Critical Data Element Completeness Scorer
Description
Score critical fields needed for sample testing, such as document number, TAS, SLOA, vendor, trading partner, contract, invoice, acceptance, asset ID, date, amount, and approver.
AI / analytics pattern
rules + ML + GenAI/RAG as appropriate with human review
Automation level / stage
assistive / analyst-in-the-loop / auditor-ready evidence support
Expected benefit
Improves audit data readiness, evidence quality, and line-item execution throughput.
Audit / financial statement impact
Supports revised audit approach with material line-item proof, evidence packages, and controlled AI output.
Controls / human review
Human review required for AI recommendations; cite source records/documents; retain prompt/output logs, model/version metadata, reviewer approval, and exception rationale; monitor accuracy and bias/adverse impact where applicable.
Data needed
Advana-FM governed data products, source system extracts, transaction populations, GL/subledger detail, supporting documents, reviewer actions, data-quality rules, lineage metadata
Possible metrics
coverage %, completeness %, source-to-statement traceability %, sample package cycle time, first-pass acceptance %, exception aging, reviewer override rate, evidence gap closure rate
MVP scope
Build read-only MVP for one DWCF reporting entity / one line-item action team; validate data completeness, source links, exception queues, and human-review controls before production workflow integration.
Related material weakness / control objective
Material line-item support; source-to-statement traceability; data completeness; evidence reliability; large-sample testing support.