2871: Mastercard Reveals Emerging Technology Trends

[00:00:00] Have you ever stopped to think about the forces that are propelling the next wave of commerce

[00:00:06] transformation?

[00:00:07] Well in today's episode I want to peel back the curtain on the future of technology with

[00:00:12] Ken Moore and he's MasterCard's Chief Innovation Officer.

[00:00:16] There are so many reasons I'm excited to get him on the podcast today, especially

[00:00:19] having read their Emerging Technology Trans Report which spotlighted the fusion of AI,

[00:00:26] computational prowess and data technology that looks set to redefine commerce in the coming

[00:00:32] years.

[00:00:33] And not only that, he's one of the coolest guys I've spoken to on this podcast.

[00:00:36] The kind of guy I could just chat with for absolutely hours about life, the universe

[00:00:42] and everything in between.

[00:00:43] So we're going to find out more about Ken, about MasterCard.

[00:00:48] We'll talk about some of the most exciting AI developments that he believes will

[00:00:51] significantly impact everything from shopping, travel, gaming and entertainment.

[00:00:57] And also why the real exciting magical moment is when all these emerging technologies begin

[00:01:02] to converge.

[00:01:03] But before we get today's guest on I need to pay the bills.

[00:01:06] We've got a huge podcast hosting fee to pay for when we're releasing 30 episodes a month

[00:01:12] and this month I've partnered with a company called Kiteworks.

[00:01:16] Now legacy MFT tools are dated and lack the security that today's remote workforce demands

[00:01:22] so companies that continue relying on outdated technology, they put their sensitive data at

[00:01:27] risk and in a world where digital threats evolve daily the need for a secure modern

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[00:01:35] Well enter Kiteworks, the beacon of security and efficiency in managed file transfer

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[00:02:01] started today.

[00:02:03] But enough from me.

[00:02:04] Buckle up and hold on tight as I beam your ears all the way to Ireland.

[00:02:09] Where Ken is waiting to share his story?

[00:02:13] So a massive warm welcome to the show Ken.

[00:02:16] Can you tell everyone listening a little about who you are and what you do?

[00:02:20] Neil first off a sincere thanks for inviting me onto the series.

[00:02:26] I'm really grateful for the opportunity to have this conversation with you today.

[00:02:30] To introduce myself, my name is Ken Moore, Irish as you can probably tell from the

[00:02:35] accent and I'm the Chief Innovation Officer at MasterCard.

[00:02:38] What do I do?

[00:02:40] I listened to one of your recent episodes with Adam Burden, I think from Accenture

[00:02:44] and he talked a lot about what a Chief Innovation Officer role means to them.

[00:02:49] I suppose in many ways it's similar for us here at MasterCard but where Adam was

[00:02:54] broadly covering many sectors were much more specifically focused on the world

[00:02:58] of commerce. So to get really practical, what does it mean here?

[00:03:02] I head up an interdisciplinary team that has product managers,

[00:03:07] future researchers, data scientists and experienced designers and developers

[00:03:12] and collectively we're responsible for MasterCard's innovation agenda,

[00:03:16] which means trying to figure out where and anticipating changes in the

[00:03:21] world of commerce and those changes can be driven by many things but are

[00:03:25] frequently driven by advancements in technology or changes in end customer

[00:03:30] needs. And then working with our clients and our partners around the

[00:03:33] world to build the products and services to kind of help people, businesses

[00:03:38] and economies thrive in that world. I think of relevance in the call today.

[00:03:43] I'm also the author of our MasterCard Signals report.

[00:03:46] So these are a set of reports that we push out orderly and in each issue

[00:03:51] we take a look at some of the latest trends that are transforming our

[00:03:55] industry so the world of commerce. So we've done recent issues I think on

[00:03:58] the future of payments on commerce and in the age of generative AI,

[00:04:03] which I know has been talked about ad nauseam. And then most recently we

[00:04:08] published the emerging technology trends for 24 where we looked at the kind

[00:04:12] of big technology advancements in AI, in computing and in data and how

[00:04:19] these are converging over the next three to five years.

[00:04:23] Outside of my day job, I do spend time being very humbled as an

[00:04:28] entrepreneur in residence in Harvard Innovation Labs in the US, where I get

[00:04:33] to meet some of the brightest and, you know, minds out there butting

[00:04:37] entrepreneurs, business leaders and really get to help them build the

[00:04:42] businesses and address some of the problems that they see out there.

[00:04:45] Personally, I would describe myself as an experience seeker and experience

[00:04:49] junky almost particularly when it comes to food.

[00:04:53] I think if my wife was doing this podcast she would probably also add

[00:04:57] that I am a wildly passionate sports fan but have almost no ability at

[00:05:02] sports. She would say I have delusions of adequacy as both a golfer and a

[00:05:07] tennis player. So I think if I'm being kind to myself there Neil,

[00:05:11] I'd say that what I lack in skill I make up for in boundless

[00:05:15] enthusiasm. You and me both I completely get where you're coming

[00:05:20] from there and you've beautifully set the scene for our conversation

[00:05:24] today because you're right in the heart of so many of the technological

[00:05:28] changes and the tech trends that we're seeing right now.

[00:05:31] And as you said Mastercard releases emerging technology trends for

[00:05:36] 2024 and your latest report explores tech trends in everything from AI,

[00:05:41] computational power and data technology.

[00:05:44] So to begin our conversation today can you just give us a bit of an

[00:05:47] overview of how these trends are actually converging to reshape

[00:05:52] the next three to five years and also of course how you were at

[00:05:55] Mastercard maybe leveraging these insights to drive innovation in

[00:06:00] your own field and maybe bring that to life with a few examples.

[00:06:03] And I appreciate I've thrown about three or four questions at you

[00:06:06] then right off the bat.

[00:06:08] I had my pen and paper on Neil.

[00:06:10] I was taking notes as you talk through that.

[00:06:13] But you're right to frame it I think in that way because if you

[00:06:16] look outside the walls of our businesses today there's just a

[00:06:19] plethora of emerging technologies that are individually important.

[00:06:24] And it's very hard to make sense of that.

[00:06:26] Which of those technologies are ready today or when will a

[00:06:30] technology be ready at some point in time in the future?

[00:06:34] What we tried to do through this signals report was actually

[00:06:37] try to make sense of the kind of big technologies both

[00:06:40] individually but also collectively how they come together

[00:06:44] to transform commerce.

[00:06:46] So in the latest issue of Mastercard Signals that report

[00:06:49] that you mentioned there we looked at nine key technology trends

[00:06:52] and those trends were really driven by technologies like augmented

[00:06:56] and mixed reality technologies like quantum computing,

[00:07:01] privacy enhancing technologies of course AI but not just

[00:07:06] generative AI also more kind of traditional forms of AI.

[00:07:11] Ultra wide band communications 5G maybe even 6G which is

[00:07:16] already a thing even though we won't really see it in the

[00:07:18] world for a number of years that tokenization,

[00:07:23] next-gen chips and other advancements in technologies.

