The call grade, management's tone measured against 177,437 other calls, what changed since the quarter before, and every one of the 500 checks.
This is the current report. Unlock its call read, expected move size, and all 500 answers.
Language counted straight from the transcript, behaviour read by the 500 checks, tone above. The band is the middle half of every call we have graded; a flag means this call sits outside it.
Q1 2025 · 500 checks
Every answer is below. Open any check to see what its YES or NO means.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
The model found enough evidence in the earnings transcript to mark this exact condition as present.
The model did not find enough evidence in the earnings transcript to confirm this exact condition. NO means “not detected,” not necessarily “disproved.”
Earlier Artul research experiments on NBHC calls. Open a question to read the model's original reasoning.
Original model output from the research archive. It may be verbose or include the model's working notes.
The task is to evaluate two gates based on the earnings call transcript and return YES only if both are YES, otherwise NO. YES The transcript shows a clear positive current development in the Cambr acquisition, which management highlights in prepared remarks as diversifying funding sources and enabling FDIC-insured deposit growth with low overhead.
We need answer only YES or NO. Need evaluate both gates. We need analyze transcript. Need determine Gate1: positive current development with Q&A adding more concrete operating detail than prepared remarks. Gate2: engine is company-created vs external. Let's parse. Company: National Bank Holdings. Prepared remarks: record loan originations, loan growth 16.5% annualized, broad based, pipeline strong, project near double digit annualized growth Q4. PPP loans. Deposits growth, cost down. NIM expanded. Asset quality strong. Noninterest income, mortgage servicing sale, Finstro investment. Expenses. Capital. Q&A: First question from Brett asks about FinTech ecosystem and revenue, banking as service. Tim gives long detailed answer about four legs: digital lending, depository/treasury, information dashboards, blockchain. Says premature to talk incremental earnings Q1 2022, but elements deliver incremental profitability next year. This is a positive current development? It's more of a plan/strategy, not current actual activity? They invested in Finstro, partnership. But the development is building ecosystem, not yet revenue. Gate1 requires real and current actual business activity, demand, execution, progress already happening now, not plan/hope. The FinTech ecosystem is future plan, though investment made. Q&A adds detail but it's about strategy, not current operations. So likely not. Other positive current development: loan growth. Prepared remarks: record originations, 16.5% annualized, broad based, pipeline, project near double digit annualized Q4. Q&A: Brett asks about loan growth dynamic vs margin, whether new clients or existing lines. Tim answers: margin deployment, PPP fees, then loan growth prospects: proud of teams engagement, back in offices, business banking officers in marketplace, new perspective business in pipeline, watching balance sheets, great success winning new relationships, feel good about pipeline. This is somewhat additive? It adds that they are back in offices, officers in marketplace, new relationships. But is it concrete operating detail? It's qualitative, not specific numbers. Another question from Andrew Liesch about loan yields, new production relative to portfolio. Aldis gives yields: originated loans FTE 4.01% including PPP, excluding 3.87%, new originations 3.9%, at or accretive. That's financial detail, not operations.
We need answer only YES or NO. Need evaluate both gates. Gate 1: positive current development with Q&A adding more concrete operating detail than prepared remarks. Transcript: prepared remarks mention loan growth, pipelines, lift outs, expense management, etc. Q&A: analysts ask about loan growth outlook, lift outs, C&I originations decline. Management says "I think you'll see a big make up here in the second quarter" and "We saw a fair amount of business slide into the second quarter and we're benefiting from that in the early stages of this quarter." That's about timing, not much concrete. Also expense management: Rick says "I will be very disappointed if we don't beat our guidance on expense management" but no specifics. Lift outs: Tim says "we have a number of, we think, very interesting lift out opportunities" and "pretty excited with some work we have in the queue right now that could be very meaningful." That's vague, no concrete detail. No positive development with additive specifics. Also much Q&A about energy credit problems. So Gate 1 NO. Gate 2 also NO. Answer NO.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need answer only YES/NO. Need analyze transcript. Need determine if management describes already possesses second, largely unmonetized position, future use largely within company's control to switch on, actively deciding how/when to turn into revenue. Let's parse. Company National Bank Holdings. They have excess capital, share buybacks, M&A, lift outs. They mention "excess capital" $115 million using 9% leverage ratio. They have share repurchase authorization. They are buying shares. They are pursuing M&A and lift outs. Is excess capital a "real holding" that is not paying bills? It is capital, not revenue-generating asset? They could deploy it. But is it "largely unmonetized position"? Excess capital is not producing earnings, but it's just capital. Management says "Given profitability... we do see buying our shares as an excellent investment." They are actively deciding how to use excess capital: organic growth, M&A, share buybacks. But is that a "second, largely unmonetized position" that is a real holding? Excess capital is not an asset separate from operations? It is on balance sheet, but it's not a "position" like land, technology, etc. It is financial slack. The question asks "something real it holds today, beyond the business that is currently producing its results — whose future use is largely within company's control to switch on." Excess capital could be deployed, but it's not "unmonetized" in sense of an asset that can be turned into revenue; it's just cash. Management says they have excess capital and are deciding between buybacks, M&A, lift outs. But is that a "second source of business"? No, it's capital allocation. Also they mention "lift out opportunities" but those are not already in hand; they are pursuing. They mention "strategic initiatives" but not specific. Another possibility: They have "acquired loans" and "310-30" portfolio? They have "failed bank previously charged off loans and OREO income" with FDIC sharing. They mention "gains on the failed bank's previously charged off loans and OREO income" as part of non-interest income. But that is already being monetized in ordinary course? They expect some level of gains. Not dormant. They have "excess capital" and "share repurchase authorization" - they are buying shares. That is not a second business. They have "investment portfolio" and "acquired loan pay downs" funding loan growth.