How AI Is Reshaping the Talent Pipeline in Asset Management, According to Clearwater Analytics’ Head Of Global Alts

The iConnections conference is in the book, but we managed to catch up with Yuriy Shterk who leads Clearwater Analytics’ global alternatives team shortly after. In an interview with Hedge Fund Alpha, Shterk discussed some of the key challenges and opportunities with alternative data, including what AI’s growing role may mean for would-be first-year analysts.

Alpha versus beta

AI has a wide range of use cases across the finance world, including generating more alpha and lowering the cost of beta. While most funds are currently using AI to automate their workflows and enable their clients to get the information they need faster, alpha is becoming an increasing focus.

“More and more, we see AI being deployed for alpha generation, signal elimination and analytics that will lead to better alpha decisions,” Shterk said. “It’s being used across the board, although a lot depends on the specific asset type. In public markets, AI is more prevalent for pure signal elimination. When you look at the private markets, you see it is being used more on the alpha side to help validate various investment opportunities and loan projections, while also being a tool on the fundraising side.”

Thus, AI is being used more to view the volumes of data available to users and to find the answers to their questions, as opposed to the public space, where use cases focus on the range of products for investors to invest in. It can also help investors determine an appropriate time or price to enter an investment position.

Independent AIs?

The hope is that one day, AI models will be able to independently rebalance portfolios or execute trades, but a key question here is where the fiduciary responsibilities lie. This was the topic of many panels at the iConnections conference.

“With the current state of technology, you don’t always know all the details as to why the recommendation was made or the decision was made when using AI,” Shterk pointed out. “So from a fiduciary perspective, or when you think about needing to go and report on your numbers, deploying AI to automate workflow or portfolio creation can be efficient, but still generates a lot of questions from the perspective of business risk and lack of transparency, and professionals still need to be responsible for decision making.”

He added that currently we’re mostly seeing AI being used as a supplement or assistant to humans. It’s able to spot some of the signals humans can’t due to the volume of data that must be processed.

“Whether it could be used as a 100% workflow and decision maker, we still don’t know yet,” Shterk said.

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