WEBVTT - Broadcasting Live from SmarshCONNECT Event

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<v Speaker 1>Bloomberg Audio Studios, Podcasts, radio news. This is Bloomberg Business

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<v Speaker 1>Wait inside from the reporters and editors who bring you

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<v Speaker 1>America's most trusted business magazine, plus global business, finance and

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<v Speaker 1>tech news. The Bloomberg Business Week Podcast with Carol Messer

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<v Speaker 1>and Tim Stenebeck from Bloomberg Radio.

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<v Speaker 2>Steve Marsh is with us, a chairman and founder of

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<v Speaker 2>Smash and joining us here on site. First of all,

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<v Speaker 2>compliance is a big issue, and it has been growing,

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<v Speaker 2>I think, coming off the Great Financial Crisis, and I

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<v Speaker 2>think it's interesting to hear how people are talking about

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<v Speaker 2>it in regards to AI. But first of all, take

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<v Speaker 2>a step back twenty years ago when you started your

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<v Speaker 2>company and kind of where we were.

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<v Speaker 3>Sure, so there's probably two thousand and one, I think

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<v Speaker 3>when I first started Smash, and so twenty three years

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<v Speaker 3>well then, so yeah, the time flies, but yeah, really,

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<v Speaker 3>I was doing some insulting for financial services firms and

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<v Speaker 3>had a few of them all around the same time

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<v Speaker 3>asked me to help them comply with what were then

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<v Speaker 3>relatively new rules and requirements forcing them to capture their email.

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<v Speaker 3>So it was really just email that was a problem,

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<v Speaker 3>and most organizations just needed to find a way to

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<v Speaker 3>retain it so that the compliance departments could produce it

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<v Speaker 3>when a regular came asking for it, and I helped

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<v Speaker 3>a few of them do it and eventually found that

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<v Speaker 3>there was a bigger and bigger business opportunity. And that's

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<v Speaker 3>how it all started.

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<v Speaker 4>What was the way that you were able to do

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<v Speaker 4>it back then that other people weren't doing. What was

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<v Speaker 4>the value add that you brought that the industry wasn't

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<v Speaker 4>saying yet?

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<v Speaker 3>I think the biggest value add was that I had

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<v Speaker 3>come from the financial services industry, and a lot of

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<v Speaker 3>my competitors at the time, and there were quite a

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<v Speaker 3>few were really web hosting companies or internet service providers

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<v Speaker 3>that thought they would just get into the email retention

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<v Speaker 3>space and sell an additional product. We were very different

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<v Speaker 3>from day one, only focusing on broker dealers and and

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<v Speaker 3>investment advisors and really understanding the regulatory requirements that they

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<v Speaker 3>had to comply with. That gave a lot of the

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<v Speaker 3>companies that we worked with much more comfort that when

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<v Speaker 3>a regulator came knocking on their door, we would understand

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<v Speaker 3>exactly what needed to be done, the step thing to

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<v Speaker 3>be taking the proof of you know, the steps that

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<v Speaker 3>we're taking or that were taken and helping them retain

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<v Speaker 3>their their compliance.

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<v Speaker 2>It's interesting, Steve, if you think about it, right, like,

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<v Speaker 2>in terms of where communications were twenty three.

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<v Speaker 5>Years ago and how they have evolved.

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<v Speaker 2>We communicate and then you know, layer on the pandemic

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<v Speaker 2>on top of it, things have gotten much more complicated.

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<v Speaker 2>How has that changed your business and what you guys do?

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<v Speaker 6>Well?

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<v Speaker 3>Early on, you know, as you alluded to, it was

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<v Speaker 3>really just email that companies needed to deal with, and

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<v Speaker 3>then eventually it was AOL and SIT messenger and of

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<v Speaker 3>course Bloomberg's messaging protocols as well.

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<v Speaker 6>So you know, over the.

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<v Speaker 3>Last two decades, that list of relatively few communication channels

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<v Speaker 3>has exploded to now include well over one hundred and

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<v Speaker 3>hundred and fifty different types of communication, and some of

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<v Speaker 3>the largest organizations that we serve we'll have you know,

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<v Speaker 3>dozens fifty one hundred different types of communication. So that

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<v Speaker 3>has created a lot of opportunity for us to up

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<v Speaker 3>new products and new solutions to help our customers, but

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<v Speaker 3>it also creates a lot of challenges for those that

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<v Speaker 3>have to to work with them.

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<v Speaker 2>I always think about in COVID, right we were talking

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<v Speaker 2>about you know, in terms of spreading the virus, like

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<v Speaker 2>the touch points, and I just think about in terms

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<v Speaker 2>of the financial community, the touch points as information is

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<v Speaker 2>shared and moved around, they have increased and that means

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<v Speaker 2>greater risk potentially absolutely.

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<v Speaker 3>I mean you have to you have to look at

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<v Speaker 3>all those different endpoints you have. You may follow a

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<v Speaker 3>conversation that starts on text message and then moves to

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<v Speaker 3>email and then is picked up later on WhatsApp or

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<v Speaker 3>you know, some other communication channel. If you don't have,

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<v Speaker 3>you know, a good sense of what's happening in your organization,

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<v Speaker 3>you're not going to be able to follow the entire conversation.

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<v Speaker 3>It's not single thread anymore. It's not just taking place

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<v Speaker 3>in one venue.

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<v Speaker 6>Okay.

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<v Speaker 4>So a big issue with the SEC has been so

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<v Speaker 4>called disappearing message services. How do you guys deal with that?

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<v Speaker 3>Well, there are certain ones that were designed specifically not

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<v Speaker 3>to be captured and retained. There are others that you know,

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<v Speaker 3>we can help with from a technology standpoint. You know,

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<v Speaker 3>if something is specifically designed not to be viewed in mind,

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<v Speaker 3>and I think that that's where policy comes in for

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<v Speaker 3>most organizations. Right wherever possible, we develop different mechanisms of

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<v Speaker 3>capturing the messages so that they can be sort of archive.

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<v Speaker 4>What if you're working with an organization where okay, yes,

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<v Speaker 4>my work accounts are ones that can be captured, but

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<v Speaker 4>a lot of my communication happens over my personal devices

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<v Speaker 4>or my personal services.

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<v Speaker 3>How does that work? Again, it's kind of nuance. It

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<v Speaker 3>depends on the communication channel. Some of the early social

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<v Speaker 3>networks introduced that very problem, where with Facebook, for example,

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<v Speaker 3>you only had a personal profile if you were also

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<v Speaker 3>using it for work, well, that meant that the organization

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<v Speaker 3>had to effectively retain your personal communications and you had

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<v Speaker 3>to authorize them or you know, acknowledge that you were

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<v Speaker 3>going to use something like Facebook for personal and business

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<v Speaker 3>communications and you'd give the firm basically the ability to

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<v Speaker 3>capture them.

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<v Speaker 6>You know.

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<v Speaker 2>One of the things I love about that we kind

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<v Speaker 2>of try and do at Bloomberg, and I think we

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<v Speaker 2>do it pretty well, is just kind of open windows

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<v Speaker 2>into worlds that maybe people don't know about, but is

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<v Speaker 2>just such a big part of our world. And we

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<v Speaker 2>did it today with an earlier story had to do

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<v Speaker 2>with roans and so on and so forth. But I

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<v Speaker 2>think about this is such a part of the financial world,

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<v Speaker 2>you know, and kind of reading in tim and I,

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<v Speaker 2>you know, I think nineteen of the world's largest twenty

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<v Speaker 2>banks are your clients. Like, this is something that every

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<v Speaker 2>financial institution is involved in a big way and has

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<v Speaker 2>to be absolutely in terms of what you do in

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<v Speaker 2>the services you provide.

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<v Speaker 3>Yeah, it's not always the most well known service, you know,

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<v Speaker 3>among the public, but every broker dealer, investment advisor, or bank,

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<v Speaker 3>you know, hedge fund, you know, really has some regulations

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<v Speaker 3>they need to comply within where they're often behind the

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<v Speaker 3>scenes or behind the scenes as one of their most

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<v Speaker 3>critical partners.

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<v Speaker 5>Is it getting more complicated?

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<v Speaker 2>And I think about with financial disruption, and I think about,

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<v Speaker 2>you know, layer kind of what we've seen in cryptocurrency,

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<v Speaker 2>and I don't know the financial industry, it's just like

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<v Speaker 2>more and more things are being thrown at them in

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<v Speaker 2>different ways. And I always think about is a regulatory

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<v Speaker 2>oversight and the systems in place to kind of keep

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<v Speaker 2>up with it.

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<v Speaker 3>It definitely gets more and more challenging, and I think,

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<v Speaker 3>you know, over the past two decades, it's gotten to

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<v Speaker 3>the point where the compliance function is probably one of

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<v Speaker 3>the most sophisticated within a financial services organization. I certainly

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<v Speaker 3>don't envy some of the professionals that have to deal

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<v Speaker 3>with other aspects of compliance, you know that's marsh doesn't

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<v Speaker 3>even really touch or play in, you know. So it's

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<v Speaker 3>a challenging job and it's a significant area of focus

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<v Speaker 3>for the financial industry.

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<v Speaker 4>One thing that's so interesting about what you do is

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<v Speaker 4>you have so many different clients, you have so many

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<v Speaker 4>touch points on the economy. And one thing that I'm

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<v Speaker 4>interested in is here we are in twenty twenty four

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<v Speaker 4>where it's sort of like if we were doing this

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<v Speaker 4>a year ago, the question would be, Okay, when's the recession?

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<v Speaker 4>But the economy it seems like it is firing on

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<v Speaker 4>all cylinders right now. What are you hearing and certainly

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<v Speaker 4>that's what the economic data is indicating to us. What

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<v Speaker 4>are you hearing from your customers right now when you're

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<v Speaker 4>talking to them about different products, different services when it

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<v Speaker 4>comes to how they're doings of how they're doing, yeah,

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<v Speaker 4>how they're doing.

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<v Speaker 2>Because it like you wonder do they pick and choose

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<v Speaker 2>and say, I mean compliance they have to do, but

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<v Speaker 2>do they pick and choose a little bit because they're

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<v Speaker 2>a little bit worried about the account the outcome, or

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<v Speaker 2>do you never see that.

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<v Speaker 3>I mean, most of the conversations we have are more

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<v Speaker 3>specifically related to their compliance and technology challenges, the types

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<v Speaker 3>of communication tools they're using, you know it. Maybe we'll

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<v Speaker 3>see a little bit in terms of how they're they're

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<v Speaker 3>expanding or contracting the organization, right not even really we

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<v Speaker 3>don't know always have a great sense of that either.

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<v Speaker 3>So as far as like their views on the economy

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<v Speaker 3>and what's happening globally, and we don't get too much

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<v Speaker 3>of that. It's more, uh, it's more focused on compliance.

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<v Speaker 2>Does crypto come up? How does does crypto come into

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<v Speaker 2>your world?

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<v Speaker 5>As well?

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<v Speaker 3>It does? And I think there was quite a bit

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<v Speaker 3>of buzz about it, especially a year and a half

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<v Speaker 3>two years ago, about you know, how crypto was going

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<v Speaker 3>to be regulated and really for us, you know, what

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<v Speaker 3>what is Marsh's role, what in what are our client's

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<v Speaker 3>role in that. I would say it's not the biggest issue,

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<v Speaker 3>you know, but it's still in the background.

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<v Speaker 5>There.

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<v Speaker 3>There's a lot more discussion today about artificial intelligence and

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<v Speaker 3>how how it should be regulated and how it can

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<v Speaker 3>be used to help with you know, communication, you know,

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<v Speaker 3>monitor and surveillance.

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<v Speaker 2>I mean, we're gonna have a bunch of conversations about that.

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<v Speaker 2>How are you guys preparing for it? I know we're

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<v Speaker 2>gonna have some some future conversations that are going to

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<v Speaker 2>dig a little bit deeper into it, But how are

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<v Speaker 2>you guys getting ready for it? Or how have you

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<v Speaker 2>been planning around it? What are your clients saying, Pea, Steve,

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<v Speaker 2>are you working on this?

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<v Speaker 3>Yeah, we've We've had an aspect of artificial intelligence as

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<v Speaker 3>part of our services for many years, and really it's

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<v Speaker 3>to address the reality that the data volumes just are

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<v Speaker 3>growing constantly, so our customers are faced with a challenge

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<v Speaker 3>where they have to sift through not only growing number

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<v Speaker 3>of communication channels, but the number of messages that are sent,

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<v Speaker 3>you know, within each of those has grown exponentially. And

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<v Speaker 3>it used to be that human beings could inspect and

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<v Speaker 3>look at the messages that we would get flagged for

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<v Speaker 3>some sort of potential compliance violation. Now it's becoming increasingly difficult.

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<v Speaker 3>So the use of artificial intelligence helps them manage that workload.

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<v Speaker 3>So that that's probably the biggest use case in the

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<v Speaker 3>biggest area that we hear about. But there's also certainly

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<v Speaker 3>a discussion about how firms need to think about their

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<v Speaker 3>own use of artificial intelligence, and if that if that

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<v Speaker 3>becomes a communication itself that needs to be archived and monitored,

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<v Speaker 3>or or if they have you know, a bot on

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<v Speaker 3>their website that's communicating with investors, you know, how does

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<v Speaker 3>that fit into the compliance obligation?

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<v Speaker 2>I didn't even think about that, like monitoring the bot right,

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<v Speaker 2>Like it's going to be part of it.

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<v Speaker 4>Who monitors the bot? That's monitoring the bot?

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<v Speaker 5>That's the question?

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<v Speaker 3>Another bot?

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<v Speaker 4>Yeah, okay, okay? So what about when it comes to

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<v Speaker 4>the AI, are you deploying the AI or is the

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<v Speaker 4>AI being deployed by these companies internally?

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<v Speaker 6>Uh?

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<v Speaker 3>For the surveillance, Yeah, and monitoring. We help the customers

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<v Speaker 3>deploy that, but it's with their own They are their

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<v Speaker 3>own input in terms of what they want to look

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<v Speaker 3>for and what they're they're trying to use it for.

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<v Speaker 4>Have you had to make specific hires around that type

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<v Speaker 4>of technology that in this environment?

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<v Speaker 7>Many?

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<v Speaker 3>So?

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<v Speaker 4>How is that? Because I mean it's like a serious

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<v Speaker 4>talent we're going on.

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<v Speaker 3>Yeah, And I think we've we've been very fortunate that

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<v Speaker 3>our that our use cases is interesting. I think to

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<v Speaker 3>the professionals that get to work get to work on

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<v Speaker 3>artificial intelligence. We've got very large data stores, you know,

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<v Speaker 3>high significance use cases to get people excited, so it's

0:10:10.920 --> 0:10:15.160
<v Speaker 3>always been relatively easy to find high quality tech talent.

0:10:15.200 --> 0:10:18.600
<v Speaker 3>It's mart just because we've got high security use cases,

0:10:18.600 --> 0:10:21.640
<v Speaker 3>big data, always on the cutting edge of the communication

0:10:21.679 --> 0:10:23.600
<v Speaker 3>tools that people want to use, so.

0:10:23.559 --> 0:10:24.480
<v Speaker 5>They want to be a part of it.

0:10:24.840 --> 0:10:27.800
<v Speaker 2>I'm just thinking about the Bloomberg audience, investing audience, just

0:10:27.800 --> 0:10:29.920
<v Speaker 2>people who want to know on trends and waves. Just

0:10:29.960 --> 0:10:32.560
<v Speaker 2>got about a minute or forty five fifty seconds left here.

0:10:33.040 --> 0:10:34.440
<v Speaker 2>What do you think they need to know about? Kind

0:10:34.440 --> 0:10:36.520
<v Speaker 2>of the world that you're seeing and smartsh connect Like

0:10:36.679 --> 0:10:39.680
<v Speaker 2>the leaders that are here, whether it's AI, compliance technology,

0:10:39.760 --> 0:10:41.000
<v Speaker 2>what do you think they need to be aware of?

