In this episode of CXO Bytes, George Maddaloni, CTO of Operations at Mastercard, joins Sanjay Podder to discuss how Mastercard is driving innovation in sustainable technology through green software practices. George shares insights on the company's approach to reducing energy consumption in software development, the role of AI and data in enhancing sustainability, and the importance of fostering a culture of green software from the top down. He also highlights Mastercard’s collaboration with the Green Software Foundation and how the organization is helping to shape their ESG goals. From edge computing to responsible AI, George provides a comprehensive look at how Mastercard is balancing technological advancement with environmental responsibility.

 

TRANSCRIPT BELOW:

Sanjay Podder: Hello and welcome to CXOBytes, a podcast brought to you by the Green Software Foundation and dedicated to supporting Chiefs of Information, Technology, Sustainability, and AI as they aim to shape a sustainable future through green software. We will uncover the strategies and a big green move that's helped drive results for business and for the planet.

I am your host, Sanjay Poddar.

Hello. Welcome to another episode of CXOBytes where we try to get into the world of sustainable software development from the perspective of the C-Suite. Today, I am extremely delighted to have a special guest, George Maddaloni. George is the CTO of Operations at Mastercard.

 I would like to talk to George today more about how Mastercard, a leading payment giant, is navigating the intersection of technology and sustainability. Also, Mastercard has been a member of the Green Software Foundation. So what has been the role of the foundation to help shape Mastercard's approach to sustainable technology? And finally, also talk a little bit about the future of sustainable technology the context of financial services. George, welcome to the podcast.

George Maddaloni: Thanks for having me. Really appreciate it and looking forward to it. 

Sanjay Podder: Absolutely. And I'm so delighted about the contribution George is having in the field of sustainable technology.

It's very rare to find a CIO who is so passionate about this topic. So this is going to be a great conversation. Before we dive further, I would like to give a reminder that all the things we discuss will be available and linked to the show note below the episode.

So George,

why don't we start with a few words from you about Mastercard and about yourself.

George Maddaloni: Yeah, sure. So, George Maddaloni, CTO of operations for Mastercard. And maybe I'll start with some things that probably most people know about Mastercard and then lead into a little bit that, from a technology perspective, you don't.

Mastercard connects billions of individuals and businesses to the digital economy and makes them an equal part of, or an inclusive part of that economy and really views its mission as enabling, empowering people as well as powering economies so that anybody that's out there, whether they're paying their bills, buying their groceries, they have that capability. And from a technology perspective,

that means a lot in terms of what Mastercard does on a day to day basis. Every product we offer is a technology product. And for my team, that goes back to the mission that we have, which is to provide reliable, scalable, secure, and sustainable, technology platforms to continue to transform the payments industry.

We, the team itself runs a vast network, that connects those billions of people to hundreds of millions of acceptance points, thousands of financial institutions, and back to many data centers around the world. To make all of that happen on a global basis, in a very low latency manner, because time matters in our business, and I really use this phrase within Mastercard that we're running a cardiovascular system of the company,

and it's why our team is one of the larger technology divisions in the company and has a really front row seat to all the innovation, all of the product development that occurs and it helps also enable all of the employee technology across globe for the company. So, it's a great job. Something I'm really passionate about is technology, and it's great have the 

Sanjay Podder: opportunity to lead such a great team. Fantastic, 

George. 

And there cannot be a better use case for sustainability, given what you are trying to do at an enterprise scale, and I'm curious I have seen you as a person who deeply cares about sustainable technology. You have got recently the board of sustainableIT.org, Mastercard has been a member, a very important member of the Green Software Foundation. What makes you feel that this is an area that you are, that is important and you are particularly passionate about? What drives that passion? 

George Maddaloni: Yeah, I think, first off, the impact that technology has is great, but you can absolutely see that the growth that is occurring in the technology landscape, at no time, have, has technology been more important to everybody's day to day life than now. And I think as we think about our ESG goals as a company, all across ESNG, that Mastercard is a place that really deeply cares about those goals. We've put actually, both executive and our own compensation goals around that. And it's important as I said, that we're not just impacting, here for the business, but we're here for the world and the impact that we're making on the world, across those goals.

So as a technologist, it's kind of natural to be understanding what's happening from an energy perspective.

