Speaker 1: Bloomberg Audio Studios, Podcasts, radio news. This is Bloomberg Business
Speaker 1: Wait inside from the reporters and editors who bring you
Speaker 1: America's most trusted business magazine, plus global business, finance and
Speaker 1: tech news. The Bloomberg Business Week Podcast with Carol Messer
Speaker 1: and Tim Stenebeck from Bloomberg Radio.
Speaker 2: Steve Marsh is with us, a chairman and founder of
Speaker 2: Smash and joining us here on site. First of all,
Speaker 2: compliance is a big issue, and it has been growing,
Speaker 2: I think, coming off the Great Financial Crisis, and I
Speaker 2: think it's interesting to hear how people are talking about
Speaker 2: it in regards to AI. But first of all, take
Speaker 2: a step back twenty years ago when you started your
Speaker 2: company and kind of where we were.
Speaker 3: Sure, so there's probably two thousand and one, I think
Speaker 3: when I first started Smash, and so twenty three years
Speaker 3: well then, so yeah, the time flies, but yeah, really,
Speaker 3: I was doing some insulting for financial services firms and
Speaker 3: had a few of them all around the same time
Speaker 3: asked me to help them comply with what were then
Speaker 3: relatively new rules and requirements forcing them to capture their email.
Speaker 3: So it was really just email that was a problem,
Speaker 3: and most organizations just needed to find a way to
Speaker 3: retain it so that the compliance departments could produce it
Speaker 3: when a regular came asking for it, and I helped
Speaker 3: a few of them do it and eventually found that
Speaker 3: there was a bigger and bigger business opportunity. And that's
Speaker 3: how it all started.
Speaker 4: What was the way that you were able to do
Speaker 4: it back then that other people weren't doing. What was
Speaker 4: the value add that you brought that the industry wasn't
Speaker 4: saying yet?
Speaker 3: I think the biggest value add was that I had
Speaker 3: come from the financial services industry, and a lot of
Speaker 3: my competitors at the time, and there were quite a
Speaker 3: few were really web hosting companies or internet service providers
Speaker 3: that thought they would just get into the email retention
Speaker 3: space and sell an additional product. We were very different
Speaker 3: from day one, only focusing on broker dealers and and
Speaker 3: investment advisors and really understanding the regulatory requirements that they
Speaker 3: had to comply with. That gave a lot of the
Speaker 3: companies that we worked with much more comfort that when
Speaker 3: a regulator came knocking on their door, we would understand
Speaker 3: exactly what needed to be done, the step thing to
Speaker 3: be taking the proof of you know, the steps that
Speaker 3: we're taking or that were taken and helping them retain
Speaker 3: their their compliance.
Speaker 2: It's interesting, Steve, if you think about it, right, like,
Speaker 2: in terms of where communications were twenty three.
Speaker 5: Years ago and how they have evolved.
Speaker 2: We communicate and then you know, layer on the pandemic
Speaker 2: on top of it, things have gotten much more complicated.
Speaker 2: How has that changed your business and what you guys do?
Speaker 6: Well?
Speaker 3: Early on, you know, as you alluded to, it was
Speaker 3: really just email that companies needed to deal with, and
Speaker 3: then eventually it was AOL and SIT messenger and of
Speaker 3: course Bloomberg's messaging protocols as well.
Speaker 6: So you know, over the.
Speaker 3: Last two decades, that list of relatively few communication channels
Speaker 3: has exploded to now include well over one hundred and
Speaker 3: hundred and fifty different types of communication, and some of
Speaker 3: the largest organizations that we serve we'll have you know,
Speaker 3: dozens fifty one hundred different types of communication. So that
Speaker 3: has created a lot of opportunity for us to up
Speaker 3: new products and new solutions to help our customers, but
Speaker 3: it also creates a lot of challenges for those that
Speaker 3: have to to work with them.
Speaker 2: I always think about in COVID, right we were talking
Speaker 2: about you know, in terms of spreading the virus, like
Speaker 2: the touch points, and I just think about in terms
Speaker 2: of the financial community, the touch points as information is
Speaker 2: shared and moved around, they have increased and that means
Speaker 2: greater risk potentially absolutely.
Speaker 3: I mean you have to you have to look at
Speaker 3: all those different endpoints you have. You may follow a
Speaker 3: conversation that starts on text message and then moves to
Speaker 3: email and then is picked up later on WhatsApp or
Speaker 3: you know, some other communication channel. If you don't have,
Speaker 3: you know, a good sense of what's happening in your organization,
Speaker 3: you're not going to be able to follow the entire conversation.
Speaker 3: It's not single thread anymore. It's not just taking place
Speaker 3: in one venue.
Speaker 6: Okay.
Speaker 4: So a big issue with the SEC has been so
Speaker 4: called disappearing message services. How do you guys deal with that?
Speaker 3: Well, there are certain ones that were designed specifically not
Speaker 3: to be captured and retained. There are others that you know,
Speaker 3: we can help with from a technology standpoint. You know,
Speaker 3: if something is specifically designed not to be viewed in mind,
Speaker 3: and I think that that's where policy comes in for
Speaker 3: most organizations. Right wherever possible, we develop different mechanisms of
Speaker 3: capturing the messages so that they can be sort of archive.
Speaker 4: What if you're working with an organization where okay, yes,
Speaker 4: my work accounts are ones that can be captured, but
Speaker 4: a lot of my communication happens over my personal devices
Speaker 4: or my personal services.
Speaker 3: How does that work? Again, it's kind of nuance. It
Speaker 3: depends on the communication channel. Some of the early social
Speaker 3: networks introduced that very problem, where with Facebook, for example,
Speaker 3: you only had a personal profile if you were also
Speaker 3: using it for work, well, that meant that the organization
Speaker 3: had to effectively retain your personal communications and you had
Speaker 3: to authorize them or you know, acknowledge that you were
Speaker 3: going to use something like Facebook for personal and business
Speaker 3: communications and you'd give the firm basically the ability to
Speaker 3: capture them.
Speaker 6: You know.
Speaker 2: One of the things I love about that we kind
Speaker 2: of try and do at Bloomberg, and I think we
Speaker 2: do it pretty well, is just kind of open windows
Speaker 2: into worlds that maybe people don't know about, but is
Speaker 2: just such a big part of our world. And we
Speaker 2: did it today with an earlier story had to do
Speaker 2: with roans and so on and so forth. But I
Speaker 2: think about this is such a part of the financial world,
Speaker 2: you know, and kind of reading in tim and I,
Speaker 2: you know, I think nineteen of the world's largest twenty
Speaker 2: banks are your clients. Like, this is something that every
Speaker 2: financial institution is involved in a big way and has
Speaker 2: to be absolutely in terms of what you do in
Speaker 2: the services you provide.
Speaker 3: Yeah, it's not always the most well known service, you know,
Speaker 3: among the public, but every broker dealer, investment advisor, or bank,
Speaker 3: you know, hedge fund, you know, really has some regulations
Speaker 3: they need to comply within where they're often behind the
Speaker 3: scenes or behind the scenes as one of their most
Speaker 3: critical partners.
Speaker 5: Is it getting more complicated?
Speaker 2: And I think about with financial disruption, and I think about,
Speaker 2: you know, layer kind of what we've seen in cryptocurrency,
Speaker 2: and I don't know the financial industry, it's just like
Speaker 2: more and more things are being thrown at them in
Speaker 2: different ways. And I always think about is a regulatory
Speaker 2: oversight and the systems in place to kind of keep
Speaker 2: up with it.
Speaker 3: It definitely gets more and more challenging, and I think,
Speaker 3: you know, over the past two decades, it's gotten to
Speaker 3: the point where the compliance function is probably one of
Speaker 3: the most sophisticated within a financial services organization. I certainly
Speaker 3: don't envy some of the professionals that have to deal
Speaker 3: with other aspects of compliance, you know that's marsh doesn't
Speaker 3: even really touch or play in, you know. So it's
Speaker 3: a challenging job and it's a significant area of focus
Speaker 3: for the financial industry.
Speaker 4: One thing that's so interesting about what you do is
Speaker 4: you have so many different clients, you have so many
Speaker 4: touch points on the economy. And one thing that I'm
Speaker 4: interested in is here we are in twenty twenty four
Speaker 4: where it's sort of like if we were doing this
Speaker 4: a year ago, the question would be, Okay, when's the recession?
Speaker 4: But the economy it seems like it is firing on
Speaker 4: all cylinders right now. What are you hearing and certainly
Speaker 4: that's what the economic data is indicating to us. What
Speaker 4: are you hearing from your customers right now when you're
Speaker 4: talking to them about different products, different services when it
Speaker 4: comes to how they're doings of how they're doing, yeah,
Speaker 4: how they're doing.
Speaker 2: Because it like you wonder do they pick and choose
Speaker 2: and say, I mean compliance they have to do, but
Speaker 2: do they pick and choose a little bit because they're
Speaker 2: a little bit worried about the account the outcome, or
Speaker 2: do you never see that.
