Mastercard, President & CTO Ed McLaughlin — Emerging Technologies in Payments | by Kailee Costello | Wharton FinTech | Feb, 2024

• Evolution of Payment Systems: Mastercard’s Journey into the Digital Era

Ed McLaughlin: That is a really broad sweep. I will start all the way back when we came out of a world dominated by cash. I like pointing that out because if you proposed cash today, people would say it is ludicrous; we just put up with it because we are used to it. Out of that very physical cash-check world, Mastercard started completely offline. I do not know if you ever remember there were (credit card) imprinters, also known as ZipZap machines or Knuckle Busters; the whole idea was a very physical thing.

It was really in the early 70s that we started putting machine-readable mag stripes on the charge plates. We built the first electronic network to tie all of that together. That was really a marvel for its time. Because of the value that has continued to evolve, you saw more and more payments start to shift. It started in the physical world, dedicated terminals connected to proprietary networks. The next big accelerant was really in the mid-90s with internet connectivity.

Afterwards, you could fully move to things like e-commerce. Consumers could have much easier digital access. Next big acceleration was mobile, because suddenly you could be online all the time, and being online was always with you. We had a whole new wave of innovation, a whole new set of capabilities that came out around that to get to where we are today, where digital is the dominant mode of transacting. If you think of what payments, if you think of what cash really always was, it was just the movement of information. We have really been able to use technology, connectivity, and these transitions in consumers’ behavior to fundamentally change how commerce happens.

• Adapting to the digital payment landscape: Mastercard’s evolution and innovations

Ed McLaughlin: I would say maybe a decade ago, people would confuse us with the actual card itself. You know, it is even in the name, and I remember I would have to explain to people, ‘no one thought Facebook was a book either.’ Sometimes it is just where you are coming from, a metaphor that people can get.

We saw a progressive shift from people interacting physically to first, e-commerce: things coming online, people buying that way. Second, a shift from buying individual items to subscription services like Spotify. Third, a shift from maybe owning a car to going to an Uber. Therefore, this is much more on-demand, much more flexible way of paying for that. Our systems have always adapted along with it.

I think some of the biggest things that have come into the network is first of all, the ongoing enhancements of security. If you have noticed the chip that is on the card to provide encryption of all transactions and payments, when we moved into mobile devices like Apple Pay or Google Pay, we used the chips in your phone to offer similar encryption capabilities. A lot of technology went into securing the payment systems to fight fraud. We have applied incredible AI capabilities and techniques to help keep the system safe for everyone who is using it and encryption techniques to help make sure all the information is protected within it.

Next, we have what we call contextual commerce. We would continue to extend into all the new things that you would want to do. Anywhere you wanted to use your Mastercard you could. For example, we worked to get Mastercard into your smartphone, and we are doing things with Mercedes to make sure it is embedded in your car. Therefore, a digital interface or API first is really the way that we’ve structured the network, so you can get instant access completely digitally to all of the accounts that you have on a Mastercard. That’s just been a great business for us and it has continued to expand everywhere that people can use their card even when it is not a card.

• Navigating quantum computing: securing payment systems and anticipating future challenges

Ed McLaughlin: I think there are two really big sides of quantum: one of which is you can use it to solve very complex problems that you can’t solve with classical computers. Now the implication with that is a lot of the encryption security we use, not just for payments, but really for just about everything online, is usually based on solving very, very hard math problems, such as prime numbering factoring (RSA encryption). It turns out the very technique that makes it so hard to solve with classical computers, quantum computers are really good at. Furthermore, there is a model called Shor’s algorithm which will allow you to solve that hard problem quite easily if you get a sufficiently capable quantum computer. This becomes an existential threat to encryption: how do you ensure you can stay encrypted when the very thing the encryption is based on, this hard problem, goes away?

There are two things we are doing there, one of which is looking at the underlying way that we are encrypting all of the payment flows and technology to not depend on something that quantum computers can do really easily but move to something which is complex in a different way. The National Institute of Standards and Technology in the US has put some very good work out on this; there are different algorithms you can use that are much more quantum resistant.

The other thing though is the advantages that quantum can do because you are solving really complex and hard problems. In the medical field, for example, quantum entanglement has been used to study protein structures.

