The latest quarterly earnings, boosted by strong trading activity, have not slowed the pace of workforce reductions at major US banks. In the second quarter, these institutions saw their employee numbers drop at the fastest quarterly rate in at least six years.

Based on staff data disclosed in quarterly financial reports, Bank of America (BAC.US), Wells Fargo (WFC.US), Citigroup (C.US), Goldman Sachs Group (GS.US), and Morgan Stanley (MS.US) collectively cut over 10,000 jobs in Q2. This marks the largest quarterly decline in the period for which data is available since early 2020.

Among the major US banks, only JPMorgan Chase (JPM.US) reported a slight increase in headcount compared to the end of the first quarter. Wall Street banks have been accelerating their workforce reductions throughout the year, with the total number of employees at major banks declining for three consecutive quarters.

Many banks are actively working to manage expenses. For instance, Citigroup has been consistently streamlining its workforce in recent months, as CEO Jane Fraser focuses on improving shareholder returns. Bank of America's CFO Alastair Borthwick told analysts on an earnings call earlier this week, "We've done a very good job of managing headcount over the last six quarters." The bank's total employee count is down nearly 1% compared to the same period last year.

Top Six US Banks Continue to Trim Workforce as AI Fuels Long-Term Job Concerns

Simultaneously, advancements in artificial intelligence (AI) are intensifying market concerns about long-term employment prospects for staff. Standard Chartered Group CEO Bill Winters indicated earlier this year that the company would cut jobs in certain roles to "replace the less valuable human capital with the financial and investment capital we put in," though he later publicly apologized for the remarks.

Wells Fargo CFO Michael Santomassimo stated on Tuesday's earnings call, "We expect to be able to operate the company with fewer people over time than we do today." He added, "Technology, and particularly AI, is certainly helping us do that in different ways or faster than we have in the past. But we do expect to continue to see efficiency gains going forward."