And for me, this became a little bit of how are we managing consumption in a more efficient way as things are growing? And a little bit of a platform for, to help, my team understand that consumption, and make sure that we're making the right choices.

so I think it was both, "hey, macro level, this is having an impact, from an energy perspective." Even at a micro level or in a day to day decision making, how can we use that lens to think about the consumption we're about to put forward for a project or a refresh or software development, and what is that going to mean in terms of our overall footprint? 

Sanjay Podder: Fantastic. George, it just reinforces the conviction we had in the Green Software Foundation that while we focus a lot on the developers and how we enable them to write greener code, what is actually required is a culture of green software or sustainable tech. A culture that comes right from the top and you kind of reinforce that because unless it comes from the top, sustainability will never be a first class concern in your software development process. So that in some sense is the essence behind this podcast series where we are able to articulate what are leaders like you doing to make this real, make, it should not be academic, but it should be actionable, you know? And, this is great to hear from you. Very recently, I read a nice article from Mastercard, your Technology Trends 2024, extremely insightful. And I like the three areas that you have articulated, AI, computing, and data. And the question is, you also kind of explored the confluence of AI, computing, and data and how that's going to reshape commerce. And that's very powerful with all the examples. Now, as a consumer I'm also a user of Mastercard Payment. I'm thinking "how does that translate into kind of innovations you foresee happening in the way we do payment as consumers?" Right? And there was a very interesting statement in the report which I really liked.

It said that, in the context of computing, it said that it's not about how computing will get more powerful, it's about how do you make that power, how do you distribute that power in an intelligent, trustworthy, and sustainable way?

And that's again the interplay of sustainability and technology. So the question that I had in my mind is, as a consumer, how do I see that innovation playing out in the payment process? And how do you balance, therefore, that innovation with the sustainability dimension, given you're thinking about AI and data 

George Maddaloni: computing. Yeah, I

Sanjay Podder: computing?

George Maddaloni: I'll start actually where you started, back to the culture, 

and it, does start at the top, the company was

one of the first first payments organizations to really put forward its net zero, an aggressive net zero goal. And that really, again, started the organization rallying around this particular topic. But every, piece of technology and those investments that we're thinking about as well, we're, back to this principle of "are we empowering people?"

And a lot of times we have to think about, especially in the world of AI and data, this has been reinforced, what are our principles and how are we going to approach this, specific innovation? So, and you can't enable AI without a key focus on data. I think knows that, especially in the generative AI world, the more data that you have, the more effective that, that model is going to run. so we established a set of data, data, principles, handling principles. One very focused on eliminating bias, another very focused on making sure it's used from an inclusive perspective, and of course consumer protection, at the forefront a lot of the regulation that we're subject to, but much less helping influence. So when you're swiping your Mastercard as you were gracefully articulating, the power of the network includes AI capabilities. those have been around for over a decade, now and we've actually won other awards for a particular AI tool that we've developed that focuses on fraud, detection.

And, you know, we've seen the improvements that we're able to make with new techniques in the AI space that, specifically generative AI techniques that we can employ in In those models, and I mean, they were already effective as well. I think everybody over the past 10 years has experienced some, "hey, is this fraud, is this not?" Or actually something that was detected and you get call saying someone is using your card.

So that, those capabilities have been there for a long time, but using these generative AI techniques, we've been able to see, an improvement in terms of, on average, a 20% plus improvement in terms of the fraud detection and even a better improvement in terms of elimination of false positives, which, we, all want that time back.

So from our perspective, that's, sending billions of dollars back into the economy, into people's pockets. and just out of the criminal hands and also preventing people from, or discouraging, at least, people stealing identity and stealing that data.

So, when we're approaching these topics, I mean, sure, there's a sustainability topic, but there's also just "are you doing the right thing?" perspective.

Are you holding your principles as you're deploying this new technology? And I think that area specifically has been a core example of  where that mission really fruits out. 

Sanjay Podder: Fantastic. And I did read about your solution for detecting fakes, scoring and approving billions of transactions. And that caught my attention because the moment you start using generative AI and you also, I think, use recurrent neural networks. And when you use it at scale, the way you are you are actually scoring billions of transactions.