Speaker 3: I mean, most of the conversations we have are more
Speaker 3: specifically related to their compliance and technology challenges, the types
Speaker 3: of communication tools they're using, you know it. Maybe we'll
Speaker 3: see a little bit in terms of how they're they're
Speaker 3: expanding or contracting the organization, right not even really we
Speaker 3: don't know always have a great sense of that either.
Speaker 3: So as far as like their views on the economy
Speaker 3: and what's happening globally, and we don't get too much
Speaker 3: of that. It's more, uh, it's more focused on compliance.
Speaker 2: Does crypto come up? How does does crypto come into
Speaker 2: your world?
Speaker 5: As well?
Speaker 3: It does? And I think there was quite a bit
Speaker 3: of buzz about it, especially a year and a half
Speaker 3: two years ago, about you know, how crypto was going
Speaker 3: to be regulated and really for us, you know, what
Speaker 3: what is Marsh's role, what in what are our client's
Speaker 3: role in that. I would say it's not the biggest issue,
Speaker 3: you know, but it's still in the background.
Speaker 5: There.
Speaker 3: There's a lot more discussion today about artificial intelligence and
Speaker 3: how how it should be regulated and how it can
Speaker 3: be used to help with you know, communication, you know,
Speaker 3: monitor and surveillance.
Speaker 2: I mean, we're gonna have a bunch of conversations about that.
Speaker 2: How are you guys preparing for it? I know we're
Speaker 2: gonna have some some future conversations that are going to
Speaker 2: dig a little bit deeper into it, But how are
Speaker 2: you guys getting ready for it? Or how have you
Speaker 2: been planning around it? What are your clients saying, Pea, Steve,
Speaker 2: are you working on this?
Speaker 3: Yeah, we've We've had an aspect of artificial intelligence as
Speaker 3: part of our services for many years, and really it's
Speaker 3: to address the reality that the data volumes just are
Speaker 3: growing constantly, so our customers are faced with a challenge
Speaker 3: where they have to sift through not only growing number
Speaker 3: of communication channels, but the number of messages that are sent,
Speaker 3: you know, within each of those has grown exponentially. And
Speaker 3: it used to be that human beings could inspect and
Speaker 3: look at the messages that we would get flagged for
Speaker 3: some sort of potential compliance violation. Now it's becoming increasingly difficult.
Speaker 3: So the use of artificial intelligence helps them manage that workload.
Speaker 3: So that that's probably the biggest use case in the
Speaker 3: biggest area that we hear about. But there's also certainly
Speaker 3: a discussion about how firms need to think about their
Speaker 3: own use of artificial intelligence, and if that if that
Speaker 3: becomes a communication itself that needs to be archived and monitored,
Speaker 3: or or if they have you know, a bot on
Speaker 3: their website that's communicating with investors, you know, how does
Speaker 3: that fit into the compliance obligation?
Speaker 2: I didn't even think about that, like monitoring the bot right,
Speaker 2: Like it's going to be part of it.
Speaker 4: Who monitors the bot? That's monitoring the bot?
Speaker 5: That's the question?
Speaker 3: Another bot?
Speaker 4: Yeah, okay, okay? So what about when it comes to
Speaker 4: the AI, are you deploying the AI or is the
Speaker 4: AI being deployed by these companies internally?
Speaker 6: Uh?
Speaker 3: For the surveillance, Yeah, and monitoring. We help the customers
Speaker 3: deploy that, but it's with their own They are their
Speaker 3: own input in terms of what they want to look
Speaker 3: for and what they're they're trying to use it for.
Speaker 4: Have you had to make specific hires around that type
Speaker 4: of technology that in this environment?
Speaker 7: Many?
Speaker 3: So?
Speaker 4: How is that? Because I mean it's like a serious
Speaker 4: talent we're going on.
Speaker 3: Yeah, And I think we've we've been very fortunate that
Speaker 3: our that our use cases is interesting. I think to
Speaker 3: the professionals that get to work get to work on
Speaker 3: artificial intelligence. We've got very large data stores, you know,
Speaker 3: high significance use cases to get people excited, so it's
Speaker 3: always been relatively easy to find high quality tech talent.
Speaker 3: It's mart just because we've got high security use cases,
Speaker 3: big data, always on the cutting edge of the communication
Speaker 3: tools that people want to use, so.
Speaker 5: They want to be a part of it.
Speaker 2: I'm just thinking about the Bloomberg audience, investing audience, just
Speaker 2: people who want to know on trends and waves. Just
Speaker 2: got about a minute or forty five fifty seconds left here.
Speaker 2: What do you think they need to know about? Kind
Speaker 2: of the world that you're seeing and smartsh connect Like
Speaker 2: the leaders that are here, whether it's AI, compliance technology,
Speaker 2: what do you think they need to be aware of?
Speaker 3: I think they need to be aware that we are
Speaker 3: working as hard as we can every single day to
Speaker 3: make sure that our clients can continue to use the
Speaker 3: communication tools that they want to which in essence, is
Speaker 3: really just allowing investors to use the communication tools they
Speaker 3: want to use when they engage with their financial professional.
Speaker 3: Sounds like a real, relatively simple order, but it's a
Speaker 3: it's a it's a big ass because there are so
Speaker 3: many different ways if people want to communicate and everybody
Speaker 3: has their own unique preferences. We're out there working with
Speaker 3: you know, our partners and our employees to try to
Speaker 3: make that all possible.
Speaker 2: Well, we talk about transparency, right, or making sure that
Speaker 2: financial systems are fluid and they work really well. Like
Speaker 2: this is a part of it, right. It's kind of
Speaker 2: a cog in the in the wheel, if you will,
Speaker 2: in terms of doing so.
Speaker 5: Thanks so much. Thanks for inviting us here.
Speaker 4: Really cool stuff and I'm glad you could join us.
Speaker 2: Yeah, it's really fun to be here. We would like
Speaker 2: to be outside though, it's really beautiful.
Speaker 4: Can we work next sure, next year, we'll do it outside.
Speaker 5: Just kidding.
Speaker 2: Steve Steve Smarsh of course, he's founder and chairman of Smarts.
Speaker 2: So we are here at smash Connect in midtown Manhattan.
Speaker 2: I'm Carol Masser along with Tim Stanevik. Life here on
Speaker 2: Bloomberg Business Week. Conversations are continuing. We're going to talk
Speaker 2: more about digital transformation and the role of all of
Speaker 2: it in compliance and managing risk for firms. We're coming
Speaker 2: back right here on Bloomberg Business Week.
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Speaker 4: Well, what is Capital One, Bank, Loomy, the London Stock
Speaker 4: Exchange Group, NUMBERA, MasterCard and HSBC all have in common? Well,
Speaker 4: they're all financial services firms that use Amazon Web Services,
Speaker 4: also known as AWS. Our next guest knows that because
Speaker 4: he leads the worldwide business and market development efforts for
Speaker 4: financial services at AWS, having also been an executive director
Speaker 4: at JP Morgan Chase, also working at NASDAQ, bear Stearns
Speaker 4: and City. John Kain is head of financial Services market
Speaker 4: Development at AWS, and he joins us on location here
Speaker 4: at smash Connect. John, how are you good?
Speaker 6: Thanks? Hey?
Speaker 4: How's how's business right now?
Speaker 7: That's pretty good. It's hard to imagine. We're actually in
Speaker 7: the second decade of cloud adoption in financial services, and
Speaker 7: some of the things when I joined AWS seven years
Speaker 7: ago that we wouldn't have thought were possible at all
Speaker 7: to kind of run in the cloud from a financial
Speaker 7: services infrastructure perspective are almost becoming sort of everyday story.
Speaker 4: Did you not think it was possible because of regulatory issues?
Speaker 7: That was one of the big concerns when we had
Speaker 7: those initial conversations from customers earlier in the day, it's like,
Speaker 7: how would our regulators think about cloud? About security? What
Speaker 7: about compliance and resilience? And over the course of the
Speaker 7: last decade, you've seen some of the most important systems
Speaker 7: actually move and run on the cloud. Was two years
Speaker 7: ago that Nasdaq moved its matching engine onto AWS Technology
Speaker 7: runs MREX their Options exchanged. Last year, the SEC gave
Speaker 7: a no objection letter to the Options Clearing Corporation to
Speaker 7: move their risk and settlement systems to the cloud. And
Speaker 7: those are the type of crown jewels in the industry
Speaker 7: that you are always aspire to run. And I think
Speaker 7: that was a twinkle in our eyes when we started
Speaker 7: on the financial services side of ABS, and now it's
Speaker 7: sort of the reality of what we're bringing to the industry.
Speaker 2: I mean safe to say, John, when we break down
Speaker 2: like Amazon earnings, we talked about AWS. It's like streaming, right,
Speaker 2: and we're talking about the cloud. And I think so
Speaker 2: much of general consumers that's what they think about. How
Speaker 2: much of what you do in the cloud is financial
Speaker 2: services based?
