JPMorgan is cutting tech costs but hiring more data scientists
In the past few years, banks have been making serious efforts to detach themselves from the constraints of legacy tech with a forward thinking eye on engineering. UBS and Deutsche bank both made significant progress decommissioning outdated applications and moving others to the cloud. JPMorgan is no exception.
In today's JPMorgan global Investor Day technology report, the bank says productivity and efficiency have the potential to cut technology costs by ~10% through the increased adoption of agile methodology alongside "high levels of automation." No doubt the layoffs earlier in the year which included some tech staff also contributes to this.
The bank puts the potential for cutting infrastructure spending at a higher 15-20%. This is being driven by increased cloud adoption and the breaking down of its self-proclaimed "monolithic applications." 300 applications have been decomissioned in the past year while cloud technology "as a percentage of total infrastructure spend" has grown 8%.
While most of the focus is on costs and efficiency, there is area within engineering where JPMorgan is prioritizing growth: AI and data science. JPMorgan's AI and machine learning team is now 1,700 people strong, consisting of over 900 data scientists, 600+ ML engineers and 200+ AI researchers. The bank expects to beat its AI/ML impact targets.
JPMorgan planned to hire 2000 engineers last year, it looks as though these AI hires have been a significant part of those efforts.
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