In this insightful interview, Prem Natarajan, Capital One’s Executive Vice President and Chief Scientist, discusses the company’s strategic decision to build its AI capabilities from the ground up rather than relying on off-the-shelf models. Rooted in Capital One’s tech-forward DNA and history of data-driven decision-making, the company views AI as a critical tool to deliver superior financial products and services. Prem emphasizes that financial services are deeply intertwined with people’s lives, making it essential to harness AI in a way that fully leverages Capital One’s proprietary data for deep customization and enhanced customer experiences.
Capital One’s AI infrastructure is built on top of public cloud services, utilizing elastic compute, storage, and GPUs, but the company develops its own platforms, reusable services, and developer tools tailored to its unique needs. A key focus is risk management, with built-in observability and monitoring to ensure responsible AI deployment. Prem highlights the importance of building an integrated stack where all components—from infrastructure to applications—work harmoniously, enabling continuous improvement and agility in responding to customer needs and operational challenges.
A concrete example of Capital One’s AI application is the “Chat Concierge,” an agentic AI-powered chatbot deployed at auto dealerships. This chatbot helps customers explore vehicle options, understand financing possibilities, and schedule appointments, enhancing the online-to-offline customer journey. The system combines reasoning and specialization, breaking down complex workflows into manageable tasks executed with precision. By deeply integrating Capital One’s data, including inventory and customer interaction history, the chatbot delivers a personalized and efficient experience while maintaining a low-risk profile.
Prem also discusses the broader AI strategy at Capital One, including applications like agent assist for customer service representatives and generative AI tools for software developers. The company’s approach prioritizes reducing cognitive burdens on employees and improving customer satisfaction through faster, more accurate responses. He underscores that building AI in-house allows Capital One to optimize latency, customize user experiences, and continuously refine models based on real-world feedback, which is often challenging with off-the-shelf solutions.
Reflecting on his extensive experience from DARPA-sponsored research to Amazon Alexa and now Capital One, Prem acknowledges the foundational role of public research in AI’s evolution. He sees the current AI landscape as multifaceted, with open-source models playing a crucial role alongside proprietary ones. Capital One favors U.S.-based open-source models for their flexibility and ability to be deeply customized. Prem concludes by inviting talent interested in shaping the future of AI in finance to join Capital One, highlighting the company’s commitment to innovation and responsible AI deployment.
