Introducing Adverse Media v2: AI-Powered Risk Classification
Our new Adverse Media endpoint now uses a fine-tuned LLM to classify news articles into 12 risk categories - reducing false positives by 64%.
Our new Adverse Media endpoint now uses a fine-tuned LLM to classify news articles into 12 risk categories - reducing false positives by 64%.
Background
Introducing Adverse Media v2: AI-Powered Risk Classification sits at the intersection of regulation, engineering and operations. The regulatory bar keeps rising while teams are asked to do more with the same headcount, which is exactly where clear process and good tooling pay off.
A practical approach
- Start with the data model. Clean entity resolution and well-defined risk thresholds prevent most downstream pain.
- Measure false positives. Track precision and analyst throughput so thresholds are tuned with evidence rather than guesswork.
- Automate the audit trail. Every decision should be reconstructable months later for a regulator or auditor.
How on8.ai fits
on8.ai provides the screening, monitoring and reporting primitives so your team can focus on policy rather than plumbing: configurable rules, a tamper-evident audit trail, and exports that are ready for your regulator.
Key takeaways
- Treat compliance as a continuous process, not a one-off project.
- Tune thresholds with data, and review them at least quarterly.
- Keep everything auditable by default.
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