George Maddaloni: Yeah,

Sanjay Podder: is a 

George Maddaloni: 140 billion last year alone with a growth rate on top of it. So 

Sanjay Podder: But what did catch my attention was the fact that we all know that there was a time where we were all concerned about the energy use and emissions during training of generative AI and AI, but now, post generative AI, we're also concerned about the inferencing part, because every inference you make, there has been a lot of interesting studies, one from Hugging Face that says 30 to 40 inference, for example, is half a liter of water, and things like that, right?

So there is an environmental aspect when we talk about training, refining the models, or, inferencing the models. So, clearly, in addition to bias, in addition to ensuring data privacy and various such responsible AI practices, a new concern is sustainability, which is also being highlighted in the EU AI Act.

So I was wondering How does one address that aspect when, especially when you're talking about large volumes, billions of transactions?

George Maddaloni: Great question, and actually, you hit on some things that are core in our technology training models. Large large data models, especially language gets very, consumes a lot very quickly. Payments language is not quite like the English language, first and foremost. So I think you got to think about from a training perspective, what do you need to focus on? And, not bring in too much information. Two,

inferencing, absolutely more intense, rightfully so.

I'd even double down on that and say, inferencing in real, in a real time business is an order of magnitude different. So, this comes back to, kind of topic we talk about a lot in the practices, you know, with the Green Software Foundation and other industry partners that we've been discussing, is how are you engineering this stuff and that decision you're making around what you're about to consume and bring into the fold? Because A, it could be very power hungry, but B, it could be very costly too. So our business wants us to make that decision at the same time.

So these things usually go hand in hand. But the practices that we focus on first and foremost from a data center perspective the traditional PUE and how we're engineering the efficiency of our data center or where we're running that workload is absolutely critical and we're constantly looking at that and improving on that.

But two, these practices around engineering for sustainability. We've incorporated for our technology team, we've created an ESG guide for technologists that cover, the things that they need to think about when considering a new technology, so from a procurement perspective, what are the things we want to see? From a new supplier, be it hardware or software for that matter, what are, what kind of information can we glean from what we're about to use? Because a lot of these tools that we're referring to, and you know, there's some heavy software underpinning that, that's making that consumption happen. And then number two, from a software practices perspective, development of code, use of data, back to that thing I was referencing before, like,

you don't need to bring the whole model, right?

You need to be focused on your actual, deployment. And then thinking about right sizing of the workload for either training or inferencing and making those decisions so that, You can create both a reactive, a responsive application and something that's not going to over-consume CPU storage, these things that we that we care about it comes to actually the deployment the technology itself. 

Sanjay Podder: Absolutely. All some great ideas. And, George, I also, read in the report, about your views on edge computing and you also referred right now real time, low latency. So, how do you see edge computing playing a role in your, operations process, and when you design with edge computing, how do you make sure that the processes are therefore getting more energy efficient, for example? Because with edge computing, with the new cloud computing at the other end you can now distribute the workloads in a very interesting way. So, how do you bring all these ideas together with the sustainability in the center to make the systems more energy efficient? You know, emit less carbon.

George Maddaloni: It's, the nature of Mastercard's technology footprint. Edge computing is a it, and it's something that I realized, when I first got here, four years ago. You look at those thousands of endpoints that we run, which connect the largest financial institutions and the smallest financial, all financial institutions around the world.

And it is, by and large, can be thought of as a large edge computing network. And We make some decisions there, we make some back in a data center or in a cloud in depending on the capability that we're, looking for, the product that we're running. And so, I think there's two things that we think about in this landscape.

One is, can we make that edge computing more efficient? And we've actually explored that very, very carefully over the past year because that is such a critical part of the whole overall technology, that cardiovascular system that I referenced. And we were able to, via the advances that you can make now in a smaller footprint of equipment, we've easily been able to run that 25 percent more efficient from a power perspective using new generation of processors and capabilities on those servers. You think about a small rack mounted server and we can do more with it. So you can get 25 percent more capability out of something that's 25 percent more efficient right? That is huge capability that you can now enable at the edge to put more decisions there. And the better part of that, as you think about it, is you're not bringing all of that decisioning and forcing that CPU back home. So you're eliminating network, you're eliminating data center CPU cycles and things of that nature.

So, I absolutely think getting that right, mean it is an engineering prequationhat you need to make, but getting that right is something that we focused on and I think is something that's a bit of core of Mastercard technology too. 