[00:07:26] And we try to you know that's a confusing world.

[00:07:28] There's a lot of acronyms.

[00:07:29] There's a lot of names there.

[00:07:31] So to kind of make it simpler to understand we tried to

[00:07:33] group these three trends together into three areas.

[00:07:37] Advancements in technologies increases in computational

[00:07:41] power and then technologies that help us unlock the

[00:07:44] power of data but to do it in the right way where we

[00:07:47] build trust with consumers.

[00:07:49] Now the importance of the report really is to say that yes,

[00:07:53] all of these trends and all of these technologies are

[00:07:55] individually important but perhaps more importantly they

[00:07:59] are collectively converging and they're amplifying

[00:08:02] each other's impact.

[00:08:04] And that's why we've got the potential to reshape

[00:08:06] commerce over the next kind of three to five years as

[00:08:10] the technologies drive commerce to be more intuitive,

[00:08:14] interactive, immersive and indeed embedded in our daily

[00:08:17] lives. Now you asked for some examples on how these

[00:08:20] are converging so maybe let me give a few now and then

[00:08:24] as we get into the conversation I'll try to bring in a

[00:08:26] few more examples from what we see that's out there

[00:08:29] as well.

[00:08:30] So when I look at artificial intelligence and increases

[00:08:33] in computational power,

[00:08:36] I think we all understand that advancements in AI have

[00:08:39] driven the need for increased computational power

[00:08:43] itself right?

[00:08:43] We've got technologies like high performance computing.

[00:08:47] We've got the scarcity we currently see in GPU so

[00:08:51] graphical processing units that they're central to

[00:08:54] actually the running of those high powered artificial

[00:08:57] intelligence algorithms and those advances in those

[00:09:01] technologies in that those compute technologies have

[00:09:04] become pivotal to not just running the models but also

[00:09:07] training those AI models themselves.

[00:09:10] Conversely though, AI itself has allowed us to

[00:09:14] revolutionize computing infrastructure.

[00:09:17] So it's enabled us to design more advanced

[00:09:19] infrastructure and allowed us to optimize resource

[00:09:22] allocation.

[00:09:23] Just getting practical for a second.

[00:09:25] What does that mean?

[00:09:27] If you're a company or a business or a merchant out

[00:09:30] there using AI and compute now allows you to

[00:09:33] reset the competitive productivity baseline that

[00:09:38] your company has when you compare it to any other

[00:09:41] company out there, right?

[00:09:43] It's probably unlikely that any new company will

[00:09:47] succeed in the world if it's not taking advantage

[00:09:51] of advancements and compute an AI across all of

[00:09:54] its functions and its operations.

[00:09:57] And you can already see companies coming together

[00:09:59] to kind of deliver that.

[00:10:00] So you've got Amazon with Nvidia on the next

[00:10:03] gen cloud stuff.

[00:10:05] If I so that's AI and compute.

[00:10:06] If I look at data and compute, we've got spatial

[00:10:10] computing.

[00:10:11] I know you touched on that in a recent episode and

[00:10:14] new hardware form factors like all managed

[00:10:16] reality glasses, headsets and even lenses that the

[00:10:20] clip in front of your iris allowing us to create

[00:10:23] very immersive engaging and personalized

[00:10:25] experiences and they allow us to kind of bring

[00:10:28] physical and digital worlds together.

[00:10:29] We can see it in gaming, but we see it in

[00:10:32] all aspects of how we work shop and socialize.

[00:10:36] So these new data technologies like real time

[00:10:38] analytics and privacy enhancing technologies

[00:10:41] just to name two have enabled us to generate

[00:10:44] insights that allow us to create ever more

[00:10:46] personalized products, but most importantly,

[00:10:48] that allows us to do that, but in the right way.

[00:10:51] Meanwhile, technologies like tokenization,

[00:10:54] you mentioned digital identities and security

[00:10:56] technologies allow us to make data available

[00:10:59] and interoperable between physical and digital

[00:11:02] world. So as we step into an out of

[00:11:05] physical and digital worlds, they're going to

[00:11:07] help us instill trust in the way that we're

[00:11:10] doing it and implications of that really.

[00:11:13] I mean, I suppose at the most simple level,

[00:11:15] it's it's the combination of new data and

[00:11:18] compute technologies enable businesses to make

[00:11:21] much improved and data driven decisions

[00:11:25] to personalize existing products, loyalty

[00:11:27] programs or offers. But as you carry out

[00:11:30] forward, it also allows businesses to create

[00:11:32] brand affinity by demonstrating that they

[00:11:35] understand their customers at a much deeper

[00:11:37] level and also enable them to extend their

[00:11:39] brand and reach as they spend time as

[00:11:42] customers, as their customers spend time in

[00:11:45] both physical and digital worlds.

[00:11:46] And that's not just true for when we shop,

[00:11:49] but also in everyday activities like

[00:11:52] working or try and travel and going to

[00:11:55] a restaurant or a concert or a sporting

[00:11:57] event. And then lastly, on your multi part

[00:12:00] question, the how do AI and data come

[00:12:04] together? Well, implementing AI effectively

[00:12:06] really relies on the quality and the

[00:12:08] accessibility of data.

[00:12:10] Tokenization and kind of data management

[00:12:13] practices have allowed us to enhance data

[00:12:16] integrity for AI training. But now with

[00:12:19] more sophisticated AI algorithms, we're

[00:12:22] able to analyze data, not just the

[00:12:24] structured data that's well organized in

[00:12:27] our companies, but also the unstructured

[00:12:29] data. So data like emails and

[00:12:32] conversations and data contained within

[00:12:34] chats and messengers. And we can extract

[00:12:37] its meaning and its context and we can use

[00:12:39] that to then help improve the integrity

[00:12:42] and utility of the algorithms themselves.

[00:12:45] So there's a, you know, a convergence

[00:12:48] of the technologies where they reinforce

[00:12:50] each other. And that's going to allow

[00:12:51] us to develop more insightful tools

[00:12:54] for merchants. In 22 alone, I think

[00:12:58] 90% of all the data created out

[00:13:02] there out of all of a company's data is

[00:13:04] unstructured mostly on social media

[00:13:07] with parts of it, then in emails, chats

[00:13:09] and calls and conversations that we

[00:13:12] have each other. So that talks to the

[00:13:14] opportunity meal across that. So those

[00:13:16] are some examples of how AI data and

[00:13:19] compute come together and how they

[00:13:21] self reinforce to actually really

[00:13:24] bring about this kind of evolution in

[00:13:26] the world of commerce. And you put it

[00:13:28] perfectly there because I think I've

[00:13:30] been saying on this podcast for several

[00:13:32] years now that it's less about the

[00:13:34] emerging technologies, the next big

[00:13:36] thing that the shiny new solution

[00:13:39] that everybody's going crazy about.

[00:13:40] It's more about the convergence of

[00:13:43] them all and the real world problems

[00:13:45] that we end up solving as a result.

