WHEN: Today, Thursday, May 10th
WHERE: CNBC's Capital Exchange event in Washington D.C.
Following is the unofficial transcript of CNBC's Kayla Tausche's sit down interview with Catherine Bessant, Bank of America Chief Operations and Technology Officer, today at CNBC's Capital Exchange event in Washington D.C.
All references must be sourced to CNBC's Capital Exchange.
TYLER MATHISEN: So-- our first guest-- is-- the-- chief technology officer, chief-- operations person at Bank of America, Catherine Bessant. And she will be interviewed-- by my friend and colleague in our Washington Bureau, Kayla Tausche. So please welcome our first guest to the stage, Catherine and Kayla. Welcome. Good to see you.
KAYLA TAUSCHE: Good to see you. Thank you, Tyler.
TYLER MATHISEN: All right. Good. Hi, Cathy--
KAYLA TAUSCHE: And thank you to CNBC and Nasdaq for having us today.
CATHERINE BESSANT: --good to see you.
TYLER MATHISEN: Good to see you.
KAYLA TAUSCHE: And for all of you, for-- getting up and joining us for this conversation. We're gonna be taking questions-- should you have them, at some point toward the end of the conversation. So be thinking-- during our chat about what you'd like to ask Cathy. Because, as you just said to me a few moments ago, we can ask you anything.
CATHERINE BESSANT: Ask me anything.
TYLER MATHISEN: All right. Here we go.
KAYLA TAUSCHE: I would say, thank you for starting your day with us. But I know it started few hours ago. Tell us a little bit about why you're in Washington and-- what you hope to accomplish with meetings that you have today at the White House.
CATHERINE BESSANT: Sure. Well, first of all, I think the discussion here -- is a really important one. So being engaged in this was-- was a big driver for being here. I'm looking forward to a rich dialogue as the day goes on. In the last couple of weeks the White House, as everybody knows, has put together a conference on artificial intelligence. And so being in the middle of the mix of that dialogue is very important to us as a firm-- and to me as a technologist. So-- so-- you know, and people keep asking me, "What do you expect to come out of it?" And I'm not sure I know the-- the precise answer to that. I think a good conversation around workforce, a good conversation about competitiveness, regulation-- and-- and really how we drive-- our thinking about the-- the pros and-- and unintent-- potential unintended consequences, I hope is a part of the dialogue.
KAYLA TAUSCHE: So why is Bank of America part of that dialogue? 'Cause when we think about technology, we think about artificial intelligence, we think of the major technology players based in Silicon Valley. What do you add to that?
CATHERINE BESSANT: Well we are, as everybody knows, as financial institutions, big producers of and consumers of data. And we have lots of-- important and very sensitive data about our customers, and our clients, and-- and how they bank, and what their financial needs and interests are-- as well as about everything from-- from how they invest, to the movement of money. So we-- we have very rich data. We use it to try to-- ensure that we are capable of meeting customers' needs. So we try to be very analytical about how we approach the marketplace-- with internal uses of data. And we run a huge workforce. On my technology and operations workforce I have 95,000 people, 35 countries. And how we transform a workforce to be ready for what the next generation of technology, or many would argue-- the generation that's already here, how we prepare that workforce is extremely important. Additionally, there isn't an quarter that goes by where any motivated company doesn't talk about-- about productivity. And to a group of people that run technology and operations, productivity, or technological advancement causes them to wonder about their jobs. So workforce is not just a future issue for us, it's an issue of how do we balance the transformation that's needed with keeping people motivated, and engaged, and confident in the future so that they produce for clients and customers in a brilliant way today.
KAYLA TAUSCHE: We normally think about technological innovation at a bank as disrupting the bank teller, or the traditional services that a bank offers. The movement of money. What else is happening within that workforce of 95,000 people that might not be visible to the naked eye?
CATHERINE BESSANT: We're doing a lot of work-- and technology holds-- a tremendous-- or plays a tremendous role in our risk management effort. Our capital and liquidity-- analysis, and--
KAYLA TAUSCHE: In what way?
CATHERINE BESSANT: --predictive capabilities.
KAYLA TAUSCHE: Tell me how risk management benefits from technology.
