Answers
Summaries recap data for readability. Risk signals are calibrated, ranked leads tied to materiality and assertions that drive scope changes, sample sizing, and test design.
AI drafts reason codes and next steps; auditors accept, edit, or reject. Every decision links to evidence, model version, and the assertion at stake.
Review time per 1k rows, first-pass closure rate, rework rate, and trail completeness—decisions linked to evidence and reviewer conclusions.
Regulators and EQCR reviewers need to understand what the system did, why a score was assigned, and which assertion the step supports—not just that AI was used.
Pilot on one population: fuse GL narration with invoice text, calibrate thresholds to materiality, and document the full trail for one manager review cycle before expanding.
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