v Speaker 8>to what extent was some of these Republican senators in

0:27:19.640 --> 0:27:23.400
<v Speaker 8>effect go against their president by blocking some of these appointees.

0:27:25.040 --> 0:27:26.840
<v Speaker 11>I think people are starting to think not that much.

0:27:28.440 --> 0:27:31.639
<v Speaker 11>It wouldn't shock me if Gates doesn't get confirmed, just

0:27:31.680 --> 0:27:34.520
<v Speaker 11>because he's made so many enemies in the Congress that

0:27:34.560 --> 0:27:39.000
<v Speaker 11>they might there'll be a reaction. But the others, I

0:27:39.000 --> 0:27:42.160
<v Speaker 11>think the betting is that the level of patronage that

0:27:42.400 --> 0:27:44.440
<v Speaker 11>Trump has and the level of sway he has over

0:27:44.440 --> 0:27:46.919
<v Speaker 11>the party he ran ahead of all of these people, right,

0:27:46.960 --> 0:27:51.520
<v Speaker 11>he got more votes than most of these people. In Michigan,

0:27:51.760 --> 0:27:55.480
<v Speaker 11>the Democrats held the Senate seat because tens of thousands

0:27:55.520 --> 0:27:58.080
<v Speaker 11>of people came in voted for Donald Trump and left

0:27:58.080 --> 0:28:02.840
<v Speaker 11>the rest of the ballot blank, yep, and so and so.

0:28:03.280 --> 0:28:05.320
<v Speaker 8>Maybe if you're a Trump supporter, I think a lot

0:28:05.320 --> 0:28:08.760
<v Speaker 8>of those folks felt like he's doing exactly what we

0:28:08.800 --> 0:28:12.760
<v Speaker 8>wanted him to do, which is to be unconventional, you know,

0:28:12.880 --> 0:28:14.679
<v Speaker 8>kind of drain the swamp, to use a term from

0:28:14.680 --> 0:28:19.159
<v Speaker 8>the past cycle. Maybe there is public support for this.

0:28:19.359 --> 0:28:22.280
<v Speaker 11>So I think there is certainly a base of Trump

0:28:22.280 --> 0:28:24.800
<v Speaker 11>supporters for whom this is exactly what they wanted, and

0:28:24.840 --> 0:28:27.600
<v Speaker 11>this is this is sort of they're extremely enthusiastic about that.

0:28:28.359 --> 0:28:30.879
<v Speaker 11>But my strong suspicion is that base is not fifty

0:28:30.920 --> 0:28:32.399
<v Speaker 11>percent of the country, and it's not anything close to

0:28:32.480 --> 0:28:34.160
<v Speaker 11>fifty percent of the country, And there are a lot

0:28:34.160 --> 0:28:36.800
<v Speaker 11>of people who probably did not vote to find out that,

0:28:37.240 --> 0:28:39.440
<v Speaker 11>you know, we're not going to be inventing new vaccines

0:28:39.480 --> 0:28:42.440
<v Speaker 11>for the next few years. And note it's not just

0:28:42.480 --> 0:28:43.320
<v Speaker 11>a four year problem.

0:28:43.440 --> 0:28:43.520
<v Speaker 3>Right.

0:28:43.560 --> 0:28:46.440
<v Speaker 11>When you eliminate these capabilities, you can't wave a magic

0:28:46.480 --> 0:28:48.960
<v Speaker 11>want and bring them back. It takes generations to build

0:28:49.000 --> 0:28:51.440
<v Speaker 11>the sort of scientific establishment that we have, and that

0:28:51.520 --> 0:28:52.200
<v Speaker 11>is now at RESK.

0:28:52.240 --> 0:28:54.000
<v Speaker 9>This is going to be in your lectures.

0:28:54.280 --> 0:28:57.960
<v Speaker 3>Yeah, it is Tom Nichols of Naval War College, all

0:28:58.000 --> 0:29:01.080
<v Speaker 3>of his work. Three times in the last two days

0:29:01.120 --> 0:29:05.040
<v Speaker 3>people have sent me Death of Expertise Tom Nichols book

0:29:05.040 --> 0:29:08.640
<v Speaker 3>that I interviewed him four years ago, The Death of Expertise?

