Capital One is one of the nation’s largest banks. It started as a credit card company, really as a startup in the late 1980s. Its founder, Richard Fairbank, is still its CEO today. Fairbank’s idea was to build a better financial services company by using information and data to make better decisions and build better products and services for customers—making Capital One an early “big data” company. The company launched around the notion of an information-based strategy, which in that era was a pretty novel concept.
In this sweeping interview, Rob Alexander, CIO of Capital One, tells how the company emerged as a forward-looking, developer-centric financial services institution. As one of the nation’s leading credit card issuers, Capital One is a leader in consumer financial services, but also has a sizeable commercial banking business.
What role does technology play in Capital One’s strategy to win in the market?
We’re in a business where two of our biggest products are software and data—intangible products. Technology plays a really central role in our strategy as a company, and that’s become even more the case with the digital revolution that is happening around us. More and more customers are expecting to interact with their banking products and services through additional channels, whether that’s predominantly mobile, online banking, ATMs, wearables or whatever. So we feel like it’s absolutely critical if we’re going to be a winner in this market, we have to deliver really well-designed solutions for our customers through software and great data capabilities.
What is driving this transformation?
We have a strategic imperative for a pretty dramatic transformation of our technology capabilities as a company. And this is a transition from being a company with an IT organization or an IT shop to really being a technology-led company.
The hardest part of that transition is really a talent transformation. It’s going from an organization where as a typical bank IT shop, we would acquire third-party solutions and bring them in and integrate them. But it’s a very different model when you are actually building your own technology solutions. It requires a different talent base, and it requires a different mindset and an entirely different operating model to do that.
That is a big shift that many financial institutions are going to find challenging to make. So we’re intent on implementing a technology operating model for how we develop our technology solutions that is based on how leading technology companies operate.
For us, that’s about building solutions in the cloud; we’re an open-source first development shop. We build a lot of open-source software that we contribute back to the open-source community. We even launched our own open-source projects.
We build our solutions in an API-based microservices architectural approach, which is a more modern way of building software. We operate with an Agile, iterative approach to building software. And we are very focused on implementing a DevOps model of continuous integration and continuous deployment of software so that we can iterate with the speed that’s demanded by the marketplace.
This technology transformation has been accompanied by a revolution in how we think about design as well. Design is an important complement to the ability to build great software. If you don’t have a great design ethos and capability, then I think you’re missing an important part of the equation. So we focus on building a great design organization.
We went out and acquired a design consulting firm. We are very much focused on design thinking and a human-centered design approach to how customers use banking products and how we can improve the end-to-end experience for customers.
What else have you done to help change the game for your developers and customers?
Some of the other things we’ve been doing recently is we launched our Capital One Wallet mobile app. We recently launched an open API platform for developers—a platform we call DevExchange, which allows developers to start to consume some of the APIs that we developed. And we believe that has the potential to create a whole ecosystem of third parties that can build on the technologies that we’ve launched.
Recently, we launched an Alexa skill on Amazon Echo that allows customers to service their credit cards through that channel. We want to help consumers do banking where they want to do banking. Banking is becoming more integrated into consumers’ lives and it will be channels like Alexa and other ways consumers want to interact that will be important channels for banking in the future.
Do you feel like Capital One is unique in this approach?
Yes, I believe we’re unique and I believe we’re unique relative to other large financial services institutions. I think the world of FinTech [financial technology], when you look at the startups in this space, they’ll employ a lot of the technology operating model that I’m talking about—they’ll build their solutions in the cloud, they’ll leverage open-source technology, they’ll build software in more modern ways. Not many big banks are doing it. And not many big banks are doing it because they are shackled to legacy technologies and they struggle to break away from that. And they struggle to break away from conventional ways of thinking and they struggle to break away from conventional talent.
Capital One Taps Open-Source, Cloud, Big Data for Advantage in Banking
It is a huge chasm between what is a traditional bank IT organization and what it needs to operate like a real technology company. It is a very difficult thing to make that transition, and what is the most difficult about it is the talent equation. The kinds of skills and experiences that you will find in a traditional bank IT department are not at all the kinds of skills and talent that you find in a leading technology organization or a startup. They’re just not the same beasts. And how you transition from one to another is a difficult thing.
If you really want to go out and get great software engineering talent or great data engineering talent or great cloud engineering talent, those folks want to come to an organization where they see a lot of folks who also have those skills who they can learn from and collaborate with. They also care about working with the latest technologies, modern ways of working and being challenged in ways that they can innovate. If you don’t offer those things, you will never be able to attract that talent. You’ve got to get to a critical mass where it becomes a self-sustaining transition to a different model. And banks are going to struggle to pull themselves up by their bootstraps from where they are today.
So what we’re doing is very different. And emblematic of that is our choice to use public cloud. Other banks are really reluctant for a variety of reasons to leverage the cloud. Other banks are reluctant for a variety of reasons to leverage open source in the ways that we’re doing it, much less to contribute back or launch their own open-source projects. So I very much believe it’s a different way of operating than other financial institutions. But the winners in this space are going to have to operate this way because the pace of innovation is ever increasing.
It’s going to require the competencies around being able to innovate quickly, the ability to build software that is really compelling and well-designed, the ability to understand data and analytics and apply modern methods of machine learning and analytics operating in real time in a way that banking just doesn’t do. Banking is an overnight, batch process, close-the-books-each-day kind of operation. The world is moving to real-time interaction and making decisions at the speed at which data can move. Banks aren’t wired to think that way, and they don’t have the infrastructure to act that way.
What prompted you to go this route and become a technology-led company? Was it an issue of meeting customers where they are or was it to gain competitive advantage?
