AI Adoption to Accelerate
Just as artificial intelligence is revolutionalizing consumer life, it is about to reach a tipping point in regards to the wholesale capital markets, according to research recently published by Greenwich Associates.
“We weren’t talking about self-driving cars five years ago, and we didn’t have Alexa in the kitchen,” said Richard Johnson, vice president, market structure and technology at Greenwich Associates and author of the report. “All these technologies have come along in the last five years, and the nature of technology is that it does advance exponentially. So I think in the next five years that we’re going to see some significant changes all over, but also in institutional finance.”
AI and the automation which it brings eventually will affect every aspect of an institutional trade’s lifecycle from research and trade idea generation to trading and back office functions like compliance, according to Johnson.
Johnson views the productivity gains that AI provides as augmenting existing roles within financial organizations rather than replacing them.
“Most of the companies I spoke to for the course of this study stressed that their technology was about helping people do their jobs better as opposed to replacing people,” he said. “I think that’s certainly a noble goal. But looking at long term, I think some jobs are going to be displaced inevitably. There have been some scary numbers put out there. I don’t know how accurate these numbers are, but I think there will be some impact.”
One function to which AI would lend itself easily is in writing research reports based on structured data using natural language generation.
“There’s a lot of structured data in finance, such as balance sheets, cash flow statements, and so forth that can be turned into well-written reports extremely quickly,” Johnson noted.
Other functions could be answering the common questions clients ask their sales traders, which would free up traders to focus on their trading performance.
However, it will take some time to develop AIs that can master the multi-disciplined art and science of generating investment strategies.
“The typical AI can’t come up with a long-range forecast taking into consideration all the different facts, and come up with an investment thesis the same way a Wall Street analyst or portfolio manager can yet,” he said. “The type of tools that are out there can help them do it better, so it’ll be interesting to watch what happens.”
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