Speaker 7: Well, for me it's a hundred percent, right, Yeah, But
Speaker 7: for AWS, it's a large chunk of your business. We
Speaker 7: don't break down the individual segment, but financial services is
Speaker 7: just one of the largest consumers of technology, as you
Speaker 7: can imagine, of course, and just because so much of
Speaker 7: what they do is just moving one than the Euros
Speaker 7: and data around. Almost everything is dependent on technology, and
Speaker 7: when we look at where our customers are focused, it's
Speaker 7: bringing more personalized experience with less friction and bringing down
Speaker 7: the kind of costs across the industry.
Speaker 4: I just want to jump in with a red headline
Speaker 4: crossing the Bloomberg terminal has to do with Boeing. The
Speaker 4: Boeing whistleblower is set to testify an April seventeenth Senate hearing.
Speaker 4: That Boeing hearing has been confirmed by a spokesperson for
Speaker 4: Center Blumenthal checking in on shares of Boeing right now
Speaker 4: in the after hours. Shares of Boeing right now moving well,
Speaker 4: really unchanged as we speak, but did fall about one
Speaker 4: percentage right.
Speaker 2: We had some news earlier today in terms of Boeing
Speaker 2: deliveries getting.
Speaker 4: Back there on percent today.
Speaker 5: Excuse me, all right, good to know, JOHNKM.
Speaker 2: We're talking with the head of Financial Services Market Development
Speaker 2: over at AWS what are like some of the top
Speaker 2: priorities that clients come to you and say, here's what
Speaker 2: we need to make sure that you know we're going
Speaker 2: to play with you in your cloud, in the in
Speaker 2: the Amazon Cloud or AWS, and just what is top
Speaker 2: of mind for them in terms of security and risk
Speaker 2: and compliance.
Speaker 7: So I think it's that's the secondary concern. If we
Speaker 7: think about sort of why firms adopt cloud first, it's
Speaker 7: to change the business dynamic. Right. It moves them from
Speaker 7: having to make three and five year capital investments to
Speaker 7: be able to buy what they need when they need it,
Speaker 7: only pay for it. And when you think about.
Speaker 5: Like the desert versus on premise enterprise exactly.
Speaker 7: And when you think about something like mortgage refinancing, right,
Speaker 7: being able to tie your business costs to the volume
Speaker 7: of business you do as opposed to an investment you
Speaker 7: made three years ago, it allows you to be more
Speaker 7: dynamic from a product and services perspective, right, So it
Speaker 7: changes the way you think about your business. But security
Speaker 7: and operational resilience are table stakes for us to be
Speaker 7: successful in the industry. Right, primary focus above all else
Speaker 7: is making sure our customers are secure and their data secure,
Speaker 7: and that our systems are running as close to perfect
Speaker 7: as possibly can be, but.
Speaker 4: It also means that you guys are taking on that
Speaker 4: capex risk.
Speaker 6: Yeah.
Speaker 7: Absolutely. One of the benefits though, kind of being at
Speaker 7: our scale and our approach to the business is the
Speaker 7: larger you are, the more you have that ability to
Speaker 7: kind of work demands across industry segments and they offset
Speaker 7: each other. And if you're very much thinking about from
Speaker 7: a financial services perspective, it's a little bit like what
Speaker 7: a clearing house or clearing broker brings to the table.
Speaker 7: If they have some customers or long positions, some customers short,
Speaker 7: they can manage that risk better than any one participant can.
Speaker 7: And from a technology perspective, we take advantage of that
Speaker 7: kind of scale to be able to do the same
Speaker 7: thing on behalf of our customers.
Speaker 2: Is Jenai Generative AI changing any of that, because you know,
Speaker 2: we've been having discussions kind of back in our newsroom
Speaker 2: about the on premise enterprise and whether or not they're
Speaker 2: going to be companies, whether it's financial or otherwise that
Speaker 2: are going to do kind of a hybrid approach and
Speaker 2: want to have some facilities on site that maybe there
Speaker 2: is some data information or processing that they want to
Speaker 2: keep kind of closer to home versus tapping the cloud,
Speaker 2: and I'm curious how that is impacting your discussions you
Speaker 2: guys are having around that.
Speaker 7: Yeah, I think in a different way. So almost all
Speaker 7: our customers start on premises, and we have to work
Speaker 7: with them from a hybrid perspective to help them take
Speaker 7: advantage of the cloud, and we want to make that
Speaker 7: infrastructural is transparent to their existing infrastructure as possible. I
Speaker 7: think Jenaia that accelerates the move to the cloud as
Speaker 7: opposed to kind of keeps it on prem When you
Speaker 7: think about the sheer computing power necessary to drive these
Speaker 7: foundational models to kind of see that expertise, it's beyond
Speaker 7: the ability for most firms to be able to make
Speaker 7: that investment. Right, when you think about the risk you're
Speaker 7: taking to buy that much specialized compute at scale to
Speaker 7: train essentially almost all of human knowledge to kind of
Speaker 7: build on these models, you can't take that risk on
Speaker 7: as an individual enterprise. You've got to figure out how
Speaker 7: to leverage kind of best of breed providers, and we
Speaker 7: have the ability to kind of invest enough in our
Speaker 7: infrastructure to specialize it so it works both at scale
Speaker 7: and at a lower price point. We even build our
Speaker 7: own silicon chips to actually make those things more efficient.
Speaker 7: So we see, especially in the generative AI space, that
Speaker 7: need to leverage the cloud to both be successful in
Speaker 7: building new foundation models, but more importantly, how most of
Speaker 7: our customers are actually going to take advantage of it.
Speaker 7: They're going to use one of the existing foundational models
Speaker 7: that are out there from an anthropic or kind of
Speaker 7: a meta or coher and want to use it themselves,
Speaker 7: and we want to make that available, and we want
Speaker 7: it so they could use it right away, right, So
Speaker 7: they're not going, hey, how do I build out a
Speaker 7: technology plan, how do I findinance this? With macfo, It's like,
Speaker 7: oh great, we can go try this right, and we
Speaker 7: make that immediately available, and we think that just accelerates
Speaker 7: the value of a tobis.
Speaker 2: So you're not seeing really any kind of shift in
Speaker 2: terms of people wanting to have it more on premise.
Speaker 7: No, actually, I think it's just the other way around
Speaker 7: the way around.
Speaker 8: Okay.
Speaker 4: Yesterday Jamie Diamond over at JP Morgan Chase his annual letter,
Speaker 4: he likened AI to the steam engine. Do you believe
Speaker 4: we're at an inflection point that is indeed that drastic.
Speaker 7: I think it is when you talk to our customers,
Speaker 7: the sheer amount of ideas that are both driven from
Speaker 7: top of house from this CEOs that are saying, look
Speaker 7: generated as a priority for us, right, we need to
Speaker 7: think about how this changes our business. But also sort
Speaker 7: of from the rank and file, anyone who's ever gone
Speaker 7: to a GP backpot and actually asked a questions sort
Speaker 7: of suddenly understands how efficient they can drive their own business.
Speaker 7: It was Travelers who kind of in their own use
Speaker 7: of generative AI so saved one hundred million dollars from
Speaker 7: an operational expense perspective, just by automating those tasks that
Speaker 7: tend to be very document labor, human intensive to kind
Speaker 7: of be able to be more efficient. You know, we're
Speaker 7: talking at this Marsh conference today. From a compliance perspective,
Speaker 7: we've seen firms like Nassex, everyfin who does any money laundering,
Speaker 7: you know, be able to reduce, you know, the time
Speaker 7: it takes to investigate a fraud alert by like sixty percent.
Speaker 7: And when you think about those operational savings at scale,
Speaker 7: you're seeing sort of just huge excitement about the potential
Speaker 7: for adoption. And I think we see it really being
Speaker 7: embedded in almost every application, So no matter what you use,
Speaker 7: it's almost going to have that kind of capability.
Speaker 2: Is that what's kind of surprising because we do you know, John,
Speaker 2: we talk about that AI is not anything new, It's
Speaker 2: been around. It's just now we're talking about kind of
Speaker 2: next level right when we when we talk about machine
Speaker 2: learning and generative AI. But I think about our audience
Speaker 2: who are listening, like, what would surprise them about what
Speaker 2: you are seeing when it comes to generative AI and
Speaker 2: the usage, it's not just about what it maybe can do,
Speaker 2: it's what it's already doing, it feels like in.
Speaker 7: Any ways, part of it is that the pace of
Speaker 7: change over the last year has been so dramatic and
Speaker 7: just with the models are capable of really yeah, I
Speaker 7: mean we saw just sort of we work part closely
Speaker 7: with anthropic commit equity investment in them and just sort
Speaker 7: of seeing the difference between sort of Claude two and
Speaker 7: Claude three in both its performance but also its cost.
