Learn how a US state auditor leveraged machine learning to detect and prevent the estimated one billion dollars wasted on fraud in healthcare per year.
Fraud Detection and Prevention
Spot and address fraud early, before it’s too late
Traditional methods for fraud detection and prevention are both expensive and ineffective. It’s impossible for most companies to sift through every transaction they’re involved in, and selecting random samples is still a time-intensive process that provides a limited view of issues that are typically widespread. For companies without a sound mitigation plan, fraud eats away at profits and hinders the ability to serve legitimate customers.
The good news? Companies who are able to analyze large amounts of data in real-time can automatically flag behaviors that are commonly associated with fraud – allowing them to proactively address issues and minimize negative financial impact. Here’s how RapidMiner can help you get started.
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Fraud Detection and Prevention: Leveraging Machine Learning to Detect Fraud Patterns, Anomalies & Unusual Behaviors
Learn how machine learning can be used for more effective fraud detection and prevention by focusing on high risk cases instead of wasting time with random checks.
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