Benjamin is using a program to analyze claims data to identify similarities or connections that might indicate fraud. This practice is known as

• A. Data mining.
• B. Telematics.
• C. Claims audits.
• D. Wearables.

Answer: (A)

Data mining is about uncovering patterns, relationships, and anomalies in large sets of data. When you apply a program to analyze claims data to find similarities or connections—such as shared providers, repeated billing for the same service, unusual claim timing, or networks of related patients—you’re performing pattern discovery that can reveal potential fraud. This goes beyond checking individual claims and looks for systematic signs across the dataset.

Telematics focuses on data from devices (often in vehicles) to measure driving behavior, not on analyzing claims data for fraud. Claims audits are thorough reviews to verify accuracy and compliance of claims, typically more about verification than discovering hidden patterns across many claims. Wearables involve collecting health or lifestyle data from wearable devices, which isn’t about fraud detection in claims data.