Namesakes
Same name, different person
A search engine doesn't know your customer's date of birth or city. Investigators do that matching by hand, and two investigators can reach different answers on the same result.
Threat squad
Oscar Gray — Senior AI OSINT Intelligence Director
AI OSINT that filters the namesakes out
Oscar Gray — Senior AI OSINT Intelligence DirectorOscar Gray is an AI agent that searches adverse media, breach databases, dark-web mentions and domain and IP reputation for the customers and cases your team is reviewing. He drops namesakes with a recorded reason and attaches what's left with a confidence level. Your analyst reads the evidence and makes the call.
Oscar Gray
Adverse media check on onboarding #7712
IllustrativeReady for review
3 relevant items · confidence high
Flag explained
“Two court reports match name, date of birth and city. Namesakes dropped with reasons.”
Job description
What Oscar Gray does Job description
Oscar Gray is a Senior AI OSINT Intelligence Director. He runs outside-in checks on customers, counterparties and cases, filters out what doesn't fit and attaches what does to the file your analyst reviews.
AI AGENT · THREAT SQUAD
OSCAR GRAY
Senior AI OSINT Intelligence Director
REPORTS TO
Your MLRO or Head of Financial Crime Investigations
WORKS WITH
Your onboarding, screening and case management systems, plus the data sources you license
DEPLOYED
Shadow mode first, then the autonomy you set
KEY RESPONSIBILITIES
01Search adverse media, breach databases, dark-web mentions and domain and IP reputation for the subjects you send him
02Match each result against the customer's identifiers and drop namesakes with a recorded reason
03Attach relevant findings to the case with the source, the date and a confidence level
04Re-check existing customers when you set a schedule or a trigger event occurs
05Log every search, every source and every discarded result so the work can be replayed
AUTONOMY MODEL
LOWMEDIUMHIGH
Low risk
Can close clear namesake-only results on his own, if you allow it
Medium risk
Goes to an analyst by default
High risk
Always goes to an analyst
You set the threshold per rule.
Kill switch: Turn Oscar off at any time
Options
How the options compare
| CRITERIA | Manual web searches | Adverse media screening tool | Oscar Gray |
|---|---|---|---|
| Time to first results | Depends on the investigator's queue | Vendor setup and threshold tuning | Shadow mode on your live cases |
| Who decides | Investigator | Match threshold, then analyst | Analyst, inside autonomy bands you set |
| Namesake handling | By hand, varies by person | Name and keyword matching | Matched on your identifiers, with the reason recorded |
| Sources covered | Whatever the investigator thinks to check | Media only, in most tools | Media, breach data, dark-web mentions and domain reputation you license |
| Record of the search | Case notes and links | Hit list | Full log of sources, results and discards |
| Where it's weaker | Slow and inconsistent at volume | Noisy on common names | Only sees the sources you license; nothing unpublished or unindexed |
Works best with
AI agents that work best with Oscar Gray
Oscar's findings matter most when they land inside a case another agent is already building.
TRUST AND IDENTITY
Rhea Ledger
Senior AI KYC/AML Compliance Director
Uses Oscar's findings in screening dispositions and customer risk ratings.
Meet RheaTHREAT
Aiden Flux
Senior AI Fraud Risk Analyst
Asks Oscar for breach data and adverse media when a fraud alert needs outside evidence.
Meet AidenTHREAT
Clara Adjusta
Senior AI Claims Intelligence Officer
Pulls public records on claimants and repairers before an SIU referral.
Meet Clara
Thoughts that matter
Insights on AI agents, financial crime and compliance
What we're learning about AML, fraud and the evidence examiners ask for.
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Questions? We Have Answers
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Frequently Asked Questions
Still have questions?
Talk to the people who build the agents. We'll answer per capability, yes or no.
An AI agent that runs open-source intelligence checks for compliance and fraud teams. Oscar Gray searches adverse media, breach databases, dark-web mentions and domain reputation, filters out namesakes and attaches relevant findings to the case with a confidence level. Your analyst reviews them.
He compares each result with the identifiers you hold, such as date of birth, city, nationality, employer or company number. Results that conflict drop out with a recorded reason. Results he can't confirm either way go to an analyst.
The ones you license and allow. Typical sources are news archives, breach data providers, dark-web monitoring feeds and domain and IP reputation services. We agree the source list with you during deployment design.
Your analyst does. Oscar can close results that are clearly about someone else, only where you allow it. Anything relevant goes to a person. A kill switch turns Oscar off without touching your other systems.
Public data about a person is still personal data under GDPR, UK GDPR and similar laws. Oscar searches only for the purposes and sources you configure, and logs every search so your data protection team can review it.
Oscar searches a sample of your customers and open cases, but nothing is closed. Your investigators keep working as they do today, and you compare Oscar's findings with theirs. You decide whether, and where, to switch on any autonomy afterwards.
FluxForce runs as SaaS, on-premise or hybrid, built on Microsoft Azure. We agree data residency and which components run inside your environment during deployment design, before any data moves.