Speaker 7: And that's over less than a year period. And what
Speaker 7: you're seeing is that there's such a variety of models
Speaker 7: and the models are getting so much better that it's
Speaker 7: not just that you're seeing immediate benefits and production with
Speaker 7: some of these productivity applications. Is that you're all thinking,
Speaker 7: oh gosh, if this keeps going, this is going to
Speaker 7: change the way I look at almost everything. And you know,
Speaker 7: generally I don't focus as much, but we're seeing that
Speaker 7: on the developer productivity side. If you're a programmer and
Speaker 7: you're looking to write code or update code, the tools
Speaker 7: are getting so powerful and you're just seeing these massive
Speaker 7: efficiencies and being able to kind of innovate from our
Speaker 7: product side, it's hard to know where it stops. And
Speaker 7: I think that's why everyone's so excited.
Speaker 4: I should note the investment in Anthropic is a huge investment,
Speaker 4: an additional two point seventy five billion dollars just a
Speaker 4: couple of weeks ago.
Speaker 2: Yeah.
Speaker 7: Well, and then the second transhot exactly as part of that.
Speaker 7: Not only do our customers get the benefit of being
Speaker 7: able to use the Anthropic model, Anthropics committed to sort
Speaker 7: of integrating with our platform to get better price and
Speaker 7: performance for our customers.
Speaker 1: Yeah.
Speaker 5: So interesting, the integration of it, John, thank you so much.
Speaker 7: Oh my pleasure.
Speaker 5: This is great.
Speaker 2: John Kaine, head of Financial Services market Development over at AWS,
Speaker 2: joining US here at smash Connect, you're.
Speaker 1: Listening to the Bloomberg Business Week podcast. Listen live each
Speaker 1: weekday starting a two pm starting on Applecarplay and Android
Speaker 1: Auto with the Bloomberg Business app. You can also listen
Speaker 1: live on Amazon Alexa from our flagship New York station
Speaker 1: Just say Alexa playing Bloomberg eleven thirty.
Speaker 2: It's a little bit of sound in the background. We
Speaker 2: are here at smash Connect in Midtown Manhattan. We've stepped
Speaker 2: outside Bloomberg headquarters. They're going to bring down the volume
Speaker 2: a little bit, but it's exciting.
Speaker 4: This is people are partying.
Speaker 5: Well, it is people are partying.
Speaker 2: It's a moment where they bring in clients and customers
Speaker 2: and they're talking things like technology, they're talking AI, they're
Speaker 2: talking compliance, and so there's a lot of good energy.
Speaker 4: Well, speaking of AI, Carol, Intel rolling out a new
Speaker 4: version of its artificial intelligence chip, aiming to challenge in
Speaker 4: VideA in one of the fastest growing parts of the
Speaker 4: semiconductor industry.
Speaker 2: Right out with an updated processor, it will be widely
Speaker 2: available on the third quarter. It's designed to boost performance
Speaker 2: in two key areas, helping train AI systems and also
Speaker 2: a process that involves bom barding them with data. We
Speaker 2: know that, and also running the finished software. It's all
Speaker 2: about AI.
Speaker 5: We know that.
Speaker 2: We've been talking about it NonStop for over year now.
Speaker 2: And someone who knows a lot about it is Brandon Carl.
Speaker 2: He's executive vice president of AI and Product Strategy at
Speaker 2: SMARSH with us on site here at SMARSH Connect.
Speaker 5: So good to have you here with us.
Speaker 8: Thank you for having me.
Speaker 2: Thank you for inviting us. Actually we're here in your
Speaker 2: home AI. There's so much going on every day. AI
Speaker 2: is not new, we know that, we say that all
Speaker 2: the time, but next level machine learning, generative AI and
Speaker 2: what it can do. How do you get your head
Speaker 2: around what really matters? It's something we ask our AI reporters.
Speaker 2: What matters, what doesn't? How do you figure that out?
Speaker 9: One of my favorite quotes in this space is AI
Speaker 9: is always what the computer can't do now right and
Speaker 9: what it could do yesterday. And so when you take
Speaker 9: a look at this, what we take a look at
Speaker 9: is what a outcome.
Speaker 4: The customer is trying to achieve.
Speaker 9: And when we look at things like AI and machine learning,
Speaker 9: they are about a dozen different technologies we use in
Speaker 9: terms of taking customers into production and their software. So
Speaker 9: when we use these and when we see things like
Speaker 9: generative AI, they're incredible new things that this technology can do,
Speaker 9: and that enables us to do incredible new things for
Speaker 9: our customers.
Speaker 4: I think back to when a I got on a
Speaker 4: lot of people's radar, not people in the space, but
Speaker 4: like investors who really started to think about it as
Speaker 4: a new category for them or lay people. Really it's
Speaker 4: this idea like kind of playing with CHATCHBT for the
Speaker 4: first time, perhaps in the fall of twenty twenty two.
Speaker 4: When did it get on your radar?
Speaker 9: A long time ago? So we have been how long
Speaker 9: We started work on natural language processing back in two thousand.
Speaker 9: It was a company Smarsh acquired called Digital Reasoning, And
Speaker 9: then we started working with the financial services industry in
Speaker 9: twenty fifteen and twenty sixteen, and we started doing very
Speaker 9: large scale deployments then.
Speaker 8: So we've been working for a long time.
Speaker 4: Why was there such a long period of time between
Speaker 4: two thousand and two fifteen twenty sixteen when you started
Speaker 4: actually implementing it.
Speaker 9: Sure, the early customers were actually government customers that were
Speaker 9: interested in national defense and security, and it wasn't until
Speaker 9: after the Libor crisis you had about three to five
Speaker 9: years where budgets increased and suddenly people said, there's got
Speaker 9: to be a better way to keep the markets safe.
Speaker 2: How does crisis and lawsuits and fines and things like
Speaker 2: that kind of shape what you guys are doing.
Speaker 5: In you particular?
Speaker 9: Sure, I would like to think that the industry could
Speaker 9: be wildly proactive. But typically what happens is some event happens, right,
Speaker 9: and then firms get budgets and they say, we need
Speaker 9: to prevent that from happening again. So there really is
Speaker 9: a unicause and effect that plays out there.
Speaker 5: Is it getting a lot more complicated though?
Speaker 9: It is mostly because the number of ways people communicates.
Speaker 4: Something we've been talking about. I mean, he has been
Speaker 4: working for years on art all. They had issues with WhatsApp,
Speaker 4: for example, just one platform.
Speaker 9: How do you put that to process more than one
Speaker 9: hundred different platforms? And if you think about this even
Speaker 9: five years, three hundred million today. So whether it's Slack, team, Zoom, WhatsApp,
Speaker 9: we chat line, signal, like, there are all different ways
Speaker 9: people communicate.
Speaker 4: I was in doing research for this this interview. I
Speaker 4: was I was trying to find information about how many
Speaker 4: messages a bank typically processes in a single day. Yep,
Speaker 4: couldn't find that data anyway. Yeah, give us some numbers.
Speaker 9: It really depends on the firm and the type of firm.
Speaker 9: Typical employee is like anywhere from one to five hundred
Speaker 9: messages a day, but.
Speaker 4: To each employee, one employee, Yeah, yep, okay, so give
Speaker 4: us some huge numbers here about the processing that you're
Speaker 4: doing in a real tier.
Speaker 6: Yeah.
Speaker 9: So so firms can you know, generate as many as
Speaker 9: tens of millions of messages every single day, right, and
Speaker 9: we will process billions and billions of communications. So if
Speaker 9: you imagine all of the comms coming together, that's what
Speaker 9: we really have to process.
Speaker 4: If everyone's here today, who's processing the communications?
Speaker 1: Yeah?
Speaker 9: I really I'm worried about that myself.
Speaker 2: Yeah, you know, I'm looking at the notes that your
Speaker 2: team shared with us and regulatory grade AI what exactly
Speaker 2: does that mean? Because I do feel like it's going
Speaker 2: to be a term that we're going to be using increasingly.
Speaker 6: Yeah.
Speaker 9: Absolutely.
Speaker 3: So.
Speaker 9: On one hand, people can log into chat GPT and
Speaker 9: just use it, right, Yeah, But when you think about
Speaker 9: a regulated industry, you have to protect against things like bias.
Speaker 9: You need to make sure that you understand how things
Speaker 9: are actually working. You need to make sure that you
Speaker 9: can rely on that over and over again. So it's
Speaker 9: really a higher standard in terms of how you approach things.
Speaker 2: I want to ask you because you do have Probably
Speaker 2: you guys in particular, have a great We tried to
Speaker 2: ask ste like, who are your clients? But he's really quiet,
Speaker 2: But we know you guys are well in trench, certainly
Speaker 2: within the financial sector. But I do wonder, Brandon, when
Speaker 2: you look at things, I mean, how equipped are is
Speaker 2: the financial community when it comes to compliance and risk
Speaker 2: and transparency In a world where increasingly, as we said,
Speaker 2: there are more and more touch points that create risk,
Speaker 2: and in a world where there are more and more
Speaker 2: oversight and regulators looking and looking for problems.