CATHERINE BESSANT: Sure. Well we can look at data points across all of our customer activity, across macro-economic trends, and say, "Here's what we predict, in terms of potential cycles. Here are sectors where we believe we should double down in terms of credit extension, or market activity. Here are sectors where we maybe wanna be more conservative right now." So I think the predictive benefit-- in the-- in a lot of-- places that-- that we heard from Nasdaq about. Predictive benefit is huge. And we do an immense amount of modeling. I think the other place where it plays that people may not see every day is in how we manage our liquidity and our balance sheet so that we can-- take advantage of and create competitive advantage around the way we manage what's on our side of the balance sheet, so that in a razor thin margin business, with interest rates notionally low, and we agree with everyone else that's a positive. But at low notional interest rates, you know, the margins that are available in banking-- make us-- make us envious of grocery stores. And when I was coming up in the business, the-- the one place where it was tough to do business as a banker was in grocery stores. 'Cause the margins are razor thin. Well we're jealous of that in banking. So how we manage every dollar that's-- that is within our system is very important. And we use technology every day to do that.
KAYLA TAUSCHE: Are your predictions panning out? Is there enough data to know whether the intelligence and the technology is working?
CATHERINE BESSANT: There is. We-- we do an extensive amount of testing. We call it back testing. So we can take the technology of today, use the data of a previous cycle, and-- and make sure that it would have accurately predicted what actually happened. So back testing helps us a lot. We're smart enough to build in the right margins of error, and the right checkpoints and milestones along the way. So it's not-- it is not the abandonment of human judgement into technology. It's the use of technology to create the data and the analytics to make great judgements by humans possible.
KAYLA TAUSCHE: We use to think of Fintech as a specific slice of small companies that were innovating. But someone told me recently, they said, "Fintech is basically anyone who has money and has a computer." How do you-- how do you-- how do you deal with that perception-- that Fintech is its own sort of niche industry, and not something that's happening across the board?
CATHERINE BESSANT: Well I'd say Silicon Valley Fintech is its own niche industry. And-- and four years ago, five years ago, I used to say that-- that as a bank, Bank of America had to be a Fintech company. Or even would go so far as to say we were a Fintech company. I-- I've come off that a great deal. Because there's a huge difference between-- a financial institution, or a large corporation, and a Fintech company. We're highly regulated. We do not have any room-- hence my previous discussion. We don't have any room for fail fast, fail big, fail often. You know, the-- the innovations that we do have to come to market in a reasonable la-- high likelihood of success. And there are lots of other-- you know, we have to report quarterly earnings. We've got-- we don't have patient venture capital, or even impatient venture capital that-- that comprises our balance sheet. We have, you know, 10 billion shares outstanding. So-- so that doesn't mean, though, that we don't have to be innovative. And so we do two things. We create this notion where-- innovation is everyone's job. And you can say, oh, well hah hah, that's funny. It's-- you know, that means it's no one's job. But in reality, we generate an immense amount of intellectual property. We-- we are the-- the financial institution with the most patents-- highest ranking on the U.S. Patent Office list. So we do prove out with 4,500 or something in-- in ventures that we have-- a capability to make innovation everyone's job. We also create pockets in the firm whose job is to either innovate themselves, or to find emerging technology firms so that we can create that thin slice that you-- that you suggest. We-- we can-- we have the scale to do it both--
KAYLA TAUSCHE: But because--
CATHERINE BESSANT: --both ways.
KAYLA TAUSCHE: --you have such a slim margin for error in you're-- shall I say, too big to fail, in-- in that way, would it make sense, then, for you to acquire technologies rather than developing them from within?
CATHERINE BESSANT: Well we do do both. And-- to your point-- success is on a world stage, if possible. And failure with 60 million U.S. households that touch us in some way, the potential-- we simply can't take the risk of failure at scale. So-- we're very difficult. Difficult, really by design, for Fintech companies to do business with because we have to be to protect our customers and-- and-- and what they do. So we test extensively. We test to make sure companies can move at scale. We watch very carefully the financial stability of the companies we do business with. We deliberately don't create single points of failure with-- with smaller firms. That said, if you go back-- if you stay, "Okay, fine, difficult by design," that said, we do business with a lot of Fintech firms. And you would find that when we do find that secret sauce, our scale and capital can put a small Fintech company that otherwise might have VC money, but not a world stage for delivery of their capabilities. We have the opportunity for them to have a world stage.
