I is hard to secure as it stands. Doing so as a legacy financial institution is even harder.

At HumanX in mid-April, The Deep View sat down with Milind Naphade, SVP of AI foundations at Capital One, to break down how longstanding, highly-regulated financial institutions are using AI to innovate without wreaking havoc.

Before joining Capital One in 2023, Naphade worked for legacy tech giants like Nvidia, IBM Research and Cisco. Stepping into an industry like finance, he said, gave him a whole new appreciation for navigating the intricacies of innovating within the purview of regulator scrutiny.

“There are a certain set of things you must do, and you cannot do,” Naphade told The Deep View. “Making AI actually operate in this ‘must’ and ‘cannot’ [environment] is actually much harder than saying, ‘Oh, we can just have guardrails.’”

Naphade found the solution out in the open: Instead of trying to retrofit proprietary, off-the-shelf models from frontier labs to develop its AI systems, Capital One relies on open-source models, developed in the US, said Naphade. “We do believe that the open weights and open models approach … It's the only way we get to deeply customize them,” he said.

It’s an unlikely approach given that open models tend to have security issues, such as model tampering, data leakage and a lack of regular, ongoing security updates.

• However, Capital One isn’t simply downloading open models off Hugging Face and plugging them in where they fit. Rather, Naphade said, “We start with open-source, and we then customize it to the point where it's almost unrecognizable.”
• And to meet regulatory standards, Naphade said, the company will completely dissect these open models, deeply studying their architecture and tracing their lineage.
• “This is not your usual enterprise, where you just take something, do a little bit of fine-tuning here and there and call it customized.”

Navigating AI with an open-source approach, however, has allowed the company to stay at the leading edge of AI without relying on frontier labs for all innovation. For instance, Naphade said, the company has been experimenting for more than two years, and debuted its first agent tool last January.

Now, however, staying ahead of the curve may be the only way to keep up with customer expectations, he said. “Everybody is using ChatGPT in their daily lives,” Naphade said. “They are going to expect every part of their interaction with their enterprise experiences to have a similar level of intelligence.”

Our Deeper View

Capital One is a prime example of the enterprise benefits that can be reaped by betting on open-source models, even in tightly regulated industries. However, with ultrapowerful models like Anthropic’s Mythos and OpenAI’s “Spud” on the horizon, it’s easy for enterprises to become distracted with shiny things, especially when those things promise productivity and efficiency beyond their wildest dreams. Still, whether or not they're in regulated industries, more enterprises could stand to gain by adopting Capital One’s approach to open models and may find greater advantages from highly customized, purpose-built models than from expensive, off-the-shelf general-purpose ones.