BNY Mellon deploys Nvidia DGX SuperPOD, identifies hundreds of AI use cases

BNY Mellon is joining a growing number of financial firms in adopting AI-powered technologies. During the bank’s 2024 Q1 earnings call, CEO Robin Vince said the firm has already identified hundreds of use cases internally and has several in production.

“We also see meaningful opportunity over the coming years from continued digitization and reengineering initiatives as well as from embracing new technologies,” Vince said. “To support this effort, we are making deliberate investments, enabling us to scale AI technologies across the organization through our enterprise AI hub.”

One of those investments is in the deployment of the Nvidia DGX SuperPOD, an AI datacenter infrastructure purpose-built for enterprises. Vince said BNY Mellon is the first bank to deploy the infrastructure, which will allow it to accelerate processing capability to innovate, reduce risk, and launch AI-powered capabilities.

Among AI capabilities already in use, Vince pointed to current software that provides predictive trade analytics around settlement failures. Clients have the ability to look out for failures and take action, with some actions directly linking to other BNY Mellon platforms. 

We are making deliberate investments, enabling us to scale AI technologies across the organization through our enterprise AI hub

Robin Vince, BNY Mellon

The bank is also embracing AI’s strength in coding and deploying GitHub CoPilot to developers. “I was walking around one of our buildings the other day and was talking to one of our developers who has been out of school for a year and change,” Vince said. “And already they think they are 25% more productive as a developer and that’s in the very early days of using GitHub CoPilot.”

Overall, the bank is approaching AI with a “hub strategy” that would create a center of excellence. “We don’t want to repeat the problems that we’ve had in the past of everyone going off in their own direction,” he said. “In AI, it’s particularly important because problem statements that sound different can in fact have very common root causes.” 

As an example, one person might want to respond to a request for proposal (RFP) while another wants to create summaries of documents and a third person wants to get a head start on a research project. While those three tasks may sound different, the best strategy may be to use an AI hub to collect use cases and then create mini platforms that can be deployed in multiple places across the enterprise.

While these developments are coming together in 2024, Vince said benefits to the expense line will likely not be seen until 2026.

Vince’s comments echo sentiments across the industry this quarter. In his annual letter to shareholders released last week, JPMorgan CEO Jamie Dimon addressed AI first in a list of topics that the bank is focusing on. Goldman Sachs CEO David Solomon shared during the bank’s Q1 earnings call on Monday that his firm was looking at AI in terms of productivity and efficiency improvements.