Speaker 9: It's a hard problem to tackle, particularly for firms to
Speaker 9: have global regulation on things. Yeah, what I can say,
Speaker 9: we genuinely have fantastic customers within this space, and what
Speaker 9: you typically see is you see a handful of them
Speaker 9: really trying to trailblaze and lead the industry forward, to
Speaker 9: make markets safer and to make their firms safer. And
Speaker 9: they help the trail blaze to create the paths for
Speaker 9: the rest of the firms to follow.
Speaker 5: Us and bring along like their supply chain with them.
Speaker 9: To some extent their supply chain, but typically less so
Speaker 9: in what we do.
Speaker 5: Okay, you know, I.
Speaker 4: Hear you and Steve speaking, and I think about another
Speaker 4: highly regulated industry, medicine and also an industry that is
Speaker 4: trying to figure out how to use AI. Any any
Speaker 4: talk discussion about getting into medicine. It has the hipA
Speaker 4: stuff when it comes to communications between patients and doctors,
Speaker 4: has the regulatory issues as well. Is that all Does
Speaker 4: that all come up on your radar?
Speaker 8: It does come up on our radar.
Speaker 9: We really look at regulated industries as areas that we
Speaker 9: can have the biggest impact. So pharma is one of
Speaker 9: those energies and other and then financial services. So we
Speaker 9: do think we can have some impact, but we're really
Speaker 9: squarely focused on solving these markets use cases as best
Speaker 9: we can in the near term.
Speaker 2: So again, like I think about, I keep thinking about
Speaker 2: the Bloomberg audience.
Speaker 5: So what are you guys.
Speaker 2: I'm sure there are scenarios you play out. Okay, these
Speaker 2: are the risk scenarios that we need to be thinking
Speaker 2: about in a world increasingly that is ruled machine learning,
Speaker 2: generative AI, what are the risks that you think that
Speaker 2: we should all be kind of preparing for because we're
Speaker 2: not going to catch everything.
Speaker 6: Yeah, we will.
Speaker 9: Unfortunately we won't catch everything. And typically what you'll see
Speaker 9: sometimes you'll see nefarious bad actors within firms, right, and
Speaker 9: then other times there are people who just don't know
Speaker 9: any better. And you really want to help the people
Speaker 9: who don't know better to say, hey, you didn't intend
Speaker 9: to do this, like this is the right way to
Speaker 9: do things. But we also have to keep an eye
Speaker 9: towards the people who are ruining the reputations of their
Speaker 9: firms or you know, other people who are trying.
Speaker 8: To do the right thing.
Speaker 5: So really bad actors, there.
Speaker 8: Are bad actors unfortunately that are out there.
Speaker 4: Are those usually internal with an affirm in in trying
Speaker 4: to have some sort of inside edge when it comes
Speaker 4: to making money, or they usually bad actors from the outside.
Speaker 9: It can be both, right, Typically the outside bad actors
Speaker 9: are more from an information security standpoint, right, And sometimes
Speaker 9: there are people internally who are just trying to make
Speaker 9: a buck and not do the right thing.
Speaker 5: AI.
Speaker 2: The conversation in a year from now just got about
Speaker 2: thirty seconds left here, Sure do you think it'll be
Speaker 2: dramatically different or just more the same.
Speaker 9: It will keep improving, absolutely, and we need to keep
Speaker 9: figuring out how we can actually use these technologies and
Speaker 9: the right way to improve the world.
Speaker 5: All right, really interesting stuff.
Speaker 2: I don't envy you, because you've got a lot coming
Speaker 2: at you. Brendan carl Executi, vice president of AI and
Speaker 2: Product Strategy at s Marsh joining us here on site
Speaker 2: at smash Connect.
Speaker 4: Really really cool stuff.
Speaker 1: You're listening to the Bloomberg Business Week podcast. Catch us
Speaker 1: Live weekday afternoons from two to five pm Eastern. Listen
Speaker 1: on Apple car Play and then brout Auto with a
Speaker 1: Bloomberg Business app or want us Live on YouTube.
Speaker 4: Last week, SEC won a jury verdict and its groundbreaking
Speaker 4: insider trading case that seeks to bar employees from using
Speaker 4: non public information about their own company to place bets
Speaker 4: on rival stock. Also, a former Flow executive and his
Speaker 4: cousin recently admitted to insider trading on confidential information about
Speaker 4: a pandemic related government loan to Eastman Kodak. All of
Speaker 4: this happening, Carol, while the agency has been dealing with
Speaker 4: a number of high profile crypto cases, and I got
Speaker 4: to tell you.
Speaker 5: We could go on and on.
Speaker 4: This is just a sampling of what I found when
Speaker 4: I typed into the Bloomberg terminal and I.
Speaker 2: Fraud and I fraud. Yeah, there's a lot. So I'm
Speaker 2: guessing it's not going to come.
Speaker 4: As a surprise fraud an alleged.
Speaker 2: Frauduct To be fair, we're guessing this will come as
Speaker 2: a surprize to our next guest. Rob Mahra is with us.
Speaker 2: He's a principal in EYS consulting practice. He spent decades
Speaker 2: working on risk and regulatory compliance, tech and operations, think sanctions,
Speaker 2: anti money laundering, fraud management, and of course working with regulators.
Speaker 2: It feels like it's all the courses that we take
Speaker 2: at Bloomberg to make sure that we are compliant and
Speaker 2: very careful.
Speaker 5: Welcome, Welcome, Nice to be talking with you, Thank you,
Speaker 5: good to be here. Tell us about your world.
Speaker 4: Many stock tips.
Speaker 5: We are a public, We're all like we've got a
Speaker 5: public lads.
Speaker 8: Doctip's a bit of a problem. So basically, the way
Speaker 8: I kind of put my job overall is, you know,
Speaker 8: I help financial institutions get out of trouble and stay
Speaker 8: out of trouble. You know, if you just see all
Speaker 8: the different things happening in the news. You know, you
Speaker 8: mentioned insider trading in just a second ago. You know,
Speaker 8: there's all sorts of different types of regulatory compliance matters
Speaker 8: that hit institutions from any number of areas, and they're
Speaker 8: very complex, you know, particularly when you start dealing with
Speaker 8: a large multinational firm. The regulations may be different. In
Speaker 8: some cases, they may be conflicting between different jurisdictions, and
Speaker 8: trying to navigate that to figure out how you can
Speaker 8: do something and do the right thing is a bit
Speaker 8: of a challenge, is it.
Speaker 4: Though, Because Okay, I gotta tell you what I was going.
Speaker 5: Through all that. When Tim does that, is it that
Speaker 5: is fraud.
Speaker 4: And alleged fraud? I mean, it seems like a lot
Speaker 4: of this stuff is pretty clear cut, and you get
Speaker 4: people the stuff that I'm reading about, mind you, Yeah,
Speaker 4: it's pretty clear cut, like okay, yes, this is okay, no,
Speaker 4: this is not okay type of stuff. And it seems
Speaker 4: like it's not necessarily the firms. It's certain individuals within
Speaker 4: firms that are just looking to make more money.
Speaker 8: It can be a combination of both. And while some
Speaker 8: of the things are very very you know, black and white.
Speaker 8: You know, if you look at you know, like front running,
Speaker 8: somebody's trade, very very straightforward in terms of how that's done,
Speaker 8: but if you start to think about how that actually
Speaker 8: works out. You know, front running, you understand the concept,
Speaker 8: but think about you have you know, thousands, if not
Speaker 8: you know, hundreds of thousands or even in some cases
Speaker 8: millions of trades going through a day, and all the
Speaker 8: particulars around those trades. So let's take a very simple example.
Speaker 8: Suppose that you place a trade on behalf of your customer,
Speaker 8: and or you place it on behalf of a bunch
Speaker 8: of customers, and then you reallocate it afterwards. Well, the
Speaker 8: way that it might show up in terms of how
Speaker 8: it looks in the data is it's actually looks like
Speaker 8: front running because you traded before the customer actually the
Speaker 8: customer order went through, but you were trading on behalf
Speaker 8: of a customer. Does that count as front running? No,
Speaker 8: obviously it doesn't. And then there's certain exemptions, it's a
Speaker 8: black box exemption. There's alsort of these different variations. Now, yeah,
Speaker 8: it doesn't mean that there aren't some things that are
Speaker 8: just straight white. You know, you mentioned some of the
Speaker 8: insider trading questions, you know, but there are other things
Speaker 8: where it becomes more of a risk question. You know,
Speaker 8: if you look at money laundering activity, other types of
Speaker 8: things like that, where it's like, well, you know, how
Speaker 8: much do you know? Versus how much should you have known?
Speaker 8: Versus how much was hidden from you?
Speaker 6: You know?
Speaker 8: Versus you know, what are your employees doing? It becomes
Speaker 8: a bit of a challenge. Again, doesn't mean there's not
Speaker 8: some black and white stuff. There's definitely some black and
Speaker 8: white stuff, but unfortunately there's a decent amount of grayness.