When it comes to Mastercard, I will give you one example for quantum technology usage. We piloted a technique called quantum key distribution, where one of the hardest things we have is moving the secrets around. If you want to make sure that you are impervious to a calculator, a mathematical attack, you can move a true random secret around, rendering it immune to any solution. There is no risk there. Therefore, we used basically quantum entanglement to assure secure delivery of keys to multiple locations, and can use that to sign the transaction, so we are sure it has not been observed or changed in any way. We did a pilot with a number of our partners — Verizon, Cisco, and a few others — and we actually demonstrated that we could use quantum entanglement or quantum secure communication to move one-time keys about the system. Therefore, while quantum technology creates an attack vector, it also creates a lot of opportunities with advanced computers and even better ways to secure the systems than we have today.

The key to quantum is when you do what we do, you have to say there is something which could have a really big impact that is reasonably within your planning horizon. Therefore, you need to start working on addressing it now so, if and when it happens, you are already ready for it.

• Quantum computing’s potential in fraud detection and loyalty enhancement

Ed McLaughlin: That is one of the business opportunities of quantum being able to solve complex problems in ways you might not have been able to before. Just like fighting fraud is trying to find the things that look normal but you are unlikely to do, for something like loyalty, we are trying to find the things which could be most appealing to you. Therefore, you are dealing with a huge sort of problem space and set where I want to rapidly come to a conclusion around that. To that end, we are working with a company called D-Wave. We also have partnerships with a number of other companies in the quantum space where we are modeling out how you could use a different type of computing technique to solve problems we have always had in new and novel ways. Therefore, in multivariate complex problems, such as detecting & fighting fraud and getting better affinity and loyalty, there are real opportunities in quantum computing. It goes back to what I said earlier, we want to be experimenting with it now, so if and when the cost curves make it accessible on a retail basis for what we want to do, we already understand the models and what is there.

At Mastercard, we are not necessarily engaged in primary or pure research, but we are extremely active in applied research like quantum key distribution, quantum analytics for things like our loyalty programs. We have long been leading in artificial intelligence and AI for ways to fight fraud and protect the network. We are constantly saying is there a way out there to do what we do better and to make sure that we are constantly trialing or experimenting with those things.

• Mastercard’s AI-Powered Fraud Detection and Prevention Strategy

Ed McLaughlin: Let me talk about AI in general, because it has been a dozen years, and we have long been a leader in AI. I think Forbes Magazine gave us their innovation of the year in 2019 for our decisioning platform, our AI-based engine, that we have put into the network.

What we have always used AI for is one, fraud because you have a very good signal; we know whether or not there is fraud on the transactions. We have the ability to see a massive data set flowing through the network. Through machine learning and backward propagation techniques, we have the ability to get a really good view of what the patterns are there for. Then we were able to do a couple amazing things, one of which is we call it Safety Net; we can see when it looks like an account has been compromised and there is a runaway set of transactions. Before a human could even intervene, we can cut that off. You can almost imagine a circuit breaker we have put into the network that is constantly looking at every transaction and can react to it immediately. That protects you, and it protects anyone away from it. Therefore, we have always said if you have a Mastercard, you have zero liability for any fraud that happens on that card. We stand behind it. We stand behind you. These are the techniques we put in place to allow us to back that promise up. Therefore, Safety Net has been a great one for us.

The other thing is just looking for suspicious transactions or fraudulent transactions themselves. The technology that used to be used was very rules-based. You would have analysts look at a whole lot of information, come up on a rule, and you put it in the system. It did not react quickly to what fraudsters were doing. It generated a whole lot of false positives. When we got out of trying to write rules and actually use machine learning and the AI algorithms in the system itself, we found two big things. One is we stopped three times more fraud, which was amazing. But we actually let six times more good transactions go through because we did not have any false positives. That generated a lot more business. It was great for consumers because if you are trying to do something that actually is legitimate, we are letting it happen for you. Therefore, it was transformative to our business when we used these sophisticated AI techniques inside the network. Now when you look at things like generative AI, it gives us a new tool. We have about 13 different AI engines we are running right now in the network. If you think of this as the 14th, it is a new technique to solve different problems. Therefore, it helps us in the core of our business, which is the safety, security, and the network, and it has been transformative there; there is literally tens of billions of dollars of fraud that we are stopping with these techniques.

