By Isla Binnie and Megan Davies
NEW YORK (Reuters) – artificial intelligence is expected to show big productivity gains at banks, panelists said at the Reuters conference Next (LON:) in New York, but until now it has been more difficult to make money with this technology.
Major banks have been applying ai to virtual assistants for clients and introducing tools for employees to use in human resources, risk, compliance and finance, as well as trying to develop products within wealth management.
Goldman Sachs CEO David Solomon said at the Reuters conference on Tuesday that the implementation of machine learning and artificial intelligence could improve productivity in areas such as coding.
“We have 11,000 engineers. We do a tremendous amount of coding,” Solomon said. “If we can use these tools to increase their coding productivity by 20 or 30%, that will be a big tailwind for us.”
US bank BNY is also investing in artificial intelligence tools, CEO Robin Vince said at the conference.
“We have thousands of people at BNY who can now create and hire agents so they can help them with their daily tasks,” Vince said.
However, ai is still not helping financial companies make money. They still need to specify their exact use cases for the technology, BMO Financial Group's head of artificial intelligence and data said at the conference Wednesday.
“The hype cycle brought a lot of positive attention to this space. I'm now chief ai officer because there was a bit of a hype cycle,” said Kristin Milchanowski, who was appointed to the role at BMO, one of Canada's largest banks. , in October.
“I think people thought it was going to impact revenue or have a different cost reduction than the effect actually has been,” Milchanowski said, adding, “We're not seeing revenue-generating activity.”
So far, ai has been most useful in tasks such as reducing the time BMO's equity teams need to produce reports – an important part of many investment banks' offerings – from more than four hours a day to less than one, leaving analysts free to perform more creative tasks.
It's important to identify specific use cases for ai in the future, Milchanowski added, noting potential applications for optimizing operations and generating customers.
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