Introducing Aparna Sinha, Capital One’s Head of AI Product

In January 2024, Aparna Sinha joined Capital One as SVP, Head of AI Product. She has been focused on working across the enterprise to drive our AI and machine learning (AI/ML) journey and build and enable well-managed AI capabilities across Capital One and the customer lifecycle.

Aparna joins Capital One from Pear VC, where she was Partner, AI/ML, focused on AI/ML, enterprise software and developer tooling startup investments. Aparna has also led cross-functional teams in Google Cloud’s Developer organization, was an early product lead for Kubernetes, and worked on the Android platform, ChromeOS and ML-driven CRM systems at Google. Following are excerpts from a conversation with Aparna after her first few months at Capital One.

I have always had a scientific mind, maybe because both my parents were physicists. So, I grew up building things, and trying to understand the world from first principle observations. I fell in love with Physics because it explains how things work, which is fundamentally important, and later got into engineering because it is satisfying to build things and see user impact.

Getting a PhD in almost anything teaches you how to learn and how to get to the edge of knowledge on a topic, and push the envelope from there. AI/ML is an area where collectively, we are pushing the envelope of what we can make machines do and how we can impart intelligence to them. Along the way, we are exploring what intelligence is, how it works in our own brains and how it works in a computational system. There are lots of unanswered questions and new research every day. My background helps me because there are many connections to basics like linear algebra and systems engineering to optimize compute and memory. But there are many new things for which there isn’t a prior background and those are fun to learn. My background in open source software (Kubernetes) is also useful at times, and overall I’m passionate about applying new technology to practical business problems.

In some sense, I have had an unlikely career arc, going from a PhD in engineering to McKinsey and then 10 years in technical product leadership at Google and then Venture Capital at PearVC. I’ve been fortunate to be part of the progress in machine learning at different levels through cloud infrastructure and startup incubation. But the disruption over the last 3 years, especially with Generative AI, convinced me of the importance of being close to the data. I think the opportunity for AI is in the enterprise context and I wanted to be at an organization that is forward leaning on this technology and its use for improving human lives.

The opportunity at Capital One to work on some of the most challenging business problems in finance and to not only leverage AI/ML, but also to invent new technologies to benefit our 100 million customers, is incredibly compelling. I could not pass this up. And I’ve found I’m much more grounded and knowledgeable about Generative AI, its inner workings and its applications than when I was working as a pure technology provider.

Capital One has been at the forefront of leaning into technology for more than a decade. After all, they were the first major bank to go all-in on the cloud and launch a new software business. Capital One also has a large, world-class in-house tech organization and has been using AI/ML all across the business to drive value. Not only has Capital One been on the cutting-edge of everything from serverless containers to leading digital banking capabilities, but it has also cultivated an innovation culture that prioritizes collaboration and strong business judgment. To me, that’s the most important thing I look for as a leader in AI today. 

I’m still doing a lot of listening, learning and soaking up information with my team and across the company. But there are four main priorities that I’ve set with my team from the outset: continuing to create an environment where all our associates feel included, recognized and do the most innovative work of their career; orchestrating well-managed platforms at scale; delivering on a bold product strategy; and thoughtfully developing and applying state-of-the-art AI and ML capabilities across our product ecosystem.

As I mentioned earlier, Capital One has undertaken a bold technology transformation in a way that many others haven’t, and as a result, we are a highly ML and data-driven organization with strong technical talent. 

AI/ML is already foundational to how we deliver value to our customers and to how we run our business. Whether that’s helping consumers shop more safely online or giving customers new insights into their finances through products like our mobile app, Capital One is constantly finding ways to use technology to make things easier and better for our customers.

AI/ML has the power to transform every aspect of our professional and personal lives. I’m especially engrossed in topics such as how we develop software, how we discover and consume information and how we enable our users to interact with their environment in ways that are financially rewarding. It’s about delivering value and empowering people to do things that they couldn’t do before—and what I most appreciate is that Capital One is deeply focused on continuing to approach the new frontier of AI in a responsible, well-managed way that puts people first.

The importance cannot be understated. Good product experts can identify where the real value and leverage is from any given disruption. And they prioritize resources and energy to achieve a certain vision.

A space like AI/ML has so many new applications and tools, knowing where to start and what to prioritize can be daunting. A product-led approach ensures customer-backed innovation and achievement of real value. Along the way, there are many new inventions, and that spirit of entrepreneurship is part of who we are at Capital One.

So I think that product is a crucial player in where AI goes from here. It plays a pivotal role in not only leveraging AI to create differentiated value, but also in helping bring together the right people to assess risk, ensure humans are in the loop and stay focused on achieving the vision of Changing Banking for Good.

Join us! We are hiring superstar learners and doers who are passionate about the applications of Generative AI. Capital One not only provides banking but it also provides many other consumer services such as shopping, travel and more. It’s also a software provider in select areas, and we invest in invention across all layers of the stack. AI builders and inventors will like being able to see the problems tangibly and work with enterprise data to achieve results.

For folks who are new to AI, we welcome learners. My advice for learning AI is first of all, read, read, read. There’s a lot of new information coming out every day and it helps to stay abreast of it; it's also a good test of whether the pace of this area is exciting to you. Secondly, if you are learning something new, develop a network outside of your comfort zone. Attend demos and hack-a-thons wherever you can find them. Network with students, researchers and engineers in the AI space. And lastly, make time to build something. Lean in and play with this technology—it is very accessible now and you can experiment with it at the level that works for you. Think about what you would like to help create with AI—disruptive change is certain with this technology and decide what kind of change you want to enable.