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Bank of America Corp. (BAC): Key takeaways from management meeting
研报英文原文证据摘录
Equity Research
10 September 2026 | 4:02PM EDT
Bank of America Corp. (BAC): Key takeaways from management meeting
On September 9th, we hosted a meeting with BAC’s: 1) Chief Technology and
Information Officer, Hari Gopalkrishnan; 2) Head of Corporate Strategy and
Operational Excellence, Jeff Busconi; and 3) Head of Investor Relations, Lee
McEntire. Further detail within.
BAC’s technology strategy is focused on: 1) strengthening risk, regulatory and
security controls foremost; and 2) prioritizing ROI and efficiency when
evaluating discretionary technology investments. In recent years, the company
noted that discretionary investments have increasingly shifted to AI centric
initiatives from traditional digital transformation. In addition, the company
highlighted its operational excellence framework as a differentiated tool in evaluating
discretionary (particularly AI related) technology spend. BAC had mapped 3,700
firmwide processes which allows them to assess the workflow impact of each
proposed project, and whether the expected efficiency uplift justifies the investment
spend.
The company highlighted that it has remained ROI focused on its technology
spend, with savings from efficiency gains partially self funding incremental
investment. In addition, BAC noted that growth within its tech spend has been
largely driven by its discretionary tech investment budget (~$4bn of ~$13bn total)
which has scaled ~45% vs. only ~15% growth in its core operational tech over the
past decade. On incremental discretionary investments, the company noted it
targets a ~3 year pay back on average.
Richard Ramsden
+1(212)357-9981 |
Goldman Sachs & Co. LLC
James Yaro
+1(212)902-1913 |
Goldman Sachs & Co. LLC
Divyam Harlalka
+1(332)245-7818 |
Goldman Sachs India SPL
Matthew Weng
+1(212)902-8484 |
Goldman Sachs & Co. LLC
Lokesh Kumar Sangewar
+1(332)245-7846 |
Goldman Sachs India SPL
Thirukumaran R
+1(332)245-7608 |
Goldman Sachs India SPL
Management believe incremental efficiency gains from AI will likely be
meaningful, but can be difficult to size numerically, as revenue based
improvements and reinvested expense savings are harder to track. The company
…
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