Service automation, operational efficiency, cost reduction and headcount rationalization, customer service and support, investment optimization, identification of market trends, fraud and anomaly detection, IT system migrations, R&D, data processing and more systems, R&D, financial data processing, personalization of advertising campaigns, compliance support, risk analysis, cybersecurity, pricing... The applications of AI in the banking industry seem endless.
According to McKinsey, this revolutionary technology could boost banks' productivity by 2.8% to 4.7% of annual sales, a gain of $200 billion to $340 billion, by improving sales, marketing, processes and software engineering.
Wells Fargo CEO Mike Mayo prides himself on having grasped the crucial dimension of AI: "If you're a bank and you don't have an AI strategy, then you don't have a strategy," he said on Bloomberg recently, highlighting the lost revenue for industry players who hadn't jumped on the bandwagon.
US lender Morgan Stanley, for example, has developed an AI assistant to help its wealth managers prepare offers. The Royal Bank of Canada has given itself a virtual assistant capable of providing financial advice and savings recommendations to customers based on their spending habits and cash management. Bank of America's chatbot addresses the questions most frequently asked by savers. In France, a virtual agent directs Orange customers to the appropriate advisors, while Crédit Mutuel's chatbot identifies e-mails requiring urgent responses.
A shortage of brains
While Machine Learning can be used to steer the deployment of Artificial Intelligence within an organization, by learning from the systems already in place and feeding off the data collected, it does require humans to direct its work and give it instructions. It's also the grey matter of our fellow human beings that has to implement AI tools, integrate them into operations and coordinate projects.
In 2022, according to a study by Evident, only 650 people were employed in AI-related positions in the world's 23 largest banks in 2022. Among the latter, JPMorgan Chase, a leading figure in the banking adoption of AI, had no fewer than 120 researchers specializing in the field in August 2022, i.e. a fifth of total forces. And 40% of these 650 people had taken up their posts by 2022. Adoption was in its infancy.
Since then, the trend has clearly accelerated. By 2023, banks had woken up to the need to integrate AI to stay competitive: CapGemini estimates that 4% of financial institutions worldwide have adopted AI tools to facilitate their IT processes. And the 60 largest North American and European banks have increased AI-related recruitment by 4% between October 2022 and April 2023, according to the same study.
Pioneer JPMorgan published more than 3,650 AI-related job offers between February and April 2023, ahead of Citigroup ( 2,100 offers), Deutsche Bank (1,295), BNP Paribas (1,202 job openings), followed by Société Générale, which reports 1% of its workforce dedicated to AI or data.
Yet, according to the New York Times, at the start of 2023, only 22,000 people worldwide had the skills needed to conduct serious AI research.
Banks on Wall Street (and elsewhere) are therefore scrambling to recruit the best in the field and retain them over the long term. According to HubFinance, by 2023, almost half of all bank recruitments will have been made by their competitors.
Goldman Sachs has learned this the hard way. In the recruitment war, it's the lender that has recorded the highest number of departures of AI-dedicated employees in recent months, seduced by more tempting proposals from competitors.
The boon for the big banks is that AI skills are to be found in the major urban and financial centers: New York, London, Toronto, Bangalore and Paris in particular.