The other thing which I am really excited about is if you look at what we are doing with generative AI and the tools there (e.g., Microsoft Copilot), it really helps people in the work they are doing by providing assistance. A lot of the AI and machine learning techniques we use are great with structured data, structured information. This gives us a whole new set of tools for unstructured data, which is really where humans live and work, not machines. We are doing things like taking really complex elements of our rules and documentation and everything else and doing it as an overlay to help our human agents and to help our customers better. We have seen great advantages in things like coding, where our engineers can get code assist as they go through that, to not write the code for them. I actually think that is a little overplayed, but to be much more effective, much more productive in the work they are already doing. We really see that, Copilot, or this idea that you have greater assistance for what the humans are doing, this human machine interaction, I think is the key to the advantages we are seeing with generative AI. That is why everyone is so excited about it right now.

• The frontier of Generative AI technology

Ed McLaughlin: I believe that whenever there is a general-purpose technology, there is always a process of learning and understanding. First, you determine what it is really good for, and secondly, what existing techniques are actually better at.

I will go back maybe a decade ago again with blockchain. I used to joke that everyone tried to end every conversation, every sentence with “on the blockchain.” You are like, well, you just need a database for that, and here is what is unique and different about it. I think that is really the state we are with generative AI. We have observed instances where caution is warranted, especially where people have datasets that are too small, and you just get in a hallucination engine. You really need a massive amount of information for it to be effective.

At the same time, I think there’s huge unexplored areas because we have always had trouble, in data processing and systems, dealing with unstructured information. The way that we can now combine things like images, patterns, text in new and novel ways, we are just beginning to explore how that can really be brought together and truly generate things at a scale that was not there before.

The other element is the generative aspect of it, the idea that the machines can learn from themselves and actually test against each other. If you look at the famous example with AlphaGo, solving the Go problem. After it got through the rules and actually started playing against itself, that is when it got the huge advantages. Therefore, we actually think AI training AI odds or bots fighting bots, there will be really interesting advances when we actually use the systems to support itself.

• Mastercard’s role in global economies: ensuring resilience, security, and innovation

Ed McLaughlin: One of the great things about Mastercard is we truly do power the economy. We are running national critical infrastructure in countries around the world. The resilience of our network and the scale of the network are great sets of challenges to have. If you think about it, we have over three billion accounts on the network that people need every day to do what they have to do, and it is an obligation we think about a lot. We really do. So first, you start with resiliency. We have multiple layers of redundancy and resiliency built into the network. We have had edge decisioning for a long time, where even if the whole network goes down, we can still have resilience and have decisioning happening on the edge. If network counterparties and banks are not there, we can actually stand in and make decisions on their behalf. This allows you as the consumer to go forward with that. Then, you design multiple redundancies within the network backbone itself. Our whole point is that if you have a Mastercard, we are always there for you; you have that availability. That is something when I talk to people about: as an engineer, what excites you? As a business person, what are the things you find important? For us, doing these things that everyone depends on in making sure we are there for them. We do this because it is important. You really feel it, and it is a vibe we have across the organization for that.

You asked about security and there are two big categories. One, the availability, the resiliency, you just build in; that is how you run the system. We are also very conscious of attacks on the system and then attacks run through the system. ‘On the system’ is where someone would disrupt and you have to think a lot about things like nation state actors. We are already seeing a new generation of warfare, which is asymmetrical, where they look at transit systems, healthcare systems, power grids, payment systems, right? We do need to really work to protect ourselves against progressively sophisticated attacks. Those are both things you build into the systems. And it is also for all of the people, all the human actors involved making sure that security stays a highest priority. One is protecting their systems themselves.

The second thing which we have talked about a lot is fraud ‘through the system’. This includes making sure that the transactions, even if they are flowing fine, are not used for the wrong purposes. And that is really where we have applied so much research, so much AI to make sure that at the massive scale we have, we are constantly stopping that fraud from coming through the system. We will do 150 billion transactions in a year.

It is amazing that the decision management platform that we talked about, our AI engine, has over a trillion parameters in it now; if you think about a million million, that is the size of scale and scope that we are talking about. It really is inspiring if you are an engineer to say: how do you build a globe-sized, unbreakable, massively scaled, really fast system? That is what we do all day.

• Fostering fintech innovation: Mastercard’s collaborative approach

Ed McLaughlin: I would say partnership has always been the heart of Mastercard because we are a network. In some ways, we are one of the original platform companies. We provide a lot of capabilities and services, but we do not hold the funds. We are not the bank. We are not the merchant. We do not sell the goods. We have always said that our job is to have a business or a platform where people can build great businesses on top of.

