In Good Company with Nicolai Tangen - HIGHLIGHTS: Brian Moynihan - CEO of Bank of America

Starting point is 00:00:00 Hi, everybody. Tune in to this short version of the podcast, which we do every Friday. For the long version, tune in on Wednesdays. Hi, everybody. I'm Nicola Tangian, the CEO of the Norwegian sovereign wealth fund. And today I'm thrilled to have Brian Moynihan with us. Brian is the chairman and CEO of Bank of America, one of the world-largest financial institutions. And we own one and a half percent of this great company. Brian has led the bank for 15 years, steering it through the aftermath of the financial crisis.

Starting point is 00:00:30 and transformed it into a digital powerhouse. So, Brian, wonderful to have you here. That's great to be here. Brian, you sit on the top of one of the world largest banks. What's happening in the world? Well, I think there's a little bit of bifurcation between what's happening in various segments of the world, but you can add it all up to the world. But I think largely what's being driven now is the United States change in this policy

Starting point is 00:00:52 towards from an economic basis, leave aside a geopolitical basis. But an economic basis, a major change going on, is that, you know, U.S. has changed with respect to four policies, trade tariff type policies, immigration policies, this is more domestic in the U.S., but the taxation, budget policy, and then deregulation. And you're seeing that play out in the U.S. and obviously as a world's large economy in the biggest trading partner with most countries, you're seeing that impact around the world as we go through that change in a set of policies with the new Trump administration. Have you any private kind of secret indicators that you are particularly keen on that nobody else is really looking at?

Starting point is 00:01:34 Well, if you look at the American consumer, the discussion of public domain was as consumer confidence factors, you know, went down after a liberation day, April 2nd and went back up, all the back and forth. What we did solve was no change in activity. So how, what are we talking about? The Bank of America consumers, 70 million, will send out. out of their accounts about four, four and a half trillion dollars this year into the economy. Year to date, it's almost two trillion because we're almost halfway through the year. If you look at that, it's up about four and a half to five percent of the first part of 25 versus the first part of 24. If you look at the month of June, four, four and a half percent, when you look at that

Starting point is 00:02:17 amount of money going in the economy, that means the American consumers participating heavily. When you look at their balances and accounts, stable to growing, bouncing around, you know, the core consumer kind of stable in the higher-end consumer money wind into the money market funds and other instruments are in interest, but the amount of cash they have is actually at record highs. And so they're in pretty good shape. Unemployment's 4.2% or whatever. The prospects for being unemployed are relatively low. So you put that aside, and then you have to balance that against what consumers are saying

Starting point is 00:02:47 they're feeling, which is negative due to all the change and all the activity going on, meaning what's that mean? That means the TARIFT. That means immigration. That means the reading at the economy is slowing down. And so what we see is the U.S. consumer is doing pretty well. We look at small, mini-sized businesses. Are you, Brian, are you surprised that the consumer is doing so well?

Starting point is 00:03:06 No. Given an answer to it. And it comes down to, Nicola, the thing people miss is if the unemployment level is 4.1 in the U.S., which is 100 basis points per full employment, number one. And number two, wage growth is actually exceeding inflation in the aggregate across the period of time. Now, it ebbs and flows. inflation came first and wage growth cut up to it, and now they're running more in sync. Is it the level of rates, which is the main concern for the business clients, or is it other types of uncertainty, do you think?

Starting point is 00:03:38 Well, our survey of small business customers over the last year has shown different elements. First, it was rates and inflation because that was preoccupied. And then it shifted back to workers. and why I say back to workers, it was at that during the great resignation a couple of years ago in the United States. And what they're saying is the inability to get enough employees that can do the jobs that they have. That is being exacerbated by a lot of discussion you hear from them about the impact of inflation. And if you're in construction in all its related parts, you're a cement company, you're a delivery company, your construction actually building

Starting point is 00:04:14 the buildings, the impact of the immigration policy is causing people not to show up. If you're in the hotel and leisure farming, it's impacting you. And so I think in the broad-based employees, that's why you're hearing the administration saying, we've got to sort this out to make sure people know they're going to have the workers to be successful, and being agriculture and travel and entertainment and other types of industries. Because it's not that the activity is affecting a lot of them. It's the worry about the activity that's going to affect them that causes the workers not to come. So they went from being all about inflation and all about rates to wait, I can't.

Starting point is 00:04:50 can't get the workers again and can I get those workers? So everything is on their mind, but uncertainty about some of these topics is critical to them. How will AI transform the bank? It's already started. So it's going to transform the bank around a couple of dimensions that are different, and it's just started an artist. First, it enables you to have replaced human interaction to human interaction.

