AI-Powered Compliance Auditing System Reduces Human Review by 99%
A regulatory compliance provider partnered with FullStack to automate expert network call auditing with AI. The proof of concept reduced human review time while maintaining accuracy.
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99%
reduction in manual review
>90%
projected annual savings
93%
accuracy
Opportunity
Expert network calls are conversations between industry professionals and investors in a highly confidential, regulated environment. These calls contain sensitive financial discussions and require careful monitoring to ensure compliance with SEC and other regulations.
The client, a leading compliance partner, provides these expert network call monitoring services.
The client’s existing process was entirely manual, requiring highly trained staff to listen to calls in real time or review transcripts—a costly, unscalable, and labor-intensive approach. They sought an AI-driven solution to improve efficiency, expand service availability, and reduce operational costs while maintaining accuracy.
Solution
FullStack Labs developed an AI-powered auditing system as a Proof of Concept (PoC) in 14 weeks, using a lean, five-person team. The goal was to test whether AI could automate expert network call monitoring with the same accuracy as human auditors while significantly reducing manual review time.
The result was a groundbreaking AI auditing platform that improves efficiency while maintaining data security.
The client's custom AI solution transcribes calls with Whisper and anonymizes sensitive data using SpaCy and Flair. AI models analyze transcripts for regulatory risks: GPT-4 Turbo flags unauthorized communication, GPT-4o detects nuanced risks like material nonpublic information disclosure, and RoBERTa classifies and scores potential violations.
A keyword matching system highlights key phrases, while a risk-ranking engine aggregates findings into a comprehensive compliance score.
Human auditors then review the flagged risks to confirm a violation or dismiss false positives.
Outcomes
99% reduction in manual review
Previously, human auditors had to review approximately 500 sentences per call. Now, AI flags only 5 for human review, dramatically improving efficiency. At the client’s current scale, the AI has automated 5,500 annual work hours.
93% average accuracy–the same as a human
The AI system effectively flags 100% of the most simple issue types and 91% of Material Nonpublic Information Disclosures (MNPI), one of the hardest compliance violations to detect due to its subjective nature. Its accuracy matched human auditors while reducing inconsistencies in regulatory enforcement.
>90% annual cost savings
By automating compliance monitoring, the AI system has significantly cut operational costs. A single auditor can tackle significantly more cases, allowing the compliance provider to scale its services without expanding its workforce.