Smart Audit Analytics

Traditional sampling-based audit methods examine a fraction of client transactions and rely heavily on manual workpaper preparation. The PCAOB has compressed documentation completion timelines and introduced new amendments to AS 1105 and AS 2301 that specifically address technology-assisted analysis in audit procedures. The profession-wide talent shortage means fewer people are available to do the same volume of work. Meanwhile, competitors like RSM have deployed Ai audit ecosystems and Grant Thornton shipped CompliAI — both analyzing full transaction populations to identify risk areas that sampling alone can miss.

This capability gives audit teams an Ai-powered analytics engine that analyzes 100% of a client's transactions — not just a sample. It identifies statistical anomalies, flags unusual patterns across revenue, expenses, journal entries, and related-party transactions, and risk-scores every finding for auditor review. It auto-generates workpaper documentation tied to specific assertions and evidence, dramatically reducing documentation time. Auditors spend their time on professional judgment and client communication instead of data manipulation. Audit quality improves because nothing falls through the sampling gap. Documentation is tighter, faster, and more defensible.