Fri, Aug 23, 2019 - Page 9 News List

Finance needs people who work well with robots

Automation could replace one-third of financial jobs by the mid-2030s, but it is also redefining and adding new roles

By Siobhan Wagner and Shelly Hagan  /  Bloomberg

Illustration: Mountain People

Today, it is not just humans competing for work in banking. Machines are becoming a threat to warm-blooded number crunchers worldwide. Indeed, almost one-third of financial services jobs could be displaced by automation by the mid-2030s, a report by PricewaterhouseCoopers LLP last year said.

Despite those stark forecasts, some optimists say that the rise of machines at banks is not simply taking away jobs, but rather changing their definition and adding some roles.

Job seekers with expertise in artificial intelligence (AI), machine learning and data science are among the most in-demand candidates in finance, according to hiring sites Glassdoor, LinkedIn, Hired and ZipRecruiter.

It is not only disrupters such as Square or Stripe hiring this talent; legacy financial companies, such as JPMorgan Chase, Capital One and Morgan Stanley, are scooping these people up as well.

In the US financial sector alone, job postings that list these big data skills as requirements increased almost 60 percent in the 12-month period ending last month, according to LinkedIn.

Business and finance professors who are preparing students for future banking careers are also seeing the trend.

Data scientist is the “hottest job function” now for employers, said Andrew Lo (羅聞全), director of the MIT Laboratory for Financial Engineering in Cambridge, Massachusetts.

Data portfolio managers, who are charged with maintaining and maximizing the value of a company’s data assets, are also gaining importance, Lo said.

“We already have that happening informally because chief technology officers are playing that role,” he said. “But this has become a much more business-oriented set of challenges that the typical CTO [chief technology officer] might not be equipped for, so I think that’s going to evolve over time.”

While machine learning has the ability to “augment” jobs and enhance the performance of organizations, it will also present risks and the need for “AI auditors” at banks, said Theodoros Evgeniou, a professor of decision sciences and technology management at INSEAD in Fontainebleau, France.

As machines make more decisions in banking, ethical and legal concerns will be raised that need to be addressed at the board level, he said.

“Let’s say you’re a bank and you’re giving credit based on credit scoring and machine learning, and your models are discriminating certain populations of people,” he said. “If you’re then sued for being discriminatory, who is liable for this? If [the models] discriminate, you are liable.”

There are also ways machine learning may indirectly create jobs. For instance, automating tasks previously done by humans in the asset management industry should theoretically reduce costs.

Lower fees will likely increase demand for financial services and, subsequently, the need for more staff to service new customers, said Bai Guo (白果), a lecturer of strategy at China Europe International Business School in Shanghai.

“It will probably be easier to serve clients that were previously excluded from financial services,” she said.

As these new clients may require a more human touch, more client relationship managers will be needed, she said.

Machine learning may also provide an opportunity to reinvent a career.

While it is not easy or affordable in all cases to go back to school, some financial sector employees who find themselves displaced by technology could be in a position to reskill.

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