0:29:09.320 --> 0:29:11.160
<v Speaker 3>Is it as grim now as it's ever been?

0:29:11.560 --> 0:29:14.200
<v Speaker 11>Tom's great and I would say it might be grimmer

0:29:14.400 --> 0:29:17.400
<v Speaker 11>than even then. I think that even he expected. You know,

0:29:17.880 --> 0:29:20.520
<v Speaker 11>going into the election, you would talk to Democrats and Republicans,

0:29:20.880 --> 0:29:23.640
<v Speaker 11>and Democrats, even the ones, the ones who are really scared,

0:29:23.840 --> 0:29:26.520
<v Speaker 11>would talk about these sorts of appointments and you know,

0:29:26.560 --> 0:29:27.600
<v Speaker 11>you'd say, like, what.

0:29:27.600 --> 0:29:28.000
<v Speaker 9>Did it not do?

0:29:28.160 --> 0:29:30.880
<v Speaker 11>Get the worst case? Yeah, And Republicans would say, well,

0:29:30.960 --> 0:29:32.920
<v Speaker 11>you know, we'll just have a normal Trump, a normal

0:29:32.960 --> 0:29:35.160
<v Speaker 11>Republican administration with a guy who makes sense mean tweets.

0:29:35.640 --> 0:29:38.640
<v Speaker 11>So when you think about the spectrum of where people

0:29:38.680 --> 0:29:40.840
<v Speaker 11>thought they were going to end up, these appointments are

0:29:40.880 --> 0:29:44.240
<v Speaker 11>sort of the worst fears of Democrats, except not even that.

0:29:44.320 --> 0:29:47.880
<v Speaker 11>Nobody was saw that Matt Gate's coming. So yeah, there's

0:29:47.920 --> 0:29:52.120
<v Speaker 11>a profound death of expertise problem. But let's back out

0:29:52.120 --> 0:29:54.880
<v Speaker 11>from that. I think we we all as a society,

0:29:55.000 --> 0:29:58.040
<v Speaker 11>just haven't thought through. Let's back up for a second.

0:29:58.200 --> 0:30:00.320
<v Speaker 11>A lot of this is about new communication technology. We

0:30:00.320 --> 0:30:02.440
<v Speaker 11>talk about social media, things like that which make the

0:30:02.440 --> 0:30:04.920
<v Speaker 11>world more transparent. So we see that the experts were

0:30:04.920 --> 0:30:06.520
<v Speaker 11>never as great as they thought they as we thought

0:30:06.560 --> 0:30:08.600
<v Speaker 11>they were in their failures. That doesn't mean they're useless.

0:30:08.640 --> 0:30:13.720
<v Speaker 11>There's there're convenience stakes. When the printing press was invented, right,

0:30:14.600 --> 0:30:16.880
<v Speaker 11>the big foreign part, the big consequence of that that

0:30:17.000 --> 0:30:19.320
<v Speaker 11>historians go back is they say the Thirty Years War,

0:30:19.520 --> 0:30:22.320
<v Speaker 11>the worst war of europe history, that killed a third

0:30:22.320 --> 0:30:26.760
<v Speaker 11>of the population of Germany, was directly driven by the

0:30:26.800 --> 0:30:27.960
<v Speaker 11>event of the printing We're.

0:30:27.800 --> 0:30:30.040
<v Speaker 3>Going to continue this discussion in New York, as I'm

0:30:30.040 --> 0:30:33.640
<v Speaker 3>sure we will with got him Conda. He's with Yale University.

0:30:33.640 --> 0:30:39.960
<v Speaker 10>Here.

0:30:41.040 --> 0:30:45.320
<v Speaker 2>This is the Bloomberg Surveillance Podcast. Listen live each weekday

0:30:45.400 --> 0:30:48.600
<v Speaker 2>starting at seven am Eastern on applecar Play and Android

0:30:48.640 --> 0:30:51.560
<v Speaker 2>Auto with the Bloomberg Business app. You can also watch

0:30:51.640 --> 0:30:54.880
<v Speaker 2>us live every weekday on YouTube and always on the

0:30:54.920 --> 0:30:55.880
<v Speaker 2>Bloomberg terminal.

