Latest / The Payments Shed / Ep. 18 - LIVE from the MoneyPot with Mastercard @ Money 20/20 USA 2025

Transcript

Ep. 18 - LIVE from the MoneyPot with Mastercard @ Money 20/20 USA 2025 · The Payments Shed

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  Welcome to the Payment Shed Podcast, the weekly podcast that
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  dives into the big topics, trends and people shaping the
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  world's of payments, fintech and business leadership.
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  Of your two Co hosts, myself Grant Heavens and Justin Hannah
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  Ranjita, please introduce yourself.
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  Tell us about your role in MasterCard.
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  Absolutely. Thank you so much for having me
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  on the podcast. So I run services for North
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  America. And as we were talking before,
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  that's a broad term, but it includes all of our safety and
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  security assets, all of our engagement, digital engagement
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  assets, so our loyalty programs and things like that, and also
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  all of our data analytics assets.
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  So all of the insights that we get from our data.
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  So it's a broad set of capabilities that enhances the
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  value of payments. Brilliant and we really want to
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  dive into cybersecurity with you today and how that kind of
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  threat has evolved specifically payment side, but also with with
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  the schemes at the moment. So I just wanted to get your
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  initial take on how that has changed in recent years.
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  Yeah. So I've been in cybersecurity
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  and fraud for maybe close to two decades now.
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  So it's a long time and I can tell you that there are three
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  major things that have changed over the last several years.
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  I would say 1 is more data and more an expanding threat
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  surface, right? So think about all the data that
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  we produce in a day. And apparently I was reading a
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  recent stat. It's 2.5 quintillion bytes of
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  data that a user that our that the planet is generating every
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  day. And that is 10 to the power of
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  18. In case you wanted to know.
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  It's a lot of data. So it's increasing the threat
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  surface a lot because of a lot of a lot of interactions, a lot
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  of channels, right, digital channels.
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  The number 2 is that now cybercrime is industrialized,
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  right? So it is no longer the guy in
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  the basement or the girl in the basement.
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  The Nigerian Prince has long gone.
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  This is industrialized crime. They're running it like a
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  business. And the third one I would say is
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  technology. So just as much as we're excited
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  about AI and we're excited about all the the great things we can
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  do with it, it's also enabling the the fraudsters, right?
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  So they're using AI to perpetrate attacks at scale,
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  completely automated. So you can get fake sites,
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  millions of them at scale, which, you know, people find it
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  hard to shut them down before, before they can perpetrate
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  fraud. And it's coming from all
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  channels, social platforms, everything.
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  So automation and they're using technologies like deepfakes.
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  So with the technology and the fact that now we have as a
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  service models even in the crime side, so ransomware as a
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  service, fraud as a service that that technology angle they're
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  using it as well for their for their endeavors.
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  So they're they're operating almost like businesses in their
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  own. Right, it's.
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  Pretty interesting topic. I think the the attackers being
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  more organized and using AI in particular.
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  How do you guys try and monitor and get ahead of that as a
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  scheme? Yeah.
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  So we're constantly looking for patterns.
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  So I would say because it's automated and it's AI driven.
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  We have been employing AI for decades actually to monitor
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  transactions, right. So protecting transactions,
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  identifying anomalies, identifying patterns that just
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  don't look quite right. And so you have to kind of use
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  AI to combat AI, right? So, and then on top of that, you
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  also have to think about things like threat intelligence because
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  there's a lot out there that's available on the dark web and
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  other sources, open web, etcetera.
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  Kind of always monitoring that, monitoring at the portfolio
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  level, looking at what kind of malware and what kind of other
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  vulnerabilities are out there that might be impacting our
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  customers and then getting the signals from that and sharing
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  that with the ecosystem, that is what's going to help us to kind
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  of stay ahead of this. Does the sheer volume of data
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  that you guys have at your fingertips help you in that
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  defense? Absolutely, Yeah.
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  The amount of data that we have absolutely helps.
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  But one thing I will caution is to get the signal out of the
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  data is really important, right? So it's like sometimes it can be
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  like fraud can be or cyber attacks can be like looking for
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  a needle in a haystack. So being able to get that right
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  signal requires a lot of machine learning, a lot of artificial
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  intelligence and a lot of scale, right?
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  I would say a lot of compute power at scale is what you need
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  to be able to get that signal from that mass of data, because
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  there's a lot of it out there, to your point.
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  It's a huge game of cut and mouse, right?
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  This is you think you'll get and now the fraud just do something
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  different and you've got to try and kind of capture that.
