That is the number of major research articles that bear the name of Venkata Vijay Satyanarayana Murthy Neelam-the ...
Optum Rx is leaning on artificial intelligence as it looks to address costly fraud, waste and abuse in the pharmacy space. The company is deploying real-time AI analytics that identify potential ...
Every so often, we receive an email that stops us cold. Not because it is dramatic. Not because it is careless. Because it feels impossible. Sheri, first, we are glad your bank flagged it. That alert ...
This story has been corrected. WASHINGTON — The Department of Veterans Affairs announced that it will analyze 1 million old disability benefits questionnaires dating to 2010 to identify possible signs ...
Section 1. Purpose and Policy. American taxpayers fund a vast benefits system for citizens in need that includes housing, food, medical care, cash assistance, and more. States administer these ...
AUSTRAC is investigating a widening mortgage loan fraud scandal, after a syndicate duped Commonwealth Bank into writing $1 ...
FraudGuard AI is a machine learning-based web application developed to detect suspicious and fraudulent transactions. The system uses a trained ML model along with rule-based checks to classify ...
FIRST ON FOX: The origins of a fraud-fighting technology now used by one of the world’s largest insurers trace back to a deadly insider attack during the Iraq War. Clearspeed founder Alex Martin was ...
On a busy, gritty street in suburban Los Angeles, the white one-story stucco building looked like any other. Among the apartments, offices, sidewalk bodegas, the only defining feature was the building ...
Tool helps payers identify synthetic or manipulated medical documentation and images earlier, strengthening fraud prevention and protecting provider trust Codoxo, the leading provider of AI and ...
WASHINGTON — The Department of Veterans Affairs plans to launch an automated fraud-detection tool to scan more than a million disability benefits questionnaires for evidence of fabrication or other ...
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