Transform your Adverse Media Screening

Save time and increase accuracy with advanced AI tools

Adverse Media and Watchlist Screening

Continuous adverse media monitoring with category-defining entity resolution and AI natural language processing

Adverse Media Screening UI Request a demo

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Optimised Customer Onboarding

Labyrinth Screening enables you to understand customer risk quickly and comprehensively, with pinpoint matching fine-tuned for your organisation.

Data agnostic

Choose the right media, watchlist, PEP and sanctions lists for your organisation, with the ability to segment customers against different data sets and combine data sets as required.

Multi-lingual machine learning

Labyrinth Screening’s machine learning algorithms read millions of media articles in 25+ languages each day to identify the adverse media that matters to your organisation. These data classifiers extract pertinent entities and identify the role of each in relation to the article risk.

Industry-leading indentity matching

Achieve unparalleled accuracy across multiple scripts and languages with our unique entity resolution and name variant capability.

Advanced AI Risk Profiles

Ripjar’s entity-specific AI profiles hugely simplify analyst workflow. All information is assembled into single 360° profile views for people and companies, identifying areas of relevant risk across adverse media, sanctions lists and watchlists and PEP status.

Ripjar placed as Category Leader

Ripjar placed as Category Leader in Chartis KYC Solutions Quadrant

Continuous Monitoring

Remain compliant and ensure your screening is always up to date with continuous monitoring. Instead of undertaking time-consuming scheduled reviews, Labyrinth Screening enables you to improve efficiency and review important new alerts as soon as they appear.

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Real-time alerts

Reduce risk and improve efficiency by moving away from periodic reviews. Continuous monitoring provides you with the most up to date view of your customer’s risk, with alerts highlighting new adverse media as it emerges.

Fine-tune monitoring

Fine-tune your continuous customer monitoring against the right data assets to balance risk identification against noise, reducing false positives.

Focused summaries

Benefit from robust AI-generated risk profiles which automatically filter, prioritise and score watchlist, sanctions list, and media matches so you are only reviewing current, pertinent data.

“We demonstrated a 13% improvement in recall and simultaneously a 91% reduction in false positives as measured by our model validation team on an unseen dataset.”

Tier 1 Bank

Flexible Deployment

Leverage Ripjar’s powerful data processing cloud to review and interpret millions of media articles per day. Machine learning models identify relevant risk-bearing data which is sent to highly secure SaaS or on-premise screening instances for matching with client records and other private data.

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Integration options

Use the intuitive screening user interface or embed functionality within your systems using Ripjar’s robust APIs.

High security

All of your client data is protected with intelligence-grade security.

Architecture flexibility

Labyrinth Screening can be deployed to your preferred architecture to meet the demands of the strictest data policies.

“Testing showed the AI technology embedded in the system could reduce data-reporting errors by over 80%, when compared to third-party legacy systems.”


Realise Your Data Potential

Make sense of structured and unstructured data from multiple sources to optimise your adverse media screening.

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Improved risk identification

AI Risk Profiles help organisations with their regulatory compliance by identifying risks they might miss using other screening methods. Labyrinth Screening uses AI-powered multi-lingual name matching and entity resolution to overcome screening challenges such as common or high profile names.

Contextualised entity resolution

Labyrinth Screening offers global, multi-jurisdictional screening which adds additional context to profiles in a way not previously possible. In addition, the extraction of more secondary identifiers leads to richer data and better recall.

Optimise analyst efficiency

Intelligent classification pinpoints the most relevant articles to review in order to most accurately assess risk, reducing analyst workload and improving operational efficiency.

“We found that the number of false positives had gone down in all regions by an average of 80% after go-live.”

Tier 1 Bank

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