[00:13:47] And we mentioned AI assistance there.

[00:13:49] And I think they did have a bad rap

[00:13:51] originally because of the data problems

[00:13:54] behind the scenes. We've all seen what

[00:13:56] happens with garbage in and garbage out.

[00:13:58] But this is changing now with AI.

[00:14:00] So how do you envision these AI

[00:14:02] assistance transforming the consumer

[00:14:04] experience now that they're improving

[00:14:07] so much right now?

[00:14:08] Yeah, I think you framed that question

[00:14:10] beautifully because this is something

[00:14:12] that we've been trying to do for a

[00:14:14] while. But I think the maturity of

[00:14:16] the technologies themselves, the way

[00:14:19] that they converse with you to kind

[00:14:21] of act as an assistant maybe

[00:14:24] hasn't been as good as it needed

[00:14:26] to be. And I think that's been one of

[00:14:28] the biggest changes that we've seen

[00:14:30] through the introduction of generative

[00:14:32] AI.

[00:14:33] I saw a comparison somewhere, Neela,

[00:14:35] I remember the source but it isn't

[00:14:37] mine originally where we looked at

[00:14:39] historical kind of

[00:14:42] assistance almost like and they were

[00:14:45] compared to kind of walking into a

[00:14:47] librarian talking to a librarian,

[00:14:49] right? And the librarian

[00:14:51] does a bunch of things to kind of

[00:14:53] help you complete a task or a research

[00:14:55] task in this instance versus

[00:14:58] generative AI almost acting like a

[00:15:00] study buddy where it engages

[00:15:03] with you to understand the outcome

[00:15:05] that you're trying to achieve. It

[00:15:06] then pulls together and aggregates

[00:15:08] all of the data from new resources

[00:15:10] to help you achieve that task.

[00:15:13] So if you take that analogy and

[00:15:15] expand it here, then I think

[00:15:18] you're right to say that over the next

[00:15:20] three to four years generative AI

[00:15:22] assistants are likely to be a

[00:15:24] key feature across multiple aspects

[00:15:27] of the consumer experience from

[00:15:30] shopping and assistance

[00:15:32] that help us buy

[00:15:34] products and services that we

[00:15:36] really want to buy that are based

[00:15:38] on our needs and our likes and

[00:15:40] on the you know, the and

[00:15:42] you know, from the brands that we

[00:15:44] really know and trust.

[00:15:46] But also as we travel, so

[00:15:48] I go back to when I was a child,

[00:15:50] my mum and my dad had

[00:15:52] an ex had a relationship with our

[00:15:54] local travel agent and our local

[00:15:56] travel agent knew things about us

[00:15:58] and they use those things.

[00:16:00] They knew how much budget we had.

[00:16:01] They knew what we liked and disliked.

[00:16:03] They knew how we wanted to get

[00:16:04] somewhere. Do we want to fly?

[00:16:05] Do we want to drive?

[00:16:07] We're going to take a boat with

[00:16:08] the car out.

[00:16:09] And on the basis of all of that,

[00:16:10] they put together an itinerary for us.

[00:16:12] I think now with generative AI,

[00:16:14] we have the ability to create

[00:16:16] that hyper personalized experience

[00:16:18] where all aspects of the travel

[00:16:19] journey get integrated again.

[00:16:22] And that's because these assistants

[00:16:23] have the ability or the capability

[00:16:25] to synthesize vast amounts of data

[00:16:28] and based on a customer's

[00:16:30] personal preferences.

[00:16:31] I can even see it in things like

[00:16:33] size and fish if we're buying

[00:16:36] clothes and price point,

[00:16:38] etc., to create these hyper

[00:16:40] personalized experience.

[00:16:41] So these these assistants,

[00:16:44] they've got, you know,

[00:16:45] will have really, really deep insights

[00:16:47] into who you are, what you do

[00:16:50] and they're going to help you cut

[00:16:51] through the sea of choice,

[00:16:52] whether you're buying a clothes item

[00:16:54] or your booking travel,

[00:16:55] because sometimes I think the choice

[00:16:56] that that comes at us through social

[00:16:58] feeds and, you know, our own

[00:17:00] searches on the web can be a little

[00:17:01] bit overwhelming today.

[00:17:03] And I think that's the space

[00:17:04] or that's the problem

[00:17:05] that these assistants actually,

[00:17:08] you know, help solve for.

[00:17:10] And they will just be specific

[00:17:12] to consumers. I can see a space

[00:17:14] for a small and medium sized

[00:17:16] enterprise who maybe can't afford

[00:17:18] to have a CFO or a chief

[00:17:21] marketing officer.

[00:17:22] And we can create a digital assistant

[00:17:24] that helps them, you know,

[00:17:26] create the communications and

[00:17:27] marketing campaigns that will

[00:17:29] reach their customers are,

[00:17:31] which helps them manage

[00:17:32] their payables and receivables,

[00:17:34] which helps them, you know,

[00:17:35] finance their stock

[00:17:37] and manage their inventory.

[00:17:39] So I can see these assistants

[00:17:41] not just for consumers,

[00:17:43] but also for

[00:17:45] for SMEs and others coming in

[00:17:47] over that time period.

[00:17:50] And as you said, looking back,

[00:17:52] the tech wasn't as good as it

[00:17:53] needed to be.

[00:17:54] And I do think it's genuinely

[00:17:55] excited the speed

[00:17:57] which is improving now.

[00:17:58] And just to further bring to

[00:18:00] life everything you're talking

[00:18:01] about here. I appreciate

[00:18:02] you probably can't share too

[00:18:03] much. But is there anything

[00:18:04] you can share around how you

[00:18:05] have mastercard you'll

[00:18:06] integrate in enhancing these

[00:18:08] capabilities and services

[00:18:09] as a result. And also our

[00:18:11] advanced analytics might also

[00:18:13] unlock new insights for

[00:18:15] businesses and how it helps

[00:18:17] you drive innovation.

[00:18:18] Sure, sure. Sure. Happy to.

[00:18:21] So we have over two decades

[00:18:23] of expertise in AI

[00:18:25] this age.

[00:18:26] We've always leaned in to

[00:18:28] try and make sure that

[00:18:30] we deliver safe,

[00:18:32] you know, secure and convenient

[00:18:34] and personalized experiences.

[00:18:36] And I think with the introduction

[00:18:37] of generative AI, we have

[00:18:39] the opportunity now to make

[00:18:41] those same experiences even

[00:18:42] smarter, even safer and even

[00:18:44] more personalized.

[00:18:46] So we've been combining

[00:18:48] generative AI with our

[00:18:50] historical strength and our

[00:18:52] traditional strength in AI,

[00:18:53] but also our expertise in data

[00:18:56] to kind of build some of the

[00:18:56] products and services that we

[00:18:58] kind of touched on there.

[00:18:59] And whilst we've some done

[00:19:01] today, we're actively

[00:19:02] building more tomorrow.

[00:19:03] But maybe let me give you a

[00:19:04] few examples on this.