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need to determine if management in the transcript explicitly generalizes a recent real success as a repeatable template and identifies specific next places where that template is being applied. The transcript covers Q1 2016 earnings call. Management discusses various topics: credit quality, energy portfolio, loan growth, expenses, etc. They mention "lift out" opportunities as a way to grow. Tim Laney says: "We’ve done a number of lift outs. It’s really how we seeded our core asset based lending operations; it’s how we really developed our government and not-for-profit business; I could go on and on. But in the absence of having the currency to make acquisitions, except in very unique situations, we’ve viewed the focus on lift outs as a key to growing the business." And later: "we’re pretty excited with some work we have in the queue right now that could be very meaningful." But is this a specific recent success that is treated as a template? They mention past lift outs that seeded businesses, but they don't point to a specific recent win that just happened and then say "this is a template we can repeat." They talk about a history of lift outs, but not a specific first instance that just occurred. Also, they don't identify specific next places where the template is being applied right now; they just say "some work we have in the queue" which is vague. Another possible angle: loan growth. They mention originations and pipelines, but that's routine. The question asks: "does management take a RECENT, REAL SUCCESS the company has actually achieved — a won customer, a completed project or deployment, a successful product introduction, a first site, market, program, or partnership that is now demonstrably working and producing real business — and explicitly GENERALIZE it, telling investors in substance: 'what we just did here is not a one-off — it is a template we can repeat,' AND does management identify the SPECIFIC NEXT PLACES where that same template is already being applied right now?" In the transcript, there is no such specific recent success that is generalized. The lift out discussion is about past successes, not a recent one. They don't name a specific recent lift out that just happened and then say "we can repeat this." They also don't identify specific next places; they just say "some work in the queue" which is not specific. Thus, the answer is NO.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need to answer YES or NO based on the transcript. The question asks: On this call, when management explains why the company is CURRENTLY winning business, does it credit a STANDING THE COMPANY ALREADY HOLDS — something durable it built, secured, or became BEFORE this period — as the operative cause of wins that are actually happening now, AND does it convey that further business is already arriving over that same standing without a proportional new push? We need to find in the transcript where management explains current wins. They talk about loan growth, originations, pipelines, lift outs, etc. They mention that they have built teams, have a strong franchise, etc. But do they attribute current wins to a standing they already hold? For example, they mention "our relationship banking model" and "taking market share" but that's more about effort. They also mention "lift out opportunities" as a way to grow, but that's about attracting teams, not a standing. They talk about "our core markets do both continue to outperform" which is external conditions. They mention "we have been active in pursuing a number of opportunities to further leverage our excess capital through M&A and the lift out of teams" but that's not a standing. The question specifically asks: "when management explains why the company is CURRENTLY winning business" — do they credit a standing? In the transcript, they discuss loan growth, originations, and pipelines. They say "our teams have built nice new business pipelines that give us confidence in our ability to deliver on our originations goal" — that's about pipeline, not a standing. They also say "we're going to continue to build our organically grown balance sheet" — that's future. They mention "we have a number of, we think, very interesting lift out opportunities" — that's about future opportunities, not current wins from a standing. They also talk about "our special assets teams work through roughly $2.5 billion of acquired very troubled loans" — that's a capability, but it's about resolving past loans, not current wins. The question is about current wins being attributed to a standing. For example, if they said "our existing customer relationships are driving new business" or "our branch network is attracting deposits" etc. But I don't see that. They talk about "relationship banking model" but that's a model, not a specific standing.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need answer YES/NO. Need determine if management describes being entrusted with materially larger/more central class of work than historically received, step-up visible in actual business won/performed today. Need use only transcript. Let's parse transcript. Company National Bank Holdings. Q1 2016 earnings call. Management discusses progress, energy exposure, loan growth, deposits, expenses, M&A, lift outs. Need see if they convey step-up in scale/consequence of engagements/projects/orders/mandates/roles won/performed relative to historical norm, already visible in actual business. Key phrases: "building an attractive community bank franchise", "grow core earnings", "goal 1% ROA and $2 EPS". Loan growth: total originated loan outstandings grew 7.9% annualized; adjusting energy pay downs 11.8%. New fundings $184M, 10% below last year. Pipelines give confidence to exceed $1B originations and full year loan growth 15-20%. Deposits growth. Noninterest income. Expenses. Capital. M&A and lift outs. "we have been active in pursuing a number of opportunities to further leverage our excess capital through M&A and the lift out of teams, but do not have a transaction to