Capital One: The Ongoing Story Of How One Firm Has Been Pioneering Data, Analytics, & AI Innovation For Over Three Decades

Pioneers are trailblazers. They operate as agents of transformation and change. They think differently. They innovate and introduce a new order. In the late 1980s, a pair of trailblazing strategy consultants came together with a new idea. Their idea? To use data to expand access to credit cards and do so more efficiently. This idea became the foundation for Capital One. In an industry historically dominated by century old banks, Capital One has been a trailblazer. From start up to top ten bank, Capital One has revolutionized the credit card industry with data and technology. Capital One is approaching its 30th anniversary under the leadership of Founder, CEO, and Chairman, Rick Fairbank. Today, Capital One serves more than 100 million customers across a diverse set of businesses and has established one of the most widely recognized brands in banking. I’ve had the good fortune to write about Capital One on multiple occasions over the years. In a 2019 Forbes article, From Analytics First to AI First at Capital One, co-authored with my industry colleague Tom Davenport, we wrote, “Capital One has long been known as a north star for financial services firms that aspire to be data-driven. Established in 1994 after spinning off of Signet Bank, the core idea behind the company’s formation was the “information-based strategy”—that important operational and financial decisions should be made on the basis of data and analytics”. Data Leadership and the Role of Chief Data Officer (CDO) at Capital One This past month, I had the privilege of interviewing Capital One’s current Chief Data Officer (CDO) and Executive Vice President, Amy Lenander, as part of a CDO panel that I have been organizing and moderating for the annual CDOIQ Symposium, which was launched 18 years ago at the Massachusetts Institute of Technology (MIT). Lenander was appointed CDO of Capital One in early 2023. She had previously led business functions for the company during a 20-year tenure, including a term as the CEO of Capital One U.K. I asked Lenander about the evolution of the CDO role at Capital One. Lenander explained, “My role as Chief Data Officer is primarily about setting our company up to make the most of our data to power the future of Capital One.” She continued, “Part of the reason that the CDO role was created more than two decades ago was our recognition that establishing a rigorous, well-managed data ecosystem across the enterprise requires dedicated leadership from the top”. Lenander understands the heritage of Capital One, noting, “In a company like Capital One, we need and expect data to enable associates across the company to discover insights, make decisions, and drive innovation and value for the business and our customers. This was true back in the early 2000s and remained true as we began our technology transformation and moved to the public cloud, and as the volume of data available continued to grow”. Lenander appreciates that being data-driven is a way of life at Capital One and has been since its founding. Lenander comments, “What’s changed over time is the methods we use to find insights and how we use them to improve our business”. She continued, “Our data-driven culture means that there’s an incredibly strong pull from business leaders to continually learn about and use better and better techniques to drive more powerful insights. Along the way, every major division of our company has had leaders accountable for the data in their line of business, and data has remained central to our culture and to how we operate”. Change has been a constant in the world of data over the past few decades. Lenander observes, “In a world where analytic techniques and even data management approaches are rapidly evolving, I look to build a team of talented people that are curious, great problem solvers, and continuous learners. In this environment, it’s also important to have a strong culture of experimentation and sharing lessons learned along the way”. I asked Lenander about the importance of having a guiding data strategy at Capital One. Lenander explained, “We have an enterprise data strategy because one of the ways we can achieve our goals is by using a common set of data platforms across the company, and to achieve that, we need data owners across the company to work back from a common strategy”. She elaborated, “One of the benefits of that strategy is to make data available to use across the company, for example, so that we can use information about customers’ experiences with their bank account to inform how we might better service their credit card account”. Lenander recognizes that what often differentiates one company from another is the ability to execute. Lenander comments, “This is one of those things where the goals and the strategy are relatively easy to say, but the execution is very difficult”. She continues, “Our data strategy is focused on ensuring we can make the most of our data as we continue to evolve our business”. Ultimately, the value of data comes from the ability to serve the business. As a longtime business leader at Capital One, Lenander appreciates that, “Our data strategy is all about enabling the business. My prior experience leading businesses across Capital One has given me empathy and a deep understanding of where the value is in the business and where data can make the most difference”. She notes, “The goal of our data strategy is to make data well-managed and easy to find, understand, use and govern”. The State of Data & AI at Capital One Today In our 2019 Forbes article on AI at Capital One, we noted that Capital One was investing in how to apply AI in its business well before most of its peers. Lenander comments, “AI raises the stakes because AI is incredibly data-hungry, uses many more types of data, including unstructured data, and can be less explainable in the relationships that models are finding within data”. She understands that great AI requires great data, noting, “That means that there’s an even bigger need with AI to ensure data is of high quality”. Lenander observes that, “Organizations that have plentiful, well-managed data have a huge advantage in their ability to leverage AI”. She continues, “Our investments in technology and data infrastructure and talent — along with our deep experience in machine learning — have set us up to be at the forefront of enterprises leveraging AI today”. To continue to capitalize on momentum in data and AI, Capital One has established dedicated leadership roles to drive and evolve its enterprise strategies in these domains, which include the early 2023 appointment of Prem Natarajan as Executive Vice President, Chief Scientist, and Head of Enterprise AI for Capital One. Lenander and Natarajan serve as