How Wells Fargo deploys AI in payments

• Key insights: Wells Fargo’s AI platform is designed to be model and cloud agnostic, allowing the bank to adapt to newer, larger and more specific models as they emerge. 
• What’s at stake: The payments landscape is changing at a fast clip, and banks will need to adapt quickly to stay ahead. 
• Expert quote: “New capabilities such as tokenized deposits, programmable liquidity and  near-real-time or atomic settlement didn’t exist five years ago, but they will be table stakes five years from now,” said Ather Williams III, head of global payments and liquidity and wholesale digital at Wells Fargo.

SAN FRANCISCO — The payments landscape is changing at a fast clip, and at Wells Fargo , AI is providing a new layer of intelligence that the bank is using to advance its payments business.

Processing Content

Wells Fargo’s AI platform is designed to be model and cloud agnostic, which allows the bank to adapt to newer, larger and more specific models as they emerge, Ather Williams III, head of global payments and liquidity and wholesale digital at Wells Fargo, said during the keynote address at American Banker’s Payments Forum in San Francisco.

“Here’s how platforms that provide intelligence use AI, in my perspective,” Williams said. “Intelligence on top of transactions converts data on balances, accounts receivable, accounts payable, foreign exchange exposure, liquidity positions into cash flow forecasting, liquidity risk detection, pricing insights [and] growth opportunities.”

Wells Fargo’s AI platforms enabled 85% of its use cases today, he said, noting that the bank has done 335 experiments and has 26 of those live in production.

“New capabilities such as tokenized deposits, programmable liquidity and near-real-time or atomic settlement didn’t exist five years ago, but they will be table stakes five years from now,” Williams said.

Wells Fargo also uses AI to enhance its sales engagement.

“We have a tool that partners with our bankers to do call summaries” that goes beyond simply dumping the call into the CRM, Williams said. “Having insights into the clients, of being advisory, providing recommendations, that’s the path of travel.”

Setting up a framework where AI use cases can scale is key to developing an AI strategy at an organization, Williams said. “We allow people to experiment, build, test and deploy, while maintaining security governance and oversight at scale. We all have our experiments. Everyone has [Microsoft] Co-pilot at their desk. Everyone messes around with Claude. We need to be able to do it at scale.”

Banks are warming up to AI use cases, according to American Banker research. About 38% of banks surveyed by American Banker said that AI technology was among a few top priorities at their organization, while 25% said it was a high priority but not in the very top tier of priorities, and 22% of respondents said it was a moderate priority. Only 3% of banks said it was the top priority, and 11% said it was a low priority.