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Machine learning and robotics to take 30% of bank jobs

Are you concerned or encouraged by the onset of technologies that provide automation?

By Tom Ball

Technologies including machine learning and robotic process automation are set to eliminate up to 30 percent of human bank jobs, according to a new report.

New alternatives to human workers are becoming desirable within the financial services, as the technology for automation is becoming more affordable.

Roles under threat typically involve a degree of manual work, the kind that is often involved in managing databases and libraries, tasks that can be handled easily by the algorithms within machine learning.

This statistic has come from a new McKinsey & Company report, says Bloomberg, who were told by Jared Moon, a co-writer of the report, that the change will “require people to use new skill sets, taking away manual work but allowing more around analytics, transformation and change.”

While concerns of simply being replaced by a new technological advancement are understandable for those with bank jobs, McKinsey has noted that there has not been a fall in the number of people employed within organisations looking to automation.

The report says that the automation of low value, manual roles will be positive for the scaling up of employees to work in other areas that benefit greatly from human intelligence, including client management.

READ MORE: Blackrock bets on robots to win big on stock markets

An example of an organisation within financial services looking to make the move to automation in some areas is the world’s largest fund company, BlackRock. The company revealed plans earlier this year to introduce machine learning.

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While the report is positive about employees being moved into other roles, the BlackRock plan included the dismissal of seven portfolio managers from its funds, as well as automating the role of stock-pickers. This strategy was planned to go into effect across 11 percent of its stock fund business.

Despite this, a great deal of positivity exists surrounding automation, especially within spaces such as cybersecurity, within which skilled analysts are desperate for support in monitoring threats and handling vast volumes of data.

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