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  And actually the point is from before is like them running it
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  as an enterprise. Yes, they're running it as an
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  enterprise, but they're not an enterprise like MasterCard.
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  They don't have a brand to protect.
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  They don't have regulatory scrutiny.
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  They don't have any values that they're running by.
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  They can, they can try anything they want, right?
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  So we're up against that too. Yeah.
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  And look, we know MasterCard sits at the global payments
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  ecosystem right in the center of it.
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  How do you approach securing something from security
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  perspective at such a vast level?
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  Yeah, that's a very, very good question.
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  So really, as I said before, we kind of started at the
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  transaction, right? So we've been protecting
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  transactions for decades, hence the the synonymous word of trust
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  with MasterCard, right? So when you swipe your card,
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  you're never thinking about it. So what we have at the
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  transaction layer is real time fraud scoring of every single
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  transaction on the planet in real time using like thousands
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  of signals per transaction. So that's at scale.
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  Then we also have what we call safety net, which is like AI
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  powered blanket over the network, which is able to pick
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  up fraud that's happening at scale anywhere around the
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  planet. If you go to our command center,
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  you'll actually see, you know, fraud is happening in in some
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  market in the Middle East. You'll see that light up and
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  we're constantly monitoring, right.
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  So that's at the transaction level.
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  We then realized that actually fraud at the transaction level
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  because of our own models at the network level, our partners
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  models at the financial institutions that we work with
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  and merchants etcetera. Everyone's getting more
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  sophisticated, which is great. So fraud at the transaction
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  level has actually been going down over the past several
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  years. However it's migrating, right?
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  So it's migrating to the point where somebody is creating an
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  account or somebody is getting a token provisioned on their
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  device. So it's that time of account
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  opening where we have to understand the individual, we
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  have to understand the identity and that's, you know, that next
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  layer of security that we need to apply.
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  So it's about device identity, it's about the person identity.
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  Is this a synthetic identity? Is this a bad device?
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  What are what do we understand about the device from the device
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  footprint? And then you take it even one
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  step further and you think about the cyber ecosystem in which us
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  and our partners are working and we can understand, we can try to
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  understand what are the vulnerabilities in those
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  ecosystems and making sure that we are compensating for those
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  vulnerabilities. And then also the next layer is
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  threat intelligence, which we just acquired recorded future
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  last year, which is a premier player in the threat
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  intelligence space. So it's about the layers, it's
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  about the transaction, it's about the identities and the
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  devices and then the cyber ecosystem as well, because
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  that's where all the breaches are happening, right.
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  So we're having thousands of breaches every year.
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  All those credentials get out there and then it monetizes on
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  the payment network. Right.
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  So MasterCard card do this all on their own, right.
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  It's, it's great what you guys are doing.
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  How do we take this from a MasterCard perspective to a
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  global issue that we can work together and collaborate?
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  Yeah. Collaboration is obviously very,
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  very critical for us. And we collaborate with our
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  merchant partners, we collaborate with our issuers.
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  And I can give you a specific example of how we collaborated
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  just last year. We had the point of interaction,
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  which is our own conference where we bring in a whole bunch
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  of merchants. And one of the things that they
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  said to us was we're really struggling with returns fraud,
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  right? So and it's a $50 billion
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  problem globally. It's a Subs, it's kind of a
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  subset of first party fraud, if you've heard that.
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  And so returns fraud is is kind of part of that.
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  And so they're like, what can we do together as a network plus
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  the merchants to kind of combat this problem?
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  So there are some signals that merchants have that they can
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  share with us and, and we can kind of share that with the
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  issuer because there's a bit of a information asymmetry, right,
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  obviously between the merchants and the issuers and the network
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  is a nice conduit to be able to pass that intelligence along.
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  So this Q4 of this year, we're actually, we're launching a
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  return fraud risk score. Plus we changed some of our
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  rules on the network so that now people can report return fraud
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  because it wasn't an actual reportable fraud type, right?
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  So we made changes there. We're launching the the return
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  fraud score. So not only can merchants send
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  the data, we can send that insight to the issuer.
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  And then the issuer also knows that somebody calls and hold the
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  chance of return on this transaction is really high.
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  They can question the card holder and be like hey.
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  There's advanced AI and the machine learning that can do
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  overarch that as a product. Absolutely.
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  Yes, it does because we are using past behavior to predict
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  whether this could become a return fraud basically, right.
