Fenergo is eliminating thousands of hours spent on compliance and onboarding processes with agentic AI, signaling a shift in the banking industry.  

The fintech’s AI agents are saving one of its largest banking clients more than 18,000 hours annually by extracting data and automating mundane tasks such as document review, Director of Market Development Garry Teekah told FinAi News.  

“That’s about 4.4 years of analyst effort that they were able to redeploy to higher-impact areas,” he said.

Fenergo’s agents also are on track to automate 111,000 significance evaluations — processes that determine the potential magnitude of certain data changes or compliance risks— for the client this year, Teekah said.  

Teekah declined to name the bank, but Fenergo’s largest clients include:

• $2.8 trillion Citi;
• $2.1 trillion SMBC Americas;
• $816 billion CIBC;
• $688 billion U.S. Bank; and
• $549 billion Truist. 

Fenergo designed agents to address repetitive workflows tied to onboarding, periodic review and offboarding because these are tangible use cases that provide near-instant efficiency gains, Teekah said.  

“When someone’s buying AI these days, they want an immediate return on investment,” he said. Banks “want to be able to show the buying committee or the board improvements” with AI.  

The system of record within Fenergo’s platform functions as a “chassis” for its AI agents by allowing easy access to regulatory or customer data and enhancing banks’ ability to validate information or flag anomalies, Teekah said. 

“Understanding how that AI is making a decision and ensuring that the decision is auditable and repeatable is incredibly important.”

— Garry Teekah, director of market development, Fenergo

Agentic future 

The global market for agentic AI in financial services is projected to hit $80.9 billion by 2034, up from $4.4 billion in 2026, according to research and consulting firm Market.us, citing “data-intensive tasks like compliance checks” as a key growth driver.  

For now, agentic AI is best suited to handle repetitive compliance tasks, but the technology could transcend deterministic processes as “sentiment analysis” improves, Teekah said.  

Better understanding the tone, intent and behavioral patterns of customers can help banks detect suspicious behavior, he added. 

“That will continue to help take out some of the workload, with folks being able to focus more on high impact-activities,” he said. 

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