0:30:56.160 --> 0:31:00.520
<v Speaker 8>Dearn Morse Conference keynote speaker and professor at UC Berkeley's

0:31:00.640 --> 0:31:02.520
<v Speaker 8>up Business School out there. Thanks so much for joining

0:31:02.600 --> 0:31:05.760
<v Speaker 8>us here. You're a keynote speaker here today. What are

0:31:05.760 --> 0:31:06.720
<v Speaker 8>you going to be talking about.

0:31:07.560 --> 0:31:11.240
<v Speaker 1>I'm gonna be talking about AI and the use in credit.

0:31:11.440 --> 0:31:16.000
<v Speaker 1>So thinking about not just in understanding AI, in terms

0:31:16.040 --> 0:31:20.200
<v Speaker 1>of deploying and getting better, better precise underwriting and.

0:31:20.120 --> 0:31:22.240
<v Speaker 7>Knowing people's risk and this sort of stuff.

0:31:22.240 --> 0:31:25.840
<v Speaker 1>That there's a general landscape of using AI for all

0:31:25.920 --> 0:31:29.360
<v Speaker 1>kinds of provision of lending to people, and then there's

0:31:29.360 --> 0:31:32.640
<v Speaker 1>some red flags, right, and so kind of putting the

0:31:32.720 --> 0:31:35.440
<v Speaker 1>landscape out there, we need to think about both sides.

0:31:35.520 --> 0:31:38.520
<v Speaker 1>We need to inform not just policy makers we're here

0:31:38.560 --> 0:31:41.840
<v Speaker 1>at the FED, but also the providers, right, so they

0:31:41.880 --> 0:31:44.400
<v Speaker 1>can think about things that they need to step up

0:31:44.440 --> 0:31:45.440
<v Speaker 1>and understand.

0:31:45.720 --> 0:31:47.360
<v Speaker 8>We were back last time I was up here in Boston.

0:31:47.400 --> 0:31:49.360
<v Speaker 8>We were doing some work with the Boston Consulting Group

0:31:49.360 --> 0:31:51.400
<v Speaker 8>and they were saying, is they talked to their clients

0:31:51.440 --> 0:31:54.840
<v Speaker 8>across all industries about the use of AI. They want

0:31:54.880 --> 0:31:56.800
<v Speaker 8>to get a commitment that they will do it in

0:31:57.400 --> 0:32:00.840
<v Speaker 8>the correct way, you know, and really, because AI is

0:32:00.880 --> 0:32:03.120
<v Speaker 8>so powerful that you want to make sure that whoever

0:32:03.160 --> 0:32:05.440
<v Speaker 8>they're talking to, that they make a commitment to doing

0:32:05.440 --> 0:32:08.000
<v Speaker 8>it in the right way, the sustainable way. How does

0:32:08.040 --> 0:32:09.880
<v Speaker 8>that apply to finance?

0:32:10.440 --> 0:32:10.720
<v Speaker 7>Right?

0:32:10.800 --> 0:32:13.080
<v Speaker 1>So the problem is there's so many different aspects of

0:32:13.080 --> 0:32:14.000
<v Speaker 1>what correct means.

0:32:14.200 --> 0:32:14.400
<v Speaker 7>Right.

0:32:14.480 --> 0:32:18.640
<v Speaker 1>So if we think about AI, where where it's going

0:32:18.680 --> 0:32:21.000
<v Speaker 1>to be deployed, right, it's not just you know, it's

0:32:21.320 --> 0:32:24.120
<v Speaker 1>understanding credit risk and reaching more of the population in

0:32:24.200 --> 0:32:26.760
<v Speaker 1>ways that biases are hindering.

0:32:26.800 --> 0:32:27.480
<v Speaker 7>So that's great.

0:32:27.800 --> 0:32:33.160
<v Speaker 1>There's also targeting and marketing, there's monitoring, there's chatbots to

0:32:33.240 --> 0:32:37.120
<v Speaker 1>get information, authenticating fraud, right, all these sort of uses.

0:32:37.800 --> 0:32:41.040
<v Speaker 1>Along the other side, though, we have to think about

0:32:41.120 --> 0:32:45.120
<v Speaker 1>things like there's been research that finds it AI teaches

0:32:45.160 --> 0:32:50.120
<v Speaker 1>itself itself how to collude, right, which has all kinds

0:32:50.160 --> 0:32:53.400
<v Speaker 1>of your mind goes crazy when you start thinking about that.