[00:19:06] So over the last

[00:19:09] year, Dynamic Yield is

[00:19:12] a micro sorry is a MasterCards

[00:19:14] company that uses AI

[00:19:17] driven recommendations.

[00:19:18] What does Dynamic Yield do?

[00:19:20] It uses AI to personalize

[00:19:23] every step of the consumer

[00:19:24] journey. So across any channel,

[00:19:26] whether it's web or mobile

[00:19:27] apps or email or SMS or

[00:19:29] digital assistance or

[00:19:30] kiosks or in store and more.

[00:19:33] So clients of Dynamic Yield

[00:19:35] like McDonald's, the

[00:19:37] restaurant chain have used it

[00:19:38] to personalize menus in 18

[00:19:41] thousand of its restaurants

[00:19:42] globally. Similarly, Dynamic

[00:19:44] Yield has worked with fabulous

[00:19:46] brands like Glasses USA and

[00:19:49] like Build with Ferguson to

[00:19:50] help them dramatically grow

[00:19:52] their revenue per user and

[00:19:54] their purchase volume overall.

[00:19:56] Now taking that as a base,

[00:19:58] we then went one step

[00:20:00] further. And if we go back

[00:20:02] to earlier in the conversation

[00:20:03] we liked, I talked about the

[00:20:05] conversation you have with

[00:20:07] somebody. I was a travel agent

[00:20:08] in that instance. But if like

[00:20:10] me, I hunt out experiences,

[00:20:12] but ironically, I hate shopping.

[00:20:14] I go into shops, I find things

[00:20:17] that work for me and I buy

[00:20:18] all of them in every cup.

[00:20:19] And I stick them in my wardrobe

[00:20:21] and I pull them out when I

[00:20:21] need them. And some of that

[00:20:23] is because I get frustrated

[00:20:25] in trying to find the products

[00:20:26] and services that are going to

[00:20:27] work for me for a particular

[00:20:29] event or for a particular

[00:20:31] situation. So we created

[00:20:34] and have just launched in the

[00:20:35] market a generative AI tool

[00:20:38] called Shopping Muse.

[00:20:40] And what Shopping Muse does is

[00:20:42] it's an advanced generative AI

[00:20:44] tool and it revolutionizes how

[00:20:46] consumers search for and

[00:20:47] discover products in a

[00:20:49] retailer's digital catalog.

[00:20:51] So it's already in early

[00:20:52] piloting the US and we'll

[00:20:54] be rolling it out more broadly

[00:20:55] in the middle and onwards of

[00:20:57] this year. What does it do?

[00:20:59] It recreates the in-store

[00:21:01] experience that you have if

[00:21:03] you were talking to a shop

[00:21:04] assistant where you might say

[00:21:05] something like, I'm going to a

[00:21:07] wedding. It's in the Bahamas.

[00:21:10] It'll be early in the morning.

[00:21:12] I've been asked to dress in,

[00:21:15] you know, bright colored

[00:21:17] clothes. And on the basis of

[00:21:19] that conversation that you

[00:21:20] have with the assistant, it

[00:21:22] will pull from the merchant

[00:21:23] catalog the relevant items

[00:21:25] that you might be interested

[00:21:26] in buying and then you can

[00:21:28] converse with it so you can

[00:21:29] refine the search by again

[00:21:31] talking to it or typing to it

[00:21:34] and it will refine the search

[00:21:36] on that basis. So it's a

[00:21:37] generative AI assistant called

[00:21:39] shopping news. There's many

[00:21:41] other examples as well, Neil,

[00:21:43] but in the interest of time, I

[00:21:44] think that's one that really

[00:21:45] jumps out for me because

[00:21:48] it's really taking and leaning

[00:21:50] into that future that we

[00:21:52] talked about where a co-pilot

[00:21:54] are an assistant helps you

[00:21:55] perform something that can for

[00:21:57] at least for some of us,

[00:21:59] maybe it's just me, can be a

[00:22:01] little bit confusing and

[00:22:02] a little bit difficult to kind

[00:22:04] of do today.

[00:22:05] It's incredibly exciting what

[00:22:07] you're doing here, but as the

[00:22:08] XIT guy and former change

[00:22:10] manager that has got many

[00:22:12] stories of what happens when

[00:22:13] things go wrong or tech teams

[00:22:15] move fast and break things, I

[00:22:16] do have to read myself in and

[00:22:18] sometimes think about some of

[00:22:19] the risks and with the

[00:22:21] potential increase in things

[00:22:22] like deep fakes, what are

[00:22:24] the implications for consumer

[00:22:26] trust and security and how

[00:22:28] we were mastercard

[00:22:29] contributing to the development

[00:22:31] of detection tools and

[00:22:33] advocating for new regulations

[00:22:35] to combat these challenges

[00:22:36] because on the flip side,

[00:22:37] this is equally as important,

[00:22:39] isn't it?

[00:22:40] It really is.

[00:22:41] I mean, I think that's an

[00:22:42] incredibly important question.

[00:22:44] I mean, we know you phrased

[00:22:46] it well, we know that

[00:22:47] ultimately trust is the

[00:22:48] currency of innovation.

[00:22:50] If consumers and businesses

[00:22:51] don't trust something new,

[00:22:54] they simply won't adopt it.

[00:22:55] Right. So we have to build

[00:22:57] trust into these new

[00:22:59] experiences that we're going to

[00:23:00] create. So to get to give you

[00:23:02] some context here, you know, the

[00:23:03] rise of malicious deep fakes

[00:23:05] has increased the market for

[00:23:07] detection tools and spurred

[00:23:08] new regulations.

[00:23:10] It also really emphasised

[00:23:12] the importance of establishing

[00:23:14] and maintaining data provenance

[00:23:16] or authenticity and origin of

[00:23:17] data and highlighted

[00:23:19] AI's role in bolstering

[00:23:21] cyber security responses.

[00:23:22] So practical terms, what

[00:23:24] does that mean?

[00:23:27] The it means that, unfortunately,

[00:23:29] sophisticated technology

[00:23:31] comes with more sophisticated

[00:23:33] threats.

[00:23:34] Bad actors have increased

[00:23:35] the market for cyber security

[00:23:38] tools as a result.

[00:23:39] So global costs and lost revenue

[00:23:42] from cyber attacks are

[00:23:44] estimated to reach 10.5

[00:23:46] trillion. That's trillion

[00:23:48] with a T by 2025.

[00:23:50] And that's not our stat.

[00:23:51] That's a stat from cyber security

[00:23:53] ventures.

[00:23:55] And we know from IBM, who

[00:23:57] measured this in 2023 that the

[00:23:59] average cost of a data breach is

[00:24:01] just under four point five

[00:24:03] million dollars.

[00:24:04] So those are frightening numbers

[00:24:06] are really frightening numbers.

[00:24:08] And it gives credence to the

[00:24:10] point that, you know, when we

[00:24:12] create technology, new technology

[00:24:14] tools, they're neither good nor

[00:24:15] bad.

