Adaptive fraud detection refers to a dynamic system that continuously analyzes and learns from data to identify and respond to fraudulent activities in real-time. By leveraging machine learning and advanced analytics, this approach adjusts its algorithms based on new information and emerging patterns, enhancing the accuracy of fraud detection over time. This method is particularly relevant in claims processing automation, where it helps organizations efficiently assess claims while minimizing fraudulent losses.
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