From online lenders using automated credit-scoring systems to “robo-advisors” that have automated the business of wealth management, there’s no question technology is changing the financial services industry.
Now, Daniel Nadler, chief executive of finance analytics firm Kensho, said low-level financial services employees aren’t the only ones who should be worried. It’s also high-paid bankers.
Speaking Monday at a financial technology panel at the Milken Institute Global Conference in Beverly Hills, Nadler said the JPMorgans of the world will still be here a decade from now, but they’ll have many fewer workers.
“All the key players are going to remain,” said Nadler, whose firm is backed by Goldman Sachs. “They’ll just be more efficient.”
While banks have already cut back on tellers at bank branches, he said the place where technology can more meaningfully save banks money is in so-called knowledge workers. That could be anyone from loan officers to mid-level executives.
“Analysts, young associates, vice presidents — anyone whose job is moving a column of data from one spreadsheet to another is going to get automated,” Nadler said.
While that’s tough to stomach for finance workers with any of those job titles, Nadler argued a more efficient financial system — that is, one that employs many fewer people — is good for the finance industry.
Part of the rap on finance is that it provides important services such as helping companies raise money to grow, but it sucks a lot of money out of the economy in the form of fees — what Nadler calls rent. That “rent” goes to, among other things, pay all those analysts, associates and VPs.
He said the industry is full of “mediocre people feeling entitled to six-figure jobs,” and that an industry-wide culling would result in a leaner, more efficient industry that not only charges less rent but is more liked (or less hated).
Nadler said many of these mid-level workers could be replaced by the kind of artificial intelligence systems that recently helped Google’s AlphaGo computer beat a world-renowned player in the complex board-game Go.
That system essentially learned to play the game by studying human players. Nadler said such a system could easily be used in the investment world.
"We’re there now,” he said. “There’s going to be very little an individual investment decision maker can do that a computer will not already have learned from him.”