[00:24:16] Right? So bad actors can use

[00:24:18] them to do bad things.

[00:24:19] So it's really important

[00:24:20] therefore that good actors

[00:24:22] lean in to use them to do good

[00:24:24] things.

[00:24:25] I think also consumers are going

[00:24:27] to increasingly seek to spend

[00:24:29] with brands that align

[00:24:30] with their values.

[00:24:31] So regulatory scrutiny

[00:24:33] in this space is absolutely

[00:24:35] inevitable. In fact, I would go

[00:24:37] so far as to say it's really

[00:24:38] desirable and robust

[00:24:40] measures have to be taken

[00:24:42] to safeguard personal information

[00:24:44] and comply with relevant

[00:24:45] regulations, both the ones we

[00:24:47] have today and those that

[00:24:48] emerge as a series

[00:24:50] of regulations roll out across

[00:24:51] the world.

[00:24:52] I think good businesses really

[00:24:54] want to earn trust and they

[00:24:55] want to comply with those

[00:24:56] regulations to gain their share

[00:24:58] of the consumer wallet.

[00:25:00] So trust truly is the currency

[00:25:02] of innovation.

[00:25:04] If you don't make security

[00:25:06] into the foundation

[00:25:08] of every product and service,

[00:25:09] then I think trust will falter

[00:25:11] and opportunities will be lost.

[00:25:13] This is something we're acute

[00:25:14] be aware of.

[00:25:16] You know, we ensure the

[00:25:18] security, the integrity and

[00:25:20] the trust in 143

[00:25:22] billion transactions that we

[00:25:24] process or manage on our global

[00:25:26] network every single year.

[00:25:29] So to give you some examples

[00:25:30] then of kind of, you know,

[00:25:32] where how do we kind of go

[00:25:34] about, you know, addressing

[00:25:36] some of those challenges?

[00:25:39] So since 20 since 2018,

[00:25:43] we've invested in excess

[00:25:45] of seven billion dollars into

[00:25:47] cybersecurity capabilities.

[00:25:49] And we've contributed to the

[00:25:50] launch of more than 20

[00:25:52] cybersecurity focused startups.

[00:25:55] We assess this, this one always

[00:25:57] flabbergast me, we assess

[00:25:59] the cybersecurity posture

[00:26:01] of every financial institution

[00:26:04] and of 14 million merchants

[00:26:06] every single every 10 days.

[00:26:09] And we leverage already

[00:26:11] a robust suite of AI models

[00:26:13] to protect consumers from

[00:26:15] fraudulent transactions.

[00:26:17] And we do that and we'll

[00:26:18] through tools like Decision

[00:26:19] Intelligence Pro, which is

[00:26:22] a market leading real time

[00:26:25] AI solution that helps banks

[00:26:27] score and therefore safety

[00:26:29] process those 143

[00:26:31] billion transactions.

[00:26:32] But we didn't stop there.

[00:26:34] We used new generative AI

[00:26:36] technology to take Decision

[00:26:38] Pro, I say to take Decision

[00:26:40] Intelligence and enhance it

[00:26:42] to the pro version, so

[00:26:43] Decision Intelligence Pro,

[00:26:45] which will scan an unprecedented

[00:26:47] one trillion data points

[00:26:50] on an annual basis to predict

[00:26:52] whether transaction is likely

[00:26:54] to be genuine or not.

[00:26:56] And if we put that together

[00:26:57] with other products like Safety

[00:26:59] Net and Biometric Authentication

[00:27:02] Score, we're seeing boosts

[00:27:04] in fraud detection rates

[00:27:05] on average of 20 percent

[00:27:07] and as high as 300 percent

[00:27:10] in certain instances.

[00:27:11] So that's maybe just some

[00:27:12] examples are very small

[00:27:14] number of examples of a larger

[00:27:16] set of products that we already

[00:27:18] have in the market today that

[00:27:19] leverage both traditional AI

[00:27:21] and generative AI.

[00:27:23] And it's probably, you know,

[00:27:25] a portent of an increasingly

[00:27:26] number of tools that we will

[00:27:28] introduce to the market over

[00:27:30] the next 12 and 18 months

[00:27:32] because the only way to really

[00:27:33] fight these new technologies

[00:27:35] is with these new technologies.

[00:27:37] And I'm curious on behalf

[00:27:39] of business leaders

[00:27:40] listening all around the world,

[00:27:41] how do these developments

[00:27:43] and trends that you're seeing,

[00:27:45] how do they create new opportunities

[00:27:46] for intelligent intelligent

[00:27:48] commerce experience?

[00:27:50] And ultimately, what role do you

[00:27:51] see Mastercard playing in that

[00:27:53] transformation?

[00:27:54] Yeah, I mean, it's a great

[00:27:56] question. So Mastercard

[00:27:58] has a proud history in cards

[00:28:00] and payments processing.

[00:28:02] Look, it's in the name

[00:28:04] and, you know, the Lord card

[00:28:05] is embedded in our name

[00:28:07] and it remains a hugely

[00:28:08] important part of our business,

[00:28:10] but it really doesn't define

[00:28:11] all that we do anymore.

[00:28:13] So over the last few decades,

[00:28:15] we've evolved from from a cards

[00:28:17] network or a cards payment

[00:28:18] network into a much broader

[00:28:20] technology company that operates

[00:28:22] in commerce.

[00:28:24] Even if you look at our payment

[00:28:25] rails, it's not just cards today.

[00:28:27] We've got fast, ACH and even

[00:28:29] blockchain based payments

[00:28:31] included within our set of rails.

[00:28:33] But we also have massive

[00:28:35] businesses and data and services

[00:28:37] in cybersecurity and intelligence

[00:28:39] and indeed new networks like

[00:28:41] open banking and identity services.

[00:28:44] But we also serve a much broader set

[00:28:45] of customers. It's not just the

[00:28:47] traditional retail banks

[00:28:49] and issuers and acquirers,

[00:28:50] it's commercial banks

[00:28:51] and new merchant segments

[00:28:54] like online marketplaces

[00:28:55] and FinTechs and telcos

[00:28:57] and mobile network operators

[00:28:58] and governments.

[00:29:00] So in a sentence, really,

[00:29:02] we see our role and our mission

[00:29:04] our priority to kind of help

[00:29:06] facilitate the transfer

[00:29:08] of something that has value

[00:29:10] between that broad set of stakeholders.

[00:29:13] So traditionally, it's been a payment

[00:29:15] that we have exchanged between

[00:29:18] businesses and consumers or between

[00:29:20] banks and merchants and consumers.

[00:29:23] But as we lean into this future,

[00:29:24] we think it will be broader than that.

[00:29:26] It could be data, it could be identities.

[00:29:29] It could be a broader set of assets

[00:29:31] that have value associated with them

[00:29:33] rather than exclusively

[00:29:35] payments themselves.

[00:29:37] And indeed, that's kind of reflected

[00:29:39] in our print in our kind of guiding

[00:29:41] vision as a company.