Speaker 2: But in a world that is increasingly digital, if not
Speaker 2: all digital, I think about, even as a journalists, go
Speaker 2: back how many years and I didn't spend as much
Speaker 2: time on a computer. Now I live on a computer.
Speaker 2: No matter what I'm doing. My whole life right now
Speaker 2: is on a computer. Does it make it easier in
Speaker 2: terms of tracking down compliance and risk or figuring out, okay,
Speaker 2: did something really wrong happen here? Or does it make
Speaker 2: it easier or more complicated?
Speaker 8: It's another little bit of both, because one thing that
Speaker 8: kind of comes into play is just the sheer volume
Speaker 8: of data. Yeah, I work within a number of customers,
Speaker 8: and if you just think about it just the data
Speaker 8: that's coming think atm footage, just the videos coming out
Speaker 8: of that that can be literally petabytes of data.
Speaker 5: Wow.
Speaker 8: Yeah, you know, if you look at the number of
Speaker 8: emails going through, or you take a large US financial institution,
Speaker 8: one of the top four, a billion transactions per day,
Speaker 8: you know, not counting the trades, not counting all the
Speaker 8: other things that are happening, all the other events onboard.
Speaker 2: So what do you do with something like that? How
Speaker 2: do you scrape through or figure out what I mean?
Speaker 2: Do you have to is everything gone over every How
Speaker 2: do you deal with that?
Speaker 8: So you you definitely rely on a lot of automated
Speaker 8: and analytics type of activity, but you're you're constantly tuning
Speaker 8: and adjusting it. You know, like I do a lot
Speaker 8: of work in the fraud space. As an example, every
Speaker 8: time you swipe your credit card, there are literally, you know,
Speaker 8: hundreds of algorithms running in the background to try and
Speaker 8: figure out whether or not this is actually you Does
Speaker 8: it make sense? Is it something that you know we
Speaker 8: should block or we should allow? And they have to
Speaker 8: make that decision in milliseconds because otherwise, you know, you're
Speaker 8: getting a rejection and you want to minimize that and
Speaker 8: that behavior is going to continue to evolve, and so
Speaker 8: you're constantly bringing in new data, you're tweaking your algorithms,
Speaker 8: you're adjusting these things, and then multiply this by the
Speaker 8: you know, literally thousands of compliance regulations you need to
Speaker 8: check too. You have to rely on the automation, and
Speaker 8: then you know, people are getting very very very advanced
Speaker 8: in you know, you've seen deep fakes. You know, how
Speaker 8: can you tell the difference between a deep fake activity
Speaker 8: and non deep activity?
Speaker 4: Let's talk about that little bit.
Speaker 8: How can you so if you're an if you're an
Speaker 8: ethical company who's built the technology to do this, and
Speaker 8: they talked a little bit about during the conference today.
Speaker 8: You can tag images, you can tag different types of
Speaker 8: things as being you know, generated by AI. If you're
Speaker 8: not an ethical company, or you're a fraudster or you're
Speaker 8: you know, some type of scammer, you are going to
Speaker 8: not put those tags in and you're going to do
Speaker 8: your best to adjust them. It doesn't mean that you
Speaker 8: can't detect them in different ways.
Speaker 4: I don't know how many how many times a day
Speaker 4: do you get text messages from somebody who's trying to
Speaker 4: spend who's literally trying to take money from you.
Speaker 8: Literally one of my favorite questions I asked people want
Speaker 8: to you know, the other one being that everybody's information
Speaker 8: is compromised and you just kind of have to accept
Speaker 8: it and protect against it. But yes, you get I
Speaker 8: got one a couple of weeks ago from the electric
Speaker 8: company told me if I didn't pay in forty five minutes,
Speaker 8: they're going to shut off my power, right, you know,
Speaker 8: And because I work in the business, I'm like, yeah, this.
Speaker 4: Is I guess what I'm saying is there's no shortage
Speaker 4: of bad actors. No, like there you know, there's no
Speaker 4: chance that the bad actors are going to tag their
Speaker 4: jenai with any sort of metadata that will show that
Speaker 4: it was generated.
Speaker 1: No.
Speaker 8: No, but there are ways and analytics techniques that can
Speaker 8: be used to detect different types of activities.
Speaker 4: But the problem is that it's only the best line
Speaker 4: of defense is a person right oftentimes, and people don't
Speaker 4: have that type of training.
Speaker 8: No, they don't. I mean I've I've told any number
Speaker 8: of people you know, pretty much, don't click on any
Speaker 8: link in any email, don't click on any pop up ad,
Speaker 8: don't you know. But you know, the fraudsters are getting sophisticated.
Speaker 8: In fact, a current trendy is now that the old
Speaker 8: style fraudsters are no longer committing fraud. They're just creating
Speaker 8: toolkits personas you know, mule accounts, other types of things,
Speaker 8: and selling the fraudsters actually commit the actual fraud.
Speaker 4: Now and shovels where that's where the money is.
Speaker 2: Are we more secure than we used to be? Are
Speaker 2: we more vulnerable because there are a lot of tools
Speaker 2: out there to enable people.
Speaker 5: To trick us.
Speaker 8: I think it's a constant battle. I think in many ways.
Speaker 8: You know, despite you know, my earlier statement that everybody's
Speaker 8: information is compromised to some extent, I mean pretty much,
Speaker 8: you know, your social Security numbers out there, address name,
Speaker 8: all that type of stuff's out there. But how you know,
Speaker 8: and there's definitely identity theft happening, and it's and it's
Speaker 8: on the rise, and it continues to occur. But is
Speaker 8: it a daily occurrence for most individuals? No, you know,
Speaker 8: is it reasonable to say that at some point in
Speaker 8: your life, you know, probably within the next five to
Speaker 8: ten years at most, you know, everybody will have some
Speaker 8: type of identity compromise of some sort. Yeah, I think
Speaker 8: that's that's a legitimate thing.
Speaker 2: But what does that mean is that just the case
Speaker 2: of a we tapped into your health insured your are
Speaker 2: you doing on that level or something more serious?
Speaker 5: When you say that it.
Speaker 8: Could be more serious. It could be that they opened
Speaker 8: up a credit card in your name, you know, and
Speaker 8: then the first thing you notice is when it shows
Speaker 8: up on your credit report, which hopefully you check regularly,
Speaker 8: and then you see that and then you can deal
Speaker 8: with it and get rid of it. It could be
Speaker 8: that you know somebody somebody like there's been the cases
Speaker 8: lately with houses where people are selling houses that they
Speaker 8: don't own, you know, and are you actually able to,
Speaker 8: you know, rely on people to find this stuff for you?
Speaker 8: And who do you rely on? I think that the
Speaker 8: tools are out there to make it better overall, and
Speaker 8: in one sense you are more secure, but you're constantly
Speaker 8: fighting a battle.
Speaker 4: Wasn't this the promise of the blockchain? And it's kind
Speaker 4: of a perfect segue to talking to you about crypto
Speaker 4: a little bit and how your life has become more
Speaker 4: complicated in a result of crypto. But wasn't this the
Speaker 4: promise of the blockchain that we'd all have our own
Speaker 4: identifying information with us at all times. Our house was
Speaker 4: our house, because it's said so on a ledger.
Speaker 8: It could be to a certain extent if it is out,
Speaker 8: you know, if it's already everything was already on the blockchain,
Speaker 8: but it's not. One of the challenges I think overall
Speaker 8: with the blockchain is that you know, bad data as
Speaker 8: well as good data becomes permanent. That becomes a bit
Speaker 8: of a challenge when you start dealing with, you know,
Speaker 8: some of these things along the way. You know, blockchain
Speaker 8: is not everywhere at the moment. So like you mentioned
Speaker 8: owning a house that's not on a blockchain right now,
Speaker 8: there's a fairly good chance it's in some you know,
Speaker 8: local county clerks, registrars or.
Speaker 5: Sound like you think it will be either in the near.
Speaker 8: Future not in the near future. I think aspects of
Speaker 8: it definitely. I mean there's a lot of activity and
Speaker 8: you know, decentralized finance, you mentioned cryptocurrency. You know, there
Speaker 8: are some definite areas where I think that it already
Speaker 8: exists and it will continue to grow in some of
Speaker 8: those areas. But is it something that is going to
Speaker 8: happen in the next you know, year, two, five years,
Speaker 8: ten years. I don't think quite so much.
Speaker 2: I mean, I hate to play like Armageddon and like
Speaker 2: you know, the Dark Day, But I mean, is there
Speaker 2: a moment in time that you would anticipate just because
Speaker 2: things are getting so much more sophisticated and the tools
Speaker 2: are out there and everybody's doing compliance is certainly trying
Speaker 2: to keep on it. But there's going to be a
Speaker 2: point where you go to access your bank and you can't,
Speaker 2: or you go to look at your investments and they're wiped.
Speaker 5: Like is that the scale? And again, I'm not trying
Speaker 5: to be aclammatory, but I'm just trying to be realistic.