0:32:53.480 --> 0:32:56.920
<v Speaker 1>And then AI can be deceptive and conveyance to get

0:32:56.960 --> 0:32:57.960
<v Speaker 1>an outcome at once.

0:32:58.040 --> 0:33:00.640
<v Speaker 9>So this is a sequel to the matrix too or something.

0:33:00.680 --> 0:33:03.880
<v Speaker 3>I mean, really, that's what reef shows up, right, right,

0:33:04.080 --> 0:33:06.520
<v Speaker 3>Paul can play Reeves. I can't play Reeves. Come on,

0:33:06.680 --> 0:33:09.800
<v Speaker 3>most of the public is scared stiff of this. Let's

0:33:09.880 --> 0:33:12.800
<v Speaker 3>begin with the timeline. Are you looking out to two

0:33:12.840 --> 0:33:15.320
<v Speaker 3>thousand and thirty or are you looking out to two

0:33:15.320 --> 0:33:16.560
<v Speaker 3>thousand and forty.

0:33:16.760 --> 0:33:19.040
<v Speaker 7>Or twenty twenty five? Right?

0:33:19.080 --> 0:33:21.440
<v Speaker 1>I mean AI is already being you Are we ready

0:33:21.440 --> 0:33:25.320
<v Speaker 1>for this? We're We're not ready, nor are the providers ready?

0:33:25.400 --> 0:33:25.560
<v Speaker 9>Right?

0:33:25.600 --> 0:33:29.440
<v Speaker 1>The providers themselves are concerned about the You know, there's

0:33:29.440 --> 0:33:32.320
<v Speaker 1>startups left and right right, and whether the startup's doing

0:33:32.360 --> 0:33:34.960
<v Speaker 1>and what inputs are we using? Do we let AI

0:33:35.440 --> 0:33:39.240
<v Speaker 1>go on all the data that's available about someone to profile?

0:33:39.280 --> 0:33:39.440
<v Speaker 9>Heay?

0:33:39.480 --> 0:33:41.440
<v Speaker 3>But do you flying to Park Avenue and you're gonna

0:33:41.440 --> 0:33:43.800
<v Speaker 3>talk to James Diamond and his team at JP Morgan.

0:33:43.920 --> 0:33:45.360
<v Speaker 9>You're gonna bring Keen Green.

0:33:45.640 --> 0:33:48.479
<v Speaker 3>Of Berkeley along just to impress everybody, and they're going

0:33:48.520 --> 0:33:51.760
<v Speaker 3>to go we need to trust this process. What's the

0:33:51.800 --> 0:33:56.080
<v Speaker 3>trust factor at this conference in Boston? To people trust AI?

0:33:56.680 --> 0:33:59.840
<v Speaker 1>I think I don't. I don't know the answer to

0:33:59.840 --> 0:34:01.680
<v Speaker 1>do they trust? I don't think they know one way

0:34:01.760 --> 0:34:04.320
<v Speaker 1>or the other. I think where we are is that

0:34:05.000 --> 0:34:09.120
<v Speaker 1>right now? If we understand what inputs AI is using,

0:34:09.160 --> 0:34:11.480
<v Speaker 1>so you can control that right where where it's going,

0:34:11.640 --> 0:34:16.200
<v Speaker 1>what information it's using to make decisions. If you control

0:34:16.320 --> 0:34:19.560
<v Speaker 1>the inputs, you're able to put a bound on what

0:34:19.680 --> 0:34:22.120
<v Speaker 1>it can do. Right, You can tell it not to lie,

0:34:22.200 --> 0:34:24.680
<v Speaker 1>you can tell it only to use these days these

0:34:24.680 --> 0:34:29.280
<v Speaker 1>certain inputs that are non discriminatory and other things. Right now,

0:34:29.360 --> 0:34:34.040
<v Speaker 1>what the how that input use is getting deployed is

0:34:34.040 --> 0:34:34.800
<v Speaker 1>a black box?