[00:29:42] Today, if you look at that for MasterCard,

[00:29:44] it says powering economies

[00:29:46] and empowering people

[00:29:48] and building sustainable

[00:29:49] world where everyone matters.

[00:29:50] And I think that really encapsulates

[00:29:52] what we're trying to be in the role

[00:29:54] that we see ourselves playing

[00:29:56] in bringing forward these exciting

[00:29:58] new worlds, but in the right way

[00:30:01] where consumers have trust

[00:30:03] in their own data that it's used

[00:30:05] for their benefits, that it's protected

[00:30:08] and that it's adhered to

[00:30:10] not just the laws as they exist today,

[00:30:12] but the principles behind the laws

[00:30:14] and the laws that we anticipate

[00:30:16] and regulations that we anticipate

[00:30:18] for tomorrow.

[00:30:19] I think to some degree

[00:30:20] we're a little bit like the Henry

[00:30:22] forward. If I'd asked people what

[00:30:23] they wanted, he would have set a

[00:30:24] faster horse, but somehow he jumped

[00:30:26] to a car.

[00:30:27] And I think that's the kind of

[00:30:28] principle that we kind of take on

[00:30:30] this one, Neil. We've got to

[00:30:31] anticipate the kind of regulations

[00:30:33] of tomorrow because we think they're

[00:30:35] a good thing and they're ultimately

[00:30:37] about creating trust and that's

[00:30:38] something that we hugely value

[00:30:41] across our ability to exchange

[00:30:43] value through this diverse

[00:30:45] set of stakeholders. And that's

[00:30:46] very much the role that we see

[00:30:48] ourselves playing.

[00:30:49] And what role do you see these

[00:30:51] transplaying in facilitating new

[00:30:53] standards in data handling too?

[00:30:55] And what does that mean for

[00:30:56] businesses and consumers?

[00:30:58] Yeah, I mean, it's interesting.

[00:31:01] I mean, let me give you an example

[00:31:02] of tokenization.

[00:31:04] For those of your listeners

[00:31:05] that may not be familiar,

[00:31:07] tokenization is a way of making

[00:31:09] data more secure, of making

[00:31:11] assets more accessible.

[00:31:13] Think of an NFT and a non-fungible

[00:31:15] token, the clues in the name,

[00:31:17] but also of making the exchange

[00:31:19] of data more interoperable.

[00:31:20] Right? So we can read tokens

[00:31:22] today at merchant terminals

[00:31:24] around the world. We can read

[00:31:26] tokens in many parts

[00:31:28] of the experiences that

[00:31:30] we have as we cross cities

[00:31:33] whether we're hopping into taxis

[00:31:35] or onto a smart

[00:31:38] transit system or whether we're

[00:31:39] going through an airport or whether

[00:31:41] we're coming into work.

[00:31:42] So tokens have already been part

[00:31:44] of our life and why?

[00:31:46] Because essentially tokens

[00:31:47] substitute sensitive information

[00:31:50] for what is sensitive information

[00:31:52] with intrinsically meaningless

[00:31:54] combinations of letters or numbers

[00:31:56] that can be cryptographically

[00:31:58] secured so can't be read

[00:32:00] without an encryption key.

[00:32:01] Now, to historically

[00:32:03] we've always tokenized things

[00:32:05] like your card number

[00:32:07] as you tap it on a merchant terminal

[00:32:09] or as you embed it on

[00:32:12] an e-commerce site when you're buying

[00:32:14] something, but actually we can

[00:32:15] tokenize any type of data.

[00:32:18] So we can tokenize identity.

[00:32:20] We can even tokenize new types

[00:32:21] of data like reward points

[00:32:23] for easier redemption or even size

[00:32:26] data if you were going to try

[00:32:28] and in an e-commerce transaction

[00:32:30] you wanted to buy clothes that

[00:32:32] help you fit better.

[00:32:33] Well, today

[00:32:34] and maybe I'm giving away a guilty

[00:32:36] secret but I tend to buy

[00:32:38] clothes in three different sizes

[00:32:40] because I can return two

[00:32:42] and keep the one that fits.

[00:32:44] But imagine tomorrow if I could

[00:32:45] tokenize by biometric data

[00:32:47] a data about my size and shape

[00:32:49] and I could exchange that

[00:32:50] at the merchant point of sale

[00:32:52] rather than choose to buy three

[00:32:54] I could get the one that fits me

[00:32:56] perfectly and that helps

[00:32:57] solve merchant returns.

[00:32:59] So I think the role

[00:33:01] we see there is this ability

[00:33:02] to kind of expand the utility

[00:33:05] of tokenization

[00:33:07] which already has standards,

[00:33:09] security, privacy and

[00:33:10] interoperability built into it

[00:33:13] from the world of commerce

[00:33:14] and we can extend that

[00:33:15] in into other areas.

[00:33:17] It doesn't stop at tokenization

[00:33:19] but I think that's a big one.

[00:33:21] Beyond that I think technologies

[00:33:22] like privacy enhancing

[00:33:24] technologies like

[00:33:27] zero trust architectures

[00:33:30] like the rollout of a broader

[00:33:32] set of identities, not just

[00:33:34] identities of people

[00:33:35] but identities of things

[00:33:36] and of businesses and of devices.

[00:33:38] I think bringing that together

[00:33:40] Neil is really what's going to

[00:33:41] help us create the confidence

[00:33:44] and security

[00:33:46] in the data that we exchange

[00:33:48] in a world tomorrow

[00:33:49] that's going to be ever more

[00:33:51] personalized and where we're

[00:33:52] going to be jumping in and out

[00:33:54] of physical worlds as we do

[00:33:57] as we shop, as we play

[00:33:59] and as we work.

[00:34:01] It's so good to hear you talking

[00:34:02] about this stuff because for years

[00:34:04] on this podcast we've been talking

[00:34:06] about blockchain tokenization

[00:34:08] and how to increase mainstream

[00:34:10] adoption, get large enterprises

[00:34:12] involved. And I've always said

[00:34:14] that when that moment happens

[00:34:16] it will be largely invisible.

[00:34:17] A mastercard customer doesn't need

[00:34:19] to know about blockchain

[00:34:21] and tokenization.

[00:34:22] It all happens without people

[00:34:24] knowing about it, right?

[00:34:26] And that didn't happen accidentally.

[00:34:28] That's built over over 60 years

[00:34:31] where we've really

[00:34:33] used our systems to protect

[00:34:34] the global network, to give

[00:34:36] confidence to that consumer

[00:34:38] across the 143 billion transactions

[00:34:41] that we handle annually.

[00:34:43] And it's taking those

[00:34:45] those technologies

[00:34:47] that are proven that we know

[00:34:48] that work.

[00:34:49] It's adding to them

[00:34:50] the new technologies today

[00:34:52] and it's evolving our principles.

[00:34:54] So we've always had principles

[00:34:56] that set out.