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  So that's what we're doing and we get those signals from our
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  transaction data and from the data that the merchant will
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  share with us. And I guess a follow up question
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  for me on that, because we're talking about agentic commerce a
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  lot of the conference. How does that agentic future?
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  Obviously you've had merchants come and speak to you and
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  they're talking about fraud. But for me, Agentic seems, you
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  know, I work in the famous industry as as most people in
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  the room do today, but that seems like something that could
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  almost be counterintuitive to the the steps forward we've made
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  as far as prevention is concerned.
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  What's what's your thought on that?
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  So Agentic is obviously brand new and every week I feel like
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  there's another new announcement on Agentic, whether it's open AI
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  with Stripe or Google that put out their protocol on Agent pay
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  protocol. So we're working with all of
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  these industry players on Agentic Pay.
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  We have our own Agentic Pay as well, which is based off of our
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  tokenization framework. So you know who the agent is,
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  it's authenticated. So that's, that's the base.
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  Then we also have APIs that will collect the car, the intent of
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  the human. So if we have intent APIs that
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  go around it as well. And then we also have consent
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  APIs that go along with it as well to ensure that the human
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  behind the agent is actually doing that.
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  But to your point, while agentic opens up a lot of exciting use
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  cases, for example, my daughter no longer needs to stay awake
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  till 1:00 AM to buy Taylor Swift tickets.
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  She can just have her agent to do that, right?
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  So which is amazing, but then you start thinking I've been in
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  fraud long enough. So I see all the dark circles
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  and the dark lurking corners and all of that.
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  But the, what is the, the, the liability framework around that,
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  right? What if your agent goes rogue?
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  Who's liable for that transaction?
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  What if your agent gets taken over, right?
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  Like agent takeover, like account takeover, right?
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  Or how do you do know your agent right, like kya?
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  So those are all the concepts that we're working on to make
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  sure that we trust is embedded in agentic payments as well.
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  Because it is coming, it will, it is going to happen.
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  It's going to be happening at scale if it hasn't already
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  started. Right.
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  It always just felt like a bit counterintuitive to me
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  particularly put my European payments on.
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  We've got really familiar in the market with Otps, your one time
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  passcodes, people more used to using those now mandated 3D
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  secure kind of rips up the playbook a little bit on some of
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  these things that we absolutely. Place, absolutely.
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  And if you think about it right now, I was thinking about just
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  sit back and think about all of these things every now and then.
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  But you think about it, you've so far been dealing with a good
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  human and a bad human, but now you're almost in a 2 by 2.
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  So you're like dealing with a good human, bad human, good bot,
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  bad bot, good agent, bad agent, and then you've got this two by
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  two. And each one of those
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  permutations could lead to all sorts of different things.
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  So it has changed the paradigm to your point.
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  And it's something that we're working very closely because we
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  think there's exciting possibilities as long as the
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  right guardrails are in place. I think it's quite interesting.
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  We look at cybersecurity and using AI as a tool, which is
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  fantastic, but it's also a risk because you know that fraudsters
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  are used in cybersecurity AI, right?
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  To do the exact opposite of what we're trying to get them to do
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  in the first place. Exactly.
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  Yeah, should. We talk a little bit then about
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  collective resilience as well, because I know that's something
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  that you're you're quite passionate about and I'd love to
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  get your take on, you know, the collaboration that's going on
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  between banks, fintechs, governments and merchants in
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  that space at the moment. Yeah, absolutely.
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  One example that can bring it to life is scams, right.
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  So scams is something where many times it's authorized push
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  payment, right is what's resulting in, in the scam.
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  And there's a lot involved in that.
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  And this is 1 specifically where when you talk about scams,
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  governments, other entities are very involved.
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  And there are there are associations like the Global
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  Anti Scam Alliance, which is I think a great organization where
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  part of it along with several of our peers as well.
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  And it is an area that really does require a lot of
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  collaboration because many times the person that's actually
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  scammed is embarrassed about it, right?
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  Like they, they're like, oh, how did that happen to me?
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  And many times they don't even report it because they don't
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  know what the recourse is. They don't know how to even go
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  about getting their money back or what they can even do knowing
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  that they might have been scammed on an investment scam or
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  could have been a romance scam or any other type of scam,
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  right? So that is a perfect area for
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  people to collaborate and governments, nations, we're
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  collaborating where the networks are collaborating as well and
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  the financial institutions. Now I know in the UK this has
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  been a big thing and there is kind of like a split liability.
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  So we're kind of monitoring how that works.
