AI solutions are on track to permeate and revolutionize a growing number of industries - and finance won't remain an exception.

Asset management in particular is ripe for AI tools due to its reliance on data, according to Tomi Poutanen, CEO and Co-founder of Signal 1, a provider of AI-powered healthcare insights, and former Senior Vice President and Chief AI Officer at TD Bank Group.

"I think asset management is going to be changed in a massive way with algorithms," Poutanen said, speaking recently at the 2023 edition of the Institutional Investment Symposium in Toronto. The event was organized by TD Global Investment Solutions.

A Silicon Valley veteran whose experience spans big tech, banking and healthcare, Poutanen predicts that algorithms will be an "intrinsic part of asset management's future."

Data rules everything in asset management and having access to data that others don't is particularly valuable.

"The really valuable stuff is not public - you have to purchase that data. Sometimes you buy a company not for its cash flow, but for its data," he explained. "Some firms spend over a hundred million dollars a year for data."

The data comes in all formats – equity prices, analyst reports, satellite images, etc. All these pieces of information come over time.

"Transformers are incredibly good at analyzing this data," Poutanen said, referring to the deep learning architecture that tracks patterns in sequential data and has made generative AI possible. "There will be enterprising funds creating algorithms that can process this data."

But there will be a need for differentiation. "Even if an algorithm can predict cash flows for a company or some other event, this will already have been priced by the market," he said.

This is why different portfolio managers will need to have unique strategies that differentiate them from others, which will help provide sustained returns, according to Poutanen.

Despite the great possibilities that AI can bring to asset management, he said "it's only hedge funds that are currently going after AI talent."

Poutanen believes insurance is another part of the financial industry which is ripe for AI applications. That's because insurance has been historically rooted in actuarial science. However, he noted that there has been resistance to AI adoption among certain insurers due to skepticism about whether machines can outperform the human actuaries working at their companies.

Risks

Job displacement is one of the larger societal risks that AI technology poses, in spite of its promise to transform and improve every sphere of life.

Job displacement is a concern particularly in industries that face a shortage of talent, such as medicine, construction and transport, Poutanen explained.

"We have few workers in many fields [...] so we’re using AI to augment a depleted workforce." But, he cautioned, eventually machines could take over: for example, if you have an insufficient number of truck drivers, you can use autonomous trucks, which could eventually displace all drivers.

"What happens when these job categories just, boom, disappear?"

Many of these displaced workers might not be able to upskill and transition to other fields, which would have huge societal costs, Poutanen explained.

This is why he thinks regulation is necessary. "As much effort as we're pouring towards the development of AI, we should pour into regulation."

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