Open-source intelligence has a reputation for being slow work done by hand. An analyst opens twenty tabs, reads for an afternoon, and writes a memo that the next analyst cannot reproduce. The findings may be right. The process is not something a bank can put inside an onboarding flow.
What OSINT screening is
OSINT, open-source intelligence, is intelligence built only from information anyone is entitled to read: public registries, company filings, court records, published press and public profiles. OSINT screening applies it to a person or a company at a specific moment, usually onboarding or a periodic review, to answer one question: does the public record raise anything a compliance team should read before it decides?
It sits beside document verification and biometrics rather than replacing them. The document proves the ID is genuine, the face proves the person holding it is its owner, and the open-source check tells you what the world has already written about that person.
The pipeline exists to make that same work repeatable, fast and reviewable. Four stages, always in the same order.
Collection
The query fans out to more than five hundred public sources at once: company and public registries, published press, open web data and public profiles. Every source is public by law. Nothing in the pipeline asks for access it was not given.
Breadth is the point. A single match is a coincidence. The same person appearing in a registry, a court filing and a news item is a pattern, and patterns are what the next stage reads.
Correlation
The engine links what the sources say about each other, not just what each one says alone. Two records with the same name and different dates of birth are two people. Two records with different transliterations of a name, the same date of birth and the same city are probably one.
This is the part that used to take the afternoon, and it is the part a machine is genuinely better at. It never gets bored on the four hundredth record.
Scoring
Every query ends in a risk score from 0 to 1. The score is not a verdict. It is a reading instruction: the higher it climbs, the more the report asks a person to read before anyone decides.
A score you cannot open is a rumour. Every number in the report traces back to the source that produced it.
Delivery
The report comes back as JSON on the same API as document and biometric verification, and as a readable document for whoever has to sign off. Both carry the same sources, in the same order, with the same timestamps.
That is what makes the result defensible six months later, in front of a regulator who was not in the room when the decision was made.
Why under thirty seconds matters
The whole pipeline, from the query to the report, runs in under thirty seconds. That number is not a benchmark for its own sake. It decides where the check can live: inside an onboarding flow, while the customer is still on the page, rather than in a queue for a team to clear next week.
A check that takes an afternoon gets skipped when the queue is long. A check that takes thirty seconds gets run every time, and consistency is what turns intelligence into a control.
What a person still decides
The pipeline does the reading. It does not do the deciding. A low score lets a routine file move on without anyone opening it; a high one asks a person to read the sources before anyone acts. The report is written for that person, with every finding tied to where it came from.
- More than 500 public sources swept at once, every one public by law.
- Correlation across sources, so a pattern is read rather than a single match.
- A risk score from 0 to 1 that traces back, number by number, to its sources.
- JSON on the same API as document and biometric checks, and a readable report.
Questions we hear about OSINT screening
Is automated OSINT screening legal?
It is when the sources are public by law and the search has a legal basis. The pipeline reads only public sources; the legal basis for searching a given person is the organisation's own, set by its obligations and its regulator.
How is it different from checking a name against a list?
A list check asks whether a name appears in one place. OSINT screening reads what hundreds of sources say, links them to each other and weighs the pattern, which is how it tells two people with the same name apart and one person with two spellings of a name together.
What does the 0 to 1 risk score mean?
It is a reading instruction rather than a verdict. A low score lets a routine file continue; a high one asks a person to read the sources first. Every point of the score traces back to the source that produced it.
Can it run during onboarding?
Yes. The whole pipeline returns in under thirty seconds, on the same API as document and biometric verification, so the check can run while the customer is still in the journey.