share at this point." "we're very excited about revealing some strategic initiatives that will accelerate us on that path." "lift out opportunities" "additional muscle" "building, taking market share in attractive markets." "we've done a number of lift outs. It's really how we seeded our core asset based lending operations; it's how we really developed our government and not-for-profit business; ... in the absence of having the currency to make acquisitions, except in very unique situations, we've viewed the focus on lift outs as a key to growing the business." "we're pretty excited with some work we have in the queue right now that could be very meaningful." Question asks: Does management describe that company is NOW BEING ENTRUSTED WITH MATERIALLY LARGER OR MORE CENTRAL CLASS OF WORK THAN HISTORICALLY RECEIVED? Need identify if any statement about customers entrusting larger projects, broader scope, core roles, larger tier. The transcript doesn't seem to contain such. It talks about loan growth, pipelines, lift outs, M&A opportunities, but not about customers giving larger/more central work. It mentions "lift out of teams" as hiring teams, not customer engagements. "strategic initiatives" future.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need answer YES/NO. Need analyze transcript. Need determine if management conveys period strengthened as progressed and attributes to company drivers still in force. Let's parse. Question: "On this call, does management convey that the just-reported period STRENGTHENED AS IT PROGRESSED — that business conditions, activity, or execution were meaningfully better in the later part of the period (or in the weeks right after it) than in the earlier part — AND does management attribute that building strength mainly to drivers attached to the company itself that are described as still in force now?" Need use only transcript. Look for statements about first quarter 2016. There is mention loan growth, pipelines, originations. Tim Laney: "we did have a fair amount of business slide from first quarter to second quarter. I think we'll learn a lot about ourselves here in the second quarter." Also "I think you'll see a big make up here in the second quarter" regarding C&I originations. "We saw a fair amount of business slide into the second quarter and we're benefiting from that in the early stages of this quarter." This suggests activity in later part? But is that "period ended stronger than it began"? They say first quarter originations were lower, but pipelines built, business slid into Q2. That is not necessarily intra-period improvement; it's deferral to next quarter. Also "new fundings were $184 million... 10% below last year. However, our teams have built nice new business pipelines that give us confidence..." That's forward-looking, not observed late-period strength. Need see if management describes Q1 as improving through course. They mention "first quarter's new fundings... 10% below last year" but "pipelines" for future. No explicit month-over-month pickup. They say "we did have a fair amount of business slide from first quarter to second quarter" - that means deals delayed, not necessarily later part of Q1 stronger. Also "I think you'll see a big make up here in the second quarter" - forecast, not observed. The question requires "already observed in real activity" during or just after period. "benefiting from that in the early stages of this quarter" - early weeks after period continuing? But is that late-period strength? They say business slid into Q2, so Q1 ended weaker, not stronger. Hmm. Need also consider other aspects: loan growth, deposits, credit.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need to determine if management describes a situation where the company has already spent or committed resources for a stage of business not yet paid back, with the return still outstanding and treated as a matter of time. The key is one coherent situation with all three elements. Let's review the transcript. The call discusses energy exposure, credit quality, loan growth, expenses, etc. Management talks about building a franchise, growing loans, and strategic initiatives. They mention "lift out" opportunities, but those are not yet done. They talk about expense management and infrastructure. They mention that they have built teams and capabilities. But is there a specific outlay already made with return outstanding? They mention that they have been building organically, and they have excess capital. They talk about buying back shares. They mention that they have invested in infrastructure. But the question is about a specific stage of business where the cost is already incurred but the revenue hasn't arrived. One possible candidate: They talk about loan growth and originations. They say that they have built pipelines and expect to deliver on originations goal. But that's not a sunk cost. Another: They mention that they have been building a community bank franchise and have made investments. But it's not specific. They also mention that they have taken a large provision for energy loans, which is a cost, but that's a loss provision, not an investment for future growth. They talk about expense management and that they are working with an outside group to identify efficiencies. That's not a sunk cost. They mention that they have been active in pursuing M&A and lift outs, but no transaction yet. They also mention that they have excess capital and are buying back shares. That's a return of capital, not an investment. The key phrase: "we have been active in pursuing a number of opportunities to further leverage our excess capital through M&A and the lift out of teams, but do not have a transaction to share at this point." So that's not done. They also talk about "strategic initiatives" that will accelerate them to $2 EPS, but they don't specify what has been spent. Perhaps the most relevant is the discussion about building the loan portfolio and the infrastructure. But it's not clear that they have already spent money for a future return that hasn't arrived.