[00:34:57] So since 2019, I think

[00:34:59] when we published the first set

[00:35:01] of our data responsibility

[00:35:03] principles and they're really,

[00:35:04] really sensible principles

[00:35:06] that's putting people first.

[00:35:08] You know, you own your data,

[00:35:09] you control it, you should benefit

[00:35:11] from it. Our job is as a company

[00:35:13] is just to protect it.

[00:35:15] Well, then we expanded those

[00:35:16] principles and we brought in

[00:35:18] enhanced principles around

[00:35:19] inclusivity and accountability

[00:35:21] and social impact.

[00:35:23] And then we started to embed

[00:35:24] privacy by design principles

[00:35:26] into it as well. So which led us

[00:35:28] to embed multiple layers of

[00:35:30] privacy and security safeguards

[00:35:32] into the design of every one

[00:35:34] of our products and services,

[00:35:35] not just tokenization, but

[00:35:37] encryption and anonymization.

[00:35:39] And we've been building those

[00:35:40] internally. We've also been

[00:35:41] acquiring companies

[00:35:43] to help us do that.

[00:35:45] And we really believe

[00:35:47] that responsible companies want

[00:35:49] to use data in the right way

[00:35:51] and therefore they're going to

[00:35:52] adopt a similar set of

[00:35:54] principles to help them to do

[00:35:56] that. So for us, you know, we

[00:35:58] haven't stopped yet.

[00:35:59] We only scratched the surface of

[00:36:01] what data can do.

[00:36:02] But we really, really believe

[00:36:04] that people deserve to benefit

[00:36:05] from the use of their data

[00:36:07] with innovations that make

[00:36:09] their lives better.

[00:36:10] And we really plan to deliver

[00:36:12] that with trust because trust

[00:36:14] is what's going to drive scale

[00:36:16] more broadly than Neil.

[00:36:18] You know, we do think that

[00:36:20] it's really important to work

[00:36:22] not just within MasterCard

[00:36:24] on this set of principles,

[00:36:25] but to actively engage

[00:36:27] with advocacy groups, with

[00:36:29] with government organizations

[00:36:31] that are setting standards and

[00:36:32] principles in what is still

[00:36:33] an emerging set of technology.

[00:36:35] So we're very, very actively

[00:36:38] engaged outside of MasterCard

[00:36:41] with many organizations

[00:36:43] around the world to help set

[00:36:45] and evolve standards

[00:36:46] that we think are really, really

[00:36:47] important.

[00:36:48] And I think that's a beautiful

[00:36:49] moment to end our conversation

[00:36:51] today. But outside of the tech

[00:36:53] conversation, I must admit,

[00:36:55] I'm a little intrigued by you being

[00:36:56] a food lover, sports fan,

[00:36:58] a thrill seeker, someone that

[00:36:59] considers themselves a citizen

[00:37:01] of the world. So it does sound

[00:37:03] like you're an international man

[00:37:04] of mystery who has picked up a few

[00:37:06] stories along the way.

[00:37:07] And as my son, he's always

[00:37:08] telling me, Dad, whoever has

[00:37:10] the most stories at the end of

[00:37:11] this life wins.

[00:37:12] So with all that in mind,

[00:37:13] can you share the most

[00:37:14] intriguing story that has happened

[00:37:16] in your career?

[00:37:17] Well, it's intriguing.

[00:37:19] Yeah, maybe one that jumps to

[00:37:20] mine and it kind of brings

[00:37:21] together a few threads here.

[00:37:23] So you're right.

[00:37:24] I, you know, self

[00:37:26] categorize as an experienced

[00:37:28] junkie. I just love doing

[00:37:30] new things.

[00:37:32] So just before the pandemic, I

[00:37:33] was traveling in Asia

[00:37:35] and I got a recommendation

[00:37:38] for a pop up restaurant

[00:37:40] in the country that I was in at

[00:37:41] the time.

[00:37:42] And the and I decided to go

[00:37:44] with it. Right. And the

[00:37:45] experience that I had there

[00:37:46] has always stayed with me.

[00:37:48] And I therefore I'll share it

[00:37:49] on this on this podcast

[00:37:51] here. So this particular

[00:37:53] restaurant was a pop

[00:37:55] up and therefore they were

[00:37:56] trying to do something unique

[00:37:57] and different. So they reached

[00:37:58] out to me in advance, they

[00:37:59] gave me a link and they said,

[00:38:00] listen, you know, we'd like

[00:38:02] to help you have a very

[00:38:04] differentiated experience.

[00:38:05] Would you mind giving us some

[00:38:06] information in advance?

[00:38:07] So I thought, OK, I'm that

[00:38:09] I'm getting for that.

[00:38:10] So it started off with very

[00:38:12] benign questions like,

[00:38:15] you know, am I allergic to

[00:38:16] X and Y and Z?

[00:38:17] Then it moved from there

[00:38:19] into suggesting flavors at

[00:38:20] me and it, you know, it

[00:38:21] would give me a flavor like,

[00:38:23] you know, orange and everyone

[00:38:24] can imagine what orange is.

[00:38:26] And and it would ask me whether

[00:38:27] I liked it or hated it.

[00:38:28] And they have a sliding scale

[00:38:29] and then was a number of

[00:38:30] flavors like that.

[00:38:32] It then asked me a little bit

[00:38:33] more personal questions as I

[00:38:35] tried to gain weight or lose

[00:38:36] weight. What have I done

[00:38:38] earlier that day?

[00:38:40] Had I exercised, etc.

[00:38:42] And I thought I was getting

[00:38:43] ever more intrigued by all

[00:38:44] of this.

[00:38:45] But anyway, when I got to

[00:38:47] the restaurant that night

[00:38:48] meal and this is the reason

[00:38:49] why I tell the story, I

[00:38:50] was so struck by how

[00:38:52] personalized the experience

[00:38:53] was to me.

[00:38:54] I didn't get given a menu.

[00:38:56] I got given this curated

[00:38:58] personalized menu for me

[00:39:01] based on all the things that I

[00:39:02] said that I had liked and what

[00:39:04] I was trying to achieve.

[00:39:05] And it wasn't even just the

[00:39:07] food that was personalized

[00:39:08] to me.

[00:39:09] Now, this happens in pop-ups

[00:39:11] and I've seen this done before.

[00:39:13] But as I was going through the

[00:39:15] different courses, the imagery

[00:39:16] around me and the table that

[00:39:18] I was sitting at changed.

[00:39:20] Right. So for a seafood course,

[00:39:22] imagine rolling waves and a

[00:39:23] puff of salt in the air.

[00:39:25] So that's the level that they

[00:39:27] went to. And it's

[00:39:29] it was pre-pandemic.

[00:39:30] So it's whatever four and a

[00:39:32] half, five years since I had

[00:39:33] that experience.

[00:39:34] But it will, it's as fresh in

[00:39:36] my mind today, Neil, as it was

[00:39:38] the day after.

[00:39:39] And I think if we were to

[00:39:40] talk again in 20 years,

[00:39:42] it would still be as fresh in

[00:39:44] my mind then as it is

[00:39:45] now.

