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A new way for business to learn

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SHANE WHITE, CONTENT MANAGER, INSTITUTIONAL, ANZ | MAY 2019

 

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Machine-learning algorithms are helping businesses solve big problems and driving productivity returns.

 

 

Machine learning won’t do all the thinking for businesses in the future but it will change the way they think, according to a panel of experts at ANZ’s Finance & Treasury Forum in October – and help drive productivity as a result.

“Machine-learning algorithms are changing the way we think about cash or when we're forecasting cash,” Greg Russo, Managing Director, Treasury Operations at General Electric said.

“Over the course of the last couple of years we have been able to cut in half the amount of excess liquidity that we're holding by using data more effectively.”

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“We have been able to cut in half the amount of excess liquidity that we're holding by using data more effectively."
Greg Russo, MD Treasury Operations, General Electric

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Speaking at the forum in Singapore, Russo said machine learning had transformed the way GE approached its cash on hand.

“Believe it or not our Treasurer, one of his biggest complaints at the time was ‘on a daily basis how come I don't know how much cash I have?’” he said. “Which seemed like a fairly reasonable question for a Treasurer to ask.”

“We now have a dashboard that is updated four times a day that anybody in our organisation would go on and see how much cash we have, where the cash is, how much is restricted, how much is freely available, by legal entity, by country.”

Jared Danaraj, Director of Ecosystems, Industry and Strategic Technology Alliances ay Cisco APJ said machine learning was helping prevent system outages at his company, to the benefit of the group and its customers – as well foresee when they may occur.

“We could predict ahead of the curve before some of these machines - which by the way it cost anywhere from half a million dollars to ten million dollars, right - we going to fail to prevent downtime,” he said.

“And as we develop a database of variables, information that you're seeing from these machines, we were able to deploy machine-learning algorithms to better predict them.”

Shane White is Content Manager, Institutional at ANZ

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