KAYLA TAUSCHE: When you say you don't create single points of failure with small firms, what does that mean?
CATHERINE BESSANT: Well we-- look along each process. I'll be-- I'll sound like an operations-- geek to you right now. But we look at every point in the process where we either do-- buy s-- that-- where we either buy something, or build it internally, and make sure that there's no place where we are singularly dependent. So if I'm trying to move a payment from A to B, and there are 16 steps in that process, and we use a vendor in four of them, how do we ensure that not only do we have the plan-- the Plan A that operates flawlessly, literally, the-- the-- the stakes of operation-- have to be flawless. How do we make sure they f-- operate flawlessly every day, but that there's also a viable Plan B? So that if they were not to function, we know exactly what we'd do.
KAYLA TAUSCHE: How do you think about cyber security in the year 2018?
CATHERINE BESSANT: Pretty much every single second of every single day. It-- really it's the-- it-- technology is interesting. Cyber puts the technology discussion in the boardroom. You know-- being cutting edge is important. But a cyber failure can cost a CEO their job. So the-- the-- the stakes of the discussion have really changed over the last five years. We thi-- we tend to think about it-- along a continuum that in its simplest terms says, "How are we prepared? How do we anticipate and understand the threats? How do we make sure that we can-- detect and mitigate any potential attacks?" And we see thousands of them every single day. And then how do we make sure that-- that what we do technologically, and how we have talent, that we have-- we say it pretty simply to the board, best tech, best talent. And so we do not constrain our talent by resources. If we believe we need it, we spend it. And if we-- and we ensure that we have the best and the brightest in what they like to think of as on the wall every day. It's-- it's-- it has to be really technologically sophisticated. But when you spend time with a cyber technologist, they're making judgements by the second. So I w-- I never discount-- in fact, I-- I think it's the most-- that talent's the most impart-- important part of that work.
KAYLA TAUSCHE: When you think about-- all of those attempted attacks, thousands, or hundreds of thousands in a given day, of course what we only see is the tip of the iceberg. But whose fault is that? Is there someone at the government level? Or someone at the-- at the intergovernmental level that should be working harder, or spending more money to thwart those bad actors?
CATHERINE BESSANT: I think that with the ubiquity of networks, as they exist today, I don't know that I believe that there is an ability to thwart the attackers. I think that in order to be accessible the-- the-- the way that we want to be accessible to clients and customers, and the way they demand-- us to be (NOISE) accessible-- that-- the risk of cyber comes naturally or inherently with that.
KAYLA TAUSCHE: I do think that we are challenged by the lack of a legal or judicial framework around cyber. Or the lack of an-- of a liability attribution model. In its simplest terms, if we have a bank robber who's coming into one of our branches and they want to take money, it's very clear who the good guy is and who the bad guy is. And there's an entire legal system to prevent it from happening, but also to prosecute-- in the event of-- that kind of-- of theft. In the area of theft of data, or theft of the ability to operate and do business, so-- the-- the creation of disruption, oftentimes the hacker, or the person who causes the leak and steal-- steals the data are considered heroic. You know, we put Julian Assange on the cover of a magazine and call him Person of the Year. And yet WikiLeaks is in the business of stealing data. So-- I do think it's-- it's-- that's-- that's at the cultural or conceptual level. Try to get cyber insurance, and to-- to create an attribution model. Which is inherent in the provision of insurance. But really rough to say, "You get atta-- an attack that looks like one country. Is it that country or another country? If it's nation state, is there a way to assign liability?" If it's an error on the part of a programmer, is it that programmer or the institution? These are very tough questions-- that-- that require answers. It's one of the reasons we try to be at the forefront of these discussions. Because-- we're not messing around with-- with data that is inconsequential. We're-- as we said earlier, we're in the business of the most fundamental-- fundamentally important data people have.