Speaker 8: Of I don't think that it's going to get quite
Speaker 8: to that because, if nothing else, the financial institutions have
Speaker 8: some pretty strong controls in place for things like that,
Speaker 8: and they also, you know, many of them will you know,
Speaker 8: reimburse you for different types of activities that happen along
Speaker 8: the way. And I mean, if you went into your
Speaker 8: brokerage account all your investments are gone, you know they
Speaker 8: are going to be taking a look at that to
Speaker 8: figure out what happens. But most likely when they saw
Speaker 8: somebody trying to sell out of your entire portfolio and
Speaker 8: transfer the money it would raise twenty seven red flags
Speaker 8: along the way, and they would have blocked it a
Speaker 8: little bit.
Speaker 5: Right when you're traveling in credit card company calls and
Speaker 5: says it's is you because.
Speaker 2: Yeah, exactly, really there good stuff, but it puts it
Speaker 2: on but it puts it on you.
Speaker 8: It does put it on you because if you didn't
Speaker 8: answer the text, well, then they're going to block it.
Speaker 8: And then that means that your credit card might be
Speaker 8: locked in a particular country because you didn't your text.
Speaker 5: And so there's an awareness on like all levels, right.
Speaker 8: Yeah, And it's not like every asset is protected at
Speaker 8: the same level. Like you know, somebody is selling your house.
Speaker 8: I mean, it's that's protected at one level somebody. You know,
Speaker 8: if your credit cards are protected differently from your debit cards,
Speaker 8: which are protected differently from your brokerage account, you know,
Speaker 8: there are different rules in place for all of those,
Speaker 8: you know, and it means that you can't be oblivious.
Speaker 8: You know, you have to be somewhat vigilant. You have
Speaker 8: to check your credit report, you have to make sure
Speaker 8: that like you know, if you do get a text
Speaker 8: from your bank, first of all, make sure it actually
Speaker 8: is from your bank, right, you know, and then you know.
Speaker 2: Just plenty of stuff there to keep you busy.
Speaker 4: Check your credit report to the to do list. Okay,
Speaker 4: I do absolutely good, right, That's what I like to hear.
Speaker 4: Rob Mehra is a principal in EUIs Consulting Practice, joining
Speaker 4: us here at a smash connect.
Speaker 1: You're listening to the Bloomberg Business Week podcast. Listen live
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Speaker 4: We just had kind of a sobering conversation with all
Speaker 4: the risks associated with AI, with data, our data being
Speaker 4: out there.
Speaker 2: Still telling us stories about fraud and just romance, fraud,
Speaker 2: pig butchering, which we've done stories, our team has done
Speaker 2: reporting on that. Like it's just every day, there's tons
Speaker 2: of stuff going on.
Speaker 4: Needless to say, I think it keeps a lot of
Speaker 4: folks up at night who are thinking about risk and
Speaker 4: risk management. And that's exactly what our next guest focus
Speaker 4: is on providing compliance and risk technology for nineteen of
Speaker 4: the world's twenty largest banks in addition to serving other
Speaker 4: customers of smash. Tom Badget is president of Enterprise Business
Speaker 4: at smartsh He's here on site with us at Smarsh Connect. Tom,
Speaker 4: how are you.
Speaker 6: I'm doing well, Thanks so much for having us here.
Speaker 6: Thanks for joining us. Tim Carroll great, Yeah.
Speaker 4: How would you describe what you do here?
Speaker 6: Great question? So we really so what I do personally personally,
Speaker 6: so I've run so we have really two segments of
Speaker 6: our business. We have small medium business think registered independent agents,
Speaker 6: small shops ten to one hundred people. And then we
Speaker 6: service the largest financial institutions in the world. And in
Speaker 6: what you find, while we delivered similar sets of capabilities,
Speaker 6: very very different needs. So when you're talking to the
Speaker 6: largest financial institutions globally, they're worried about things that maybe
Speaker 6: are a little bit different than some of the smaller companies.
Speaker 6: Still regulated, but looking for a lot of complexity that
Speaker 6: maybe isn't inherent in all smaller organization.
Speaker 2: I always say that conversation that Jamie Diamond did, I
Speaker 2: don't know is it now, ten years ago, fifteen years
Speaker 2: ago up on stage and he said like they were like,
Speaker 2: what's the thing that keeps him up at night, what's
Speaker 2: the number? We think he was talking about cybersecurity guys
Speaker 2: and the technology spend and that he was focusing on it,
Speaker 2: And I think about, Okay, here we are over a
Speaker 2: decade or so later, and I can just think top
Speaker 2: of mind, what the executives say that they need to
Speaker 2: be thinking about.
Speaker 6: It's a huge board level topic. Yeah, right, what are
Speaker 6: the risks we're exposed to? Obviously two thousand and eight
Speaker 6: had a huge impact on this space, so the ability
Speaker 6: to and what's really exciting now too is we've gone
Speaker 6: from a world where we've we've gotten all this information,
Speaker 6: petabytes and petabytes of information, all the communications with customers,
Speaker 6: and it's been really more of a okay, what can
Speaker 6: we personally find out there that might be there and
Speaker 6: utilizing AI to do that? I know, buzzword AI, right,
Speaker 6: But now it's turned into a world with generative AI. Okay,
Speaker 6: what can the machines tell us that maybe we never thought?
Speaker 6: How can we take this information whis hugely critical to
Speaker 6: protect our institutions but also make us better at what
Speaker 6: we do?
Speaker 2: Why will generative AI machine learning kind of make us
Speaker 2: be better when it comes to risk and compliance?
Speaker 6: Yeah? So it helps So think of it this way,
Speaker 6: and it can get like some I'm even like, what
Speaker 6: the heck? So we've been using a all of us
Speaker 6: have been using AI.
Speaker 5: For a long term, and we keep saying that too
Speaker 5: as it's not a new thing.
Speaker 6: Yeah, it's not a new thing.
Speaker 5: So what it can do its capability.
Speaker 6: So think part of what we're doing now is generative.
Speaker 6: We're bringing things. So it's that difference between Okay, I'm
Speaker 6: gonna tell it what to look for and what to
Speaker 6: ask and then it comes back and gives me something
Speaker 6: based on loads and loads of information. Generative is the
Speaker 6: machines really thinking and thinking things that Caroly, you didn't
Speaker 6: think of, Tim, you didn't think of, I didn't think of,
Speaker 6: and wow, I never thought of that, And wow that
Speaker 6: could now protect me in a way that I never
Speaker 6: knew I even even to look at. It's really really exciting.
Speaker 4: I understand this from product development perspective. I understand it
Speaker 4: from a drug development perspective. Carol, and I've talked to
Speaker 4: our colleagues at Bloomberg who've reported extensively on those. But
Speaker 4: when you think of financial services, what can it provide
Speaker 4: that that we don't know is out there?
Speaker 6: There's so much so, So first and foremost, let's think better,
Speaker 6: better service, right, So think about what we deal with
Speaker 6: for for your your listeners are communications intelligence. So all
Speaker 6: communications data that a financial institution might have with their
Speaker 6: customer has to be stored archived. Okay, So the ability
Speaker 6: to go in and say how many how many things
Speaker 6: you see out there, like, well, what do our customers
Speaker 6: really want? What do they need? Well, you now know
Speaker 6: and can see and understand and hear firsthand what it
Speaker 6: is they're looking for, and it's oftentimes it's so buried
Speaker 6: in massive volumes. It's beyond looking for a needle in
Speaker 6: a haystack and haystack and a haystack. It's even more well,
Speaker 6: now the machines can go through and figure that out
Speaker 6: and provide a better level of service or potentially protect
Speaker 6: the organization.
Speaker 2: Where they make sure that the machines that are going
Speaker 2: in and either providing or going to provide better service
Speaker 2: or better you know catching you know, problems where there's
Speaker 2: kind of risks if you will, how do you make
Speaker 2: sure that they're going to do the right thing? Because
Speaker 2: it's only as good as the information that goes into.
Speaker 6: It, and you just hit on the magic question, which is, okay,
Speaker 6: do we just turn these loose in a way we
Speaker 6: go to answer that is no. So you need to
Speaker 6: make sure that the large LLM large language models that
Speaker 6: are being used, that there's some level of oversight on
Speaker 6: those and what is included there. So the machine can
Speaker 6: go off in a way that you never intended to. Right,
Speaker 6: So there also needs so they call it drift machine
Speaker 6: drift it starts to drift off, there needs to continue
Speaker 6: to be This is why it's a bit of a faucy.
Speaker 6: You'll hear all jobs will be gone. That's not true.
Speaker 6: Jobs will change, they'll be different, but you'll need people
Speaker 6: to look and say, this model is starting to drift
Speaker 6: in a way we never wanted it to, or a
Speaker 6: minute to hey let's rain this back in.
Speaker 4: What jobs do you think all at risk?
