Vital4 announces today a rare first-action allowance from the United States Patent and Trademark Office (USPTO) for “Systems and Processes for Contextualized Entity Resolution and Sentiment Analysis in Adverse Media Screening,” a major milestone in AI-driven risk and compliance innovation.
Vital4 announces a rare first-action allowance from the United States Patent and Trademark Office (USPTO) for “Systems and Processes for Contextualized Entity Resolution and Sentiment Analysis in Adverse Media Screening,” a major milestone in AI-driven risk and compliance innovation. The patent covers methods that use machine learning and natural language processing to link sentiment and adverse context to the correct entity in unstructured media, significantly improving screening precision at global scale.
“Receiving a first-action allowance from the USPTO is an exceptional validation of our approach to eliminating noise in adverse media,” said “Amy Barbieri,” Co-Founder, President, and Chief Growth Officer of Vital4. “This patent advances the Adverse Media 2.0 vision: cleaner, contextualized insights that let compliance teams move faster with confidence”.
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“Receiving a first-action allowance from the USPTO is an exceptional validation of our approach to eliminating noise in adverse media,” said “Amy Barbieri,” Co-Founder, President, and Chief Growth Officer of Vital4.
“This achievement reflects years of innovation from our team and partners,” said “Kristin Stafford,” Co-Founder and CEO of Vital4. “By tying adverse context to the right entity, we are setting a new standard for precision that protects customers from false positives, review fatigue, and missed risk”.
What the patent enables
Filters out articles where negative concepts are present but not tied to the screened person or business, reducing false positives across AML, KYC, Enhanced Customer Due Diligence, and third-party risk workflows.
Contextualizes entity mentions and enriches results with details like location and age enabling faster more accurate adjudication with minimal reviewer effort.
Proven impact
97% reduction in irrelevant results and a 99% drop-in review time in a recent case study, enabling teams to double case reviews with the same headcount.
Measurable cost savings, stronger auditability, and reduced risk of regulatory penalties and reputational damage
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