If you go all the way back to our founding 60-something years ago, we were founded as a bank association. We were founded as a way of people being able to work together. That has always been the heart and DNA of what we have done. Through the years, you have seen us build and grow through partnership, and fintech has been an essential part of that.

I am proud to say if you really think about some of the big breakthrough innovations that people like to look at, whether it was Amazon e-commerce or an Uber and mobility, iTunes and digital media, Netflix, the way they were able to build those innovations was because they had access to the Mastercard network.

We have been an ingredient in just about every one of those digital innovations you see. When people were shifting their behavior to their smartphones, we worked with Google and Apple in partnership to bring the best of Mastercard to help design safe and secure usage of Mastercard for payment and craft a great user experience that is delivered through their platforms.

For Fintech itself, we have what we call a Fintech Express program, where we work with young companies to show them how they can connect to the Mastercard network to help them thrive and grow and be successful. We have launch events we do with them. We have been heavily funding, you know, selective companies that we think are doing particularly interesting things that will help advance the space. One stat we had a couple of years ago, I think 90% of the fintechs in the UK were working with Mastercard because we really wanted to do what we could do to help them be successful.

Nubank, one of the biggest, I think maybe the biggest Fintech in the world coming out of Brazil, was a Mastercard exclusive partner from the start, because we really invested in their success. Therefore, what I love about fintechs is that you have this unbelievable unleashing of creativity, where people are harnessing new technology and applying it to solve problems that have not been solved before. Our ability to, with financial inclusion, reach and serve people we could never reach before, to create new contextual commerce, to say how in new spaces or new environments that people are exploring can we ensure that they can access the Mastercard network, which helps them build their businesses. This also means everyone who has a Mastercard gets access to all these great new experiences. This goes from the smallest nascent companies with a good idea, that we want to make sure it can easily tap into our APIs and our network, to working with an Apple for something like Apple Pay.

There is a great story that Jim McKelvey, the co-founder of Square, tells about working with Mastercard to actually get Square going at the beginning and the work we did to help them design their service and define it in our network. Therefore, the amount of creativity, energy, and access we see coming out of the fintech community is just amazing. And it really gets back to the heart of our business.

What I love about digital is this digital combinatory effect where we can bring amazing capabilities; those three billion plus payment accounts can all be available to a fintech just by tapping into our network. Whether it is Apple or a couple of kids out of school, they are all part of our partnership model.

• Shaping the future of payments: Mastercard’s vision and innovations

Ed McLaughlin: I think I am contractually obligated to say the future of payments looks like a Mastercard. I am being a little flip on that. One of the things that we talk about a lot is multi-rail or all the different payment types that you want to have as a consumer: whether you want to access to a line of credit for something that you can pay down over time; whether you want to use an installment payment, which we have on the network, so you can have a fixed set of payments known for that purchase; whether you are accessing your store of funds, such as your deposit account at a bank; whether it is a specially prepaid product, like some of the great things we have done in healthcare with flexible spending accounts and other things. Really any way or any type of transaction you want to do as a consumer is included. We have done a lot of work in direct account access through things like open banking. What we firmly believe is you as a consumer are going to want to have easy access to all the types of funds and materials that you want.

We have done a lot of work with blockchain technology, particularly stablecoin. We have been working with governments on what is called central bank digital currency, or CBDC. I think that is another great example where we do over 150 currencies on the network today. I am not so worried about the physical representation of them; if there’s a few more currencies that come out, we can already see how to handle that in. So, we have prototyped things like “how do you settle in a stablecoin versus a traditional fiat currency”. There is a lot of really interesting work that is going on there, but really what drives us is what I said earlier: What are people trying to do? What is the right contextual commerce? What is the best way to do it for you? Then, providing that seamless and secure access back to whatever account or funding mechanism we want to use, whether it is dollars in a bank, a line of credit, a crypto store, or whatever makes sense for that environment. Therefore, it really gets back to the core of what we do. It is actually what even the brand is. If you look at the Venn diagram we have, it is bringing the retailer, the merchant, the person you want to do business with, together with the consumer for the way that they can make it happen.

I think what you are going to see is an ongoing array of possible ways that people can make payments and an equal desire of consumers to have someone simplify it, bring it all together for them and give them the safety and trust in the systems that they can use it.

I will give you one example of future payments I really like. We did an announcement with Mercedes for contextual commerce in cars and the holy trinity of things like parking, tolls, and fuel (gasoline or electric charging). It is just a different way to have an easier and better experience.

