As we discussed yesterday, AI’s potential to remake the finance sector is increasingly evident. But what shape would such a transformation take?
Brave New World
“‘All-pervasive’” AI is rapidly unlocking new opportunities for fintech startups. Research firm Market to Market projects a nearly eightfold expansion in the AI-for-fintech industry globally to $7.3B by 2022.
Moreover, that expansion is outpacing other sectors in its uptake of AI. In Europe, finance leads all sectors with a 23% share of AI startups.
Those trends highlight AI’s potential for creative destruction in finance — albeit without the terminators-chasing-John-Connor-through-a-global-junkyard dynamic strident media narratives of robot apocalypse have stressed.
Opimas estimates automation and AI will displace 400,000 finance jobs — nearly one in five — by 2030. Still, when paired with the 190,000 jobs added in the last decade, that number amounts to less than 10% of the industry workforce.
Asset managers (157,000 cuts) and broker-dealers (97,000) could be the hardest hit, while banks (8,000) will escape relatively unscathed.
Such prospective cuts reveal a shift in the positioning of investment in technology. Once a growth-oriented expenditure of prospering firms, tech investment has become a necessity for struggling companies looking to streamline their operations.
The Future You
But enough of industry-level trends — what about the Future You?
If the soothsayers are right, you’ll be richer, have a liberal arts background, and be able to trade instantaneously from your mind.
Even as the workforce contracts, pay for “survivors” of AI attrition will rise, per McKinsey. Overall compensation costs could drop by as much as 20%, driving industry-wide cost savings of up to $600M a year — figures that would land finance firms on more profitable footing even absent industry growth.
The beneficiaries of that windfall may be somewhat counterintuitive, though. In a recent interview, entrepreneur Mark Cuban argued the value of a computer science degree would “‘diminish over time’” as demand for positions requiring “‘creativity, collaboration, communication’” — skills not easily replicated by AI — grows.
And now for the juicy stuff. A recent report from trading outfit IG mused that in fifty years, traders will be able to open and close positions directly from their brains in a mere 0.1 seconds.
Unfortunately, even that utopian vision of the future leaves ample room for latency arbitrage while exposing us to the ire of the spouse we ignored while buying still more shares of Cyber Dynamics Systems Corp. on date night.
The Data Wrinkle
But prophecies of a finance realm remade by AI face a complication: data. A Refinitiv survey of financial professionals found that the two biggest barriers to AI adoption are poor data quality and a lack of data availability — beating out access to talent.
A similar PwC survey of 300 financial executives found that while 76% said their firms are looking to extract value from existing data, only 15% have the data they need to achieve that goal. Companies’ historical data was often “‘acquired haphazardly’ and may ‘lack the detail and demonstrable accuracy needed for use with AI,’” PwC said.
Those studies reveal that the quality of the data from which AI learns, rather than AI itself, is emerging as the gating factor in pacing AI’s push to transform finance.
In a world increasingly conscious of the value of data and wary of privacy concerns, mastering that challenge will require patience.