KAYLA TAUSCHE: With 95,000 employees, how do you make sure there's not a bad actor--
CATHERINE BESSANT: I'm sure there are.
KAYLA TAUSCHE: --among one of them?
CATHERINE BESSANT: I'm sure there is a bad actor. The law of statistics. That's-- a big, big problem for my people, as I'm a statistics freak. But the law of statistics would say that not every person employed by any large organization is a good person. So we do an extensive amount of work to make sure we hire properly. But then an extensive amount of work to make sure we monitor movement, monitor structured and unstructured data. So we monitor communications. We look at behavioral mon-- analytics, so we know who's doing things that are on the edge of what would normally be expected. And we operate with a swift and severe consequence model for people who violate our data or information-- our information policies.
KAYLA TAUSCHE: From the spectrum of a couple hundred bucks being siphoned from someone's account to Julian Assange leaking data, to, you know, a nation state taking down another country's power grid-- what is the riskiest scenario that you see as possible right now that you are trying to help prevent against?
CATHERINE BESSANT: They are-- they all point to-- the conversation that we have at the board level is-- there's-- it's one thing to speculate on the source. They all, though, drive to the same outcome. Which is either loss of data, m-- movement of money, or-- or business interruption. So it's one of those three things. And-- there-- while there-- they all may be equally devastating, the loss of money is what has to be protected against the most.
KAYLA TAUSCHE: Do we have any questions from the audience? We'll open it up briefly, if there are any. We do have a couple. We'll go right here first.
WALTER WHITE: Walter White, with Verizon Communications. I'd be curious-- crypto currency, blockchain technology, I think they're kinda different subjects. What is your-- I think blockchain is real. Crypto currency, probably another thing I'd like your opinion on that.
CATHERINE BESSANT: Yeah. I think of it three ways. There's the asset class of crypto currency, the potential investment, or speculation vehicle. And to-- to us, that's an individual investment decision. So-- so there is one aspect of-- of that. And it's your-- all about your appetite for volatility, or your belief that there's an underlying-- source of value supporting that particular asset class. The second way we think about it is as a currency. As a money to pay or receive-- to be paid or received. And to us, that's an anathema that goes completely against what financial institutions are all about. The-- the entire system is based on transparency of sender and receiver. That we know who is sending, and know who is receiving. That we can look at behavior and look at money patterns to detect-- people doing illegal activities. I mean, we are accountable, under more than you could count-- regulatory regimes, to be able to assist law enforcement in understanding the flow of money. And so crypto currency, blind on the sender, blind on the receiver, designed to be that way, goes completely against that. It shouldn't surprise us that ransomware is usually ransomed for Bitcoin. The person who kidnapped the software doesn't want you to know who they are. And that-- that's possible. Now, I'm with you. Blockchain-- distributed ledger technology, holds a ton of potential to make business better, to make us more cost effective, to be faster for customers and clients. The challenge is-- today I would characterize it as largely a theoretical set of capabilities. The number of commercial use cases are very limited. We are actively driving for those use cases. So we've got 70 patents either applied for or received that use blockchain, or distributed ledger technology. But the piloting that all of us are doing together-- in the private sector and public sector, the piloting hasn't yet produced something that works at scale, or that-- that we can market across a variety of industries or business opportunities. So it's a great technology, and we've got to find the right business use for it. But it's real. I'm-- I'm totally where you are.
KAYLA TAUSCHE: Are there questions on this side of the room? I think I saw a couple over here. Peter?
PETER COOK: Peter Cook, with the American Bankers Association. You-- announced recently—a partnership with Harvard's Belfer Center on the study of AI, ethical, technological issues. What does Bank of America hope to get out of that specifically. And is it specific to banking? Or does it go beyond that?