I think what we are always seeing is people wanting to extend into new environments and they want to take the things that they have to do every day and just make it easier to access. And that is what it is going to look like. Payments will become much more an embedded part of many different contexts.

• Consumer-facing interface of blockchain and stablecoin

Ed McLaughlin: Well, a few things on this. It is really important to separate out blockchain as a technology. There is application of blockchain technology in an environment where it is hard to establish trust. This application is distinct from payments and currencies.

Furthermore, much of what we have seen so far is it is really used more as an asset class. I think if you look at the SEC rulings that are coming out now, people have used it like a speculative asset, like you do gold or art or other things of that nature, not so much as a means of commercial exchange.

In fact, what we have seen the most is people will hold it as an asset and then they actually want to convert it into a Mastercard, into real money. We have a lot of programs where people can on the fly convert their Bitcoin or whatever coin they have into something that they can use and spend with a merchant the way they can have it. I think that bridging and interfacing has been really, really successful. Therefore, the coin-based asset class is one element we have seen from there.

On the stablecoin side of it, we actually have a digital proxy, whether it is a stablecoin that is tied to an underlying financial instrument or what certain governments like Jamaica and others have been working with have done for actual digital currency. That just becomes another means of settlement that we can use.

Therefore, whether it is registered as dollars in an account or if the object itself is the store of value, it is almost like you would have cashier’s or treasurer’s checks back from the banks in the day. We have done a lot of work there on how you can have what we call tokenized deposits, which again you can use the reach of the network and the access to it and have a different means of transacting.

• Harnessing technology for financial inclusion

Ed McLaughlin: It is one of the most amazing and dynamic spaces that are out there. I am probably a little biased because almost my entire career has been the intersection of finance and technology. However, if you think about it, money is just information.

I think there are only a few profoundly universal and interesting sort of data sets that are out there: you have search, all of human knowledge, and now with what we are doing with generative AI, much better ways to interact and deal with it; you have geospatial, where things are; you have commerce, what people buy. It is just such a native part; it is human activity. Therefore, this whole idea of helping people with their assets, helping them plan, helping them have better experiences using it and extending what is there is just a foundational element, and technology will change it profoundly. Who we are as people does not change; how we do it will. That is really where I see a lot of the fintech work happening.

If there is one area out of that I would highlight, because it has been such a passion for us at Mastercard, is, as I said earlier, using technology to reach and serve people you never could before. I think in 2014 we set a goal around financial inclusion, that the internet of everything must lead to the inclusion of everyone. We commit ourselves to bring half a billion people into the formal financial system.

Because if you think about it, even if we can connect to you technically, if you cannot transact, you are still cut off. You do not have the educational options. You do not have the entertainment options. You do not have what we enjoy. A few years ago, we accomplished that goal of bringing a half a billion people in. We doubled down to say we want to bring another half a billion people in. Much of what we are doing is finding new and novel ways to harness technology, to bring the value of financial inclusion to people around the world and the fintech community has been particularly vibrant there.

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About Mastercard

Mastercard is a global technology company in the payments industry. Our mission is to connect and power an inclusive, digital economy that benefits everyone, everywhere by making transactions safe, simple, smart and accessible. Using secure data and networks, partnerships and passion, our innovations and solutions help individuals, financial institutions, governments and businesses realize their greatest potential. With connections across more than 210 countries and territories, we are building a sustainable world that unlocks priceless possibilities for all.

About Ed McLaughlin

Ed McLaughlin is the president and chief technology officer of Mastercard and a member of the company’s management committee. He oversees the company’s technology functions,

including the global payments network, enterprise platforms, technology infrastructure and operations, information security and global technology hubs.

Prior to this role, he served as chief information officer, directing the development of Mastercard products and services. In 2010, Ed was named chief emerging payments officer, leading the development and launch of the company’s digital strategy, partnerships and platforms, including Mastercard Send and Mastercard Digital Enablement System (MDES), the digital token program. Ed joined Mastercard in 2005 as head of Bill Pay and Healthcare, and served as chief franchise officer between 2008 and 2010, where he was responsible for the Mastercard global rules, licensing, brand standards and compliance programs.

About the Author

Kailee Costello is an MBA Candidate at The Wharton School, where she leads the Wharton FinTech Podcast team. She’s most passionate about how FinTech is breaking down barriers to make financial products and services more accessible — particularly in the personal finance space. Don’t hesitate to reach out with questions, comments, feedback, and opportunities at [email protected].

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