peers who partner closely on Capital One’s data journey. Natarajan leads Capital One’s AI initiatives, and both are part of a central Enterprise organization that has leaders accountable for core domains like AI and Data, as well as for core functions such as Engineering, Science, Design, and Product. The senior leaders of the Enterprise organization collectively drive Data, AI, and the innovation agenda for Capital One in close partnership with senior leaders across the company. I asked Natarajan about his vision for AI at Capital One. Natarajan commented, “From its inception, Capital One has had a reverence for insights derived from data. Culturally, we subscribe to data-driven methodologies for decision making”. He explains, “That has set us up very, very well for the current age of machine learning and AI”, adding, “When we think about future waves of AI and their impact, we take a cautiously optimistic view that is informed by our vision of an AI-powered enterprise in which all our associates and customers benefit from the real-time intelligent experiences and services that such an enterprise will deliver”. Lenander adds her perspective, noting, “Data, machine learning and AI are central components of how we operate and serve our customers. Today we are embedding AI throughout our business with proprietary solutions built on our modern tech stack, and we have hundreds of use cases in production that use machine learning or AI to deliver value for our customers, associates, and the company”. Developing Safeguards and Charting an AI Future Natarajan is highly cognizant of the need for safeguards to ensure responsible AI use, recognizing that, as with any new and rapidly evolving technology, the potential benefits have to be balanced with a thoughtful, responsible approach that appropriately manages risk right from the start. This is especially the case due to the more powerful capabilities of modern Generative AI technologies. He comments, “We are anchoring on a test-and-learn approach to both identify the highest leverage areas for AI as well as the safest ways to deploy them while delivering benefits to our customers”. Continuing on the topic of responsible AI, Natarajan states that across AI initiatives, Capital One is guided by a mission to build and deploy AI in a responsible, well-managed way that puts people first. Natarajan notes, “When developed responsibly, AI will continue to democratize access to a whole suite of insights, resources, and everyday conveniences across the entire social spectrum – in areas from finance to healthcare to education and more”. He continues, “Perhaps the most important safeguard is a cultural one, because it is such a strong determinant of practices and outcomes”. Natarajan underscores the importance of thoughtful collaboration, commenting, “To maximize the benefits of AI, it is important to adopt an inclusive approach from the outset”. He adds, “A spirit of responsibility and thoughtfulness needs to pervade the entire development process, from research and experimentation to design, building, testing, and refining, through the whole development and production lifecycles”. Capital One recognizes the need for extensive testing and implementation of human-centered guardrails before introducing AI systems into any customer or business setting. Natarajan comments, “For Capital One, this includes a Model Risk Management framework to evaluate, assess, validate, and govern models to effectively manage and mitigate risks associated with AI”. He notes that banks like Capital One have robust risk management infrastructure, oversight mechanisms, and governance capabilities that are required to manage risk and to deploy and scale AI appropriately. Earlier this year, Capital One established the Center for AI and Responsible Financial Innovation with Columbia University and the Center for Responsible AI and Decision Making in Finance with the University of Southern California to advance state-of-the-art research in responsible AI and its application to finance. Capital One are also partners in multisector consortiums like the Partnership on AI, where Natarajan is on the Board, and with institutions like the National Sciences Foundation. Natarajan comments, “We have a strong belief in the value of multi-sector partnerships between industry, academia, and government to ensure diverse perspectives and equities when developing, testing, and deploying AI”. He adds, “We are helping to advance research and strengthen our national capabilities in AI”. Examples of Capital One initiatives that have been designed to measure the value of new data, analytics, and AI techniques, include: 1. A proprietary generative AI agent servicing tool which is helping agents access information to resolve customer questions more quickly and efficiently. For example, if a customer calls in about a lost or misplaced credit card, agents can get them a virtual card number immediately and have a new card delivered, so their ability to spend is uninterrupted and resolved more efficiently than ever. Lenander notes, “This tool has been used thousands of times by hundreds of agents, with over 95% of search results found highly relevant by our agents”. 2. An AI model that is used to customize the user experience across digital and mobile channels to help put the most relevant information in customers’ hands. Lenander comments, “The model is driving double digit improvement in relevance of personalization than the prior machine learning model and allows for rapid experimentation and iteration as we continue to enhance the customer experience”. 3. A proprietary fraud platform that leverages AI and machine learning to proactively surface and mitigate fraud in the time it takes a customer to swipe their card. Lenander notes, “We are continuing to experiment with new AI capabilities in fraud to stay at the leading edge of this space”. Reflecting on the Capital One data and AI journey and how the company has evolved over the past three decades, Lenander concludes, “We have a long history of using data to drive our business strategies, and in a cloud and AI world, there is both massive opportunity and the potential for massive complexity”. She adds, “Cultivating a modern data ecosystem and being AI-ready is an ongoing journey, and we continually evolve our approach to data so that we can be best-prepared”. Natarajan, reflecting on his mandate to advance the development and application of AI within Capital One, concludes, “Ultimately, AI is at its best when it empowers individuals and societies to achieve things that weren’t possible before – and we all need to come together to actively work towards that future”. I look forward to seeing what comes next from Capital One as they further pioneer data, analytics, and AI leadership on the frontier of business innovation. What’s in your wallet?