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need to determine if the transcript conveys a situation where the cost of attempting something new has dramatically fallen, the company is taking multiple such swings now, and at least one has produced real results. Let's analyze the transcript. The main topics are: energy loan provisions, credit quality, loan growth, expenses, and strategic initiatives. The management discusses "lift out" opportunities, M&A, and share buybacks. They mention building pipelines, growing loans, and expense management. Key phrases: "we have been active in pursuing a number of opportunities to further leverage our excess capital through M&A and the lift out of teams" - but no transaction to share. They talk about "strategic initiatives" that will accelerate growth. They mention "lift out" as a way to grow without capital allocation. However, they don't explicitly contrast the cost of attempting something new now versus in the past. They don't say "it used to take X, now it takes Y". They mention that they have done lift outs before, but not that the cost has dramatically fallen. They talk about expense management and being more efficient, but that's about cost of operations, not cost of attempting new things. The question asks: "does management convey that IT HAS BECOME DRAMATICALLY CHEAPER, FASTER, OR EASIER FOR THE COMPANY TO ATTEMPT A NEW THING THAN IT USED TO BE" - I don't see that. They talk about building pipelines, but not about a step-change in cost of trying. They mention "we have been active in pursuing a number of opportunities" but that's not about cost. They also mention "we are prepared and looking at getting more efficient on the expense side" but that's about existing operations. Also, they mention "we have a number of, we think, very interesting lift out opportunities" but no results yet. They say "we're pretty excited with some work we have in the queue right now that could be very meaningful" - but that's future, not already producing results. The only real results mentioned are loan growth, but that's not a new attempt. The energy provisions are a negative. Thus, the answer is NO. The transcript does not convey a dramatic drop in the cost of attempting something new, nor multiple new attempts already in flight with at least one producing results. The management talks about strategic initiatives but not in the context of cheaper attempts. So answer NO.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need answer only YES/NO. Need analyze transcript. Need determine if management explains business about to be meaningfully larger via already-taken actions of external parties, at least two separate external parties, and reported numbers lag. Let's parse. Question asks: "On this call, when management explains why the company's business is about to be meaningfully larger, is that explanation carried primarily by the ALREADY-TAKEN ACTIONS OF EXTERNAL PARTIES — and are there AT LEAST TWO SEPARATE such external parties or party groups whose actions management describes as already underway, with the resulting business only beginning to appear in the reported results?" Need answer YES if all three. Need use only transcript. Let's examine management statements. They discuss loan growth, pipelines, lift outs, M&A, share buybacks. Key: "we have been active in pursuing a number of opportunities to further leverage our excess capital through M&A and the lift out of teams, but do not have a transaction to share at this point." That's prospective, not external already done. "we have built nice new business pipelines that give us confidence in our ability to deliver on our originations goal to exceed $1 billion this year and to support a full year total loan growth of 15% to 20%." Pipelines are internal, not external already taken. "We saw a fair amount of business slide from first quarter to second quarter." That's internal timing, not external actions. "we're pretty excited with some work we have in the queue right now that could be very meaningful." That's prospective. What about external parties? They mention "lift out opportunities" - attracting teams, but not external parties' actions already taken? "It's really how we seeded our core asset based lending operations; it's how we really developed our government and not-for-profit business" - historical, not current. No specific external parties. They mention "premium merger prices that have been announced in our marketplace" - external M&A transactions by other banks, but that's not actions that make NBHC's business larger. It's valuation context. They mention "we have been active in pursuing a number of opportunities" but no transaction. So no. They mention "our teams have built nice new business pipelines" - internal. They mention "we expect to continue to fund the loan growth with cash flow..." - internal.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need answer YES/NO. Need analyze transcript. Need determine if management points to something already finished built/acquired/put in place but not yet earning/running/just switched on. Need use only transcript. Let's parse. Company National Bank Holdings. Q1 2016. Discussion about energy exposure, credit quality, loan growth, expenses, buybacks, M&A, lift outs. Need identify any completed asset not yet contributing. Potential candidates: - "lift out" teams? They have been active pursuing opportunities, no transaction to share. Not completed. - "strategic initiatives" to reveal, not yet. - "we have $115 million excess capital" not asset. - "we have $27.5 million remaining from prior share repurchase authorization" not. - "we have been active in pursuing a number of opportunities to further leverage excess capital through M&A and lift out of teams, but do not have a transaction to share at this point." Not completed. - "we have no second lien or subordinated loans" no. - "we have specifically reserved $11.2 million" no. - "we have built nice new business pipelines" not completed asset. - "we have conducted intensive stress testing" no. - "we have developed pretty strong capability in being able to attract teams" no. - "we have a number of, we think, very interesting lift out opportunities" not completed. - "we have a fair amount of business slide from first quarter to second quarter" pipeline, not completed. - "we have no incremental funding needs" no. - "we have been active in pursuing..." no. Question asks "does management point to something the company has ALREADY FINISHED BUILDING, ACQUIRING, OR PUTTING IN PLACE — but which is NOT YET EARNING..." Need answer YES only if concrete completed thing waiting. Transcript has no such thing. It's a bank; no mention of branch built, system implemented, acquisition closed. They mention "we have $115 million in excess capital" but not earning? Capital is deployed? Not a completed piece. "We have $27.5 million remaining from prior share repurchase authorization" but not yet used? That's authorization, not asset. "We have been active in pursuing M&A and lift outs, but do not have a transaction to share." Not completed. "We have built nice new business pipelines" not concrete. "We have developed pretty strong capability" not. Need answer NO. Ensure no hidden: "we have no second lien or subordinated loans" no.
