Efficiency in finance
Technology has revolutionized the f inancial services industry. Most prominently, automated creditscoring systems have replaced underwriters and “robo- advisors” are taking the place of human wealth managers.
Now, Daniel Nadler, chief executive of f inance analytics f irm Kensho Technologies Inc., said lower- level f inancial services employees aren’t the only ones who should be worried. It’s also highly 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.”
Although 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, including loan officers and 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.
Although that’s tough to stomach for finance workers with any of those job titles, Nadler argued that a more efficient f inancial system — that is, one that employs many fewer people — is good for the finance industry.
Part of the rap on the industry 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 for analysts, associates and vice presidents.
He said the industry is full of “mediocre people feeling entitled to six- f igure jobs,” and that an industrywide culling would result in a leaner, more efficient industry that not only charges less rent but also 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 Inc.’ 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.”