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Adverse Media Screening
Contextual Adverse Media for Smarter AML Decisions
Shufti Adverse Media Screening software structures every story into entity roles, explainable adverse media intelligence , and AML-aligned signals , so compliance teams review actual exposure, apply policy consistently, and keep a clear audit trail from screening to sign-off.
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Our Numbers Speak Volumes
How Shufti Reads the News Differently
Full-article NLP, not keyword triggers
The engine interprets complete stories rather than scanning for isolated terms. It distinguishes between an entity accused of fraud and one mentioned as a witness in the same article.
Per-entity profiles built automatically.
For each entity detected, Shufti assembles available attributes, country, entity type (person, organisation, group), industry, occupation, and date of birth where known. These attributes support confident matching and reduce false positives on common names.
Sentiment with justification
Each mention receives a sentiment with a short written rationale. Analysts see not just “negative” but why, enabling faster, defensible decisions.
415+ adverse keywords mapped to AML risk themes
Structured tagging tied to predicate offence categories and regulatory risk themes. Consistent categorisation across teams, jurisdictions, and review cycles. The deep multi-entity intelligence stays in the backend. Analysts get a clean, focused view for the entity they are screening.
EXPLORE THE FULL AML SUITE
Adverse Media Is One Layer Here Is the Rest
PEP & RCA Screening
Surface political exposure and map relatives and close associates across jurisdictions with real-time multilingual profiling.
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Sanctions Screening
Screen individuals and entities against global sanctions regimes with consolidated coverage and real-time enforcement updates.
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Watchlist Screening
Screen against global watchlists including enforcement registers, criminal records, and law-enforcement lists with continuous refresh cycles.
Explore API DocsSTRUCTERED NEGATIVE NEWS SCREENING
Screening That Fits AML Workflows
From Screening to Sign-Off, Faster
Less Noise, Fewer False Positives
Context-aware AI focuses on entities actually linked to wrongdoing. Sentiment, and adverse keywords push low-value mentions to the bottom. Analysts spend time on material risk, not harmless references.
Faster Reviews, Less Analyst Fatigue
Each alert includes a summary, adverse keywords, entity role, and sentiment with explanation. Per-entity details , country, entity type, industry, DOB , are presented in a single view. Analysts add comments, attach documents, and record decisions in the same workspace.
Faster Reviews, Lower Review Load
Entity-first relevance ranking.
Alerts are ranked by how serious the matter is, how strongly the match fits, and how recently the story broke. The cases that need a closer look rise to the top of the queue, and minor mentions sit below them.
Syndication deduplication
Groups repeated and syndicated coverage into a single consolidated result. The same story published across forty outlets does not generate forty alerts.
One-view alert summaries
Each alert presents the core story upfront. Analysts assess exposure from the summary without opening multiple links.
Policy-based filters
Refine outputs by geography, source type, risk category, and other controls to match internal policy and escalation rules.
Accurate Matching Across Markets
Phonetic and variant matching
Captures transliterations, spelling variations, and alias patterns to reduce missed hits across languages and scripts, Arabic, Cyrillic, Chinese, and Latin variants.
Multilingual coverage
Monitors adverse media across 80+ languages and regions. Risk often appears first in local-language reporting; missing it means missing the earliest signal.
Smart entity matching
Uses key details to match the right person or business and reduce false positives.
Explainable Context for Decisioning
Full-article NLP
Interprets the complete story rather than matching isolated keywords. The difference: fewer irrelevant alerts and more accurate risk assessment.
Clear identification
Shows how the person or business is involved in the story, not just that they are mentioned.
AML-aligned adverse keywords.
415+ structured tags mapped to AML risk themes and predicate offence categories for consistent categorisation across teams and jurisdictions.
Sentiment with justification
Every adverse media mention is analysed for sentiment, with a short written sentiment analysis of each result. Analysts see not just that a story reads negative, but why, so escalation or clearance is always defensible.
Monitoring and Evidence
Continuous Adverse Media Monitoring
Ongoing surveillance for customers, counterparties, UBOs, and portfolios , across onboarding, periodic refreshes, and event-driven rescreening.
Higher risk, more frequent checks
Set monitoring durations and alert frequencies to match entity risk levels , from weekly checks on high-risk PEPs to quarterly reviews on lower-risk portfolios.
Consolidated entity view
Each entity gets a single profile with prioritised alerts, summaries, and full decision history. No switching between tools to build the picture.
AI Compliance Co-Pilot
Shufti's AI layer reads every adverse media alert before it reaches an analyst, filtering out duplicate coverage and low-relevance mentions. L1 reviewers see only what matters, with clear reasoning attached to every alert so decisions are fast, consistent, and defensible.
Single API, Seamless Integration
Build fully customisable verification flows with seamless backend integration.
- Gain full control by customising verification flows end-to-end.
- Integrate seamlessly with your backend for quick implementation.
- Design flexible verification journeys tailored to your users.
Launch a native verification experience in your mobile app within minutes.
- Launch native verification within minutes on iOS or Android.