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  We don't have that here in the US, but sometimes things like
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  that can actually help to fuel innovation and fuel
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  collaboration, which is really critical.
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  For many years we've been talking about, you know, sharing
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  of consortium data. And while there are several
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  examples of things, I think more needs to be done there to be
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  honest. It's not an all right way with
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  data sharing sometimes as well. I mean, we have GDPR in in the
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  UK and there's this question mark, I guess your government
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  organization and you know, again, we're very precious about
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  the data that sits within there there ecosystem.
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  So you like leaning into how we best collaborate in a fair and
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  trustworthy way, but also not breaching those policies that we
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  have internally. Correct.
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  Exactly. I think everyone gets very kind
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  of, you know, a little bit uncomfortable when you talk
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  about sharing data. But again, let's keep in mind,
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  and I think there are many, I know of many consortiums where,
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  you know, data is being shared at that consortium level and
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  it's, it's useful, but I think part of the problem is there are
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  many, right? So it still creates these silos
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  of data and things like that, which which isn't helpful.
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  Ultimately, at the end of the day, I think we really need a
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  step change in the way that data is shared because the criminal
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  rings, they're sharing, right? So we can't, we have to be
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  sharing in order to be able to combat them.
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  And I think we will get to a point where that will be the way
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  that we will need to get better. Because if, if something is
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  happening in one particular financial institution or
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  multiple, chances are it's going to, it's going to spread, right?
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  So the sooner we have that data and we have that information and
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  the sooner we can put defenses in place, the better because
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  we're all fighting against common enemy at that point.
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  And I think the piece there as well is when we talk about the
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  data, it's different businesses within that ecosystem need
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  different pieces of that data, right?
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  So sometimes you're taking all this data and consuming that,
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  but you don't need all of that. So you're trying to kind of
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  decipher 3, what you do need from the data to make a decision
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  within your own engine. And how does then mask and then
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  share them best practices do you think with the wider ecosystem?
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  Yeah. So we are always participating
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  in, in many different forums. We, we participate at the
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  industry level to set protocols like for example, Agent pay, you
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  brought that up before. Like I said, there's a lot to be
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  worked out with agent pay and we are on at least 10-15 different
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  like industry forums and working directly with partners like
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  Google and Microsoft and others that are heavily focused in
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  that. So that's from a standard
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  setting perspective, because obviously we have a large
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  franchise and we have rules around how this works.
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  And we also work with another entity called EMV Code to set
• 17:04
  the standards. Then when it comes to actually
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  developing solutions, we work very closely with our merchant
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  partners, our small businesses, because small businesses are
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  many times left out or they're very underserved, right?
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  Yet they are the backbone of most economies around the world.
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  So we need more. Inclusive tools, you think?
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  Many more inclusive tools and being able to whatever data
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  insights that we get and we're sharing, making sure that that's
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  actually helping them so that they're not left behind in this
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  game, right? So that's the other piece of it.
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  And then we also participate in several consortia as well to
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  kind of share best practices and data.
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  So looking ahead, what do you think comes next when it comes
• 17:46
  to cyber resilience? Kind of what's the next phase?
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  Good question. This is the crystal ball
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  question. So I think Agentic we're,
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  despite the fact that we're talking about AI and Agentic all
• 18:00
  the time, I feel like just being in this industry, we're still
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  very, very early on in this whole journey with Agentic.
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  So I think there's a lot more to come there to the point where
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  it's scaled and being used by consumers at scale.
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  I think there's a lot more to be done for that to happen.
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  Yes, today we're using it just to get some recommendations and
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  stuff. But like at the point where it's
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  autonomously buying for you or doing tasks for you, I think
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  we're still getting there. So that's, I think 1 trend that
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  you will see a lot of advancement in the next couple
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  of years. The other one that I think
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  you'll see a lot of is probably a lot of advancements around
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  quantum resistant because we know quantum is coming.
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  It's the next kind of frontier. They've been saying that for a
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  while, but now I'm starting to see a lot more happening there.
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  And I'm also starting to see a lot of startups and other
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  companies kind of focused on quantum resistant technology,
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  which is good. And then I think we'll also end
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  up seeing a lot more from a cyber perspective, particularly
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  a lot more innovation in the zero trust architectures, right.
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  So those are you, I think we'll see start seeing a lot more
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  innovations there as well. And all of those things are good
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  for cyber. If you were then to pull out one
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  high level, you'll you'll go to tip for all organizations out
• 19:24
  there as far as protecting themselves, what would that be?
