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Chapter 6: Advanced Adverse Media Screening

Chapter 1: The AML Compliance Rush Chapter 2: AML Data & Core Features Chapter 3: Sanction Screening Chapter 4: PEP Screening Chapter 5: International Leaks Data Chapter 6: Adverse Media Screening Chapter 7: Test The Vendors Chapter 8: Advanced Features Chapter 9: Choose the Right Price Chapter 10: Finalize the Decision

Detect the Unbiased Risks with Advanced Adverse Media Screening

How does your AML solution take into account potential left-wing and right-wing bias while checking criminal background through adverse media screening?

 

Navigate The Noise To Find The Truth

At AML Watcher our human experts with the help of the latest AI techniques examine the details of flagged content, cross-referencing and validating information to ensure it paints a true and accurate picture of potential risks. We integrate feedback from our data experts who monitor and evaluate random hits generated by the sentiment analysis. Our sentiment analysis feature understands the context and subtleties of the information. This includes recognizing sarcasm, detecting bias, and differentiating between factual reporting and opinion; thus providing a real negative coverage.

Conducting an adverse media screening lowers the possibility of doing business with a firm or individual that has a track record of financial crimes, terrorist financing, and money laundering.

Make sure your company has access to high-quality structured adverse media content to recognize possible risks, make informed decisions during onboarding, and continue monitoring to adhere to legal requirements and confidently move your business forward.

 

How Legacy Vendors Offer Adverse Media Screening

 

Lack of Contextual Analysis

Basic screening methods may not analyze the context or sentiment of the media content. This ignores the requirement to evaluate each news piece based on its tone, language, intention, and credibility.

Without understanding the sentiment, it’s challenging to differentiate between false positives (irrelevant hits) and genuine threats.

Limited News Data Sources

Legacy vendors often struggle with accurate results from adverse media screening due to outdated technologies and limited data sources. They mainly focus on covering international and mainstream news and avoid covering the local and regional news. 

This may lead to missed risks and false negatives, undermining the effectiveness of AML compliance efforts.

Their inability to integrate real-time updates and advanced analytics results in slower, less accurate detection of adverse media, which can expose institutions to heightened financial and reputational risks.

 

Features Of Efficient Adverse Media Screening Solution

 

Broader Adverse Media Data Sources

AML Watcher extracts data from a wide array of sources, including international and local news outlets, blogs, social media, and other digital platforms.

AML Watcher keeps 5000+ most reliable global media sources to precisely screen each risky profile associated with news headlines. Not only that, AML Watcher allows you to customize your search. So, you can include the domains that provide news relevant to your specific industry.

Sentiment Analysis for Accurate Screening

AML Watcher incorporates sentiment analysis into its screening process. Sentiment Analysis is a natural language processing technique used to determine the emotional tone behind words. 

It helps identify and categorize opinions expressed in a piece of text, especially to determine whether the writer’s attitude towards a particular topic, person, or entity is positive, negative, or neutral. 

Each piece of text is analyzed to classify its sentiment as positive, negative, or neutral. This involves evaluating the language used and the context within which certain keywords appear. Differentiates between negative news that is relevant and that is not, significantly reducing false positives and ensuring a focus on genuine threats.

Automated Under Human Expertise

AML Watcher leverages automation under human expertise to handle large volumes of data efficiently. High-priority items flagged by sentiment analysis are reviewed by our compliance experts to validate the findings and ensure no critical information is missed.

Insights from human reviewers are fed back into the machine-learning models to improve future sentiment analysis accuracy.

Scalable for organizations of any size, ensuring comprehensive coverage without the limitations of lengthy review processes.

Scoring As Per Linked Risks

Our solution gives a sentiment score based on the intensity and nature of the negative sentiment on each identified piece of adverse media. Then Results with high negative sentiment scores are prioritized for further manual review by our in-house analyst, ensuring that the most relevant adverse information is addressed promptly.

This image shows how AML Watcher uses sentiment analysis to give scores to different adverse media data based on their nature.

Real-Time Data Updates

AML Watcher updates its adverse media database in real time, capturing the latest negative news as it appears. Ensures timely identification of news adverse information, reducing the risk of missing recent developments.

AML Watcher’s ongoing monitoring keeps you updated with continuously changing news and global trends, so you do not have to screen every time a big event occurs.

Advanced Keyword and Contextual Searches

AML Watcher uses advanced algorithms to conduct both keyword and contextual searches, ensuring more accurate identification of adverse media. Reduces irrelevant data and improves the accuracy of identifying genuine threats.

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