Original model output from the research archive. It may be verbose or include the model's working notes.
The question asks whether management devotes a clearly disproportionate share of its energy, enthusiasm, and detail to one identifiable part of the business that is still a minority of the company's overall results today, and whether that favored part is described as already producing real, current business. Let me analyze the transcript. The call covers: 1. Energy loan portfolio issues (credit quality, non-accruals, reserves) 2. Overall loan growth and guidance 3. Expense management 4. Capital and buybacks 5. M&A and lift-out opportunities The energy portfolio is $132 million, 5.1% of total loans, 3.1% of earning assets, 25% of risk-based capital. This is a minority of the business. Rick Newfield spends a lot of time on it - three key points, detailed discussion of the four non-accrual loans, stress testing, reserves, etc. But is the energy portfolio described as "already producing real, current business" that is the main driver going forward? No - the energy portfolio is a problem area, not a growth driver. Management is managing it down, taking reserves, expecting charge-offs. It's not presented as the company's trajectory. What about the "lift out" opportunities? Tim Laney mentions "strategic initiatives" and "lift out opportunities" but these are described as opportunities in the queue, not current producing business. He says "we have a number of, we think, very interesting lift out opportunities" - this is aspirational, not current. What about the core loan growth? Brian Lilly talks about 15-20% loan growth, originations goals, pipelines. But this is spread across the business, not one identifiable piece. The energy discussion is detailed but it's about managing a problem, not about a favored growth area. The question asks about a piece that is "plainly smaller today than the company's established base, yet it receives the richest discussion... management returns to it repeatedly, volunteers specifics... and frames the company's future primarily around it." And it must be "described as genuinely working NOW - real paying activity." The energy portfolio is not described as working - it's stressed, deteriorating, with charge-offs expected. The lift-outs are not yet producing. The core loan growth is the main business. So the answer is NO. The energy discussion is about risk management, not a favored growth driver. The lift-outs are aspirational.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need answer YES/NO. Need analyze transcript. Need determine if management repeatedly grounds case in fresh early operating facts. Let's parse. Question asks: On this call, does management repeatedly ground its case for company's future in OPERATING FACTS THAT ARE BOTH FRESH AND EARLY — concrete business developments that began/occurred/visible only within last quarter or two, already real today, and explicitly described as only beginning, most effect still ahead. Need answer YES if management's own words convey one coherent evidentiary posture: strongest support consists of recently-arrived, already-real developments whose weight has not yet landed in published numbers. Need NO if forward case rests mainly on market conditions, pipeline, opportunity, general optimism, plans, etc. Let's examine transcript. Tim Laney opening: "We continued to make progress during the quarter in building an attractive community bank franchise, and we remain confident in our ability to grow core earnings and realize our goal..." Then energy actions. No specific fresh facts. Rick Newfield credit: non-energy portfolio strong, energy stressed. No forward case based on fresh developments. Brian Lilly: "We covered a lot... focus on update to outlook." He says "inherent within our guidance, our economic assumptions consistent with current outlook of leading economists where our markets continue to perform better than national averages and we look for 2016 to continue to provide good growth opportunities. Please note that we have not included any interest rate increases in our guidance. Given our asset sensitive position, we would benefit nicely from increasing interest rates, but we decided to be more conservative." This is market/economic assumptions, not fresh facts. Loan growth: "Total loans ended quarter at $2.6 billion and grew slightly from year end as new fundings were offset by higher levels of payments and pay downs. Within total loans, the total originated loan outstandings of $2.2 billion grew $42.7 million or 7.9% annualized. Adjusting for elevated energy credits, line of credit pay downs of $20.9 million, the growth of originated loan outstandings was stronger at $63.9 million for the quarter or 11.8% annualized. The first quarter’s new fundings were $184 million, excluding the $20.9 million related to the energy clients pay downs, and was 10% below last year.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need to answer YES or NO based on the transcript. The question asks: does management describe that money or binding financial commitment is arriving at the company ahead of the work it will pay for, and does management treat this advance funding as something that is currently growing and that finances or de-risks the company's next stage of growth? We need to look for any mention of deposits, prepayments, advance payments, etc. The transcript is about a bank. Banks take deposits. But the question is about "money or binding financial commitment arriving ahead of the work it will pay for" - that is, customers paying in advance. For a bank, deposits are a form of funding, but they are not necessarily "ahead of work" - they are the raw material. The question is about the company's own counterparties financing its next stage. For a bank, deposits are liabilities, but they are not "paying for work" - they are just deposits. The question specifically says "the parties on the other side of the company's business are putting cash down, paying earlier, or locking themselves into pay-regardless obligations BEFORE they receive what they are buying". For a bank, what is it buying? The bank's products are loans and services. Deposits are not payments for services; they are the bank's funding. So this doesn't fit. Look for any mention of advance payments, prepayments, etc. In the transcript, they talk about deposits, but that's normal banking. They talk about loan growth, but that's the bank lending money, not receiving money ahead of work. They talk about fee income, but that's normal. The question is about a specific phenomenon: customers paying in advance for something they will receive later. In the transcript, there is no such mention. They talk about "transaction deposits" and "time deposits" but that's just deposit composition. They don't say that customers are paying in advance for services. They talk about "treasury management fees" and "interchange fees" but that's normal. Also, the question says "management treats this advance funding as something that is currently growing and that finances or de-risks the company's next stage of growth." In the transcript, they talk about deposits growing, but they don't connect that to financing growth in the sense of paying for work ahead. They talk about using deposits to fund loans, but that's standard banking.
