Answers
Sampling reviews a fraction of entries while thousands go unexamined. High-risk entries—duplicates, backdated postings, round-number anomalies—often hide in the unreviewed majority.
Duplicates, backdated postings, round-number anomalies, reversed journals, unexpected account pairings, and suspicious narration patterns—each with a reason code and risk score.
Yes. Full-population screening with risk-based prioritization and documented reviewer actions produces stronger audit trails than arbitrary sampling—and aligns with SOX expectations for journal entry testing.
The engine ranks every entry by risk. Reviewers focus on the top 1%—investigating flagged items first while maintaining 100% coverage documentation.
Load one period's journal entries, run full-population screening with conservative thresholds, and compare AI-flagged items against your current sample results before expanding.
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