Risk-categorised results
Matches are grouped by risk theme such as fraud, money laundering, corruption, and organised crime, so analysts see why a name surfaced instead of an undifferentiated list of articles.
Screen customers and entities against negative news and adverse media from thousands of sources, with risk-categorised results, reduced noise, and ongoing monitoring.
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Screen a name against thousands of global news and media sources in seconds.
Results are relevance-scored and grouped by risk theme such as fraud, corruption, and organised crime.
Ongoing re-screening flags new coverage as it appears, with sources and decisions captured for audit.
Searching a customer's name against the world's media returns a great deal of material, and most of it belongs to a different person with the same name, or describes something that is not a financial crime risk at all. Volume is not coverage. The work is separating the article that changes a risk rating from the thousand that do not, and doing it the same way every time.
Sanctions screening best practice, and what firms get wrongMatches are grouped by risk theme such as fraud, money laundering, corruption, and organised crime, so analysts see why a name surfaced instead of an undifferentiated list of articles.
Relevance scoring, entity resolution, and date filtering cut coincidental name matches and stale coverage, so review time is spent on articles that actually describe your customer.
Customers are re-screened as new coverage appears, so adverse media that emerges after onboarding is flagged for review rather than missed.
Source articles, links, dates, and analyst decisions are stored against each customer, giving you a defensible record of what was found and how it was assessed.
Run adverse media checks inside onboarding and periodic review through the MemberCheck API, alongside sanctions and PEP screening on the same customer record.
Sanctions and PEP screening checks structured lists of designated persons. Adverse media screening searches news and media for negative coverage such as fraud, corruption, or investigations that may never reach an official list, so it surfaces reputational risk the lists miss.
Results are relevance-scored, resolved to the correct entity, and filtered by date and risk theme, so coincidental name matches and years-old articles about someone else are pushed down while coverage that describes your customer is surfaced.
Yes. Customers are re-screened as new coverage is published, so negative news that emerges during the relationship is flagged for review rather than only checked once at onboarding.
Yes. The source article, link, publication date, and the analyst's decision are recorded against the customer, giving you a defensible trail of what was found and how it was assessed.
A short walkthrough of screening, verification and ongoing monitoring in one platform, set to the thresholds and jurisdictions your programme actually uses.