- Use ready-made UI with camera, capture, and real-time feedback.
- Customise flows to fit seamlessly into your mobile app.
Run Shufti within your own identical-capability infrastructure for maximum data control and privacy.
- Keep all sensitive information in-house to meet strict governance and data residency requirements.
- Keep sensitive information fully private and secure in-house.
- Deploy in highly regulated sectors without compromising compliance.
Quickly launch identity verification through a secure, customisable web link, no code required. Learn more.
- Start verifying users instantly with a no-code setup.
- Deliver a consistent identity experience via a link or embedded iframe.
- Deploy quickly via a secure link or embedded iframe.
With KYC Journey Builder, create personalised verification journeys without writing a single line of code.
- Customise your journey effortlessly with drag-and-drop functionality.
- Instantly see how your verification flow looks for your users.
- Easily connect with Hosted Verification for a consistent, branded experience.
Where Adverse Media Screening Fits
Built For Regulated and High-Risk Businesses
Trusted Sellers, Fewer Bad Actors
Marketplaces face repeated abuse: seller cycling, counterfeit networks, fraud, and high-risk merchants slipping through with new identities. Shufti flags credible negative coverage and builds entity-level context, helping platforms approve sellers confidently and intervene earlier when risk patterns emerge.
Don't just take our word for it, hear from our customers
The Confidence Our Clients Share
The future of digital identity is defined by trust, interoperability, and regulatory alignment, so our partnership with Shufti reinforces DevCode Identity's commitment to supporting our global customers with the most secure, best-in-class, complaints identity verification solutions available today.
Combining our Conversion Driven Compliance Orchestration Platform with Shufti's global KYC and IDV capabilities allows our customers not only to navigate complex regulatory demands but also to maintain a seamless customer onboarding experience with the highest achievable conversion rates.
Shufti gives us verification journeys we can trust across every market we serve. The ability to route players through passive database checks, eID authentication, and full biometric liveness — all behind one API — has reshaped how we think about onboarding compliance.
Their team acts like an extension of ours. When regulators added new requirements across two European markets, Shufti’s journey builder let us adapt in days, not months.
FXBO customers demand speed without compromising AML rigour. Shufti’s eIDV fits exactly there — high-assurance verification for large deposits, invisible background checks for everything else, and one compliance trail across the board.
Integration took a single sprint. The SDK handled the full journey, so our product team stayed focused on trading features instead of building KYC screens.
As a regulated European payments platform, we need identity verification that meets eIDAS 2.0 and AMLD6 without multi-vendor stitching. Shufti delivers both — native eID authentication for high-assurance markets and docless database checks where eIDs don’t reach.
One contract, one audit log. That changes the compliance conversation entirely.
Frequently Asked Questions
What is adverse media screening?
Adverse media screening Provider checks news and media sources for negative coverage linked to an individual or organisation , helping identify potential financial crime, sanctions exposure, reputational risk, or regulatory concerns. It is a required component of risk-based AML due diligence under FATF guidance and EU AML Directives.
How does structured screening differ from keyword-based tools?
Keyword tools return link lists. Shufti structures each story into decision-ready attributes , entity matching, role in the story, AML-aligned tags, and sentiment with justification, so reviewers assess exposure faster and more consistently.
What sources does Shufti monitor?
Shufti monitors a broad set of global sources ,including online news and other media channels , across regions and in 80+ languages. Coverage can be filtered by geography and source type to match internal policy.
How quickly are new stories processed?
New coverage is processed within minutes. Alerts can be triggered as relevant adverse media appears, supporting both onboarding and ongoing monitoring use cases.
How does Shufti reduce duplicate alerts?
Shufti groups syndicated and repeated coverage so teams do not review the same story multiple times. This reduces review workload and keeps cases cleaner.
How does name matching work across languages and scripts?
Shufti applies phonetic and variant logic to match across spelling differences, transliterations, and known alias patterns , helping reduce missed matches across languages and non-Latin scripts.
What context do reviewers get beyond the article link?
Each alert includes a structured summary, entity role in the story (e.g., accused vs. mentioned), AML-aligned adverse keywords, sentiment with a short rationale, and key metadata such as source and timestamp.
Can screening criteria be configured to match internal policy?
Yes. Thresholds and filters ,geography, sentiment, risk tags, source types , can be configured to align outputs with internal policy and escalation rules.
Does Shufti support both onboarding and ongoing monitoring?
Yes. Shufti supports onboarding screening, periodic refreshes, and continuous monitoring across customers, counterparties, UBOs, and portfolios.
How does audit evidence work?
Actions and decisions can be logged. Evidence packs containing sources, timestamps, alert attributes (roles, tags, sentiment rationale), and full review history can be exported for regulatory inspection or internal audit.
How does integration work?
Shufti supports API-based integration for screening and monitoring. Results can be pushed into existing workflows using webhooks, and teams can review cases directly in the platform.
Stop Reviewing Noise. Start Making Decisions.
Evaluate how structured adverse media screening reduces review time, improves decision consistency, and strengthens audit readiness.