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BlackRock is quietly building a team of 30 data scientists to create a next-generation stock-lending platform


larry fink

  • BlackRock founded AI Labs last year to research artificial intelligence. Since then, it's expanded to a staff of 30.
  • The team continues to grow — the firm is looking for a senior data scientist, among other roles — and job postings indicate the kinds of projects the Stanford-advised group is tackling.
  • AI Labs' work includes building a next-generation stock-lending platform, working with alternative data sets, and automating rote tasks.
  • Visit Business Insider's homepage for more stories.

The world's largest asset manager is on a mission to automate and innovate through its growing artificial-intelligence team.

BlackRock founded a Palo Alto, California-based group called AI Labs last year, directed by the Stanford professor Stephen Boyd. Now, according to job postings reviewed by Business Insider, the 30-member team is tackling projects ranging from next-generation lending platforms to automating human tasks.

Read more:Artificial intelligence is transforming a $22.9 trillion investing strategy — but the cutting-edge technology comes with a new set of problems

AI Labs is set up to work on new capabilities, from ideas through execution, at the $6.5 trillion asset manager.

"There is a rich problem space for data scientists and engineers across all areas of the business including investments, sales, marketing, operations, product, UX, etc. and the potential to have large scale impact," one recent posting for a senior data scientist said. ("UX" refers to user experience.)

Current projects include building a dynamic pricing and auto-bidding engine for the security-lending business, a $1.7 trillion business that BlackRock has been active in since 1981, according to promotional materials.

AI Labs' staff is also working with alternative data sets to find useful signals. That's been a conundrum across asset management as experts say the booming space has been difficult to generate incredible returns in, despite new providers seemingly popping up daily.

In a blog post last year, Jody Kochansky, BlackRock's chief engineer, highlighted some of the ways artificial-intelligence techniques were already helping to sort through vast amounts of what he called "messy data." Investment professionals, he wrote, could begin to glean insights into areas including "the speed of construction in China, foot traffic into major department stores and sentiment picked up from thousands of online employee reviews."

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AI Labs is also tackling natural language processing — synthesizing information from financial reports, news, and contracts — as well as automation on repeatable tasks, as it tries to free staff members "to work on the tasks that require their human intelligence."

A BlackRock representative declined to comment further.

BlackRock is far from the only asset manager thinking about how to use artificial intelligence across its businesses. Established managers like Franklin Templeton are embedding data scientists in their investment teams, while startups like Pagaya are using artificial intelligence to reshape investment strategies.

Managers are eyeing artificial-intelligence techniques as one way to boost fund managers' performance, particularly as investors flee higher-revenue active funds for cheaper passive strategies, and as a way to cut costs by automation.

Not all managers are on board, however. In January, the chief technology officer at Cohen & Steers, a $55 billion alternatives-focused firm, told Business Insider that artificial intelligence was "right in the middle of a hype cycle," so the firm was focused on building up its internal infrastructure, staying away from AI.

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