AI has already been thought to have the potential to change jobs in every industry profoundly. But, according to a new report from Citigroup researchers, “finance will be at the forefront of the changes.”
“What a bank or financial firm looks like in the mid-2020s, be it retail or wholesale finance, looks very different to the mid-1980s, or the mid-1940s,” the report said. “AI will repeat this cycle, possibly speeding it up.”
While general-purpose technologies, or GPTs, create new opportunities for innovation and can improve quality of life, “they also destroy existing ways of doing things,” the report added. “And as such, they also create losers, especially in the short term.”
With data pulled from Accenture Research and the World Economic Forum, Citi’s researchers said that about 67% of banking jobs have “higher potential” to be automated or augmented by AI. That means “banking jobs” (which the report didn’t narrowly define) have the highest potential for AI-led job displacement.
However, according to Citi, a decline in head count may be partially or completely offset by an increase in AI-related compliance managers and ethics and governance staff.
One upside Citi pointed out, however, is that they estimate the profit pool for the 2023 global banking sector “could increase 9% or $170 billion from the adoption of AI, rising from just over $1.7 trillion to close to $2 trillion.”
AI adoption in finance will be slow
The Citi researchers believe the “pace of implementing modern AI tools in financial services, in particular, GenAI, will be relatively slow when compared to other sectors,” they said in the report, in part because of the “highly regulated nature of the sector and lack of ‘ready to go globally aligned rules.'”
“A regulatory landscape is evolving in some jurisdictions, but it is a challenging road ahead for financial services firms when it comes to implementation because countries are moving to different speeds, taking different approaches towards regulation and in some cases changing their position on whether to regulate,” it said.
In an interview featured in the report, Shameek Kundu, the head of financial services and chief strategy officer at TruEra, weighed in on the same point.
“I would describe traditional AI adoption in financial services as: widespread, shallow, and inconsequential,” said Kundu.
Kundu explains that there are “a large number of enterprises experimenting with AI across different use cases,” yet “limited scale of AI adoption across use cases” and a “limited perceived impact of AI system failures on critical business operations.”
He cited a 2022 Bank of England survey, which found that “72% of firms reported using or developing machine learning applications,” yet the “median number of ML applications for mainstream UK financial institutions to be just 20-30” and “less than 20% of the already few AI use cases were critical to business.”
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