Temporal Sequence Modelling and Anomaly Localisation: A Real-Time Deep Learning Framework for Insurance Claims Fraud Detection
Keywords:
temporal sequence modelling, anomaly localisation, real-time deep learning framework, insurance claims fraud detection, machine learningAbstract
Today, the insurance companies are facing a significant challenge in the form of detecting fraud in insurance claims. It is projected that approximately 10 percent of all non-healthcare insurance claims are fraudulent, amounting to $40 billion in losses in a year in the United States alone. The prevalence and widespread proliferation of the problem of insurance fraud have elicited the need to strengthen the detection mechanisms to address the issue in real time.Downloads
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