0:10:41.280 --> 0:10:42.880
<v Speaker 3>I think they need to be aware that we are

0:10:43.000 --> 0:10:44.960
<v Speaker 3>working as hard as we can every single day to

0:10:45.000 --> 0:10:49.560
<v Speaker 3>make sure that our clients can continue to use the

0:10:49.559 --> 0:10:51.960
<v Speaker 3>communication tools that they want to which in essence, is

0:10:52.000 --> 0:10:55.439
<v Speaker 3>really just allowing investors to use the communication tools they

0:10:55.480 --> 0:10:58.520
<v Speaker 3>want to use when they engage with their financial professional.

0:10:59.360 --> 0:11:02.679
<v Speaker 3>Sounds like a real, relatively simple order, but it's a

0:11:02.800 --> 0:11:04.480
<v Speaker 3>it's a it's a big ass because there are so

0:11:04.520 --> 0:11:06.520
<v Speaker 3>many different ways if people want to communicate and everybody

0:11:06.559 --> 0:11:08.959
<v Speaker 3>has their own unique preferences. We're out there working with

0:11:09.920 --> 0:11:11.720
<v Speaker 3>you know, our partners and our employees to try to

0:11:11.720 --> 0:11:12.520
<v Speaker 3>make that all possible.

0:11:12.520 --> 0:11:15.439
<v Speaker 2>Well, we talk about transparency, right, or making sure that

0:11:15.480 --> 0:11:17.520
<v Speaker 2>financial systems are fluid and they work really well. Like

0:11:17.559 --> 0:11:18.800
<v Speaker 2>this is a part of it, right. It's kind of

0:11:18.800 --> 0:11:20.520
<v Speaker 2>a cog in the in the wheel, if you will,

0:11:20.559 --> 0:11:21.360
<v Speaker 2>in terms of doing so.

0:11:21.920 --> 0:11:23.360
<v Speaker 5>Thanks so much. Thanks for inviting us here.

0:11:24.040 --> 0:11:25.680
<v Speaker 4>Really cool stuff and I'm glad you could join us.

0:11:25.720 --> 0:11:27.720
<v Speaker 2>Yeah, it's really fun to be here. We would like

0:11:27.760 --> 0:11:29.120
<v Speaker 2>to be outside though, it's really beautiful.

0:11:29.400 --> 0:11:31.640
<v Speaker 4>Can we work next sure, next year, we'll do it outside.

0:11:32.120 --> 0:11:32.520
<v Speaker 5>Just kidding.

0:11:32.559 --> 0:11:35.520
<v Speaker 2>Steve Steve Smarsh of course, he's founder and chairman of Smarts.

0:11:35.520 --> 0:11:37.840
<v Speaker 2>So we are here at smash Connect in midtown Manhattan.

0:11:37.880 --> 0:11:39.760
<v Speaker 2>I'm Carol Masser along with Tim Stanevik. Life here on

0:11:39.800 --> 0:11:42.959
<v Speaker 2>Bloomberg Business Week. Conversations are continuing. We're going to talk

0:11:43.000 --> 0:11:46.480
<v Speaker 2>more about digital transformation and the role of all of

0:11:46.520 --> 0:11:49.160
<v Speaker 2>it in compliance and managing risk for firms. We're coming

0:11:49.200 --> 0:11:50.840
<v Speaker 2>back right here on Bloomberg Business Week.

0:11:53.160 --> 0:11:56.719
<v Speaker 1>You're listening to the Bloomberg Business Week podcast. Catch us

0:11:56.720 --> 0:11:59.840
<v Speaker 1>live weekday afternoons from two to five pm Eastern list

0:12:00.080 --> 0:12:02.680
<v Speaker 1>on applecar Play and and Broud Auto with a Bloomberg

0:12:02.760 --> 0:12:07.360
<v Speaker 1>Business app, or watch us live on YouTube.

0:12:08.240 --> 0:12:11.320
<v Speaker 4>Well, what is Capital One, Bank, Loomy, the London Stock

0:12:11.400 --> 0:12:15.640
<v Speaker 4>Exchange Group, NUMBERA, MasterCard and HSBC all have in common? Well,

0:12:15.640 --> 0:12:18.800
<v Speaker 4>they're all financial services firms that use Amazon Web Services,

0:12:18.800 --> 0:12:21.720
<v Speaker 4>also known as AWS. Our next guest knows that because

0:12:21.760 --> 0:12:24.480
<v Speaker 4>he leads the worldwide business and market development efforts for

0:12:24.600 --> 0:12:27.679
<v Speaker 4>financial services at AWS, having also been an executive director

0:12:27.679 --> 0:12:31.040
<v Speaker 4>at JP Morgan Chase, also working at NASDAQ, bear Stearns

0:12:31.240 --> 0:12:34.320
<v Speaker 4>and City. John Kain is head of financial Services market

0:12:34.360 --> 0:12:37.440
<v Speaker 4>Development at AWS, and he joins us on location here

0:12:37.480 --> 0:12:39.480
<v Speaker 4>at smash Connect. John, how are you good?

0:12:39.559 --> 0:12:40.400
<v Speaker 6>Thanks? Hey?

0:12:40.440 --> 0:12:42.720
<v Speaker 4>How's how's business right now?

0:12:43.040 --> 0:12:46.240
<v Speaker 7>That's pretty good. It's hard to imagine. We're actually in

0:12:46.280 --> 0:12:50.280
<v Speaker 7>the second decade of cloud adoption in financial services, and

0:12:50.360 --> 0:12:52.839
<v Speaker 7>some of the things when I joined AWS seven years

0:12:52.880 --> 0:12:55.640
<v Speaker 7>ago that we wouldn't have thought were possible at all

0:12:55.800 --> 0:12:57.400
<v Speaker 7>to kind of run in the cloud from a financial

0:12:57.400 --> 0:13:01.480
<v Speaker 7>services infrastructure perspective are almost becoming sort of everyday story.

0:13:01.600 --> 0:13:04.080
<v Speaker 4>Did you not think it was possible because of regulatory issues?

0:13:04.320 --> 0:13:05.920
<v Speaker 7>That was one of the big concerns when we had

0:13:05.920 --> 0:13:08.839
<v Speaker 7>those initial conversations from customers earlier in the day, it's like,

0:13:08.880 --> 0:13:11.360
<v Speaker 7>how would our regulators think about cloud? About security? What

0:13:11.360 --> 0:13:14.559
<v Speaker 7>about compliance and resilience? And over the course of the

0:13:14.640 --> 0:13:18.079
<v Speaker 7>last decade, you've seen some of the most important systems

0:13:18.240 --> 0:13:20.760
<v Speaker 7>actually move and run on the cloud. Was two years

0:13:20.760 --> 0:13:24.400
<v Speaker 7>ago that Nasdaq moved its matching engine onto AWS Technology

0:13:24.720 --> 0:13:28.000
<v Speaker 7>runs MREX their Options exchanged. Last year, the SEC gave

0:13:28.040 --> 0:13:31.560
<v Speaker 7>a no objection letter to the Options Clearing Corporation to

0:13:31.600 --> 0:13:34.000
<v Speaker 7>move their risk and settlement systems to the cloud. And

0:13:34.040 --> 0:13:36.080
<v Speaker 7>those are the type of crown jewels in the industry

0:13:36.160 --> 0:13:39.440
<v Speaker 7>that you are always aspire to run. And I think

0:13:39.440 --> 0:13:41.320
<v Speaker 7>that was a twinkle in our eyes when we started

0:13:41.400 --> 0:13:44.520
<v Speaker 7>on the financial services side of ABS, and now it's

0:13:44.559 --> 0:13:46.560
<v Speaker 7>sort of the reality of what we're bringing to the industry.

0:13:46.679 --> 0:13:48.679
<v Speaker 2>I mean safe to say, John, when we break down

0:13:48.720 --> 0:13:51.480
<v Speaker 2>like Amazon earnings, we talked about AWS. It's like streaming, right,

0:13:51.520 --> 0:13:53.680
<v Speaker 2>and we're talking about the cloud. And I think so

0:13:53.800 --> 0:13:56.200
<v Speaker 2>much of general consumers that's what they think about. How

0:13:56.240 --> 0:13:58.040
<v Speaker 2>much of what you do in the cloud is financial

0:13:58.080 --> 0:13:58.840
<v Speaker 2>services based?

0:13:59.000 --> 0:14:01.600
<v Speaker 7>Well, for me it's a hundred percent, right, Yeah, But

0:14:01.920 --> 0:14:04.480
<v Speaker 7>for AWS, it's a large chunk of your business. We

0:14:04.480 --> 0:14:07.720
<v Speaker 7>don't break down the individual segment, but financial services is

0:14:07.760 --> 0:14:10.079
<v Speaker 7>just one of the largest consumers of technology, as you

0:14:10.080 --> 0:14:13.080
<v Speaker 7>can imagine, of course, and just because so much of

0:14:13.120 --> 0:14:15.160
<v Speaker 7>what they do is just moving one than the Euros

0:14:15.200 --> 0:14:18.840
<v Speaker 7>and data around. Almost everything is dependent on technology, and

0:14:18.880 --> 0:14:21.480
<v Speaker 7>when we look at where our customers are focused, it's

0:14:21.520 --> 0:14:27.360
<v Speaker 7>bringing more personalized experience with less friction and bringing down

0:14:28.720 --> 0:14:31.480
<v Speaker 7>the kind of costs across the industry.

0:14:31.640 --> 0:14:33.520
<v Speaker 4>I just want to jump in with a red headline

0:14:33.520 --> 0:14:36.480
<v Speaker 4>crossing the Bloomberg terminal has to do with Boeing. The

0:14:36.520 --> 0:14:40.440
<v Speaker 4>Boeing whistleblower is set to testify an April seventeenth Senate hearing.

0:14:40.800 --> 0:14:44.360
<v Speaker 4>That Boeing hearing has been confirmed by a spokesperson for

0:14:44.720 --> 0:14:48.000
<v Speaker 4>Center Blumenthal checking in on shares of Boeing right now

0:14:48.360 --> 0:14:52.640
<v Speaker 4>in the after hours. Shares of Boeing right now moving well,

0:14:52.800 --> 0:14:55.240
<v Speaker 4>really unchanged as we speak, but did fall about one

0:14:55.280 --> 0:14:55.960
<v Speaker 4>percentage right.

0:14:55.960 --> 0:14:57.960
<v Speaker 2>We had some news earlier today in terms of Boeing

0:14:57.960 --> 0:14:59.400
<v Speaker 2>deliveries getting.

0:14:59.160 --> 0:15:00.760
<v Speaker 4>Back there on percent today.

0:15:00.760 --> 0:15:02.280
<v Speaker 5>Excuse me, all right, good to know, JOHNKM.

0:15:02.280 --> 0:15:04.360
<v Speaker 2>We're talking with the head of Financial Services Market Development

0:15:04.400 --> 0:15:07.720
<v Speaker 2>over at AWS what are like some of the top

0:15:07.760 --> 0:15:09.800
<v Speaker 2>priorities that clients come to you and say, here's what

0:15:09.800 --> 0:15:11.280
<v Speaker 2>we need to make sure that you know we're going

0:15:11.320 --> 0:15:13.440
<v Speaker 2>to play with you in your cloud, in the in

0:15:13.480 --> 0:15:16.880
<v Speaker 2>the Amazon Cloud or AWS, and just what is top

0:15:16.920 --> 0:15:19.280
<v Speaker 2>of mind for them in terms of security and risk

0:15:19.320 --> 0:15:20.000
<v Speaker 2>and compliance.

0:15:20.640 --> 0:15:23.360
<v Speaker 7>So I think it's that's the secondary concern. If we

0:15:23.360 --> 0:15:26.920
<v Speaker 7>think about sort of why firms adopt cloud first, it's

0:15:26.960 --> 0:15:29.640
<v Speaker 7>to change the business dynamic. Right. It moves them from

0:15:29.760 --> 0:15:32.680
<v Speaker 7>having to make three and five year capital investments to

0:15:32.720 --> 0:15:34.800
<v Speaker 7>be able to buy what they need when they need it,

0:15:34.840 --> 0:15:37.000
<v Speaker 7>only pay for it. And when you think about.

0:15:36.800 --> 0:15:39.640
<v Speaker 5>Like the desert versus on premise enterprise exactly.

0:15:39.400 --> 0:15:42.640
<v Speaker 7>And when you think about something like mortgage refinancing, right,

0:15:42.960 --> 0:15:45.720
<v Speaker 7>being able to tie your business costs to the volume

0:15:45.720 --> 0:15:47.840
<v Speaker 7>of business you do as opposed to an investment you

0:15:47.840 --> 0:15:49.720
<v Speaker 7>made three years ago, it allows you to be more

0:15:49.800 --> 0:15:52.720
<v Speaker 7>dynamic from a product and services perspective, right, So it

0:15:52.800 --> 0:15:55.600
<v Speaker 7>changes the way you think about your business. But security

0:15:55.600 --> 0:15:58.200
<v Speaker 7>and operational resilience are table stakes for us to be

0:15:58.240 --> 0:16:02.040
<v Speaker 7>successful in the industry. Right, primary focus above all else

0:16:02.120 --> 0:16:05.240
<v Speaker 7>is making sure our customers are secure and their data secure,

0:16:05.520 --> 0:16:08.240
<v Speaker 7>and that our systems are running as close to perfect

0:16:08.240 --> 0:16:09.400
<v Speaker 7>as possibly can be, but.

0:16:09.360 --> 0:16:10.960
<v Speaker 4>It also means that you guys are taking on that

0:16:11.000 --> 0:16:11.760
<v Speaker 4>capex risk.

0:16:12.160 --> 0:16:12.400
<v Speaker 6>Yeah.

0:16:12.440 --> 0:16:15.040
<v Speaker 7>Absolutely. One of the benefits though, kind of being at

0:16:15.040 --> 0:16:17.240
<v Speaker 7>our scale and our approach to the business is the

0:16:17.320 --> 0:16:19.480
<v Speaker 7>larger you are, the more you have that ability to

0:16:19.560 --> 0:16:23.160
<v Speaker 7>kind of work demands across industry segments and they offset

0:16:23.200 --> 0:16:24.760
<v Speaker 7>each other. And if you're very much thinking about from

0:16:24.800 --> 0:16:27.160
<v Speaker 7>a financial services perspective, it's a little bit like what

0:16:27.240 --> 0:16:29.480
<v Speaker 7>a clearing house or clearing broker brings to the table.

0:16:29.600 --> 0:16:32.120
<v Speaker 7>If they have some customers or long positions, some customers short,

0:16:32.280 --> 0:16:35.320
<v Speaker 7>they can manage that risk better than any one participant can.

0:16:35.480 --> 0:16:37.920
<v Speaker 7>And from a technology perspective, we take advantage of that

0:16:38.000 --> 0:16:39.760
<v Speaker 7>kind of scale to be able to do the same

0:16:39.800 --> 0:16:40.960
<v Speaker 7>thing on behalf of our customers.

0:16:41.080 --> 0:16:43.800
<v Speaker 2>Is Jenai Generative AI changing any of that, because you know,

0:16:43.840 --> 0:16:46.600
<v Speaker 2>we've been having discussions kind of back in our newsroom

0:16:46.640 --> 0:16:48.920
<v Speaker 2>about the on premise enterprise and whether or not they're

0:16:49.000 --> 0:16:51.800
<v Speaker 2>going to be companies, whether it's financial or otherwise that

0:16:52.040 --> 0:16:53.640
<v Speaker 2>are going to do kind of a hybrid approach and

0:16:53.680 --> 0:16:56.640
<v Speaker 2>want to have some facilities on site that maybe there

0:16:56.680 --> 0:16:58.760
<v Speaker 2>is some data information or processing that they want to

0:16:58.840 --> 0:17:01.040
<v Speaker 2>keep kind of closer to home versus tapping the cloud,

0:17:01.040 --> 0:17:03.480
<v Speaker 2>and I'm curious how that is impacting your discussions you

0:17:03.480 --> 0:17:04.399
<v Speaker 2>guys are having around that.

