English only
The story that matters ran in a local paper, in a language nobody searched.
Data · Adverse media
Adverse Media Database
Negative news from 190+ countries in 30+ languages, categorized by predicate offense and delivered with its source and evidence, so an adverse media hit is a defensible finding, not a headline.
30+
Languages read
300,000+
Articles crawled a day
190+
Countries covered
By offense
Hits categorized by predicate offense
Why this matters
Keyword searches find headlines, not risk
Adverse media screening breaks down in three places: it searches in English when the story ran in the local language, it scores stories by sentiment instead of by the crime they describe, and it returns hits without the source an auditor will ask for. Complead reads news, social media and local-language sources in 30+ languages, categorizes every hit by predicate offense and keeps its source and evidence with it.
Sentiment, not offense
A bad review and a fraud indictment both read as negative, so the real risk sinks in the noise.
No evidence
A hit without its source cannot be defended when the auditor asks why it was cleared.
How it works
Scroll to advance
Four steps, from article to a categorized hit
-
Step 01
Crawl the sources
News, social media and local-language sources are crawled, more than 300,000 articles a day.
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Step 02
Match the entity
Stories are matched to the person or company you screen, with the relevance rules you set.
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Step 03
Categorize by offense
Each hit is categorized by the predicate offense it describes, not by the tone of the article.
-
Step 04
Deliver with evidence
Every hit is delivered with its source, category and evidence, ready for review and audit.
complead / crawl
- sourcesnews, social
- languages30+
- articles today300,000+
complead / match
- entityK. Demir
- countryTR
- rulesapplied
complead / category
- categoryfraud
- basispredicate offense
- hits3
complead / deliver
- sourceattached
- evidenceattached
- delivered overAPI
Crawl
Match
Categorize
Deliver
Capabilities
What the data gives you
30+ languages
Stories found in the language they were published in.
Offense categories
Hits categorized by predicate offense, not by sentiment.
Source and evidence
Every hit carries its source, category and evidence.
Relevance rules
Rules you define decide which stories count.
News and social media
News, social media and local-language sources in one feed.
Ongoing monitoring
New stories on the names you monitor surface as they are published.
Data tour
Three views of the data
The hit, categorized and sourced
The story, matched to the entity, with its offense category and source.
- Offense category shown
- Source and date
- Matched entity
complead / hit
- K. Demir
- categoryfraud
- sourcelocal news
- languageTR
The evidence behind the flag
The passage that triggered the hit, kept with the record for review.
- Triggering passage
- Original-language text kept
- Link to the source
complead / evidence
- excerptquoted
- originalkept
- translationEN
Relevance, on your terms
Relevance rules you define, so only the categories that matter reach a reviewer.
- Categories you include
- Rules you define
- Only relevant stories reach review
complead / rules
- includefraud, bribery
- excludeopinion pieces
- reviewernotified
Data coverage
What is covered, and how it stays current
News, social media and local-language sources, read in 30+ languages across 190+ countries, with every hit categorized by offense and kept with its source.
Coverage reference
Sources
News, social media and local-language sources
Reach
30+ languages across 190+ countries
Categories
Predicate offense, with source and evidence on every hit
Freshness
300,000+ articles crawled a day
Runs on Fusion
Adverse media, in the same score as sanctions and PEP
An adverse media hit lands on the same Fusion customer record as sanctions and PEP status, carried with its offense category, so the risk score reflects what a story is about rather than how many stories there are.
This product
Adverse Media Database
Categorized negative news
Powers
Fusion engine
Adverse media as a scoring input
You get
One record
Media, sanctions and PEP in one risk score
Integration
Fetch the hits for an entity, open the evidence
Pull the adverse media hits on a person or company, each with its category and source, and open the evidence behind any one of them.
// fetch the hits for an entity
GET /v1/data/adverse-media/hits?entity=demir
200 OK · 3 hits · fraud · bribery · sources attached
// open the evidence
GET /v1/data/adverse-media/hits/7719/evidence
200 OK · excerpt · original language · source link
FAQ
Before you ask us
Which sources do you cover?
News, social media and local-language sources, across 190+ countries.
Which languages do you read?
More than 30, so a story is found in the language it was published in.
How are hits categorized?
By predicate offense rather than sentiment, so a fraud story and a customer complaint are not treated the same.
Can we decide what counts as relevant?
Yes. You define the relevance rules that decide which stories reach a reviewer.
Does every hit show where it came from?
Yes. Each hit carries its source, category and evidence.
Where is our data stored?
You choose the region: EU, UK or Türkiye.
Testimonials
All case studies
What compliance teams say
We went from checking customers one by one to a single platform that screens more than 3,000 of them around the clock, so our analysts can finally focus on real risk.
We moved from screening customers one by one to a unified platform where our analysts can focus on what actually matters.
We focus on real risks, not false positives, meeting our AML obligations and our customers' expectations.
Screen against categorized adverse media
Bring a sample of names. In 30 minutes you will see the stories that matter, matched, categorized by offense and sourced.
3,000+
Data sources checked
220+
Countries covered
15 min
Always real-time data