0:34:35.840 --> 0:34:41.200
<v Speaker 8>How from your research talking to providers of credit, how

0:34:41.239 --> 0:34:43.279
<v Speaker 8>are they using AI yet? Are they using AI? Or

0:34:43.320 --> 0:34:44.840
<v Speaker 8>is it still the loan officer that I got to

0:34:45.000 --> 0:34:46.320
<v Speaker 8>convince I'm a good credit.

0:34:46.440 --> 0:34:46.600
<v Speaker 7>No?

0:34:46.600 --> 0:34:49.120
<v Speaker 1>No, definitely they are using AI, right, I mean from

0:34:49.320 --> 0:34:52.400
<v Speaker 1>the you know, the simple way the chatbots right getting

0:34:52.400 --> 0:34:56.080
<v Speaker 1>information in right that that is, those are AI driven,

0:34:56.160 --> 0:35:02.680
<v Speaker 1>but also the processing and understanding under general parameters right

0:35:02.800 --> 0:35:06.320
<v Speaker 1>under you know, how would you maximize for for profitably

0:35:06.440 --> 0:35:11.000
<v Speaker 1>lending or how would you for profitably marketing new new.

0:35:10.880 --> 0:35:11.920
<v Speaker 7>Products to people?

0:35:12.239 --> 0:35:12.439
<v Speaker 8>Right?

0:35:12.480 --> 0:35:16.920
<v Speaker 1>They are using there? Are they deploying underwriting at a

0:35:16.920 --> 0:35:18.080
<v Speaker 1>full scale using AI?

0:35:18.440 --> 0:35:18.520
<v Speaker 8>No?

0:35:18.719 --> 0:35:21.160
<v Speaker 7>Probably not. There are some exceptions to that.

0:35:21.680 --> 0:35:24.839
<v Speaker 1>But but we're using it little bits here and there,

0:35:24.960 --> 0:35:27.920
<v Speaker 1>and it pretty soon the whole arena changes.

0:35:28.280 --> 0:35:33.040
<v Speaker 3>Is America behind on this or are we leading the way? Ah?

0:35:33.360 --> 0:35:35.920
<v Speaker 7>Probably leading? Leading?

0:35:36.000 --> 0:35:39.160
<v Speaker 1>Is not you know the the there are other countries

0:35:39.239 --> 0:35:41.480
<v Speaker 1>that are also deploying.

0:35:41.680 --> 0:35:42.680
<v Speaker 7>China's deploying.

0:35:43.080 --> 0:35:46.200
<v Speaker 1>There's there's a whole movement in Europe and a law

0:35:46.239 --> 0:35:49.000
<v Speaker 1>in Europe regarding some of these things, and so it's

0:35:49.719 --> 0:35:52.800
<v Speaker 1>we are ahead, but we are with others in that

0:35:52.800 --> 0:35:53.239
<v Speaker 1>that lead.

0:35:53.520 --> 0:35:55.600
<v Speaker 3>So Paul I got a credit rating of one hundred,

0:35:55.640 --> 0:35:58.480
<v Speaker 3>it's like so low. You know, they don't even talk

0:35:58.520 --> 0:36:00.799
<v Speaker 3>to me and I get email all the time. We'll

0:36:00.800 --> 0:36:03.200
<v Speaker 3>give you forty five thousand, We'll give you ten thousand.

0:36:03.560 --> 0:36:05.440
<v Speaker 3>Is that AI driven? Is it your fault?

0:36:06.880 --> 0:36:08.520
<v Speaker 7>I don't know the answer to that question.

0:36:08.680 --> 0:36:11.359
<v Speaker 1>But but that's where we are, right, that's where we

0:36:11.840 --> 0:36:15.040
<v Speaker 1>you know, there there are people that are you know,

0:36:15.080 --> 0:36:17.600
<v Speaker 1>they have credits course that maybe those credits course are

0:36:17.640 --> 0:36:21.239
<v Speaker 1>not right, and maybe AI helps right and and so,

0:36:21.440 --> 0:36:23.200
<v Speaker 1>and then there are other people that you know.

0:36:23.719 --> 0:36:27.080
<v Speaker 8>Well, here's my concern is that small community banks, they're

0:36:27.120 --> 0:36:29.360
<v Speaker 8>not going to be able to make the technology investments.