0:17:04.560 --> 0:17:06.600
<v Speaker 7>Yeah, I think in a different way. So almost all

0:17:06.600 --> 0:17:09.280
<v Speaker 7>our customers start on premises, and we have to work

0:17:09.280 --> 0:17:11.680
<v Speaker 7>with them from a hybrid perspective to help them take

0:17:11.680 --> 0:17:13.480
<v Speaker 7>advantage of the cloud, and we want to make that

0:17:13.560 --> 0:17:17.199
<v Speaker 7>infrastructural is transparent to their existing infrastructure as possible. I

0:17:17.200 --> 0:17:19.679
<v Speaker 7>think Jenaia that accelerates the move to the cloud as

0:17:19.720 --> 0:17:21.679
<v Speaker 7>opposed to kind of keeps it on prem When you

0:17:21.720 --> 0:17:25.520
<v Speaker 7>think about the sheer computing power necessary to drive these

0:17:25.560 --> 0:17:29.480
<v Speaker 7>foundational models to kind of see that expertise, it's beyond

0:17:29.560 --> 0:17:31.680
<v Speaker 7>the ability for most firms to be able to make

0:17:31.680 --> 0:17:33.880
<v Speaker 7>that investment. Right, when you think about the risk you're

0:17:33.920 --> 0:17:36.840
<v Speaker 7>taking to buy that much specialized compute at scale to

0:17:36.880 --> 0:17:39.639
<v Speaker 7>train essentially almost all of human knowledge to kind of

0:17:39.680 --> 0:17:42.320
<v Speaker 7>build on these models, you can't take that risk on

0:17:42.359 --> 0:17:44.600
<v Speaker 7>as an individual enterprise. You've got to figure out how

0:17:44.600 --> 0:17:47.879
<v Speaker 7>to leverage kind of best of breed providers, and we

0:17:47.920 --> 0:17:49.760
<v Speaker 7>have the ability to kind of invest enough in our

0:17:49.800 --> 0:17:53.200
<v Speaker 7>infrastructure to specialize it so it works both at scale

0:17:53.240 --> 0:17:54.959
<v Speaker 7>and at a lower price point. We even build our

0:17:54.960 --> 0:17:57.960
<v Speaker 7>own silicon chips to actually make those things more efficient.

0:17:58.240 --> 0:18:02.000
<v Speaker 7>So we see, especially in the generative AI space, that

0:18:02.200 --> 0:18:04.639
<v Speaker 7>need to leverage the cloud to both be successful in

0:18:04.720 --> 0:18:07.320
<v Speaker 7>building new foundation models, but more importantly, how most of

0:18:07.320 --> 0:18:09.040
<v Speaker 7>our customers are actually going to take advantage of it.

0:18:09.280 --> 0:18:11.560
<v Speaker 7>They're going to use one of the existing foundational models

0:18:11.600 --> 0:18:13.760
<v Speaker 7>that are out there from an anthropic or kind of

0:18:14.119 --> 0:18:16.639
<v Speaker 7>a meta or coher and want to use it themselves,

0:18:16.720 --> 0:18:18.600
<v Speaker 7>and we want to make that available, and we want

0:18:18.600 --> 0:18:20.600
<v Speaker 7>it so they could use it right away, right, So

0:18:20.640 --> 0:18:22.720
<v Speaker 7>they're not going, hey, how do I build out a

0:18:22.760 --> 0:18:26.080
<v Speaker 7>technology plan, how do I findinance this? With macfo, It's like,

0:18:26.119 --> 0:18:28.399
<v Speaker 7>oh great, we can go try this right, and we

0:18:28.440 --> 0:18:30.959
<v Speaker 7>make that immediately available, and we think that just accelerates

0:18:30.960 --> 0:18:32.439
<v Speaker 7>the value of a tobis.

0:18:32.520 --> 0:18:35.320
<v Speaker 2>So you're not seeing really any kind of shift in

0:18:35.400 --> 0:18:37.280
<v Speaker 2>terms of people wanting to have it more on premise.

0:18:37.400 --> 0:18:39.080
<v Speaker 7>No, actually, I think it's just the other way around

0:18:39.240 --> 0:18:39.680
<v Speaker 7>the way around.

0:18:39.720 --> 0:18:39.960
<v Speaker 8>Okay.

0:18:40.560 --> 0:18:44.120
<v Speaker 4>Yesterday Jamie Diamond over at JP Morgan Chase his annual letter,

0:18:44.200 --> 0:18:48.359
<v Speaker 4>he likened AI to the steam engine. Do you believe

0:18:48.359 --> 0:18:51.320
<v Speaker 4>we're at an inflection point that is indeed that drastic.

0:18:52.280 --> 0:18:55.119
<v Speaker 7>I think it is when you talk to our customers,

0:18:55.960 --> 0:18:58.960
<v Speaker 7>the sheer amount of ideas that are both driven from

0:18:59.119 --> 0:19:01.240
<v Speaker 7>top of house from this CEOs that are saying, look

0:19:01.280 --> 0:19:04.720
<v Speaker 7>generated as a priority for us, right, we need to

0:19:04.720 --> 0:19:07.720
<v Speaker 7>think about how this changes our business. But also sort

0:19:07.720 --> 0:19:10.439
<v Speaker 7>of from the rank and file, anyone who's ever gone

0:19:10.520 --> 0:19:14.080
<v Speaker 7>to a GP backpot and actually asked a questions sort

0:19:14.080 --> 0:19:17.480
<v Speaker 7>of suddenly understands how efficient they can drive their own business.

0:19:18.359 --> 0:19:20.240
<v Speaker 7>It was Travelers who kind of in their own use

0:19:20.280 --> 0:19:24.000
<v Speaker 7>of generative AI so saved one hundred million dollars from

0:19:24.000 --> 0:19:27.840
<v Speaker 7>an operational expense perspective, just by automating those tasks that

0:19:27.920 --> 0:19:32.800
<v Speaker 7>tend to be very document labor, human intensive to kind

0:19:32.800 --> 0:19:35.440
<v Speaker 7>of be able to be more efficient. You know, we're

0:19:35.480 --> 0:19:38.640
<v Speaker 7>talking at this Marsh conference today. From a compliance perspective,

0:19:38.640 --> 0:19:41.440
<v Speaker 7>we've seen firms like Nassex, everyfin who does any money laundering,

0:19:41.680 --> 0:19:43.800
<v Speaker 7>you know, be able to reduce, you know, the time

0:19:43.840 --> 0:19:46.679
<v Speaker 7>it takes to investigate a fraud alert by like sixty percent.

0:19:46.920 --> 0:19:50.919
<v Speaker 7>And when you think about those operational savings at scale,

0:19:51.160 --> 0:19:54.080
<v Speaker 7>you're seeing sort of just huge excitement about the potential

0:19:54.119 --> 0:19:57.320
<v Speaker 7>for adoption. And I think we see it really being

0:19:57.320 --> 0:19:59.840
<v Speaker 7>embedded in almost every application, So no matter what you use,

0:20:00.000 --> 0:20:01.640
<v Speaker 7>it's almost going to have that kind of capability.

0:20:01.800 --> 0:20:03.840
<v Speaker 2>Is that what's kind of surprising because we do you know, John,

0:20:03.920 --> 0:20:06.560
<v Speaker 2>we talk about that AI is not anything new, It's

0:20:06.560 --> 0:20:08.159
<v Speaker 2>been around. It's just now we're talking about kind of

0:20:08.160 --> 0:20:10.160
<v Speaker 2>next level right when we when we talk about machine

0:20:10.200 --> 0:20:13.200
<v Speaker 2>learning and generative AI. But I think about our audience

0:20:13.240 --> 0:20:15.560
<v Speaker 2>who are listening, like, what would surprise them about what

0:20:15.600 --> 0:20:18.520
<v Speaker 2>you are seeing when it comes to generative AI and

0:20:18.560 --> 0:20:21.119
<v Speaker 2>the usage, it's not just about what it maybe can do,

0:20:21.160 --> 0:20:23.080
<v Speaker 2>it's what it's already doing, it feels like in.

0:20:23.000 --> 0:20:26.040
<v Speaker 7>Any ways, part of it is that the pace of

0:20:26.119 --> 0:20:28.920
<v Speaker 7>change over the last year has been so dramatic and

0:20:29.000 --> 0:20:31.600
<v Speaker 7>just with the models are capable of really yeah, I

0:20:31.640 --> 0:20:34.879
<v Speaker 7>mean we saw just sort of we work part closely

0:20:34.880 --> 0:20:37.920
<v Speaker 7>with anthropic commit equity investment in them and just sort

0:20:37.960 --> 0:20:40.080
<v Speaker 7>of seeing the difference between sort of Claude two and

0:20:40.119 --> 0:20:44.520
<v Speaker 7>Claude three in both its performance but also its cost.

0:20:44.760 --> 0:20:46.960
<v Speaker 7>And that's over less than a year period. And what

0:20:47.080 --> 0:20:49.840
<v Speaker 7>you're seeing is that there's such a variety of models

0:20:49.880 --> 0:20:53.640
<v Speaker 7>and the models are getting so much better that it's

0:20:53.800 --> 0:20:56.480
<v Speaker 7>not just that you're seeing immediate benefits and production with

0:20:56.520 --> 0:20:59.480
<v Speaker 7>some of these productivity applications. Is that you're all thinking,

0:20:59.560 --> 0:21:02.560
<v Speaker 7>oh gosh, if this keeps going, this is going to

0:21:02.640 --> 0:21:05.800
<v Speaker 7>change the way I look at almost everything. And you know,

0:21:06.119 --> 0:21:08.280
<v Speaker 7>generally I don't focus as much, but we're seeing that

0:21:08.320 --> 0:21:11.159
<v Speaker 7>on the developer productivity side. If you're a programmer and

0:21:11.200 --> 0:21:14.040
<v Speaker 7>you're looking to write code or update code, the tools

0:21:14.040 --> 0:21:16.800
<v Speaker 7>are getting so powerful and you're just seeing these massive

0:21:16.800 --> 0:21:19.000
<v Speaker 7>efficiencies and being able to kind of innovate from our

0:21:19.000 --> 0:21:21.679
<v Speaker 7>product side, it's hard to know where it stops. And

0:21:21.720 --> 0:21:23.119
<v Speaker 7>I think that's why everyone's so excited.

0:21:23.160 --> 0:21:26.640
<v Speaker 4>I should note the investment in Anthropic is a huge investment,

0:21:26.680 --> 0:21:29.960
<v Speaker 4>an additional two point seventy five billion dollars just a

0:21:29.960 --> 0:21:30.680
<v Speaker 4>couple of weeks ago.

0:21:30.800 --> 0:21:31.040
<v Speaker 2>Yeah.

0:21:31.080 --> 0:21:33.639
<v Speaker 7>Well, and then the second transhot exactly as part of that.

0:21:33.800 --> 0:21:35.840
<v Speaker 7>Not only do our customers get the benefit of being

0:21:35.880 --> 0:21:39.280
<v Speaker 7>able to use the Anthropic model, Anthropics committed to sort

0:21:39.280 --> 0:21:41.359
<v Speaker 7>of integrating with our platform to get better price and

0:21:41.400 --> 0:21:42.600
<v Speaker 7>performance for our customers.

0:21:42.760 --> 0:21:42.960
<v Speaker 1>Yeah.

0:21:43.000 --> 0:21:45.199
<v Speaker 5>So interesting, the integration of it, John, thank you so much.

0:21:45.240 --> 0:21:45.800
<v Speaker 7>Oh my pleasure.

0:21:45.840 --> 0:21:46.240
<v Speaker 5>This is great.

0:21:46.280 --> 0:21:49.280
<v Speaker 2>John Kaine, head of Financial Services market Development over at AWS,

0:21:49.359 --> 0:21:54.680
<v Speaker 2>joining US here at smash Connect, you're.

0:21:54.520 --> 0:21:58.440
<v Speaker 1>Listening to the Bloomberg Business Week podcast. Listen live each

0:21:58.480 --> 0:22:02.040
<v Speaker 1>weekday starting a two pm starting on Applecarplay and Android

0:22:02.080 --> 0:22:04.960
<v Speaker 1>Auto with the Bloomberg Business app. You can also listen

0:22:05.080 --> 0:22:08.160
<v Speaker 1>live on Amazon Alexa from our flagship New York station

0:22:08.560 --> 0:22:12.600
<v Speaker 1>Just say Alexa playing Bloomberg eleven thirty.

0:22:12.880 --> 0:22:14.879
<v Speaker 2>It's a little bit of sound in the background. We

0:22:14.920 --> 0:22:17.480
<v Speaker 2>are here at smash Connect in Midtown Manhattan. We've stepped

0:22:17.480 --> 0:22:20.439
<v Speaker 2>outside Bloomberg headquarters. They're going to bring down the volume

0:22:20.480 --> 0:22:21.960
<v Speaker 2>a little bit, but it's exciting.

0:22:22.000 --> 0:22:23.040
<v Speaker 4>This is people are partying.

0:22:23.160 --> 0:22:24.560
<v Speaker 5>Well, it is people are partying.

0:22:24.600 --> 0:22:27.320
<v Speaker 2>It's a moment where they bring in clients and customers

0:22:27.359 --> 0:22:30.040
<v Speaker 2>and they're talking things like technology, they're talking AI, they're

0:22:30.080 --> 0:22:33.119
<v Speaker 2>talking compliance, and so there's a lot of good energy.

0:22:33.200 --> 0:22:35.439
<v Speaker 4>Well, speaking of AI, Carol, Intel rolling out a new

0:22:35.520 --> 0:22:38.680
<v Speaker 4>version of its artificial intelligence chip, aiming to challenge in

0:22:38.760 --> 0:22:41.639
<v Speaker 4>VideA in one of the fastest growing parts of the

0:22:41.640 --> 0:22:43.119
<v Speaker 4>semiconductor industry.

0:22:42.840 --> 0:22:45.439
<v Speaker 2>Right out with an updated processor, it will be widely

0:22:45.480 --> 0:22:47.960
<v Speaker 2>available on the third quarter. It's designed to boost performance

0:22:47.960 --> 0:22:51.200
<v Speaker 2>in two key areas, helping train AI systems and also

0:22:51.600 --> 0:22:54.080
<v Speaker 2>a process that involves bom barding them with data. We

0:22:54.160 --> 0:22:56.719
<v Speaker 2>know that, and also running the finished software. It's all

0:22:56.800 --> 0:22:57.320
<v Speaker 2>about AI.

0:22:57.480 --> 0:22:57.879
<v Speaker 5>We know that.

0:22:57.920 --> 0:23:00.520
<v Speaker 2>We've been talking about it NonStop for over year now.

0:23:00.800 --> 0:23:03.119
<v Speaker 2>And someone who knows a lot about it is Brandon Carl.

0:23:03.160 --> 0:23:06.200
<v Speaker 2>He's executive vice president of AI and Product Strategy at

0:23:06.240 --> 0:23:09.160
<v Speaker 2>SMARSH with us on site here at SMARSH Connect.

0:23:09.520 --> 0:23:10.760
<v Speaker 5>So good to have you here with us.

0:23:10.880 --> 0:23:11.720
<v Speaker 8>Thank you for having me.

0:23:11.720 --> 0:23:14.399
<v Speaker 2>Thank you for inviting us. Actually we're here in your

0:23:14.440 --> 0:23:18.240
<v Speaker 2>home AI. There's so much going on every day. AI

0:23:18.320 --> 0:23:19.840
<v Speaker 2>is not new, we know that, we say that all

0:23:19.920 --> 0:23:23.520
<v Speaker 2>the time, but next level machine learning, generative AI and

0:23:23.520 --> 0:23:25.320
<v Speaker 2>what it can do. How do you get your head

0:23:25.359 --> 0:23:28.440
<v Speaker 2>around what really matters? It's something we ask our AI reporters.