CATHERINE BESSANT: The council will go beyond banking. It-- in fact, its beauty has to be that it's multi-sector. Because this is-- the-- the issues we're talking about here, workforce transformation being the top one-- at-- top of mind for me right this second, those are multi-sector issues. The gap between the skills we will need, and the skill availability in the marketplace, no one-- industry sector can solve that alone. So it's-- one of its-- points of beauty is that it will be multi-sector. We wanna get two or three things out of this. 1) I think it's time to rebalance the conversation between the sellers or artificial intelligence and the users of artificial intelligence. We are all sold the notion that artificial intelligence is better than humans, when reality, it's a subset of humans. It's only as good as we can program it to be. And getting that balance right between the intended consequences of a seller and the responsibility for the unintended consequences of a user, that is bigtime important. So-- so rebalancing that conversation from the glitz to the use, I think, is very important. And then we really hope to get-- work around-- it'll sound lofty, but a societal framework for literally the responsible use of AI. A company that can state its business strategy, as we can, in two words (responsible growth), it shouldn't surprise you that we expect AI to be a big source of growth and opportunity, but its responsible use is important. And there's another rebalancing that needs to happen, which is not just focus on the opportunity at hand, but to focus on minimizing in advance of experiencing them, the unintended consequences. To me, the debate is not about what we can do. Machines can do a lot. And machines are ahead of us in-- in understanding-- the implications of what can happen.
KAYLA TAUSCHE: I know that's a conversation that you will likely be having across the street here, across the park here-- a little bit later today. I'm curious how you view the White House's approach to technology. Because we did get-- the resignation of the cyber security director. And reports that they are going to dissolve the cyber security unit. How do you see the White House dealing with technological threats in this day and age?
CATHERINE BESSANT: Well, first of all, they-- the-- there's no question government has to play a huge role. There's expertise and experience there that doesn't exist anywhere else in the world be-- if for no other reason than we've been in the defense business for so long, and defense is a huge target for-- for-- for artificial intelligence used for good or for evil-- just to frame it up that way. So-- I also don't think there are ever enough hands on deck. And-- and so the administration, whether it's in one particular unit, or across the range of-- of parts of the administration that-- that-- that can be involved in this discussion, there-- we have to have all the smart people that we can have-- in the mix. And there is a public policy element of this, and as I said earlier, a legal, and judicial, and regulatory framework, that if we don't own it, if the-- if our government doesn't own it, in effect, they're the only potentially agnostic player in the game. I have one perspective. I promise you, I like to say it's agnostic. But it really reflects the needs of our customers, and the needs of my company. True of the providers and producers of data and AI. And so-- the government has to play an important role. I tend not to draw conclusions from an individual announcement, or an individual happening. But across the broad spectrum, we need them.
KAYLA TAUSCHE: Finally-- ten years after the financial crisis, there are efforts underway to loosen some of the regulations that were put in place at a time when companies are innovating more than ever. Do you feel that there's a risk that we are still Monday morning quarterbacking the financial crisis and not thwarting future potential risks?
CATHERINE BESSANT: We did a lot to earn the additional regulation that we got as a result of the financial crisis. We did a lot to earn it. And we're very humble about that. And I think it's-- it-- the empirical evidence, and our-- my own company's sense of this, and belief about this, is there's no question that the financial system is stronger than it was pre-crisis. And a lot-- a fair amount of that has to do with high quality regulation that simply ensures that we are better capitalized, with more liquidity, and better plans for what would happen in the crisis. I think the question becomes have we gotten to those outcomes with efficiency in administration of those rules? So I don't-- I don't-- we wouldn't characterize it as a loosening. We might characterize it as-- an administrative relook at whether or not all of the complexity that goes into those regulations is warranted. And I think that there's a lot of po-- a lot of positive conversation going on about tiering the-- the complexity of the regulatory regime by size of company, or by-- extent of risk. Obviously as-- as a hu-- large-- bank, super large bank, we wouldn't expect-- the outcomes or the risk management element of those rules to be lessened. I mean, as I said, we believe they produced a lot of good. But when your capital submission is 18,000 pages long, and you're excited because that's down from 23,000 last year, we've got a r-- we've got room to maneuver between getting the right outcome and-- and not being burdensome.
KAYLA TAUSCHE: You're helping the legal industry return to growth though. That's for sure. Cathy, we're out of time today.
CATHERINE BESSANT: Kayla, thank you.
KAYLA TAUSCHE: But we appreciate yours.
CATHERINE BESSANT: Great to see you.
KAYLA TAUSCHE: Thank you so much.
CATHERINE BESSANT: Thank you.
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