Starting point is 00:05:19 Second, it replaces your, it helps you analyze what we call text-to-text. In other words, big amounts of information, how do you pull them together and have them come out the other side? So somebody then can take that and utilize it differently. It also can help you with testing and checking things. We file, you know, literally millions and millions of reports a day and it helps you not only prepare those, but more importantly to test those to make sure they're accurate and and helps you find out ways to improve them.

Starting point is 00:05:49 So, you know, if you're back and it helps us in computer coding, we're already using it, 18,000 plus programmers already use it and stuff. So let me give a very concrete, straightforward example. So this product, this technique we called Erica. So Erica is the way a consumer can have a virtual assistant of Bank of America. You're hearing a lot about agent bots and all that stuff. We've had this now for five, seven, eight years. We started about 10, 12 years ago, and what we had them develop is we looked at the search

Starting point is 00:06:22 technology, and it just wasn't going to work in financial services. So we had them develop a new natural language processing predictive model, which today we call a small language model. Back then, nobody would have called it that because it was a different world. We had them build that for us, and then we used it and trained on our own data, and then it can answer questions. And now 20 million Bank of America customers use. Erica each quarter, about 200 million times to ask questions that it can answer.

Starting point is 00:06:49 Now, Erica has a lot of room to go in refinements and improvements and doing it, but we know it works. And those 200 million interactions would have been a phone call, a text or an email, or walking into the branch. So 200 million times a quarter, we're moving. We're heavy digitalized already. We have 50 billion consumer interactions a year, so it's a massive amount of activity. It's heavy digitalized.

Starting point is 00:07:11 but the room to go to digitalize it more with AI is different with machine learning and other types of models we had. And Erica shows us that bridge. So, Brian, you became CEO in 2010 after the financial crisis. What's the toughest decision you made during your tenure in the bank? Well, the toughest decisions all ran around how we got through the aftermath of financial crisis and how we had to be so resolute on results. resolving issues. So we had a quarter where, you know, we several lawsuits, the $20 billion

Starting point is 00:07:48 lawsuit, et cetera, you know, those are tough decisions. It wasn't necessarily the financial decision. That was tough enough. But it was the people in vacations of deciding to take a completely different position in the mortgage business. And, you know, from company it was doing one in five mortgages, we had to go down to where we got to 5% share because what we were doing was not directly with consumers. Those are hard decisions could they affect the people's lives and our ability and had to retrain a whole brain power in the company. All the decisions that are toughest are about people, you know, and disrupting other people's lives.

Starting point is 00:08:22 So downsizing people, changing people. And that's why we frankly have worked very hard to do headcount management to avoid layoffs. And we've been pretty good at the last 10, 15 years. In the early days, we had to do some layoffs. And to me, that's a toughest decision because you're basically walking to somebody who was a great work or worked for the company and say, you know what, we just can't use you anymore. And that's going to our A.A.

Starting point is 00:08:43 Conversations, why we're managing headcount so carefully and trying to figure out how to make sure that we aren't over-staffing and then having to take people out. The other tough decision... Do you tell anybody yourself or is a delegated to other people? Oh, I never started a process like this unless I'm willing to change the people who work for me. So actually, ironically, in the first downsizing we did as a financial crisis,

Starting point is 00:09:09 I lost my job. And it was before I was CEO. I was running integration, and I decided that one of the positions they had to eliminate was mine. And I was almost down the company, and they offered me a different job when I stayed. So I believe resolutely that you have to start from the top. This is not a bottoms up thing. What are the biggest reasons for failure that you are trying to avoid? I think, A, complacency, B, you get stuck in bureaucracy and progress, a large company.

Starting point is 00:09:36 How do you break through that? see you don't get ahead or get ahead of a trend. And this is where AI is kind of interesting is we've got to utilize this and drive it. But if you get too far ahead, you can bet the company in a way that may not work. And so that's, you know, and those are the source of failure people who get too far ahead of a trend or don't keep up with a trend. And or don't keep the brand fresh. You don't think they're doing well when they're not doing well. And I'm willing to poke it and ask questions.

Starting point is 00:10:03 So while CEO always has to be optimistic, you know, in the heat of the night, you have to be very sort of, what are we doing wrong? What can we do better all the time? But you have to make sure you translate that into action into process so it gets done.

In Good Company with Nicolai Tangen - HIGHLIGHTS: Brian Moynihan - CEO of Bank of America

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