0:23:28.520 --> 0:23:31.040
<v Speaker 2>What matters, what doesn't? How do you figure that out?

0:23:31.240 --> 0:23:33.359
<v Speaker 9>One of my favorite quotes in this space is AI

0:23:33.520 --> 0:23:35.919
<v Speaker 9>is always what the computer can't do now right and

0:23:36.359 --> 0:23:38.479
<v Speaker 9>what it could do yesterday. And so when you take

0:23:38.520 --> 0:23:40.560
<v Speaker 9>a look at this, what we take a look at

0:23:40.600 --> 0:23:41.600
<v Speaker 9>is what a outcome.

0:23:41.320 --> 0:23:42.560
<v Speaker 4>The customer is trying to achieve.

0:23:42.760 --> 0:23:45.200
<v Speaker 9>And when we look at things like AI and machine learning,

0:23:45.240 --> 0:23:47.639
<v Speaker 9>they are about a dozen different technologies we use in

0:23:47.760 --> 0:23:51.840
<v Speaker 9>terms of taking customers into production and their software. So

0:23:52.240 --> 0:23:53.919
<v Speaker 9>when we use these and when we see things like

0:23:53.960 --> 0:23:57.240
<v Speaker 9>generative AI, they're incredible new things that this technology can do,

0:23:57.760 --> 0:23:59.760
<v Speaker 9>and that enables us to do incredible new things for

0:23:59.760 --> 0:24:00.520
<v Speaker 9>our customers.

0:24:00.800 --> 0:24:03.080
<v Speaker 4>I think back to when a I got on a

0:24:03.119 --> 0:24:05.520
<v Speaker 4>lot of people's radar, not people in the space, but

0:24:05.600 --> 0:24:07.760
<v Speaker 4>like investors who really started to think about it as

0:24:07.880 --> 0:24:11.680
<v Speaker 4>a new category for them or lay people. Really it's

0:24:11.720 --> 0:24:14.320
<v Speaker 4>this idea like kind of playing with CHATCHBT for the

0:24:14.320 --> 0:24:16.600
<v Speaker 4>first time, perhaps in the fall of twenty twenty two.

0:24:19.359 --> 0:24:20.600
<v Speaker 4>When did it get on your radar?

0:24:21.320 --> 0:24:24.200
<v Speaker 9>A long time ago? So we have been how long

0:24:24.600 --> 0:24:27.720
<v Speaker 9>We started work on natural language processing back in two thousand.

0:24:28.119 --> 0:24:31.080
<v Speaker 9>It was a company Smarsh acquired called Digital Reasoning, And

0:24:31.119 --> 0:24:33.840
<v Speaker 9>then we started working with the financial services industry in

0:24:33.880 --> 0:24:36.800
<v Speaker 9>twenty fifteen and twenty sixteen, and we started doing very

0:24:36.880 --> 0:24:38.000
<v Speaker 9>large scale deployments then.

0:24:38.040 --> 0:24:39.080
<v Speaker 8>So we've been working for a long time.

0:24:39.119 --> 0:24:41.360
<v Speaker 4>Why was there such a long period of time between

0:24:41.960 --> 0:24:45.119
<v Speaker 4>two thousand and two fifteen twenty sixteen when you started

0:24:45.119 --> 0:24:45.960
<v Speaker 4>actually implementing it.

0:24:46.040 --> 0:24:49.280
<v Speaker 9>Sure, the early customers were actually government customers that were

0:24:49.280 --> 0:24:52.439
<v Speaker 9>interested in national defense and security, and it wasn't until

0:24:52.520 --> 0:24:55.160
<v Speaker 9>after the Libor crisis you had about three to five

0:24:55.240 --> 0:24:57.920
<v Speaker 9>years where budgets increased and suddenly people said, there's got

0:24:57.960 --> 0:25:00.120
<v Speaker 9>to be a better way to keep the markets safe.

0:25:00.720 --> 0:25:04.000
<v Speaker 2>How does crisis and lawsuits and fines and things like

0:25:04.000 --> 0:25:05.600
<v Speaker 2>that kind of shape what you guys are doing.

0:25:05.440 --> 0:25:06.120
<v Speaker 5>In you particular?

0:25:06.320 --> 0:25:08.480
<v Speaker 9>Sure, I would like to think that the industry could

0:25:08.520 --> 0:25:13.040
<v Speaker 9>be wildly proactive. But typically what happens is some event happens, right,

0:25:13.440 --> 0:25:15.520
<v Speaker 9>and then firms get budgets and they say, we need

0:25:15.560 --> 0:25:18.000
<v Speaker 9>to prevent that from happening again. So there really is

0:25:18.000 --> 0:25:20.200
<v Speaker 9>a unicause and effect that plays out there.

0:25:20.240 --> 0:25:21.880
<v Speaker 5>Is it getting a lot more complicated though?

0:25:22.440 --> 0:25:27.480
<v Speaker 9>It is mostly because the number of ways people communicates.

0:25:27.080 --> 0:25:29.119
<v Speaker 4>Something we've been talking about. I mean, he has been

0:25:29.160 --> 0:25:32.160
<v Speaker 4>working for years on art all. They had issues with WhatsApp,

0:25:32.240 --> 0:25:34.560
<v Speaker 4>for example, just one platform.

0:25:34.720 --> 0:25:37.760
<v Speaker 9>How do you put that to process more than one

0:25:37.800 --> 0:25:40.440
<v Speaker 9>hundred different platforms? And if you think about this even

0:25:40.480 --> 0:25:46.040
<v Speaker 9>five years, three hundred million today. So whether it's Slack, team, Zoom, WhatsApp,

0:25:46.080 --> 0:25:48.240
<v Speaker 9>we chat line, signal, like, there are all different ways

0:25:48.240 --> 0:25:48.960
<v Speaker 9>people communicate.

0:25:49.080 --> 0:25:52.119
<v Speaker 4>I was in doing research for this this interview. I

0:25:51.880 --> 0:25:55.120
<v Speaker 4>was I was trying to find information about how many

0:25:55.160 --> 0:25:58.760
<v Speaker 4>messages a bank typically processes in a single day. Yep,

0:25:58.840 --> 0:26:01.959
<v Speaker 4>couldn't find that data anyway. Yeah, give us some numbers.

0:26:02.560 --> 0:26:04.600
<v Speaker 9>It really depends on the firm and the type of firm.

0:26:05.160 --> 0:26:07.800
<v Speaker 9>Typical employee is like anywhere from one to five hundred

0:26:07.800 --> 0:26:08.639
<v Speaker 9>messages a day, but.

0:26:08.720 --> 0:26:13.160
<v Speaker 4>To each employee, one employee, Yeah, yep, okay, so give

0:26:13.240 --> 0:26:15.640
<v Speaker 4>us some huge numbers here about the processing that you're

0:26:15.640 --> 0:26:16.560
<v Speaker 4>doing in a real tier.

0:26:16.680 --> 0:26:16.920
<v Speaker 6>Yeah.

0:26:16.960 --> 0:26:19.520
<v Speaker 9>So so firms can you know, generate as many as

0:26:19.520 --> 0:26:22.479
<v Speaker 9>tens of millions of messages every single day, right, and

0:26:22.560 --> 0:26:25.800
<v Speaker 9>we will process billions and billions of communications. So if

0:26:25.800 --> 0:26:28.239
<v Speaker 9>you imagine all of the comms coming together, that's what

0:26:28.280 --> 0:26:29.280
<v Speaker 9>we really have to process.

0:26:29.440 --> 0:26:32.119
<v Speaker 4>If everyone's here today, who's processing the communications?

0:26:32.720 --> 0:26:32.920
<v Speaker 1>Yeah?

0:26:33.560 --> 0:26:35.560
<v Speaker 9>I really I'm worried about that myself.

0:26:35.640 --> 0:26:37.440
<v Speaker 2>Yeah, you know, I'm looking at the notes that your

0:26:37.480 --> 0:26:40.760
<v Speaker 2>team shared with us and regulatory grade AI what exactly

0:26:40.760 --> 0:26:42.040
<v Speaker 2>does that mean? Because I do feel like it's going

0:26:42.080 --> 0:26:44.440
<v Speaker 2>to be a term that we're going to be using increasingly.

0:26:44.920 --> 0:26:45.320
<v Speaker 6>Yeah.

0:26:45.359 --> 0:26:46.000
<v Speaker 9>Absolutely.

0:26:46.080 --> 0:26:46.199
<v Speaker 3>So.

0:26:46.600 --> 0:26:49.040
<v Speaker 9>On one hand, people can log into chat GPT and

0:26:49.080 --> 0:26:51.040
<v Speaker 9>just use it, right, Yeah, But when you think about

0:26:51.040 --> 0:26:54.160
<v Speaker 9>a regulated industry, you have to protect against things like bias.

0:26:54.320 --> 0:26:56.480
<v Speaker 9>You need to make sure that you understand how things

0:26:56.480 --> 0:26:58.439
<v Speaker 9>are actually working. You need to make sure that you

0:26:58.440 --> 0:27:01.080
<v Speaker 9>can rely on that over and over again. So it's

0:27:01.119 --> 0:27:04.040
<v Speaker 9>really a higher standard in terms of how you approach things.

0:27:04.400 --> 0:27:06.400
<v Speaker 2>I want to ask you because you do have Probably

0:27:06.440 --> 0:27:09.000
<v Speaker 2>you guys in particular, have a great We tried to

0:27:09.000 --> 0:27:11.199
<v Speaker 2>ask ste like, who are your clients? But he's really quiet,

0:27:11.440 --> 0:27:14.000
<v Speaker 2>But we know you guys are well in trench, certainly

0:27:14.000 --> 0:27:16.800
<v Speaker 2>within the financial sector. But I do wonder, Brandon, when

0:27:16.800 --> 0:27:21.040
<v Speaker 2>you look at things, I mean, how equipped are is

0:27:21.080 --> 0:27:25.160
<v Speaker 2>the financial community when it comes to compliance and risk

0:27:25.359 --> 0:27:28.720
<v Speaker 2>and transparency In a world where increasingly, as we said,

0:27:28.720 --> 0:27:31.480
<v Speaker 2>there are more and more touch points that create risk,

0:27:31.880 --> 0:27:33.560
<v Speaker 2>and in a world where there are more and more

0:27:33.760 --> 0:27:36.960
<v Speaker 2>oversight and regulators looking and looking for problems.

0:27:36.680 --> 0:27:39.679
<v Speaker 9>It's a hard problem to tackle, particularly for firms to

0:27:39.680 --> 0:27:42.360
<v Speaker 9>have global regulation on things. Yeah, what I can say,

0:27:42.359 --> 0:27:46.800
<v Speaker 9>we genuinely have fantastic customers within this space, and what

0:27:46.840 --> 0:27:49.040
<v Speaker 9>you typically see is you see a handful of them

0:27:49.119 --> 0:27:52.040
<v Speaker 9>really trying to trailblaze and lead the industry forward, to

0:27:52.080 --> 0:27:54.520
<v Speaker 9>make markets safer and to make their firms safer. And

0:27:54.560 --> 0:27:56.480
<v Speaker 9>they help the trail blaze to create the paths for

0:27:56.560 --> 0:27:58.240
<v Speaker 9>the rest of the firms to follow.

0:27:58.080 --> 0:28:00.160
<v Speaker 5>Us and bring along like their supply chain with them.

0:28:01.480 --> 0:28:04.119
<v Speaker 9>To some extent their supply chain, but typically less so

0:28:04.240 --> 0:28:04.880
<v Speaker 9>in what we do.

0:28:05.080 --> 0:28:05.960
<v Speaker 5>Okay, you know, I.

0:28:06.440 --> 0:28:09.240
<v Speaker 4>Hear you and Steve speaking, and I think about another

0:28:09.320 --> 0:28:15.040
<v Speaker 4>highly regulated industry, medicine and also an industry that is

0:28:15.080 --> 0:28:18.720
<v Speaker 4>trying to figure out how to use AI. Any any

0:28:19.440 --> 0:28:24.400
<v Speaker 4>talk discussion about getting into medicine. It has the hipA

0:28:24.440 --> 0:28:27.720
<v Speaker 4>stuff when it comes to communications between patients and doctors,

0:28:28.040 --> 0:28:30.879
<v Speaker 4>has the regulatory issues as well. Is that all Does

0:28:30.920 --> 0:28:31.920
<v Speaker 4>that all come up on your radar?

0:28:32.119 --> 0:28:33.400
<v Speaker 8>It does come up on our radar.

0:28:33.560 --> 0:28:36.199
<v Speaker 9>We really look at regulated industries as areas that we

0:28:36.240 --> 0:28:38.720
<v Speaker 9>can have the biggest impact. So pharma is one of

0:28:38.760 --> 0:28:42.040
<v Speaker 9>those energies and other and then financial services. So we

0:28:42.080 --> 0:28:43.800
<v Speaker 9>do think we can have some impact, but we're really

0:28:43.800 --> 0:28:47.400
<v Speaker 9>squarely focused on solving these markets use cases as best

0:28:47.440 --> 0:28:48.640
<v Speaker 9>we can in the near term.

0:28:48.680 --> 0:28:50.720
<v Speaker 2>So again, like I think about, I keep thinking about

0:28:50.720 --> 0:28:51.640
<v Speaker 2>the Bloomberg audience.

0:28:51.680 --> 0:28:52.680
<v Speaker 5>So what are you guys.

0:28:53.840 --> 0:28:55.719
<v Speaker 2>I'm sure there are scenarios you play out. Okay, these

0:28:55.760 --> 0:28:57.520
<v Speaker 2>are the risk scenarios that we need to be thinking

0:28:57.520 --> 0:29:01.320
<v Speaker 2>about in a world increasingly that is ruled machine learning,

0:29:01.400 --> 0:29:04.720
<v Speaker 2>generative AI, what are the risks that you think that

0:29:04.760 --> 0:29:07.120
<v Speaker 2>we should all be kind of preparing for because we're

0:29:07.120 --> 0:29:08.040
<v Speaker 2>not going to catch everything.

0:29:08.320 --> 0:29:08.800
<v Speaker 6>Yeah, we will.

0:29:08.880 --> 0:29:12.160
<v Speaker 9>Unfortunately we won't catch everything. And typically what you'll see

0:29:12.800 --> 0:29:15.600
<v Speaker 9>sometimes you'll see nefarious bad actors within firms, right, and

0:29:15.640 --> 0:29:17.280
<v Speaker 9>then other times there are people who just don't know

0:29:17.320 --> 0:29:19.200
<v Speaker 9>any better. And you really want to help the people

0:29:19.200 --> 0:29:21.920
<v Speaker 9>who don't know better to say, hey, you didn't intend

0:29:21.920 --> 0:29:23.240
<v Speaker 9>to do this, like this is the right way to

0:29:23.240 --> 0:29:25.120
<v Speaker 9>do things. But we also have to keep an eye

0:29:25.120 --> 0:29:28.520
<v Speaker 9>towards the people who are ruining the reputations of their

0:29:28.600 --> 0:29:30.440
<v Speaker 9>firms or you know, other people who are trying.

0:29:30.280 --> 0:29:30.800
<v Speaker 8>To do the right thing.

0:29:30.920 --> 0:29:32.320
<v Speaker 5>So really bad actors, there.

0:29:32.240 --> 0:29:34.600
<v Speaker 8>Are bad actors unfortunately that are out there.

0:29:34.680 --> 0:29:37.480
<v Speaker 4>Are those usually internal with an affirm in in trying

0:29:37.520 --> 0:29:39.440
<v Speaker 4>to have some sort of inside edge when it comes

0:29:39.520 --> 0:29:42.840
<v Speaker 4>to making money, or they usually bad actors from the outside.

