/CE Catalog|
Auditing Enterprise AI Pipelines: Hallucination Controls, SR 11-7 & SOC 2 Trust Criteria
Auditing Enterprise AI Pipelines: Hallucination Controls, SR 11-7 & SOC 2 Trust Criteria
Walks through an end-to-end audit of a publicly traded SaaS company that deployed a Retrieval-Augmented Generation (RAG) agent to automate ASC 606 contract review and AP invoice coding—uncovering a $4.8M Q4 revenue cutoff misstatement caused by PDF OCR truncation and missing deterministic reconciliation controls.
Architecture of Financial RAG Pipelines & NIST AI RMF Risk Mapping
The Q4 close at 'FinTech Innovations Inc.' (FTI), a publicly traded SaaS provider, was supposed to be seamless. Their newly deployed Retrieval-Augmented Generation (RAG) agent, designed to automate ASC 606 contract review and AP invoice coding, promised unprecedented efficiency. Instead, a preliminary review of workpaper 'WP-Q4-REV-001' revealed a glaring $4.8 million revenue cutoff misstatement. The RAG agent, intended to extract key revenue recognition terms from customer contracts, had consistently failed to process multi-page PDF agreements fully, truncating critical clauses due to an unverified Optical Character Recognition (OCR) output. This led to premature revenue recognition for several large contracts, pushing revenue into Q4 that belonged in Q1 of the following year. The audit team's initial findings suggest a complete absence of deterministic reconciliation controls between the RAG agent's output and the source documents, creating a black box where material financial reporting decisions were made without human oversight or validation. The stakes are high: a material misstatement for a public company, potential restatement, and significant reputational damage.