Bank of America (BAC)

EarningsTranscriptsUpdated

Every word

41–47 of 47, most settled first · page 2 of 2
Bank of America: every word with settled markets, most settled first
WordQ4’24Jan '25Q1’25Apr '25Q2’25Jul '25Q3’25Oct '25Q4’25Jan '26Q1’26Apr '26Q2’26Jul '26Q3’26last callTrendLast 8ScriptedAll-timeProbability
Monetize0 times: Monetize, Q4’24 Jan '250 times: Monetize, Q1’25 Apr '250 times: Monetize, Q2’25 Jul '250 times: Monetize, Q3’25 Oct '250 times: Monetize, Q4’25 Jan '260 times: Monetize, Q1’26 Apr '260 times: Monetize, Q2’26 Jul '260 times: Monetize, Q3’26 Oct '26steady0/80%0/80%6/768%12%n=1+tx from settlement history blended with transcripts
Pivotnever said0 times: Pivot, Q4’24 Jan '250 times: Pivot, Q1’25 Apr '250 times: Pivot, Q2’25 Jul '250 times: Pivot, Q3’25 Oct '250 times: Pivot, Q4’25 Jan '260 times: Pivot, Q1’26 Apr '260 times: Pivot, Q2’26 Jul '260 times: Pivot, Q3’26 Oct '26steady0/80%0/80%0/760%12%n=1+tx from settlement history blended with transcripts
Subscriber0 times: Subscriber, Q4’24 Jan '250 times: Subscriber, Q1’25 Apr '250 times: Subscriber, Q2’25 Jul '250 times: Subscriber, Q3’25 Oct '250 times: Subscriber, Q4’25 Jan '260 times: Subscriber, Q1’26 Apr '260 times: Subscriber, Q2’26 Jul '260 times: Subscriber, Q3’26 Oct '26steady0/80%0/80%1/761%12%n=1+tx from settlement history blended with transcripts
Synergy0 times: Synergy, Q4’24 Jan '250 times: Synergy, Q1’25 Apr '250 times: Synergy, Q2’25 Jul '250 times: Synergy, Q3’25 Oct '250 times: Synergy, Q4’25 Jan '260 times: Synergy, Q1’26 Apr '260 times: Synergy, Q2’26 Jul '260 times: Synergy, Q3’26 Oct '26steady0/80%0/80%5/767%12%n=1+tx from settlement history blended with transcripts
Tailwind2 times: Tailwind, Q4’24 Jan '25, counts as said0 times: Tailwind, Q1’25 Apr '251 time: Tailwind, Q2’25 Jul '25, counts as said0 times: Tailwind, Q3’25 Oct '250 times: Tailwind, Q4’25 Jan '264 times: Tailwind, Q1’26 Apr '26, counts as said0 times: Tailwind, Q2’26 Jul '260 times: Tailwind, Q3’26 Oct '26steady3/838%1/812%25/7633%37%n=1+tx from settlement history blended with transcripts
Trump0 times: Trump, Q4’24 Jan '250 times: Trump, Q1’25 Apr '250 times: Trump, Q2’25 Jul '250 times: Trump, Q3’25 Oct '250 times: Trump, Q4’25 Jan '261 time: Trump, Q1’26 Apr '26, counts as said0 times: Trump, Q2’26 Jul '260 times: Trump, Q3’26 Oct '26steady1/812%0/80%3/764%20%n=1+tx from settlement history blended with transcripts
Workflow0 times: Workflow, Q4’24 Jan '250 times: Workflow, Q1’25 Apr '250 times: Workflow, Q2’25 Jul '250 times: Workflow, Q3’25 Oct '250 times: Workflow, Q4’25 Jan '260 times: Workflow, Q1’26 Apr '262 times: Workflow, Q2’26 Jul '26, counts as said0 times: Workflow, Q3’26 Oct '26rising1/812%1/812%3/764%24%n=1+tx from settlement history blended with transcripts
What the columns mean
Last N
of the appearances shown, how many counted as said
Trend
how the count moved over these calls
Scripted
calls of the last 8 where it was said in the prepared remarks
All-time
every call on file
Probability
the calibrated probability for the next listing; n is the settled observations behind it when it was computed, '+tx' adds the transcripts, 'new' means too little history

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Agents: this page as TSV at /api/v1/entity/bank-of-america · words: /api/v1/history?entity=bank-of-america · columnar JSON in #parrot-data · llms.txt · MCP