Speaker 6: You know what I would say is anything that is
Speaker 6: is and I don't think it's risk isn't necessarily the
Speaker 6: right word, But hey, what are ones that the machines
Speaker 6: do really think repetitive in nature? So let me give
Speaker 6: you an example. So one of the areas on AI
Speaker 6: right now some organizations had historically used was okay, I
Speaker 6: just got at one point in time we would get
Speaker 6: we would get a thousands, very cute, a thousand notifications
Speaker 6: of things. It might potentially be risky communications. All right,
Speaker 6: so you may have a team of people that go
Speaker 6: through that in a in a email. Let's use email,
Speaker 6: email by email. What did Carol really mean here? Well,
Speaker 6: when she was talking about her children at home, she
Speaker 6: really meant her children at home. I asked that question.
Speaker 4: Yeah, so there's a machine that can help me.
Speaker 6: That's a that's a level of and very rarely do speople.
Speaker 6: I love doing that. And now think about it this way.
Speaker 6: What used to be thousands of identified now is millions.
Speaker 6: Well what had been a solution is okay, we just
Speaker 6: need to get a lot of people to look at that.
Speaker 5: So what do they call it? Tech adjacent or human?
Speaker 3: Like?
Speaker 5: Right?
Speaker 9: That?
Speaker 2: Bas think technology adjacent with human or like working together side?
Speaker 2: I forgive me if I'm mangling the term.
Speaker 6: Yeah, very much.
Speaker 2: So you know, I'm listening to you speak, and I
Speaker 2: know the financial community is kind of your bread and butter,
Speaker 2: and that's your guys focus. But I'm thinking about the
Speaker 2: world of social media in general and the problems that
Speaker 2: are there that why can you It sounds like from
Speaker 2: your knowledge and expertise to create something that can also
Speaker 2: go in and scrape the things that are incorrect, false, wrong, dangerous.
Speaker 2: So for me, is it that potentially easy?
Speaker 6: The technology is there? Yeah, So from from our perspective,
Speaker 6: we do.
Speaker 8: So.
Speaker 6: It's one of the communications.
Speaker 5: That we need to do right to protect this.
Speaker 6: Absolutely. So our customers have to make sure that tim
Speaker 6: works for our institution and you have a Twitter account,
Speaker 6: we have to make sure that that is something that
Speaker 6: we can capture, that we make sure that nothing's going
Speaker 6: out in a way for that financial institution. We absolutely
Speaker 6: do that.
Speaker 5: But I mean bigger broadly in terms of social media.
Speaker 2: You know that I'm not necessarily trying to put you
Speaker 2: on the spot, but this idea of social media and
Speaker 2: all of the bad information that's out there, and it
Speaker 2: doesn't seem like we can get a grasp on it,
Speaker 2: but it sounds.
Speaker 6: Like technologically the ability. Now, then you get into other like, hey,
Speaker 6: what do we want to do? I won't I won't
Speaker 6: get into that, but hey, what do we want to
Speaker 6: be able to look at? What do we want to limit?
Speaker 6: But the technology and keep in mind too, we don't
Speaker 6: say not what you can to do, but we will identify, Hey,
Speaker 6: this communication that went out is not in compliance with
Speaker 6: your standards. That is something that we absolutely do, and
Speaker 6: financial institutions are all over that.
Speaker 4: Give us an idea of how often that happens.
Speaker 6: Yeah, gosh, it's crazy and oftentimes here the biggest challenge
Speaker 6: of financial institutions have are false positive.
Speaker 5: So so let's happens a lot.
Speaker 6: Yeah, sure, because what can happen is the bad folks
Speaker 6: are really really creative. So you know, I'll use an example.
Speaker 6: I always tell my wife, she's like, what do you do.
Speaker 6: Nobody's gonna say, Hey, I think I'm gonna do an
Speaker 6: insider trade. I'm feeling like this is something I need
Speaker 6: to do. Now there's gonna be they'll go from chant
Speaker 6: what we say, cross channel, Hey, let's take this offline. Yeah,
Speaker 6: those are the types of things. So the machine can
Speaker 6: go in and identify intent even and say, hey, you
Speaker 6: probably need to look at this.
Speaker 4: One, meaning asking somebody to take it off to a
Speaker 4: different form.
Speaker 6: Of Tim Tim said go pick up my children from school.
Speaker 6: Tim really meant go pick up my children from school.
Speaker 6: Or Tim said go pick up my children from school,
Speaker 6: and somebody else said, well, the children at school waiting
Speaker 6: for you to pull the all of a sudden, the
Speaker 6: machine can pick that. And again one of the challenges
Speaker 6: that now the volumes of data are so massive, which
Speaker 6: really a lot of that came from COVID, where I
Speaker 6: used to be able to dictate and mandate to you, Tim,
Speaker 6: you can't use plug into a name.
Speaker 4: Well, okay, so are you capturing You capture communications on
Speaker 4: the phone.
Speaker 6: Over one hundred different channels of communication, but voices something
Speaker 6: it's a little more difficult, something that we are working
Speaker 6: on a lot. But you get in a transcription. The
Speaker 6: crazy part about voice that gets into is and it's funny,
Speaker 6: we had we have this conversation constantly. Spanish is not Spanish,
Speaker 6: is not Spanish, It's not Spanish. English is not English.
Speaker 6: So you have to The machines are still not great
Speaker 6: at that, but from a technical person perspective, it is
Speaker 6: absolutely something we look at.
Speaker 4: So so phone's part of it, voice part of it,
Speaker 4: and zoom teams all that stuff.
Speaker 6: Yeah, yeah, so so all those and so use those
Speaker 6: those examples. Pre COVID, I as a financial institution con
Speaker 6: mandate you can't use this. You can't use this tool
Speaker 6: to talk to your customers. All of a sudden, you
Speaker 6: have to use it to talk to your customers. So
Speaker 6: there's been such an explosion of data. You know, it's funny.
Speaker 6: I joke sometimes with our customers. I say, we adopted
Speaker 6: this crazy concept back in twenty seventeen. I think you
Speaker 6: talked to Steve earlier called the cloud well, and truly
Speaker 6: at that time people thought we were nuts. People said,
Speaker 6: nobody will ever put their compliance data in the cloud.
Speaker 6: It will not happen. Now it's the only way to scale.
Speaker 6: So COVID hits now we have these on prem. I'm
Speaker 6: you know, I'm using these terms on prem.
Speaker 5: PREMI yeah, enterprise systems and so.
Speaker 6: All of a sudden, I'm an internal financial institution. I
Speaker 6: have an on prem system and massive volumes of data.
Speaker 6: The hardware costs alone to keep up with that. Versus
Speaker 6: if you partner with a partner like us. We partner
Speaker 6: with AWS Francis, they can scale like a globally.
Speaker 2: What about speed and reliability? Like so I might say,
Speaker 2: he listen, I want to have it closer. So maybe
Speaker 2: I'm going to have a hybrid and I'm going to
Speaker 2: play around cloud and you know, a little bit of combination.
Speaker 5: Yeah, I don't know if that's a hunting you guys
Speaker 5: at all it.
Speaker 6: Does, and it's a conversation.
Speaker 5: A lot of what we do is if you say,
Speaker 5: don't do it, no.
Speaker 6: No, So what we say and we show and a
Speaker 6: lot of what we do is prove it's actually a
Speaker 6: lot of the assumptions are not valid. So speed and
Speaker 6: reliability and safety is actually higher in the cloud. So
Speaker 6: these are institutions that that you know, these big hyper skills.
Speaker 6: This is what they do and they're used to handling
Speaker 6: those massive volumes.
Speaker 2: Okay, oh go ahead, Well I know we have to
Speaker 2: wrap thirty seconds. So I'm thinking about we Bloomberg investment
Speaker 2: community and thinking about Okay, I'm listening you know to
Speaker 2: Tom talk here.
Speaker 5: So what does that mean?
Speaker 2: Do you think you know, cloud is just it's just
Speaker 2: going to grow even more exponentially, Like what what's the
Speaker 2: investment thought?
Speaker 5: Our thesis off of yeah, you are sick.
Speaker 6: Cloud is here to stay, that's not going anywhere. And
Speaker 6: in fact, oftentimes you get to a point where's like, well,
Speaker 6: of course that's how you're going to scale it. Their
Speaker 6: their organizations and companies. This is again what they do.
Speaker 6: And when I say, what they do not just scale,
Speaker 6: but they're used to those bad actors that are trying again.
Speaker 6: They deal with that all the time. So again not
Speaker 6: to get into too much technology, but we are a
Speaker 6: what we call triple active architecture. So think at any
Speaker 6: given time, your data is in three potential areas. So
Speaker 6: if all of a sudden there's an event that happens
Speaker 6: here shuts it down, you run with you never even
Speaker 6: the other.
Speaker 4: We got to run, but next you got You have
Speaker 4: nineteen of the twenty largest banks when we talk to
Speaker 4: you in a year, you can have twenty of twenty.
Speaker 4: I'm pretty sure I want to share their names there
Speaker 4: it is.
Speaker 6: I got close a couple of times.
Speaker 2: Tom Paget, Thank you, Thank you, really fun Tom Paget.
Speaker 2: He's president Enterprise Business here at smash.
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