0:36:29.440 --> 0:36:31.880
<v Speaker 8>Therefore that whatever benefits may be out there, and I

0:36:31.880 --> 0:36:33.520
<v Speaker 8>don't know if there are, bye by the way, you

0:36:33.520 --> 0:36:36.120
<v Speaker 8>have to convince me. I'm afraid that they're not going

0:36:36.160 --> 0:36:38.480
<v Speaker 8>to have the same capabilities to say a JP Morgan Chase.

0:36:38.920 --> 0:36:41.799
<v Speaker 1>So I'm I'm a big fan of having a community

0:36:41.840 --> 0:36:45.759
<v Speaker 1>financial architecture. Banks, the lenders the CDFI's right, and the

0:36:45.840 --> 0:36:50.160
<v Speaker 1>reason it's so important is because in downturns, these the

0:36:50.160 --> 0:36:55.560
<v Speaker 1>research shows that these these local community facing lenders and banks,

0:36:55.920 --> 0:36:59.719
<v Speaker 1>they they're able to stick with their customers and when

0:36:59.760 --> 0:37:03.920
<v Speaker 1>they them the most. So so far, technology has not

0:37:04.040 --> 0:37:08.080
<v Speaker 1>replicated that. Now, whether AI becomes a localized lender because

0:37:08.120 --> 0:37:10.680
<v Speaker 1>its ability to act local is a question.

0:37:10.520 --> 0:37:11.080
<v Speaker 7>We don't know.

0:37:12.120 --> 0:37:15.160
<v Speaker 1>And how what does that mean for the financial architecture

0:37:15.160 --> 0:37:17.080
<v Speaker 1>of the United States is a complete unknown.

0:37:17.360 --> 0:37:18.480
<v Speaker 8>So I mean, at the end of the day, if

0:37:18.480 --> 0:37:21.600
<v Speaker 8>I'm providing credit, I want to just I want a

0:37:21.640 --> 0:37:24.239
<v Speaker 8>good credit environment where I get paid back, where I'm

0:37:24.280 --> 0:37:28.000
<v Speaker 8>able to diverse, you know, distribute you know, debt into

0:37:28.040 --> 0:37:30.200
<v Speaker 8>my marketplace. But I want to get paid back. I

0:37:30.239 --> 0:37:33.520
<v Speaker 8>don't want to take undw credit risk. Ideally AI will

0:37:33.560 --> 0:37:34.600
<v Speaker 8>help me do that better.

0:37:35.239 --> 0:37:38.120
<v Speaker 1>Ideally it will help you do that better, and also

0:37:37.920 --> 0:37:41.200
<v Speaker 1>to manage new products and new services for customers to

0:37:41.239 --> 0:37:44.719
<v Speaker 1>figure out where they might be exposed to risk or

0:37:44.760 --> 0:37:47.320
<v Speaker 1>where they might be evolving in their business or household.

0:37:47.560 --> 0:37:50.960
<v Speaker 3>Thirty second question, We don't enough time. It's unfair Type

0:37:50.960 --> 0:37:55.000
<v Speaker 3>one Type two construct. Is AI in banking going to

0:37:55.080 --> 0:37:57.680
<v Speaker 3>help banks or help them not lose money.

0:37:58.600 --> 0:38:00.799
<v Speaker 7>It's going to help them grow their business.

0:38:01.640 --> 0:38:03.160
<v Speaker 8>That's kind of what they want to that's what they

0:38:03.160 --> 0:38:04.560
<v Speaker 8>want to hear at. Dear Morse, thank you so much

0:38:04.640 --> 0:38:05.200
<v Speaker 8>for joining us.

0:38:05.440 --> 0:38:05.960
<v Speaker 5>A deare Moorese.

0:38:05.960 --> 0:38:09.640
<v Speaker 8>She's professor of finance at the University of California at Berkeley.

0:38:10.000 --> 0:38:14.440
<v Speaker 2>This is the Bloomberg Surveillance podcast, available on Apple, Spotify,

0:38:14.600 --> 0:38:18.720
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0:38:18.840 --> 0:38:21.880
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0:38:25.840 --> 0:38:29.120
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0:38:29.280 --> 0:38:30.840
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