0:29:42.920 --> 0:29:46.479
<v Speaker 9>It can be both, right, Typically the outside bad actors

0:29:46.480 --> 0:29:50.080
<v Speaker 9>are more from an information security standpoint, right, And sometimes

0:29:50.120 --> 0:29:52.640
<v Speaker 9>there are people internally who are just trying to make

0:29:52.640 --> 0:29:53.880
<v Speaker 9>a buck and not do the right thing.

0:29:54.880 --> 0:29:55.160
<v Speaker 5>AI.

0:29:55.280 --> 0:29:57.360
<v Speaker 2>The conversation in a year from now just got about

0:29:57.360 --> 0:29:59.320
<v Speaker 2>thirty seconds left here, Sure do you think it'll be

0:29:59.440 --> 0:30:01.320
<v Speaker 2>dramatically different or just more the same.

0:30:01.680 --> 0:30:04.600
<v Speaker 9>It will keep improving, absolutely, and we need to keep

0:30:04.680 --> 0:30:07.640
<v Speaker 9>figuring out how we can actually use these technologies and

0:30:07.680 --> 0:30:09.160
<v Speaker 9>the right way to improve the world.

0:30:09.400 --> 0:30:11.000
<v Speaker 5>All right, really interesting stuff.

0:30:11.440 --> 0:30:14.680
<v Speaker 2>I don't envy you, because you've got a lot coming

0:30:14.720 --> 0:30:17.040
<v Speaker 2>at you. Brendan carl Executi, vice president of AI and

0:30:17.040 --> 0:30:19.440
<v Speaker 2>Product Strategy at s Marsh joining us here on site

0:30:19.560 --> 0:30:20.560
<v Speaker 2>at smash Connect.

0:30:20.680 --> 0:30:21.800
<v Speaker 4>Really really cool stuff.

0:30:23.400 --> 0:30:26.960
<v Speaker 1>You're listening to the Bloomberg Business Week podcast. Catch us

0:30:26.960 --> 0:30:30.240
<v Speaker 1>Live weekday afternoons from two to five pm Eastern. Listen

0:30:30.240 --> 0:30:32.400
<v Speaker 1>on Apple car Play and then brout Auto with a

0:30:32.440 --> 0:30:36.560
<v Speaker 1>Bloomberg Business app or want us Live on YouTube.

0:30:37.920 --> 0:30:41.160
<v Speaker 4>Last week, SEC won a jury verdict and its groundbreaking

0:30:41.200 --> 0:30:43.720
<v Speaker 4>insider trading case that seeks to bar employees from using

0:30:44.160 --> 0:30:47.440
<v Speaker 4>non public information about their own company to place bets

0:30:47.560 --> 0:30:51.040
<v Speaker 4>on rival stock. Also, a former Flow executive and his

0:30:51.080 --> 0:30:54.520
<v Speaker 4>cousin recently admitted to insider trading on confidential information about

0:30:54.520 --> 0:30:58.440
<v Speaker 4>a pandemic related government loan to Eastman Kodak. All of

0:30:58.440 --> 0:31:01.080
<v Speaker 4>this happening, Carol, while the agency has been dealing with

0:31:01.120 --> 0:31:03.240
<v Speaker 4>a number of high profile crypto cases, and I got

0:31:03.240 --> 0:31:03.640
<v Speaker 4>to tell you.

0:31:03.720 --> 0:31:04.560
<v Speaker 5>We could go on and on.

0:31:04.720 --> 0:31:06.800
<v Speaker 4>This is just a sampling of what I found when

0:31:06.840 --> 0:31:09.080
<v Speaker 4>I typed into the Bloomberg terminal and I.

0:31:09.080 --> 0:31:12.640
<v Speaker 2>Fraud and I fraud. Yeah, there's a lot. So I'm

0:31:12.640 --> 0:31:13.720
<v Speaker 2>guessing it's not going to come.

0:31:13.600 --> 0:31:15.760
<v Speaker 4>As a surprise fraud an alleged.

0:31:15.360 --> 0:31:18.600
<v Speaker 2>Frauduct To be fair, we're guessing this will come as

0:31:18.640 --> 0:31:20.360
<v Speaker 2>a surprize to our next guest. Rob Mahra is with us.

0:31:20.360 --> 0:31:23.080
<v Speaker 2>He's a principal in EYS consulting practice. He spent decades

0:31:23.120 --> 0:31:27.160
<v Speaker 2>working on risk and regulatory compliance, tech and operations, think sanctions,

0:31:27.200 --> 0:31:30.720
<v Speaker 2>anti money laundering, fraud management, and of course working with regulators.

0:31:30.760 --> 0:31:32.520
<v Speaker 2>It feels like it's all the courses that we take

0:31:32.720 --> 0:31:35.640
<v Speaker 2>at Bloomberg to make sure that we are compliant and

0:31:35.760 --> 0:31:36.440
<v Speaker 2>very careful.

0:31:37.120 --> 0:31:38.880
<v Speaker 5>Welcome, Welcome, Nice to be talking with you, Thank you,

0:31:38.920 --> 0:31:40.320
<v Speaker 5>good to be here. Tell us about your world.

0:31:40.440 --> 0:31:41.280
<v Speaker 4>Many stock tips.

0:31:43.080 --> 0:31:45.320
<v Speaker 5>We are a public, We're all like we've got a

0:31:45.320 --> 0:31:45.920
<v Speaker 5>public lads.

0:31:45.960 --> 0:31:50.320
<v Speaker 8>Doctip's a bit of a problem. So basically, the way

0:31:50.360 --> 0:31:53.560
<v Speaker 8>I kind of put my job overall is, you know,

0:31:53.600 --> 0:31:56.760
<v Speaker 8>I help financial institutions get out of trouble and stay

0:31:56.760 --> 0:31:59.800
<v Speaker 8>out of trouble. You know, if you just see all

0:31:59.840 --> 0:32:02.880
<v Speaker 8>the different things happening in the news. You know, you

0:32:02.960 --> 0:32:05.400
<v Speaker 8>mentioned insider trading in just a second ago. You know,

0:32:05.440 --> 0:32:08.240
<v Speaker 8>there's all sorts of different types of regulatory compliance matters

0:32:08.280 --> 0:32:10.640
<v Speaker 8>that hit institutions from any number of areas, and they're

0:32:10.720 --> 0:32:12.720
<v Speaker 8>very complex, you know, particularly when you start dealing with

0:32:12.760 --> 0:32:16.479
<v Speaker 8>a large multinational firm. The regulations may be different. In

0:32:16.480 --> 0:32:19.200
<v Speaker 8>some cases, they may be conflicting between different jurisdictions, and

0:32:19.200 --> 0:32:21.440
<v Speaker 8>trying to navigate that to figure out how you can

0:32:21.480 --> 0:32:23.800
<v Speaker 8>do something and do the right thing is a bit

0:32:23.840 --> 0:32:26.040
<v Speaker 8>of a challenge, is it.

0:32:26.000 --> 0:32:28.600
<v Speaker 4>Though, Because Okay, I gotta tell you what I was going.

0:32:28.480 --> 0:32:30.160
<v Speaker 5>Through all that. When Tim does that, is it that

0:32:30.320 --> 0:32:31.120
<v Speaker 5>is fraud.

0:32:30.880 --> 0:32:34.160
<v Speaker 4>And alleged fraud? I mean, it seems like a lot

0:32:34.160 --> 0:32:36.280
<v Speaker 4>of this stuff is pretty clear cut, and you get

0:32:36.280 --> 0:32:38.800
<v Speaker 4>people the stuff that I'm reading about, mind you, Yeah,

0:32:38.840 --> 0:32:42.960
<v Speaker 4>it's pretty clear cut, like okay, yes, this is okay, no,

0:32:43.520 --> 0:32:46.240
<v Speaker 4>this is not okay type of stuff. And it seems

0:32:46.280 --> 0:32:51.960
<v Speaker 4>like it's not necessarily the firms. It's certain individuals within

0:32:52.040 --> 0:32:54.880
<v Speaker 4>firms that are just looking to make more money.

0:32:55.600 --> 0:32:58.760
<v Speaker 8>It can be a combination of both. And while some

0:32:58.800 --> 0:33:01.520
<v Speaker 8>of the things are very very you know, black and white.

0:33:01.600 --> 0:33:04.040
<v Speaker 8>You know, if you look at you know, like front running,

0:33:04.120 --> 0:33:08.000
<v Speaker 8>somebody's trade, very very straightforward in terms of how that's done,

0:33:08.040 --> 0:33:10.200
<v Speaker 8>but if you start to think about how that actually

0:33:10.240 --> 0:33:13.520
<v Speaker 8>works out. You know, front running, you understand the concept,

0:33:13.840 --> 0:33:16.320
<v Speaker 8>but think about you have you know, thousands, if not

0:33:16.440 --> 0:33:18.320
<v Speaker 8>you know, hundreds of thousands or even in some cases

0:33:18.320 --> 0:33:21.360
<v Speaker 8>millions of trades going through a day, and all the

0:33:21.400 --> 0:33:24.200
<v Speaker 8>particulars around those trades. So let's take a very simple example.

0:33:24.240 --> 0:33:27.520
<v Speaker 8>Suppose that you place a trade on behalf of your customer,

0:33:28.160 --> 0:33:29.760
<v Speaker 8>and or you place it on behalf of a bunch

0:33:29.800 --> 0:33:33.000
<v Speaker 8>of customers, and then you reallocate it afterwards. Well, the

0:33:33.040 --> 0:33:34.840
<v Speaker 8>way that it might show up in terms of how

0:33:34.840 --> 0:33:37.440
<v Speaker 8>it looks in the data is it's actually looks like

0:33:37.480 --> 0:33:40.600
<v Speaker 8>front running because you traded before the customer actually the

0:33:40.600 --> 0:33:43.680
<v Speaker 8>customer order went through, but you were trading on behalf

0:33:43.720 --> 0:33:46.640
<v Speaker 8>of a customer. Does that count as front running? No,

0:33:46.680 --> 0:33:48.800
<v Speaker 8>obviously it doesn't. And then there's certain exemptions, it's a

0:33:48.800 --> 0:33:51.960
<v Speaker 8>black box exemption. There's alsort of these different variations. Now, yeah,

0:33:52.000 --> 0:33:53.600
<v Speaker 8>it doesn't mean that there aren't some things that are

0:33:53.640 --> 0:33:55.560
<v Speaker 8>just straight white. You know, you mentioned some of the

0:33:55.560 --> 0:33:58.440
<v Speaker 8>insider trading questions, you know, but there are other things

0:33:58.480 --> 0:34:00.520
<v Speaker 8>where it becomes more of a risk question. You know,

0:34:00.560 --> 0:34:02.720
<v Speaker 8>if you look at money laundering activity, other types of

0:34:02.760 --> 0:34:05.320
<v Speaker 8>things like that, where it's like, well, you know, how

0:34:05.400 --> 0:34:08.439
<v Speaker 8>much do you know? Versus how much should you have known?

0:34:08.880 --> 0:34:10.680
<v Speaker 8>Versus how much was hidden from you?

0:34:10.680 --> 0:34:10.840
<v Speaker 6>You know?

0:34:10.920 --> 0:34:13.240
<v Speaker 8>Versus you know, what are your employees doing? It becomes

0:34:13.280 --> 0:34:14.920
<v Speaker 8>a bit of a challenge. Again, doesn't mean there's not

0:34:14.960 --> 0:34:16.920
<v Speaker 8>some black and white stuff. There's definitely some black and

0:34:16.920 --> 0:34:19.680
<v Speaker 8>white stuff, but unfortunately there's a decent amount of grayness.

0:34:19.840 --> 0:34:21.840
<v Speaker 2>But in a world that is increasingly digital, if not

0:34:21.840 --> 0:34:23.640
<v Speaker 2>all digital, I think about, even as a journalists, go

0:34:23.680 --> 0:34:25.520
<v Speaker 2>back how many years and I didn't spend as much

0:34:25.560 --> 0:34:27.120
<v Speaker 2>time on a computer. Now I live on a computer.

0:34:27.160 --> 0:34:29.359
<v Speaker 2>No matter what I'm doing. My whole life right now

0:34:29.400 --> 0:34:31.360
<v Speaker 2>is on a computer. Does it make it easier in

0:34:31.440 --> 0:34:35.560
<v Speaker 2>terms of tracking down compliance and risk or figuring out, okay,

0:34:36.080 --> 0:34:38.879
<v Speaker 2>did something really wrong happen here? Or does it make

0:34:38.880 --> 0:34:41.319
<v Speaker 2>it easier or more complicated?

0:34:42.239 --> 0:34:46.560
<v Speaker 8>It's another little bit of both, because one thing that

0:34:46.680 --> 0:34:48.360
<v Speaker 8>kind of comes into play is just the sheer volume

0:34:48.400 --> 0:34:51.160
<v Speaker 8>of data. Yeah, I work within a number of customers,

0:34:51.280 --> 0:34:53.040
<v Speaker 8>and if you just think about it just the data

0:34:53.040 --> 0:34:56.839
<v Speaker 8>that's coming think atm footage, just the videos coming out

0:34:56.880 --> 0:34:59.120
<v Speaker 8>of that that can be literally petabytes of data.

0:34:59.160 --> 0:34:59.359
<v Speaker 5>Wow.

0:34:59.440 --> 0:35:01.000
<v Speaker 8>Yeah, you know, if you look at the number of

0:35:01.040 --> 0:35:03.840
<v Speaker 8>emails going through, or you take a large US financial institution,

0:35:03.920 --> 0:35:07.040
<v Speaker 8>one of the top four, a billion transactions per day,

0:35:07.480 --> 0:35:09.200
<v Speaker 8>you know, not counting the trades, not counting all the

0:35:09.239 --> 0:35:11.000
<v Speaker 8>other things that are happening, all the other events onboard.

0:35:12.000 --> 0:35:13.880
<v Speaker 2>So what do you do with something like that? How

0:35:13.920 --> 0:35:15.879
<v Speaker 2>do you scrape through or figure out what I mean?

0:35:15.960 --> 0:35:19.600
<v Speaker 2>Do you have to is everything gone over every How

0:35:19.600 --> 0:35:20.279
<v Speaker 2>do you deal with that?

0:35:20.400 --> 0:35:23.680
<v Speaker 8>So you you definitely rely on a lot of automated

0:35:23.880 --> 0:35:28.200
<v Speaker 8>and analytics type of activity, but you're you're constantly tuning

0:35:28.280 --> 0:35:30.440
<v Speaker 8>and adjusting it. You know, like I do a lot

0:35:30.440 --> 0:35:32.879
<v Speaker 8>of work in the fraud space. As an example, every

0:35:32.880 --> 0:35:36.000
<v Speaker 8>time you swipe your credit card, there are literally, you know,

0:35:36.200 --> 0:35:38.719
<v Speaker 8>hundreds of algorithms running in the background to try and

0:35:38.719 --> 0:35:40.520
<v Speaker 8>figure out whether or not this is actually you Does

0:35:40.560 --> 0:35:42.440
<v Speaker 8>it make sense? Is it something that you know we

0:35:42.440 --> 0:35:44.680
<v Speaker 8>should block or we should allow? And they have to

0:35:44.680 --> 0:35:47.920
<v Speaker 8>make that decision in milliseconds because otherwise, you know, you're

0:35:47.920 --> 0:35:50.960
<v Speaker 8>getting a rejection and you want to minimize that and

0:35:51.400 --> 0:35:53.520
<v Speaker 8>that behavior is going to continue to evolve, and so

0:35:53.560 --> 0:35:56.320
<v Speaker 8>you're constantly bringing in new data, you're tweaking your algorithms,

0:35:56.360 --> 0:35:58.960
<v Speaker 8>you're adjusting these things, and then multiply this by the

0:35:59.080 --> 0:36:01.840
<v Speaker 8>you know, literally thousands of compliance regulations you need to

0:36:01.920 --> 0:36:04.759
<v Speaker 8>check too. You have to rely on the automation, and

0:36:04.800 --> 0:36:08.440
<v Speaker 8>then you know, people are getting very very very advanced

0:36:08.520 --> 0:36:11.359
<v Speaker 8>in you know, you've seen deep fakes. You know, how

0:36:11.360 --> 0:36:13.719
<v Speaker 8>can you tell the difference between a deep fake activity

0:36:13.719 --> 0:36:14.800
<v Speaker 8>and non deep activity?