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  I think you need to invest in very sophisticated AI if you
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  haven't done so already. We know a lot of companies and a
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  lot of institutions are doing that.
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  But you need to continue to invest because think about
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  Agentic, right? It could change the paradigm and
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  shift everything. Cuz all this time we kept saying
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  bots are bad, right? Because they were the bad bots.
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  But now I could have a perfectly good bot trying to buy Taylor
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  Swift ticket for my daughter. You don't want to, you don't
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  want to shy that bot away, right?
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  Because you want, it's going to drive business.
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  So I think those types of paradigm shifts are going to
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  happen. So you're going to have to get
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  ready for that. So just because you've invested
• 20:04
  in AI doesn't mean you can just kind of sit on the laurels.
• 20:07
  You need to continue to evolve as the kind of ecosystem.
• 20:10
  Market though, isn't it? I mean, it's great advice, but
• 20:12
  at the same time it's, it's just so much, so many brands, so many
• 20:16
  startup companies, you know, even SMB are getting hammered
• 20:19
  every single day with come use our AI for this, come use our AI
• 20:22
  for that. How do you kind of cut through
• 20:23
  the noise? Yeah, it's a good question.
• 20:26
  I think one of the things that you have to focus on as a
• 20:29
  company is focus on your key strategic value that you're
• 20:33
  providing your customers. If that can be enhanced by AI
• 20:37
  and you determine how that can be enhanced by AI, go for it.
• 20:40
  Invest in it. Build the infrastructure to
• 20:42
  measure the success of that investment from the ground up.
• 20:45
  Build the infrastructure to be able to scale that from the
• 20:48
  ground up and build the security infrastructure and the
• 20:52
  governance around it to be able to monitor that as well from the
• 20:56
  ground up. I think if you did that, you
• 20:58
  know you'd be in a good. Spot and other than your
• 21:00
  daughter going to watch Taylor Swift, what excites you the most
• 21:04
  of the next couple of years of the future?
• 21:08
  I think the the potential with AI and agents is amazing.
• 21:12
  It's going to change the way things I think we operate, how
• 21:16
  we work, potentially even in the workplace.
• 21:19
  I think that's quite exciting. We can, I can see a future where
• 21:22
  as managers, we're managing a workforce of agents and humans
• 21:27
  with the, with the thought of, you know, the agents augmenting
• 21:31
  the human workforce, right? Yeah.
• 21:33
  Because there's a there's a very big human element here that we
• 21:36
  cannot forget. But I think that it opens up a
• 21:38
  lot of exciting possibilities as.
• 21:39
  Well, Sky, that's here, it's creeping in, isn't it?
• 21:41
  But thank you so much for joining us today.
• 21:43
  We have got one final section. I'm not sure if you've watched
• 21:45
  our show in the past, but we have an end item called the
• 21:48
  Shelf of Shame where I guess nominates something that call it
• 21:51
  a payments ick or a business ick if you like.
• 21:54
  It really grinds your gears that you can nominate to put on the
• 21:56
  Shelf of Shame, never to return again.
• 22:00
  As much as I hate to say it, passwords are still used and I
• 22:04
  know my parents use them and I know many people use them and
• 22:08
  we've been talking about for decades we have to kill
• 22:10
  passwords. But we haven't done it yet and I
• 22:13
  would love to see a world where there's literally no password.
• 22:16
  I just looked on informationisbeautiful.com.
• 22:19
  I don't know if you've seen that website, but password 12345 is
• 22:23
  still the most prevalent password.
• 22:25
  Which blows my mind after two decades in security.
• 22:28
  But. Has everyone in this room got a
• 22:30
  question mark or an exclamation mark in a lot of their passwords
• 22:33
  as well for being honest? I don't think we have a choice
• 22:35
  anymore, right? You've got to be in the most
• 22:37
  obscure kind of password, so you forget it most of the time
• 22:40
  anyway. So you're hoping your safety can
• 22:42
  save you every time, right? So let's just get rid of it all
• 22:44
  together. It makes life a little bit
• 22:46
  easier. We don't need 100%.
• 22:48
  I agree going into the shuttle show.
• 22:49
  Never to return well. Thank you so much for joining us
• 22:51
  today. Where can people get in touch
• 22:53
  with you if they want to find out more about what you do at
• 22:54
  MasterCard? They can e-mail me at
• 22:57
  ranjitaranjita.iriyer@mastercard.com. Amazing.
• 23:02
  Thank you so much, Ranjita. Thank you.