Original model output from the research archive. It may be verbose or include the model's working notes.
The question asks whether management speaks from a secure, settled core business while also describing more than one distinct avenue of additional growth beyond that core, each already real and producing early results. Let me analyze the transcript: 1. Core business: The non-energy loan portfolio ($2.4 billion) is described as having excellent credit quality, with positive trends, low charge-offs, and improving classified loans. Management is not defending or fixing the core - it's performing well. The energy portfolio is only 5.1% of loans, and management treats it as a manageable issue, not a core problem. The core banking business (loans, deposits, fee income) is presented as solid. 2. Additional growth avenues: - Loan growth: 15-20% full-year guidance, with pipelines building, new fundings of $184 million in Q1, and originations goal to exceed $1 billion. This is core loan growth though - is it a distinct avenue or just continuation of core? It's more of the same business. - Lift-outs: Tim Laney discusses "lift out opportunities" - attracting teams to build new business lines. He says "we have a number of, we think, very interesting lift out opportunities" and mentions this is how they seeded asset-based lending, government and not-for-profit business. This is described as already in motion - they've done this before and have work in the queue. This seems like a distinct avenue - adding new capabilities/teams. - M&A: Brian Lilly mentions being "active in pursuing a number of opportunities to further leverage our excess capital through M&A and the lift out of teams" - but no transaction to share. This is aspirational, not yet producing results. - Share buybacks: They have $27.5 million remaining and see buying shares as an excellent investment. This is capital deployment, not really a growth avenue in the business sense. So the question is: are there TWO distinct avenues already producing results? The lift-outs are described as already in motion - they've seeded businesses this way before and have current opportunities. But is this "already producing results"? Tim says "we're pretty excited with some work we have in the queue right now that could be very meaningful" - this sounds more like pipeline/aspirational than already producing. The loan growth is really just the core business growing - more of the same customers buying the same products.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need answer YES/NO based on transcript. Need determine if management reveals company's own working assumptions overtaken by actual business, and already changed something concrete, still catching up. Let's parse transcript. It's a bank earnings call. Key topics: energy loan portfolio deterioration, credit quality, expenses, loan growth, etc. Need find if real activity outran company's own assumptions and management already acted. Possible candidates: Energy portfolio deterioration? They had identified four loans earlier, now moved to nonaccrual. But that's negative surprise, not positive overshoot. The question asks "REALITY HAS OUTRUN THE COMPANY'S OWN ASSUMPTIONS" in sense of demand/activity beyond plan. Here energy stress worse than expected? They said "industry sentiment and market for oil and gas assets worsened" and "A few of our clients realized setbacks" - that's negative, not positive. Also they took provisions. But question specifically about "business" overshoot, not negative. It says answer NO if surprise is negative, or adjustments are defensive. So energy is negative, defensive. Not it. What about loan growth? They guided 15-20% total loan growth. First quarter total loans grew slightly, originated loan outstandings grew 7.9% annualized, adjusted 11.8%. They say pipelines give confidence. No indication actual outran assumptions. They had new fundings $184M, 10% below last year. So no. What about expenses? They said first quarter expenses came in better than guidance, lower expense level driven by better seasonality and timing. That's positive but not operating activity outrunning assumptions. No action. What about "strategic initiatives" and "lift out opportunities"? They mention "we have been active in pursuing a number of opportunities to further leverage our excess capital through M&A and the lift out of teams, but do not have a transaction to share at this point." That's not an overshoot. What about "we are forecasting earning assets to increase in low single digits" etc. No. What about "we have not included any interest rate increases in our guidance" - conservative. What about "we see buying our shares as excellent investment" - buyback. Not. What about "we are reiterating full-year guidance" etc. Need look for management saying actual business came in beyond what company planned, and they already changed something concrete.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need to determine if the transcript describes a situation where customers or counterparties have already paid or irrevocably committed money for things the company has not yet delivered, and this obligation is large relative to the company's current business, with the work of discharging it being central. The transcript is about a bank. The company is National Bank Holdings Corporation. They discuss loans, deposits, energy portfolio, etc. Key points: They talk about loan growth, deposits, etc. But the question is about customers paying ahead of delivery. In banking, deposits are liabilities, but they are not "unearned revenue" in the typical sense. The company takes deposits and pays interest, but that's not a prepayment for goods/services. The question is about customers paying for something the company still owes. In banking, that might be something like loan commitments? But they talk about loan originations, pipelines, etc. They mention "line of credit pay downs" and "new fundings". They talk about "originated loan outstandings" growing. But that's not customers paying ahead. They also mention "transaction deposits" and "time deposits". But