0:36:14.840 --> 0:36:15.920
<v Speaker 4>Let's talk about that little bit.

0:36:15.960 --> 0:36:19.879
<v Speaker 8>How can you so if you're an if you're an

0:36:19.880 --> 0:36:22.560
<v Speaker 8>ethical company who's built the technology to do this, and

0:36:22.840 --> 0:36:25.000
<v Speaker 8>they talked a little bit about during the conference today.

0:36:25.480 --> 0:36:28.160
<v Speaker 8>You can tag images, you can tag different types of

0:36:28.200 --> 0:36:32.960
<v Speaker 8>things as being you know, generated by AI. If you're

0:36:33.560 --> 0:36:36.560
<v Speaker 8>not an ethical company, or you're a fraudster or you're

0:36:36.640 --> 0:36:40.200
<v Speaker 8>you know, some type of scammer, you are going to

0:36:40.200 --> 0:36:41.840
<v Speaker 8>not put those tags in and you're going to do

0:36:41.880 --> 0:36:43.520
<v Speaker 8>your best to adjust them. It doesn't mean that you

0:36:43.560 --> 0:36:45.160
<v Speaker 8>can't detect them in different ways.

0:36:45.200 --> 0:36:47.160
<v Speaker 4>I don't know how many how many times a day

0:36:47.200 --> 0:36:49.279
<v Speaker 4>do you get text messages from somebody who's trying to

0:36:49.280 --> 0:36:51.239
<v Speaker 4>spend who's literally trying to take money from you.

0:36:51.680 --> 0:36:53.839
<v Speaker 8>Literally one of my favorite questions I asked people want

0:36:53.840 --> 0:36:56.440
<v Speaker 8>to you know, the other one being that everybody's information

0:36:56.520 --> 0:36:58.360
<v Speaker 8>is compromised and you just kind of have to accept

0:36:58.360 --> 0:37:00.480
<v Speaker 8>it and protect against it. But yes, you get I

0:37:00.520 --> 0:37:03.880
<v Speaker 8>got one a couple of weeks ago from the electric

0:37:03.880 --> 0:37:05.680
<v Speaker 8>company told me if I didn't pay in forty five minutes,

0:37:05.719 --> 0:37:07.200
<v Speaker 8>they're going to shut off my power, right, you know,

0:37:07.400 --> 0:37:09.480
<v Speaker 8>And because I work in the business, I'm like, yeah, this.

0:37:09.400 --> 0:37:11.200
<v Speaker 4>Is I guess what I'm saying is there's no shortage

0:37:11.200 --> 0:37:14.120
<v Speaker 4>of bad actors. No, like there you know, there's no

0:37:14.200 --> 0:37:16.480
<v Speaker 4>chance that the bad actors are going to tag their

0:37:16.560 --> 0:37:19.080
<v Speaker 4>jenai with any sort of metadata that will show that

0:37:19.120 --> 0:37:19.720
<v Speaker 4>it was generated.

0:37:19.920 --> 0:37:20.560
<v Speaker 1>No.

0:37:20.560 --> 0:37:24.200
<v Speaker 8>No, but there are ways and analytics techniques that can

0:37:24.239 --> 0:37:26.680
<v Speaker 8>be used to detect different types of activities.

0:37:27.160 --> 0:37:29.919
<v Speaker 4>But the problem is that it's only the best line

0:37:29.920 --> 0:37:33.800
<v Speaker 4>of defense is a person right oftentimes, and people don't

0:37:33.800 --> 0:37:34.960
<v Speaker 4>have that type of training.

0:37:35.640 --> 0:37:38.839
<v Speaker 8>No, they don't. I mean I've I've told any number

0:37:38.840 --> 0:37:40.959
<v Speaker 8>of people you know, pretty much, don't click on any

0:37:41.000 --> 0:37:43.160
<v Speaker 8>link in any email, don't click on any pop up ad,

0:37:43.160 --> 0:37:46.680
<v Speaker 8>don't you know. But you know, the fraudsters are getting sophisticated.

0:37:46.680 --> 0:37:49.640
<v Speaker 8>In fact, a current trendy is now that the old

0:37:49.680 --> 0:37:53.240
<v Speaker 8>style fraudsters are no longer committing fraud. They're just creating

0:37:53.280 --> 0:37:57.399
<v Speaker 8>toolkits personas you know, mule accounts, other types of things,

0:37:57.440 --> 0:38:00.040
<v Speaker 8>and selling the fraudsters actually commit the actual fraud.

0:37:59.840 --> 0:38:02.400
<v Speaker 4>Now and shovels where that's where the money is.

0:38:02.560 --> 0:38:06.000
<v Speaker 2>Are we more secure than we used to be? Are

0:38:06.080 --> 0:38:10.400
<v Speaker 2>we more vulnerable because there are a lot of tools

0:38:10.400 --> 0:38:13.120
<v Speaker 2>out there to enable people.

0:38:12.840 --> 0:38:13.880
<v Speaker 5>To trick us.

0:38:14.160 --> 0:38:18.120
<v Speaker 8>I think it's a constant battle. I think in many ways.

0:38:18.360 --> 0:38:22.759
<v Speaker 8>You know, despite you know, my earlier statement that everybody's

0:38:22.760 --> 0:38:25.160
<v Speaker 8>information is compromised to some extent, I mean pretty much,

0:38:25.200 --> 0:38:27.520
<v Speaker 8>you know, your social Security numbers out there, address name,

0:38:27.560 --> 0:38:30.120
<v Speaker 8>all that type of stuff's out there. But how you know,

0:38:30.160 --> 0:38:32.799
<v Speaker 8>and there's definitely identity theft happening, and it's and it's

0:38:32.800 --> 0:38:35.960
<v Speaker 8>on the rise, and it continues to occur. But is

0:38:35.960 --> 0:38:39.040
<v Speaker 8>it a daily occurrence for most individuals? No, you know,

0:38:39.200 --> 0:38:41.640
<v Speaker 8>is it reasonable to say that at some point in

0:38:41.680 --> 0:38:44.600
<v Speaker 8>your life, you know, probably within the next five to

0:38:44.640 --> 0:38:47.960
<v Speaker 8>ten years at most, you know, everybody will have some

0:38:48.160 --> 0:38:50.520
<v Speaker 8>type of identity compromise of some sort. Yeah, I think

0:38:50.520 --> 0:38:51.759
<v Speaker 8>that's that's a legitimate thing.

0:38:51.800 --> 0:38:53.319
<v Speaker 2>But what does that mean is that just the case

0:38:53.360 --> 0:38:56.480
<v Speaker 2>of a we tapped into your health insured your are

0:38:56.480 --> 0:38:58.560
<v Speaker 2>you doing on that level or something more serious?

0:38:58.600 --> 0:38:59.759
<v Speaker 5>When you say that it.

0:38:59.760 --> 0:39:01.960
<v Speaker 8>Could be more serious. It could be that they opened

0:39:02.040 --> 0:39:04.960
<v Speaker 8>up a credit card in your name, you know, and

0:39:05.000 --> 0:39:06.680
<v Speaker 8>then the first thing you notice is when it shows

0:39:06.760 --> 0:39:09.200
<v Speaker 8>up on your credit report, which hopefully you check regularly,

0:39:09.760 --> 0:39:11.279
<v Speaker 8>and then you see that and then you can deal

0:39:11.320 --> 0:39:13.600
<v Speaker 8>with it and get rid of it. It could be

0:39:13.760 --> 0:39:17.240
<v Speaker 8>that you know somebody somebody like there's been the cases

0:39:17.280 --> 0:39:19.680
<v Speaker 8>lately with houses where people are selling houses that they

0:39:19.719 --> 0:39:22.560
<v Speaker 8>don't own, you know, and are you actually able to,

0:39:23.320 --> 0:39:25.680
<v Speaker 8>you know, rely on people to find this stuff for you?

0:39:25.800 --> 0:39:27.880
<v Speaker 8>And who do you rely on? I think that the

0:39:27.920 --> 0:39:31.080
<v Speaker 8>tools are out there to make it better overall, and

0:39:31.120 --> 0:39:33.920
<v Speaker 8>in one sense you are more secure, but you're constantly

0:39:33.960 --> 0:39:34.680
<v Speaker 8>fighting a battle.

0:39:34.800 --> 0:39:37.120
<v Speaker 4>Wasn't this the promise of the blockchain? And it's kind

0:39:37.120 --> 0:39:38.880
<v Speaker 4>of a perfect segue to talking to you about crypto

0:39:38.920 --> 0:39:40.520
<v Speaker 4>a little bit and how your life has become more

0:39:40.560 --> 0:39:42.920
<v Speaker 4>complicated in a result of crypto. But wasn't this the

0:39:42.920 --> 0:39:44.799
<v Speaker 4>promise of the blockchain that we'd all have our own

0:39:45.239 --> 0:39:48.560
<v Speaker 4>identifying information with us at all times. Our house was

0:39:48.560 --> 0:39:50.240
<v Speaker 4>our house, because it's said so on a ledger.

0:39:51.800 --> 0:39:54.479
<v Speaker 8>It could be to a certain extent if it is out,

0:39:54.600 --> 0:39:58.160
<v Speaker 8>you know, if it's already everything was already on the blockchain,

0:39:59.280 --> 0:40:02.800
<v Speaker 8>but it's not. One of the challenges I think overall

0:40:02.840 --> 0:40:05.799
<v Speaker 8>with the blockchain is that you know, bad data as

0:40:05.840 --> 0:40:09.239
<v Speaker 8>well as good data becomes permanent. That becomes a bit

0:40:09.280 --> 0:40:11.000
<v Speaker 8>of a challenge when you start dealing with, you know,

0:40:11.040 --> 0:40:13.800
<v Speaker 8>some of these things along the way. You know, blockchain

0:40:13.880 --> 0:40:16.560
<v Speaker 8>is not everywhere at the moment. So like you mentioned

0:40:16.640 --> 0:40:19.440
<v Speaker 8>owning a house that's not on a blockchain right now,

0:40:19.480 --> 0:40:22.080
<v Speaker 8>there's a fairly good chance it's in some you know,

0:40:22.320 --> 0:40:24.279
<v Speaker 8>local county clerks, registrars or.

0:40:24.400 --> 0:40:26.560
<v Speaker 5>Sound like you think it will be either in the near.

0:40:26.400 --> 0:40:28.840
<v Speaker 8>Future not in the near future. I think aspects of

0:40:28.880 --> 0:40:30.960
<v Speaker 8>it definitely. I mean there's a lot of activity and

0:40:31.040 --> 0:40:34.319
<v Speaker 8>you know, decentralized finance, you mentioned cryptocurrency. You know, there

0:40:34.320 --> 0:40:37.920
<v Speaker 8>are some definite areas where I think that it already

0:40:37.920 --> 0:40:39.960
<v Speaker 8>exists and it will continue to grow in some of

0:40:39.960 --> 0:40:43.920
<v Speaker 8>those areas. But is it something that is going to

0:40:43.920 --> 0:40:46.320
<v Speaker 8>happen in the next you know, year, two, five years,

0:40:46.360 --> 0:40:48.600
<v Speaker 8>ten years. I don't think quite so much.

0:40:48.680 --> 0:40:50.719
<v Speaker 2>I mean, I hate to play like Armageddon and like

0:40:50.800 --> 0:40:52.719
<v Speaker 2>you know, the Dark Day, But I mean, is there

0:40:52.719 --> 0:40:55.160
<v Speaker 2>a moment in time that you would anticipate just because

0:40:55.160 --> 0:40:57.160
<v Speaker 2>things are getting so much more sophisticated and the tools

0:40:57.160 --> 0:40:59.680
<v Speaker 2>are out there and everybody's doing compliance is certainly trying

0:40:59.719 --> 0:41:01.120
<v Speaker 2>to keep on it. But there's going to be a

0:41:01.120 --> 0:41:04.280
<v Speaker 2>point where you go to access your bank and you can't,

0:41:04.560 --> 0:41:07.440
<v Speaker 2>or you go to look at your investments and they're wiped.

0:41:07.560 --> 0:41:10.520
<v Speaker 5>Like is that the scale? And again, I'm not trying

0:41:10.560 --> 0:41:13.120
<v Speaker 5>to be aclammatory, but I'm just trying to be realistic.

0:41:13.400 --> 0:41:15.520
<v Speaker 8>Of I don't think that it's going to get quite

0:41:15.600 --> 0:41:19.480
<v Speaker 8>to that because, if nothing else, the financial institutions have

0:41:19.560 --> 0:41:22.080
<v Speaker 8>some pretty strong controls in place for things like that,

0:41:22.160 --> 0:41:25.239
<v Speaker 8>and they also, you know, many of them will you know,

0:41:25.400 --> 0:41:28.080
<v Speaker 8>reimburse you for different types of activities that happen along

0:41:28.080 --> 0:41:29.279
<v Speaker 8>the way. And I mean, if you went into your

0:41:29.280 --> 0:41:33.359
<v Speaker 8>brokerage account all your investments are gone, you know they

0:41:33.400 --> 0:41:34.719
<v Speaker 8>are going to be taking a look at that to

0:41:34.719 --> 0:41:37.000
<v Speaker 8>figure out what happens. But most likely when they saw

0:41:37.040 --> 0:41:39.080
<v Speaker 8>somebody trying to sell out of your entire portfolio and

0:41:39.120 --> 0:41:42.000
<v Speaker 8>transfer the money it would raise twenty seven red flags

0:41:42.000 --> 0:41:43.239
<v Speaker 8>along the way, and they would have blocked it a

0:41:43.280 --> 0:41:43.600
<v Speaker 8>little bit.

0:41:43.719 --> 0:41:45.799
<v Speaker 5>Right when you're traveling in credit card company calls and

0:41:45.800 --> 0:41:47.040
<v Speaker 5>says it's is you because.

0:41:46.840 --> 0:41:50.160
<v Speaker 2>Yeah, exactly, really there good stuff, but it puts it

0:41:50.200 --> 0:41:52.200
<v Speaker 2>on but it puts it on you.

0:41:52.320 --> 0:41:53.759
<v Speaker 8>It does put it on you because if you didn't

0:41:53.760 --> 0:41:55.759
<v Speaker 8>answer the text, well, then they're going to block it.

0:41:55.880 --> 0:41:57.719
<v Speaker 8>And then that means that your credit card might be

0:41:57.760 --> 0:42:00.560
<v Speaker 8>locked in a particular country because you didn't your text.

0:42:00.600 --> 0:42:03.040
<v Speaker 5>And so there's an awareness on like all levels, right.

0:42:03.040 --> 0:42:05.400
<v Speaker 8>Yeah, And it's not like every asset is protected at

0:42:05.400 --> 0:42:07.720
<v Speaker 8>the same level. Like you know, somebody is selling your house.

0:42:07.840 --> 0:42:10.600
<v Speaker 8>I mean, it's that's protected at one level somebody. You know,

0:42:10.640 --> 0:42:13.040
<v Speaker 8>if your credit cards are protected differently from your debit cards,

0:42:13.080 --> 0:42:16.080
<v Speaker 8>which are protected differently from your brokerage account, you know,

0:42:16.120 --> 0:42:18.480
<v Speaker 8>there are different rules in place for all of those,

0:42:19.680 --> 0:42:23.000
<v Speaker 8>you know, and it means that you can't be oblivious.