[00:39:46] And that's because it really

[00:39:48] captured. It spoke to me

[00:39:49] it felt like something that was

[00:39:51] really bespoke to me and I

[00:39:53] really, really enjoyed it.

[00:39:54] So I think that's probably the

[00:39:56] most interesting that the

[00:39:57] funniest, that's probably a beer

[00:39:59] conversation.

[00:40:02] Absolutely lovely.

[00:40:03] And what a fantastic story.

[00:40:05] It does make me think just how

[00:40:06] much further along we are

[00:40:08] ahead and being able to create

[00:40:10] those experiences now.

[00:40:11] And there was a great line from

[00:40:12] the IBM chief.

[00:40:13] I think it was about 10 years

[00:40:14] ago now. And she said that the

[00:40:16] best experience that any of us

[00:40:18] have anywhere becomes the

[00:40:20] standard expectation for that

[00:40:21] future experience we expect

[00:40:24] everywhere.

[00:40:25] It's so true, isn't it?

[00:40:26] Yeah, it really is.

[00:40:29] I think somebody else

[00:40:31] said the future happens very

[00:40:32] slowly and then all at once.

[00:40:34] And I think if I look out there,

[00:40:36] I think the Lego bricks for the

[00:40:38] experience of tomorrow are

[00:40:40] already there at some level in

[00:40:42] the world today.

[00:40:43] We've got frictionless stores.

[00:40:44] We've got contactless devices.

[00:40:47] We've got interoperable data

[00:40:48] transition standards like

[00:40:51] tokenization.

[00:40:52] We've got ultra wide band

[00:40:54] arms. We've got six G's

[00:40:56] already a thing.

[00:40:57] And it's the same step level

[00:40:59] increase over 5G as 5G was

[00:41:02] over four.

[00:41:02] We've got smart stadiums and

[00:41:04] we've got a plethora of new

[00:41:06] form factors like augmented

[00:41:08] reality glasses and headsets

[00:41:10] all coming.

[00:41:11] So I think the ingredients or

[00:41:13] the Lego bricks are there,

[00:41:15] Neil. It's it's simply about

[00:41:17] putting them together with

[00:41:19] with trust at their heart

[00:41:21] to really deliver on the

[00:41:23] opportunities of tomorrow.

[00:41:24] So I completely agree with you.

[00:41:26] And obviously we've covered so

[00:41:28] much in a short amount of time

[00:41:29] today from the Mastercard

[00:41:31] emerging technology trends

[00:41:33] for 2024 signals report

[00:41:35] and all the areas that we've

[00:41:37] delved into that.

[00:41:38] And the Mastercard website

[00:41:40] is a huge website.

[00:41:41] So where would you like to

[00:41:42] point everyone listening who

[00:41:44] maybe want to check out the

[00:41:45] report or just learn a little bit

[00:41:47] more about some of the work you're

[00:41:48] doing with technology?

[00:41:50] We love them to do that, Neil.

[00:41:51] Thank you for offering.

[00:41:52] If they search for Mastercard

[00:41:54] signals, they'll find the

[00:41:56] reports and not just the latest

[00:41:58] one, but we've published one

[00:41:59] every quarter for the last

[00:42:01] couple of years.

[00:42:02] So you'll find a series of

[00:42:03] reports there. So Mastercard

[00:42:04] signals SIG and ALS

[00:42:07] and you will find the reports.

[00:42:09] And I'd also if anyone would

[00:42:10] like to connect to me, I

[00:42:13] love and I'm intrigued

[00:42:14] and I'm super passionate about

[00:42:16] how technology makes things

[00:42:18] possible tomorrow that aren't

[00:42:19] possible today.

[00:42:20] So please do connect with me

[00:42:22] on my LinkedIn profile.

[00:42:24] You'll find me under Kenmore

[00:42:26] Mastercard or Kenmore CIO

[00:42:28] Chief Innovation Officer.

[00:42:29] Really, really would love to

[00:42:31] connect and exchange views so

[00:42:33] that we can help this world

[00:42:34] arrive in the right way.

[00:42:35] Well, as we said at the very

[00:42:36] beginning of our conversation,

[00:42:38] the real magic happens when

[00:42:39] technologies converge.

[00:42:42] And today we've learned about

[00:42:43] artificial intelligence,

[00:42:45] compute and data and trust

[00:42:47] as well. It's so important.

[00:42:49] And when all that converges,

[00:42:50] the things that you're creating

[00:42:52] here is just phenomenal.

[00:42:53] I'd love to stay in touch with

[00:42:54] you. See how this continues

[00:42:56] to evolve and also find out

[00:42:57] about your next big

[00:42:59] personalized experience that

[00:43:00] you may or may not encounter

[00:43:02] in the months ahead.

[00:43:03] But more than anything,

[00:43:04] just thank you for sharing

[00:43:05] your story and the insights

[00:43:07] from this report today.

[00:43:08] Neil, it was my absolute

[00:43:10] pleasure and I'd love to

[00:43:11] have you along for that next

[00:43:12] restaurant adventure.

[00:43:13] I think it's clear that the

[00:43:14] landscape of commerce and

[00:43:16] consumer experience is on

[00:43:18] the brink of a monumental

[00:43:19] transformation and it's

[00:43:21] powered by advancements in

[00:43:23] AI, computational technology,

[00:43:25] data innovation, all these

[00:43:27] technologies converging.

[00:43:28] And that is what helps build

[00:43:30] trust. So Ken's insights

[00:43:32] have not only showcased MasterCard

[00:43:34] 's pivotal role in that

[00:43:35] evolution, but I think I've

[00:43:36] also illuminated the pathway

[00:43:38] towards a future where

[00:43:40] technology creates more

[00:43:41] intelligent, secure and

[00:43:44] engaging consumer experiences.

[00:43:46] And for everybody listening,

[00:43:48] I turn the microphone over to

[00:43:49] you. You've heard from me,

[00:43:50] you've heard from Ken.

[00:43:52] The question for you is how

[00:43:54] do you envision these

[00:43:55] technologies shaping your

[00:43:56] daily interaction

[00:43:58] from shopping to travelling

[00:44:00] and beyond?

[00:44:01] And how is it impacting

[00:44:02] your business,

[00:44:04] the future of your business

[00:44:06] and how you're preparing

[00:44:07] for that future?

[00:44:09] Please share your thoughts,

[00:44:10] join the conversation by

[00:44:11] emailing me techblogwriteroutlook.com,

[00:44:14] Twitter, LinkedIn,

[00:44:15] Instagram, just at Neil CQs.

[00:44:18] I'd love to hear your thoughts.

[00:44:20] Now I will return again

[00:44:21] tomorrow with another guest,

[00:44:22] another topic and I'd love to

[00:44:24] invite you once again

[00:44:26] to join me. But more than

[00:44:27] anything, thank you for

[00:44:28] listening today. And until next

[00:44:30] time, don't be a stranger.