deposits are not unearned revenue; they are borrowed funds. The company owes the depositors their money back, but that's not a prepayment for services. The question specifically asks: "management describe that CUSTOMERS OR COUNTERPARTIES HAVE ALREADY PUT MONEY OR IRREVERSIBLE COMMITMENT INTO THE COMPANY FOR THINGS THE COMPANY HAS NOT YET DELIVERED" - In banking, that could be something like loan commitments where the bank has committed to lend but not yet disbursed? But that's the bank owing money, not the customer. Or maybe it's about the bank's own obligations? No. The transcript discusses energy loans, provisions, etc. There is no mention of customers prepaying for services. The company is a bank, so its revenue is interest and fees. There is no mention of deferred revenue or unearned revenue. The only thing that might resemble is "deposits" but those are not unearned revenue; they are liabilities that the bank pays interest on. The bank doesn't "deliver" anything to depositors except interest and safekeeping. That's not a prepayment for goods/services. The question is about a company that has received money ahead of delivering something. In banking, that could be like a mortgage servicing right? No.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need answer YES or NO based on transcript. Need evaluate criteria. Company National Bank Holdings. Is it still unprofitable or only marginally profitable? Actually they report adjusted metrics: without large energy provision, delivered first quarter return on tangible assets 68 bps and $0.23 EPS. They have net income? They had provision for loan losses large, but overall? Need see. They mention "pre-credit" return on tangible assets 1.18%. They are profitable? They had EPS $0.23 adjusted excluding energy provision. But actual reported? They took large provision, maybe still profitable? Need determine if "STILL UNPROFITABLE OR ONLY MARGINALLY PROFITABLE" but gap closing. They are a bank with earnings. They have goals 1% ROA and $2 EPS. They are not yet at that but profitable. The question asks "still unprofitable or only marginally profitable" with losses/burn/shortfall shrinking. This company is profitable, albeit below targets. They had adjusted EPS $0.23, ROA 68 bps. They are not unprofitable. They are solidly? They have positive earnings. So answer NO? Need be careful: "only marginally profitable" could apply? They are profitable but below goals. But criteria: "THE COMPANY IS NOT YET COMFORTABLY PROFITABLE, AND THE GAP IS CLOSING NOW." They are not comfortably profitable? They have 68 bps ROA, target 1%+. They are profitable but not comfortably? The question asks "STILL UNPROFITABLE OR ONLY MARGINALLY PROFITABLE" - they are only marginally profitable? They have positive EPS. But improvement driven by growth? They discuss loan growth, revenue. But management treats reaching profitability? They already are profitable. They talk about "grow core earnings and realize goal of 1%+ ROA and $2+ EPS." They are on journey. But not "unprofitable" or "losses". So likely NO because company is already solidly profitable? Need assess. The prompt: "Answer YES when management's own words convey... (1) THE COMPANY IS NOT YET COMFORTABLY PROFITABLE, AND THE GAP IS CLOSING NOW. Management discusses losses, negative margins, cash burn, or borderline results as a current reality — but points to concrete, already-reported improvement..." Here management does not discuss losses or negative margins. They discuss adjusted metrics excluding energy provision. They had a large provision due to energy, but still? Let's see actual net income? They don't state net income.
Original model output from the research archive. It may be verbose or include the model's working notes.
We need answer only YES or NO. Need evaluate based on transcript. Need determine if management conveys both halves: (1) per-unit economics already stepped up due to company actions, observed in recent period; (2) volume arriving but early, with evidence. Let's parse transcript. Company National Bank Holdings. Q1 2016. They took energy provision. Adjusted metrics: return on tangible assets before provision and taxes 1.18% vs 1.0% last year. Without energy provision, ROTA 68 bps and EPS $0.23, compare favorably. They talk about expense reduction: non-interest expenses $34.9 million vs guidance $36 million, lower expense level driven by better seasonality and timing. They reiterate full-year low $140 million range, with expected increase in Q2. They mention "significant reduction in run rate expense levels" forecasted. They are working on expense efficiency. But is that "structurally better profit-making setup" already achieved? They say first quarter more than delivered on forecasted significant reduction in run rate expense levels. But also they expect Q2 increase. They mention "we have not included any interest rate increases." They talk about loan growth: total loans grew slightly, originated loan outstandings grew 7.9% annualized, adjusting for energy paydowns 11.8% annualized. New fundings $184M, 10% below last year. Pipelines give confidence to exceed $1B originations and full year loan growth 15-20%. So volume story: pipelines, but also actual growth in originated loans. They say "first quarter's new fundings were $184 million... 10% below last year. However, our teams have built nice new business pipelines that give us confidence..." So volume is mostly ahead? They expect growth. But is there "real current evidence that it is coming"? They mention pipelines, and some business slide from Q1 to Q2. They say "We saw a fair amount of business slide into the second quarter and we're benefiting from that in the early stages of this quarter." That is evidence. But is the per-unit economics already stepped up? Need see if management describes company now keeping more from each unit due to changes already made. They mention adjusted metrics excluding energy provision. But that's not structural improvement; it's excluding a one-time provision. They mention pre-provision ROTA 1.18% vs 1.0% last year. That could indicate improved core profitability.
