How Minerva evaluates an article
Minerva uses trained machine-learning models to evaluate new articles in real time, through the UI and the API. Each article that may pertain to the subject of the search is scored in two ways:- Sentiment analysis sets the tone of the article as “negative”, “positive”, or “neutral”.
- Risk analysis scores the supported financial and non-financial adverse media categories that are enabled for the applicable workspace and screening channel.
Categories and configuration
Minerva supports 32 category keys. The standard configuration enables 28 financial crime categories and the legacy Other (Non-Financial) category. DUI, Property Damage, and Assault and Battery are available but disabled by default, so they do not appear unexpectedly in existing integrations. Administrators can add or remove categories independently for Onboarding, Ongoing Monitoring, Direct API Calls, and Risk Assessments. API integrations can also override the category set for one synchronous search or one entity in a batch. The Adverse Media Categories page carries the complete financial and non-financial category reference, the AML scope of financial crime adverse media, the workspace and four-channel configuration steps, and the request-levelsearch-sync and batch search overrides.