Sanjay Podder: Wonderful. George, moving to a slightly different topic on Mastercard has always been known for the programs of financial institutions, you know, empowering communities. I'm sure these initiatives are backed with intelligent digital solutions. When you build the solutions, how are sustainability factored in? Any thoughts there that you'd like to share? 

George Maddaloni: Yeah, sure. We've, I think everybody globally is starting to get interested what is in their own personal consumption, so we've actually, at a payments level begin to enrich, we not only do we enrich data that we share in our network around fraud, as I mentioned earlier, but we do have a service that some financial institutions take on in "hey, what is the sustainability information for this particular purchase people are making?" And we've partnered with various data sources that. are out there to provide that information. 'Cause it is, as you know, and we're very good at providing the technology as we think about that sustainability, scoping or the, what's the CO2 of an emissions aspect and all that. So we're bringing that data through as best we can and it's been a successful launch of that sustainability product and certain cusrtomers and financial institutions are using it. 

A lot of our capabilities continue to focus on "what are we doing for small and businesses give them competitive capabilities and to grow?" Countless examples of that in and probably, small, micro businesses, giving them the ability, throughout the world, great examples going on in India as well,

in terms of community pass programmes things of that nature.

Sanjay Podder: Great. And, George, I think it has been sometimes, you have maybe a year since you joined the foundation, the Green Software. Very curious to know, has the foundation been able to influence some of your thinking as you are trying to bring sustainability in the center of the way you do technology in Mastercard? So anything you would like to share?

George Maddaloni: Yeah, the partnership with the Green Software Foundation has certainly helped us. I referenced before this ESG guide for technologists and some of the, we point

people to the training program that the Green Software Foundation created with the Linux Foundation.

I've received the certificates. I was one of many people at Mastercard that went through that training, and I think it's great because it helps people understand what is the index of the technology that they're deploying. There were several great examples provided from other organizations are doing great work.

And I think any company, I think, gets very focused on what they're doing. So it's great to have that exposure of outside in. And we get that through a lot of the that we have. We've hosted before.

We, have a software engineering guild or practice within Mastercard that has been participating in the Green Software Foundation. They have a special interest group within Mastercard where people can questions. The members that have participated in the sessions with the Green Software Foundation can help answer those questions. So, while we have close to, I think over 6 000 software engineers at Mastercard, all of those can be, you know, feeding off one another in terms of the knowledge that they're getting.

And then by hosting some of the events, we have some of those players show up, hear from the other people that come in, and I think those are great examples, and I know we've got one coming up in October. 

Sanjay Podder: Absolutely, we are all looking forward to the summit in October. George it has been a wonderful discussion, but there's one question I like to ask all my guests.

What would be your bite sized advice to tech leaders as they try to balance innovation and sustainability? 

George Maddaloni: I think, three things. I'll try to keep them bite sized. You know, all this is extremely important that we continue to collaborate within communities like we're here talking about, and others to understand how to work on sustainability and green practices.

It's, this is a complex problem that I don't think anybody's out of the box, figured out.

So that's number one. Keep collaborating. Number two is get ffocused on your data. Youknow, there's, like

we just talked through, our tech footprint is a lot different than everybody else's tech footprint. You've got to dive into your own data and really get focused on that and understand what's happening. And then number three, I go back to, this is a great, focus on consumption. This is a great parallel to what you're spending, what you're producing, what you're consuming. And I've seen that culture, when you bring that to the table, the culture in your organization can really benefit from that.

Because that's something that everybody wants understand

and can start to make decisions off of it. So, it's collaborate, focus on the data, and then bring it to the culture. 

Sanjay Podder: Thank you, George. Thank you, George, for your contribution to this area of sustainable tech and for joining this CXOBytes podcast.

So, that's all for this podcast. But again, a reminder, everything we discussed will be linked in the show notes below the episode. I will also request you to go to podcast.greensoftware.foundation and listen to other episodes of CXOBytes. So until then, I hope to meet you in the next podcast. Bye for now. 

Hey, everyone. Thanks for listening. Just a reminder to follow CXOBytes on Spotify, Apple, YouTube, or wherever you get your podcast. And please do leave a rating and review if you like what we are doing. It helps other people discover the show. And of course, we want more listeners. To find out more about the Green Software Foundation, please visit greensoftware.foundation. Thanks again, and see you in the next episode.