It’s a number of factors. Even in the early days, technology played a critical role at Capital One in that our information-based strategy was about leveraging data and analytics and using a test-and-learn methodology to figure out how best to serve customers.
Over time, the imperative around technology grew even greater as the digital revolution took off. And it was around 2010 when it became glaringly obvious that the way banking is going is that customers are demanding to consume banking services—whether credit cards or checking accounts or investing—they wanted to do these things through digital channels and their expectations are being shaped by how the world is moving to digital channels. So we looked at that and said if we are going to set the pace of innovation in this industry, we are going to have to really be responsive to customer needs and change the way we do things.
It was a recognition that banks typically move in this slow pace of product introduction that’s driven by a waterfall methodology of delivering projects. And we recognized that the world was moving to Agile, iterative delivery and operating at fast time scales and we needed a different way of working. So we moved to an agile delivery methodology and we focused on bringing in great software engineering talent and recognizing that the way these folks want to work, we’ve got to be able to operate in the cloud, we need to leverage open-source software and tools, we need to build our software in a different way based on a RESTful API architecture that allows for reuse and speed of delivery. All of these things started to come together as the technology operating model for us, all driven by the imperatives of the market.
Traditional banks are going to really struggle to get there. And it may not be traditional banks that win in the end. It may be companies that come at it from a very different direction.
Why the decision to go open?
We recognized there’s a whole ecosystem of innovation out there in the digital world and we can multiply our impact by having third-party developers partner with us to create solutions in ways that we might not even imagine. This goes back to the notion of can you integrate banking more into where customers are in the moment they need it. We think the ability to expose our capabilities to third parties will allow us to tap into an ecosystem of innovation that leverages what we’re able to do ourselves.
Capital One Taps Open-Source, Cloud, Big Data for Advantage in Banking
Are there any key technologies such as programming languages or frameworks that you have taken a particular interest in? I know you guys have a keen interest in Node.js for one.
We have a large innovative organization and we’re doing a little bit of everything. We’ve certainly had a lot of success with Node.js. All of our mobile applications we build natively. So for iOS, we build apps using Swift. We do native Android apps. There are just a lot of the modern technologies in use here. Our Web technologies are all Angular and React based.
We want the best performance in our apps and we also want to attract the best talent. And they want to work in the most leading-edge ways. That’s really important to us—being able to leverage those frameworks and do it on the public cloud. We have a great partnership with Amazon Web Services and being able to innovate on the public cloud. It allows us to move at a speed that enables us to innovate quickly.
There’s a whole data dimension to this as well. We heavily leverage open-source data tools to build our data solutions. If you want to get to real-time banking, you really need to move to a streaming data kind of platform. So we have a heavy implementation of Kafka for instance. We stream our data in real time so we are able to make our decisions in real time, whether we leverage things like Spark or Apache Apex or other tools that allow us to do stream processing those are critical technologies for us. Those are all predecessors to being able to apply more machine learning and artificial intelligence kinds of capabilities into how you make decisions.
These are areas where banks are going to really struggle. They’re wrapped up in their batch processes today. First of all, they have to move to real-time streaming data and be able to deal with that. And then the notion of applying more sophisticated modeling and machine-learning and artificial-intelligence tools on top of that streaming data so you can make better decisions and more interactive decisions with customers. That is a really hard transition for financial institutions to make.
Are you doing anything with cognitive apps and AI? Where do you stand with that?
Yes, we are. We’re applying machine-learning technologies in a number of different areas. One of the areas we’re focused on as a financial institution is cyber-security, not surprisingly. This is a place that is a great opportunity for the application of machine learning. It starts with building a comprehensive data infrastructure on what’s going on in your environment in order to be able to build tools and have insights into things that might be anomalies. And then you can use machine learning as a way to discriminate normal behavior from abnormal behavior. So we’ve applied machine learning in that context. It helps us identify malware or anomalous behavior or other kinds of things that are indicators of threats in our environment. That’s a really well-suited domain for leveraging machine learning.
There are other places around fraud and risk decisions, the ability to apply it in interactions with customers where you move from one-off interactions with customers to real-time, dynamic interactions with customers. For example, we launched a product called Second Look. It is a feature for card customers where if you’re in a restaurant and you leave an unusually large tip, we can send you a notification in real time and say we noticed you left a large tip; did you intend to do that? And that’s kind of useful if you do it 24 hours after the fact, after processing that over night. It’s incredibly useful if you’re able to do that in the moment while you’re still sitting there in the restaurant. And, similarly, if you double-swipe, we’ll be able to pick that up in real time and let you know that this transaction was just double-swiped, was that intentional or not?
Do you address this at the developer level?
Yes, we typically leverage open-source machine-learning frameworks. We build those into our apps. We hesitate to use the black-box approach. We feel like it’s important for us to have the machine-learning skill sets in our organization. So we have a particular focus on recruiting and developing those skill sets internally.
What we’re seeing come together on this is this whole world of open-source data capability—starting with Hadoop and the whole ecosystem around that. Think about the move to streaming data, and then stream processing tools like Spark and Apex and Flink and those that allow you to process streams of data in real-time, those are the frameworks where we’re building in more machine-learning intelligence. So, for us, it is really coming out in the world of the data ecosystem and those sets of tools. That’s where we’re seeing the real potential to apply machine-learning capabilities as opposed to just software engineering. The data world is where it’s really powerful.
You don’t sound like a bank. You sound like a born-on-the-cloud startup.
We feel like that’s how we have to operate. It starts with our CEO and our business leaders really believing that for us to win as a company in this industry where it’s going, we have to operate like a technology company. It is a sincerely deeply held belief; it is not a lip-service thing. And if you start with that, you are compelled to figure out how the best technology companies are operating and you turn yourself into that. And you won’t be able to get the best talent out there to come and work for you unless you’re doing these things.