0:42:23.360 --> 0:42:25.440
<v Speaker 8>You know, you have to be somewhat vigilant. You have

0:42:25.480 --> 0:42:27.799
<v Speaker 8>to check your credit report, you have to make sure

0:42:27.840 --> 0:42:29.360
<v Speaker 8>that like you know, if you do get a text

0:42:29.360 --> 0:42:32.160
<v Speaker 8>from your bank, first of all, make sure it actually

0:42:32.239 --> 0:42:36.120
<v Speaker 8>is from your bank, right, you know, and then you know.

0:42:36.360 --> 0:42:39.160
<v Speaker 2>Just plenty of stuff there to keep you busy.

0:42:39.840 --> 0:42:41.600
<v Speaker 4>Check your credit report to the to do list. Okay,

0:42:41.680 --> 0:42:43.839
<v Speaker 4>I do absolutely good, right, That's what I like to hear.

0:42:44.239 --> 0:42:47.640
<v Speaker 4>Rob Mehra is a principal in EUIs Consulting Practice, joining

0:42:47.680 --> 0:42:49.440
<v Speaker 4>us here at a smash connect.

0:42:50.920 --> 0:42:54.760
<v Speaker 1>You're listening to the Bloomberg Business Week podcast. Listen live

0:42:54.880 --> 0:42:58.000
<v Speaker 1>each weekday starting a two pm Eastern Apple card Play

0:42:58.080 --> 0:43:00.960
<v Speaker 1>and and Royd Auto with the Bloomberg Busines. You can

0:43:00.960 --> 0:43:04.200
<v Speaker 1>also listen live on Amazon Alexa from our flagship New

0:43:04.280 --> 0:43:09.160
<v Speaker 1>York station Just Say Alexa playing Bloomberg eleven thirty.

0:43:10.120 --> 0:43:12.440
<v Speaker 4>We just had kind of a sobering conversation with all

0:43:12.440 --> 0:43:15.880
<v Speaker 4>the risks associated with AI, with data, our data being

0:43:15.920 --> 0:43:16.640
<v Speaker 4>out there.

0:43:16.360 --> 0:43:19.120
<v Speaker 2>Still telling us stories about fraud and just romance, fraud,

0:43:19.120 --> 0:43:21.279
<v Speaker 2>pig butchering, which we've done stories, our team has done

0:43:21.280 --> 0:43:24.000
<v Speaker 2>reporting on that. Like it's just every day, there's tons

0:43:24.040 --> 0:43:24.560
<v Speaker 2>of stuff going on.

0:43:24.640 --> 0:43:26.360
<v Speaker 4>Needless to say, I think it keeps a lot of

0:43:26.360 --> 0:43:28.560
<v Speaker 4>folks up at night who are thinking about risk and

0:43:28.640 --> 0:43:31.120
<v Speaker 4>risk management. And that's exactly what our next guest focus

0:43:31.200 --> 0:43:34.160
<v Speaker 4>is on providing compliance and risk technology for nineteen of

0:43:34.200 --> 0:43:36.719
<v Speaker 4>the world's twenty largest banks in addition to serving other

0:43:36.760 --> 0:43:40.480
<v Speaker 4>customers of smash. Tom Badget is president of Enterprise Business

0:43:40.520 --> 0:43:43.959
<v Speaker 4>at smartsh He's here on site with us at Smarsh Connect. Tom,

0:43:43.960 --> 0:43:44.440
<v Speaker 4>how are you.

0:43:44.560 --> 0:43:46.839
<v Speaker 6>I'm doing well, Thanks so much for having us here.

0:43:46.840 --> 0:43:49.680
<v Speaker 6>Thanks for joining us. Tim Carroll great, Yeah.

0:43:49.719 --> 0:43:51.279
<v Speaker 4>How would you describe what you do here?

0:43:52.480 --> 0:43:55.880
<v Speaker 6>Great question? So we really so what I do personally personally,

0:43:56.000 --> 0:43:58.640
<v Speaker 6>so I've run so we have really two segments of

0:43:58.680 --> 0:44:02.680
<v Speaker 6>our business. We have small medium business think registered independent agents,

0:44:02.719 --> 0:44:06.160
<v Speaker 6>small shops ten to one hundred people. And then we

0:44:06.200 --> 0:44:09.759
<v Speaker 6>service the largest financial institutions in the world. And in

0:44:09.840 --> 0:44:13.480
<v Speaker 6>what you find, while we delivered similar sets of capabilities,

0:44:13.960 --> 0:44:17.440
<v Speaker 6>very very different needs. So when you're talking to the

0:44:17.640 --> 0:44:21.640
<v Speaker 6>largest financial institutions globally, they're worried about things that maybe

0:44:21.640 --> 0:44:24.520
<v Speaker 6>are a little bit different than some of the smaller companies.

0:44:24.960 --> 0:44:28.880
<v Speaker 6>Still regulated, but looking for a lot of complexity that

0:44:28.920 --> 0:44:32.200
<v Speaker 6>maybe isn't inherent in all smaller organization.

0:44:32.280 --> 0:44:34.360
<v Speaker 2>I always say that conversation that Jamie Diamond did, I

0:44:34.400 --> 0:44:36.200
<v Speaker 2>don't know is it now, ten years ago, fifteen years

0:44:36.239 --> 0:44:37.800
<v Speaker 2>ago up on stage and he said like they were like,

0:44:37.880 --> 0:44:39.279
<v Speaker 2>what's the thing that keeps him up at night, what's

0:44:39.280 --> 0:44:41.719
<v Speaker 2>the number? We think he was talking about cybersecurity guys

0:44:42.280 --> 0:44:44.600
<v Speaker 2>and the technology spend and that he was focusing on it,

0:44:44.640 --> 0:44:46.680
<v Speaker 2>And I think about, Okay, here we are over a

0:44:46.680 --> 0:44:49.200
<v Speaker 2>decade or so later, and I can just think top

0:44:49.200 --> 0:44:51.880
<v Speaker 2>of mind, what the executives say that they need to

0:44:51.880 --> 0:44:52.479
<v Speaker 2>be thinking about.

0:44:52.640 --> 0:44:55.719
<v Speaker 6>It's a huge board level topic. Yeah, right, what are

0:44:55.760 --> 0:44:58.560
<v Speaker 6>the risks we're exposed to? Obviously two thousand and eight

0:44:58.600 --> 0:45:02.800
<v Speaker 6>had a huge impact on this space, so the ability

0:45:02.840 --> 0:45:05.759
<v Speaker 6>to and what's really exciting now too is we've gone

0:45:05.800 --> 0:45:08.240
<v Speaker 6>from a world where we've we've gotten all this information,

0:45:08.320 --> 0:45:12.360
<v Speaker 6>petabytes and petabytes of information, all the communications with customers,

0:45:12.640 --> 0:45:14.879
<v Speaker 6>and it's been really more of a okay, what can

0:45:14.920 --> 0:45:17.239
<v Speaker 6>we personally find out there that might be there and

0:45:17.320 --> 0:45:20.120
<v Speaker 6>utilizing AI to do that? I know, buzzword AI, right,

0:45:20.160 --> 0:45:23.720
<v Speaker 6>But now it's turned into a world with generative AI. Okay,

0:45:23.760 --> 0:45:26.760
<v Speaker 6>what can the machines tell us that maybe we never thought?

0:45:27.360 --> 0:45:29.799
<v Speaker 6>How can we take this information whis hugely critical to

0:45:29.840 --> 0:45:33.399
<v Speaker 6>protect our institutions but also make us better at what

0:45:33.440 --> 0:45:33.759
<v Speaker 6>we do?

0:45:33.920 --> 0:45:38.480
<v Speaker 2>Why will generative AI machine learning kind of make us

0:45:38.520 --> 0:45:40.719
<v Speaker 2>be better when it comes to risk and compliance?

0:45:40.960 --> 0:45:43.319
<v Speaker 6>Yeah? So it helps So think of it this way,

0:45:43.320 --> 0:45:46.240
<v Speaker 6>and it can get like some I'm even like, what

0:45:46.280 --> 0:45:48.200
<v Speaker 6>the heck? So we've been using a all of us

0:45:48.200 --> 0:45:49.160
<v Speaker 6>have been using AI.

0:45:48.920 --> 0:45:50.239
<v Speaker 5>For a long term, and we keep saying that too

0:45:50.280 --> 0:45:52.080
<v Speaker 5>as it's not a new thing.

0:45:52.200 --> 0:45:53.000
<v Speaker 6>Yeah, it's not a new thing.

0:45:53.000 --> 0:45:55.439
<v Speaker 5>So what it can do its capability.

0:45:55.960 --> 0:45:58.680
<v Speaker 6>So think part of what we're doing now is generative.

0:45:59.400 --> 0:46:02.319
<v Speaker 6>We're bringing things. So it's that difference between Okay, I'm

0:46:02.320 --> 0:46:04.000
<v Speaker 6>gonna tell it what to look for and what to

0:46:04.080 --> 0:46:06.600
<v Speaker 6>ask and then it comes back and gives me something

0:46:06.640 --> 0:46:09.880
<v Speaker 6>based on loads and loads of information. Generative is the

0:46:09.960 --> 0:46:12.879
<v Speaker 6>machines really thinking and thinking things that Caroly, you didn't

0:46:12.920 --> 0:46:15.279
<v Speaker 6>think of, Tim, you didn't think of, I didn't think of,

0:46:15.360 --> 0:46:17.960
<v Speaker 6>and wow, I never thought of that, And wow that

0:46:17.960 --> 0:46:19.600
<v Speaker 6>could now protect me in a way that I never

0:46:19.640 --> 0:46:23.360
<v Speaker 6>knew I even even to look at. It's really really exciting.

0:46:23.400 --> 0:46:26.239
<v Speaker 4>I understand this from product development perspective. I understand it

0:46:26.239 --> 0:46:29.520
<v Speaker 4>from a drug development perspective. Carol, and I've talked to

0:46:29.719 --> 0:46:32.759
<v Speaker 4>our colleagues at Bloomberg who've reported extensively on those. But

0:46:32.800 --> 0:46:35.840
<v Speaker 4>when you think of financial services, what can it provide

0:46:35.920 --> 0:46:37.160
<v Speaker 4>that that we don't know is out there?

0:46:37.320 --> 0:46:39.960
<v Speaker 6>There's so much so, So first and foremost, let's think better,

0:46:40.040 --> 0:46:42.839
<v Speaker 6>better service, right, So think about what we deal with

0:46:42.920 --> 0:46:46.920
<v Speaker 6>for for your your listeners are communications intelligence. So all

0:46:46.960 --> 0:46:49.960
<v Speaker 6>communications data that a financial institution might have with their

0:46:49.960 --> 0:46:54.200
<v Speaker 6>customer has to be stored archived. Okay, So the ability

0:46:54.200 --> 0:46:55.719
<v Speaker 6>to go in and say how many how many things

0:46:55.760 --> 0:46:57.520
<v Speaker 6>you see out there, like, well, what do our customers

0:46:57.560 --> 0:47:00.440
<v Speaker 6>really want? What do they need? Well, you now know

0:47:00.560 --> 0:47:03.719
<v Speaker 6>and can see and understand and hear firsthand what it

0:47:03.800 --> 0:47:07.120
<v Speaker 6>is they're looking for, and it's oftentimes it's so buried

0:47:07.440 --> 0:47:10.279
<v Speaker 6>in massive volumes. It's beyond looking for a needle in

0:47:10.320 --> 0:47:13.040
<v Speaker 6>a haystack and haystack and a haystack. It's even more well,

0:47:13.080 --> 0:47:15.520
<v Speaker 6>now the machines can go through and figure that out

0:47:15.520 --> 0:47:18.920
<v Speaker 6>and provide a better level of service or potentially protect

0:47:19.080 --> 0:47:20.320
<v Speaker 6>the organization.

0:47:19.920 --> 0:47:22.080
<v Speaker 2>Where they make sure that the machines that are going

0:47:22.120 --> 0:47:25.640
<v Speaker 2>in and either providing or going to provide better service

0:47:25.920 --> 0:47:29.719
<v Speaker 2>or better you know catching you know, problems where there's

0:47:29.840 --> 0:47:31.719
<v Speaker 2>kind of risks if you will, how do you make

0:47:31.719 --> 0:47:33.319
<v Speaker 2>sure that they're going to do the right thing? Because

0:47:33.360 --> 0:47:35.760
<v Speaker 2>it's only as good as the information that goes into.

0:47:35.560 --> 0:47:39.280
<v Speaker 6>It, and you just hit on the magic question, which is, okay,

0:47:39.600 --> 0:47:41.480
<v Speaker 6>do we just turn these loose in a way we

0:47:41.520 --> 0:47:43.840
<v Speaker 6>go to answer that is no. So you need to

0:47:43.840 --> 0:47:46.680
<v Speaker 6>make sure that the large LLM large language models that

0:47:46.719 --> 0:47:49.600
<v Speaker 6>are being used, that there's some level of oversight on

0:47:49.680 --> 0:47:52.080
<v Speaker 6>those and what is included there. So the machine can

0:47:52.120 --> 0:47:54.200
<v Speaker 6>go off in a way that you never intended to. Right,

0:47:54.320 --> 0:47:57.120
<v Speaker 6>So there also needs so they call it drift machine

0:47:57.160 --> 0:48:00.000
<v Speaker 6>drift it starts to drift off, there needs to continue

0:48:00.120 --> 0:48:01.680
<v Speaker 6>to be This is why it's a bit of a faucy.

0:48:01.719 --> 0:48:03.720
<v Speaker 6>You'll hear all jobs will be gone. That's not true.

0:48:04.239 --> 0:48:06.879
<v Speaker 6>Jobs will change, they'll be different, but you'll need people

0:48:06.880 --> 0:48:08.760
<v Speaker 6>to look and say, this model is starting to drift

0:48:08.760 --> 0:48:10.279
<v Speaker 6>in a way we never wanted it to, or a

0:48:10.320 --> 0:48:12.080
<v Speaker 6>minute to hey let's rain this back in.

0:48:12.800 --> 0:48:14.160
<v Speaker 4>What jobs do you think all at risk?

0:48:15.200 --> 0:48:17.680
<v Speaker 6>You know what I would say is anything that is

0:48:17.680 --> 0:48:20.719
<v Speaker 6>is and I don't think it's risk isn't necessarily the

0:48:20.800 --> 0:48:22.760
<v Speaker 6>right word, But hey, what are ones that the machines

0:48:22.800 --> 0:48:25.839
<v Speaker 6>do really think repetitive in nature? So let me give

0:48:25.880 --> 0:48:28.480
<v Speaker 6>you an example. So one of the areas on AI

0:48:28.640 --> 0:48:31.920
<v Speaker 6>right now some organizations had historically used was okay, I

0:48:32.040 --> 0:48:34.680
<v Speaker 6>just got at one point in time we would get

0:48:35.360 --> 0:48:46.600
<v Speaker 6>we would get a thousands, very cute, a thousand notifications

0:48:46.640 --> 0:48:50.680
<v Speaker 6>of things. It might potentially be risky communications. All right,

0:48:50.719 --> 0:48:53.480
<v Speaker 6>so you may have a team of people that go

0:48:53.600 --> 0:48:57.040
<v Speaker 6>through that in a in a email. Let's use email,

0:48:57.239 --> 0:49:01.040
<v Speaker 6>email by email. What did Carol really mean here? Well,

0:49:01.480 --> 0:49:03.719
<v Speaker 6>when she was talking about her children at home, she

0:49:03.760 --> 0:49:05.800
<v Speaker 6>really meant her children at home. I asked that question.

0:49:07.239 --> 0:49:10.239
<v Speaker 4>Yeah, so there's a machine that can help me.

0:49:10.360 --> 0:49:15.040
<v Speaker 6>That's a that's a level of and very rarely do speople.

0:49:15.320 --> 0:49:18.160
<v Speaker 6>I love doing that. And now think about it this way.

0:49:18.360 --> 0:49:22.560
<v Speaker 6>What used to be thousands of identified now is millions.