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| Call | Date | Grade | Guidance | Demand | Margins | Candor | Evasion |
|---|---|---|---|---|---|---|---|
| Q1 2024 | 2024-04-25 | B | maintained | mixed | stable | 7/9 | 2/9 |
| Q4 2023 | 2024-01-24 | B | maintained | stable | stable | 7/9 | 2/9 |
| Q3 2023 | 2023-10-25 | A | maintained | stable | contracting | 7/9 | 2/9 |
| Q2 2023 | 2023-07-20 | C+ | maintained | stable | contracting | 7/9 | 3/9 |
| Q1 2023 | 2023-04-20 | B | maintained | stable | contracting | 8/9 | 3/9 |
| Q4 2022 | 2023-01-25 | B+ | maintained | stable | contracting | 8/9 | 2/9 |
| Q3 2022 | 2022-10-28 | A | maintained | accelerating | expanding | 7/9 | 2/9 |
| Q2 2022 | 2022-07-20 | B | maintained | stable | expanding | 7/9 | 2/9 |
| Q1 2022 | 2022-04-19 | C+ | lowered | accelerating | expanding | 7/9 | 2/9 |
| Q4 2021 | 2022-01-21 | A | maintained | accelerating | expanding | 7/9 | 2/9 |
| Q3 2021 | 2021-10-20 | B+ | raised | accelerating | expanding | 7/9 | 2/9 |
| Q2 2021 | 2021-07-27 | B | maintained | accelerating | stable | 7/9 | 2/9 |
| Q1 2021 | 2021-04-23 | A | raised | accelerating | contracting | 7/9 | 2/9 |
| Q4 2020 | 2021-01-22 | A | maintained | accelerating | stable | 7/9 | 2/9 |
| Q3 2020 | 2020-10-21 | A | maintained | mixed | contracting | 8/9 | 2/9 |
| Q2 2020 | 2020-07-22 | B+ | maintained | mixed | contracting | 8/9 | 2/9 |
| Q1 2020 | 2020-04-22 | C | withdrawn | mixed | contracting | 8/9 | 2/9 |
| Q4 2019 | 2020-01-24 | B | maintained | stable | contracting | 7/9 | 2/9 |
| Q3 2019 | 2019-10-23 | B+ | maintained | stable | contracting | 8/9 | 2/9 |
| Q2 2019 | 2019-07-24 | A | raised | accelerating | stable | 8/9 | 2/9 |
| Q1 2019 | 2019-04-24 | A | maintained | accelerating | expanding | 7/9 | 2/9 |
| Q4 2018 | 2019-01-25 | A | maintained | accelerating | expanding | 7/9 | 1/9 |
| Q3 2018 | 2018-10-24 | C+ | maintained | stable | expanding | 7/9 | 3/9 |
| Q2 2018 | 2018-07-25 | B+ | lowered | accelerating | expanding | 8/9 | 1/9 |
| Q1 2018 | 2018-04-28 | A | maintained | accelerating | expanding | 8/9 | 1/9 |
| Q4 2017 | 2018-01-26 | A | raised | accelerating | expanding | 8/9 | 1/9 |
| Q3 2017 | 2017-10-19 | C+ | lowered | stable | stable | 8/9 | 2/9 |
| Q2 2017 | 2017-07-21 | B+ | maintained | accelerating | expanding | 8/9 | 2/9 |
| Q1 2017 | 2017-04-21 | A | maintained | accelerating | expanding | 8/9 | 1/9 |
| Q4 2016 | 2017-01-27 | A | maintained | accelerating | expanding | 8/9 | 2/9 |
| Q3 2016 | 2016-10-21 | A | raised | accelerating | stable | 8/9 | 1/9 |
| Q2 2016 | 2016-07-22 | B | lowered | accelerating | contracting | 8/9 | 2/9 |
| Q1 2016 | 2016-04-22 | C+ | maintained | stable | stable | 7/9 | 3/9 |
| Q4 2015 | 2016-01-29 | B | maintained | stable | contracting | 8/9 | 2/9 |