0:49:23.040 --> 0:49:25.480
<v Speaker 6>Well what had been a solution is okay, we just

0:49:25.520 --> 0:49:27.640
<v Speaker 6>need to get a lot of people to look at that.

0:49:28.160 --> 0:49:29.839
<v Speaker 5>So what do they call it? Tech adjacent or human?

0:49:29.960 --> 0:49:30.000
<v Speaker 3>Like?

0:49:30.080 --> 0:49:30.279
<v Speaker 5>Right?

0:49:30.440 --> 0:49:30.520
<v Speaker 9>That?

0:49:30.880 --> 0:49:34.200
<v Speaker 2>Bas think technology adjacent with human or like working together side?

0:49:34.239 --> 0:49:36.359
<v Speaker 2>I forgive me if I'm mangling the term.

0:49:36.640 --> 0:49:37.799
<v Speaker 6>Yeah, very much.

0:49:37.800 --> 0:49:39.920
<v Speaker 2>So you know, I'm listening to you speak, and I

0:49:39.960 --> 0:49:42.600
<v Speaker 2>know the financial community is kind of your bread and butter,

0:49:42.640 --> 0:49:44.680
<v Speaker 2>and that's your guys focus. But I'm thinking about the

0:49:44.719 --> 0:49:47.279
<v Speaker 2>world of social media in general and the problems that

0:49:47.360 --> 0:49:51.000
<v Speaker 2>are there that why can you It sounds like from

0:49:51.040 --> 0:49:54.880
<v Speaker 2>your knowledge and expertise to create something that can also

0:49:54.920 --> 0:50:01.000
<v Speaker 2>go in and scrape the things that are incorrect, false, wrong, dangerous.

0:50:01.440 --> 0:50:05.160
<v Speaker 2>So for me, is it that potentially easy?

0:50:05.320 --> 0:50:08.640
<v Speaker 6>The technology is there? Yeah, So from from our perspective,

0:50:08.680 --> 0:50:08.960
<v Speaker 6>we do.

0:50:09.080 --> 0:50:09.200
<v Speaker 8>So.

0:50:09.239 --> 0:50:11.000
<v Speaker 6>It's one of the communications.

0:50:10.360 --> 0:50:11.880
<v Speaker 5>That we need to do right to protect this.

0:50:12.239 --> 0:50:15.959
<v Speaker 6>Absolutely. So our customers have to make sure that tim

0:50:16.000 --> 0:50:18.720
<v Speaker 6>works for our institution and you have a Twitter account,

0:50:18.800 --> 0:50:20.400
<v Speaker 6>we have to make sure that that is something that

0:50:20.400 --> 0:50:22.680
<v Speaker 6>we can capture, that we make sure that nothing's going

0:50:22.719 --> 0:50:26.200
<v Speaker 6>out in a way for that financial institution. We absolutely

0:50:26.280 --> 0:50:26.520
<v Speaker 6>do that.

0:50:26.560 --> 0:50:28.959
<v Speaker 5>But I mean bigger broadly in terms of social media.

0:50:29.000 --> 0:50:30.960
<v Speaker 2>You know that I'm not necessarily trying to put you

0:50:31.000 --> 0:50:33.320
<v Speaker 2>on the spot, but this idea of social media and

0:50:33.360 --> 0:50:36.440
<v Speaker 2>all of the bad information that's out there, and it

0:50:36.480 --> 0:50:38.160
<v Speaker 2>doesn't seem like we can get a grasp on it,

0:50:38.160 --> 0:50:38.920
<v Speaker 2>but it sounds.

0:50:38.680 --> 0:50:42.560
<v Speaker 6>Like technologically the ability. Now, then you get into other like, hey,

0:50:42.800 --> 0:50:44.600
<v Speaker 6>what do we want to do? I won't I won't

0:50:44.640 --> 0:50:46.440
<v Speaker 6>get into that, but hey, what do we want to

0:50:46.440 --> 0:50:48.200
<v Speaker 6>be able to look at? What do we want to limit?

0:50:48.640 --> 0:50:51.640
<v Speaker 6>But the technology and keep in mind too, we don't

0:50:52.000 --> 0:50:55.680
<v Speaker 6>say not what you can to do, but we will identify, Hey,

0:50:55.719 --> 0:50:59.200
<v Speaker 6>this communication that went out is not in compliance with

0:50:59.280 --> 0:51:01.640
<v Speaker 6>your standards. That is something that we absolutely do, and

0:51:01.719 --> 0:51:03.480
<v Speaker 6>financial institutions are all over that.

0:51:03.520 --> 0:51:04.960
<v Speaker 4>Give us an idea of how often that happens.

0:51:05.040 --> 0:51:08.359
<v Speaker 6>Yeah, gosh, it's crazy and oftentimes here the biggest challenge

0:51:08.360 --> 0:51:10.800
<v Speaker 6>of financial institutions have are false positive.

0:51:11.680 --> 0:51:13.600
<v Speaker 5>So so let's happens a lot.

0:51:14.080 --> 0:51:18.680
<v Speaker 6>Yeah, sure, because what can happen is the bad folks

0:51:19.000 --> 0:51:22.520
<v Speaker 6>are really really creative. So you know, I'll use an example.

0:51:22.520 --> 0:51:24.080
<v Speaker 6>I always tell my wife, she's like, what do you do.

0:51:24.160 --> 0:51:25.640
<v Speaker 6>Nobody's gonna say, Hey, I think I'm gonna do an

0:51:25.680 --> 0:51:28.640
<v Speaker 6>insider trade. I'm feeling like this is something I need

0:51:28.680 --> 0:51:31.200
<v Speaker 6>to do. Now there's gonna be they'll go from chant

0:51:31.280 --> 0:51:35.000
<v Speaker 6>what we say, cross channel, Hey, let's take this offline. Yeah,

0:51:35.160 --> 0:51:37.080
<v Speaker 6>those are the types of things. So the machine can

0:51:37.120 --> 0:51:41.560
<v Speaker 6>go in and identify intent even and say, hey, you

0:51:41.600 --> 0:51:43.040
<v Speaker 6>probably need to look at this.

0:51:42.960 --> 0:51:47.360
<v Speaker 4>One, meaning asking somebody to take it off to a

0:51:47.360 --> 0:51:48.040
<v Speaker 4>different form.

0:51:47.920 --> 0:51:50.400
<v Speaker 6>Of Tim Tim said go pick up my children from school.

0:51:51.400 --> 0:51:53.520
<v Speaker 6>Tim really meant go pick up my children from school.

0:51:54.239 --> 0:51:56.480
<v Speaker 6>Or Tim said go pick up my children from school,

0:51:56.480 --> 0:51:58.800
<v Speaker 6>and somebody else said, well, the children at school waiting

0:51:58.840 --> 0:52:01.319
<v Speaker 6>for you to pull the all of a sudden, the

0:52:01.360 --> 0:52:03.720
<v Speaker 6>machine can pick that. And again one of the challenges

0:52:03.760 --> 0:52:07.799
<v Speaker 6>that now the volumes of data are so massive, which

0:52:07.880 --> 0:52:11.200
<v Speaker 6>really a lot of that came from COVID, where I

0:52:11.320 --> 0:52:13.399
<v Speaker 6>used to be able to dictate and mandate to you, Tim,

0:52:13.560 --> 0:52:16.200
<v Speaker 6>you can't use plug into a name.

0:52:16.280 --> 0:52:19.480
<v Speaker 4>Well, okay, so are you capturing You capture communications on

0:52:19.520 --> 0:52:20.319
<v Speaker 4>the phone.

0:52:20.000 --> 0:52:24.080
<v Speaker 6>Over one hundred different channels of communication, but voices something

0:52:24.080 --> 0:52:26.200
<v Speaker 6>it's a little more difficult, something that we are working

0:52:26.200 --> 0:52:28.440
<v Speaker 6>on a lot. But you get in a transcription. The

0:52:28.520 --> 0:52:30.960
<v Speaker 6>crazy part about voice that gets into is and it's funny,

0:52:30.960 --> 0:52:35.080
<v Speaker 6>we had we have this conversation constantly. Spanish is not Spanish,

0:52:35.200 --> 0:52:37.800
<v Speaker 6>is not Spanish, It's not Spanish. English is not English.

0:52:37.880 --> 0:52:40.480
<v Speaker 6>So you have to The machines are still not great

0:52:40.560 --> 0:52:43.759
<v Speaker 6>at that, but from a technical person perspective, it is

0:52:43.800 --> 0:52:45.040
<v Speaker 6>absolutely something we look at.

0:52:45.120 --> 0:52:46.880
<v Speaker 4>So so phone's part of it, voice part of it,

0:52:46.920 --> 0:52:48.760
<v Speaker 4>and zoom teams all that stuff.

0:52:49.800 --> 0:52:53.279
<v Speaker 6>Yeah, yeah, so so all those and so use those

0:52:53.360 --> 0:52:58.799
<v Speaker 6>those examples. Pre COVID, I as a financial institution con

0:52:58.880 --> 0:53:01.399
<v Speaker 6>mandate you can't use this. You can't use this tool

0:53:01.440 --> 0:53:03.080
<v Speaker 6>to talk to your customers. All of a sudden, you

0:53:03.239 --> 0:53:05.960
<v Speaker 6>have to use it to talk to your customers. So

0:53:06.200 --> 0:53:10.600
<v Speaker 6>there's been such an explosion of data. You know, it's funny.

0:53:10.640 --> 0:53:14.040
<v Speaker 6>I joke sometimes with our customers. I say, we adopted

0:53:14.040 --> 0:53:16.600
<v Speaker 6>this crazy concept back in twenty seventeen. I think you

0:53:16.600 --> 0:53:20.760
<v Speaker 6>talked to Steve earlier called the cloud well, and truly

0:53:20.800 --> 0:53:23.680
<v Speaker 6>at that time people thought we were nuts. People said,

0:53:23.719 --> 0:53:26.200
<v Speaker 6>nobody will ever put their compliance data in the cloud.

0:53:26.239 --> 0:53:29.920
<v Speaker 6>It will not happen. Now it's the only way to scale.

0:53:30.280 --> 0:53:33.239
<v Speaker 6>So COVID hits now we have these on prem. I'm

0:53:33.280 --> 0:53:35.520
<v Speaker 6>you know, I'm using these terms on prem.

0:53:35.960 --> 0:53:37.759
<v Speaker 5>PREMI yeah, enterprise systems and so.

0:53:37.960 --> 0:53:39.960
<v Speaker 6>All of a sudden, I'm an internal financial institution. I

0:53:40.040 --> 0:53:43.040
<v Speaker 6>have an on prem system and massive volumes of data.

0:53:43.080 --> 0:53:46.360
<v Speaker 6>The hardware costs alone to keep up with that. Versus

0:53:46.400 --> 0:53:48.360
<v Speaker 6>if you partner with a partner like us. We partner

0:53:48.400 --> 0:53:51.360
<v Speaker 6>with AWS Francis, they can scale like a globally.

0:53:51.520 --> 0:53:53.560
<v Speaker 2>What about speed and reliability? Like so I might say,

0:53:53.400 --> 0:53:55.080
<v Speaker 2>he listen, I want to have it closer. So maybe

0:53:55.120 --> 0:53:56.279
<v Speaker 2>I'm going to have a hybrid and I'm going to

0:53:56.320 --> 0:53:58.560
<v Speaker 2>play around cloud and you know, a little bit of combination.

0:53:58.600 --> 0:54:00.919
<v Speaker 5>Yeah, I don't know if that's a hunting you guys

0:54:00.960 --> 0:54:01.560
<v Speaker 5>at all it.

0:54:01.520 --> 0:54:02.719
<v Speaker 6>Does, and it's a conversation.

0:54:02.840 --> 0:54:04.080
<v Speaker 5>A lot of what we do is if you say,

0:54:04.120 --> 0:54:05.200
<v Speaker 5>don't do it, no.

0:54:04.960 --> 0:54:07.160
<v Speaker 6>No, So what we say and we show and a

0:54:07.200 --> 0:54:09.239
<v Speaker 6>lot of what we do is prove it's actually a

0:54:09.280 --> 0:54:11.840
<v Speaker 6>lot of the assumptions are not valid. So speed and

0:54:11.880 --> 0:54:17.520
<v Speaker 6>reliability and safety is actually higher in the cloud. So

0:54:17.600 --> 0:54:20.960
<v Speaker 6>these are institutions that that you know, these big hyper skills.

0:54:21.000 --> 0:54:25.360
<v Speaker 6>This is what they do and they're used to handling

0:54:25.400 --> 0:54:26.960
<v Speaker 6>those massive volumes.

0:54:26.960 --> 0:54:29.480
<v Speaker 2>Okay, oh go ahead, Well I know we have to

0:54:29.520 --> 0:54:32.880
<v Speaker 2>wrap thirty seconds. So I'm thinking about we Bloomberg investment

0:54:32.920 --> 0:54:35.640
<v Speaker 2>community and thinking about Okay, I'm listening you know to

0:54:35.680 --> 0:54:36.319
<v Speaker 2>Tom talk here.

0:54:36.360 --> 0:54:37.080
<v Speaker 5>So what does that mean?

0:54:37.120 --> 0:54:40.960
<v Speaker 2>Do you think you know, cloud is just it's just

0:54:41.000 --> 0:54:44.719
<v Speaker 2>going to grow even more exponentially, Like what what's the

0:54:44.840 --> 0:54:45.760
<v Speaker 2>investment thought?

0:54:46.040 --> 0:54:47.920
<v Speaker 5>Our thesis off of yeah, you are sick.

0:54:48.000 --> 0:54:51.000
<v Speaker 6>Cloud is here to stay, that's not going anywhere. And

0:54:51.040 --> 0:54:53.040
<v Speaker 6>in fact, oftentimes you get to a point where's like, well,

0:54:53.080 --> 0:54:54.759
<v Speaker 6>of course that's how you're going to scale it. Their

0:54:54.800 --> 0:54:57.480
<v Speaker 6>their organizations and companies. This is again what they do.

0:54:57.520 --> 0:54:59.600
<v Speaker 6>And when I say, what they do not just scale,

0:54:59.600 --> 0:55:02.600
<v Speaker 6>but they're used to those bad actors that are trying again.

0:55:02.680 --> 0:55:05.400
<v Speaker 6>They deal with that all the time. So again not

0:55:05.480 --> 0:55:07.840
<v Speaker 6>to get into too much technology, but we are a

0:55:08.080 --> 0:55:11.359
<v Speaker 6>what we call triple active architecture. So think at any

0:55:11.360 --> 0:55:13.920
<v Speaker 6>given time, your data is in three potential areas. So

0:55:13.960 --> 0:55:15.880
<v Speaker 6>if all of a sudden there's an event that happens

0:55:15.920 --> 0:55:19.480
<v Speaker 6>here shuts it down, you run with you never even

0:55:19.880 --> 0:55:20.239
<v Speaker 6>the other.

0:55:21.800 --> 0:55:24.080
<v Speaker 4>We got to run, but next you got You have

0:55:24.200 --> 0:55:26.360
<v Speaker 4>nineteen of the twenty largest banks when we talk to

0:55:26.360 --> 0:55:28.040
<v Speaker 4>you in a year, you can have twenty of twenty.

0:55:28.400 --> 0:55:30.279
<v Speaker 4>I'm pretty sure I want to share their names there

0:55:30.280 --> 0:55:30.560
<v Speaker 4>it is.

0:55:31.000 --> 0:55:32.279
<v Speaker 6>I got close a couple of times.

0:55:34.040 --> 0:55:36.400
<v Speaker 2>Tom Paget, Thank you, Thank you, really fun Tom Paget.

0:55:36.440 --> 0:55:38.440
<v Speaker 2>He's president Enterprise Business here at smash.

0:55:39.120 --> 0:55:42.920
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0:55:43.160 --> 0:55:47.080
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