Healthcare insurance claim fraud detection using datasets derived from multiple insurersVarious techniques are described that enable a smaller insurer (or an insurer with a less developed dataset) to be able to characterize whether certain healthcare insurance claim elements are potentially fraudulent or ...
Additionally, exploring the integration of association rule mining with other techniques like unsupervised classifiers or ensemble methods could further enhance the accuracy and effectiveness of fraud detection systems in the healthcare insurance domain. Materials & methods Dataset In this study, the ...
Additionally, exploring the integration of association rule mining with other techniques like unsupervised classifiers or ensemble methods could further enhance the accuracy and effectiveness of fraud detection systems in the healthcare insurance domain. Materials & methods Dataset...
This study uses deep learning models, particularly convolutional neural networks, to tackle fraud detection. Using a dataset of 1,000 car collision claims from seven US states in 2015, we aim to demonstrate the effectiveness of deep learning, even with small datasets. Despite the limitations of ...
AutoInsuranceFraudDetectThis is my very first time to implement a machine learning model.The dataset is from kaggleMost of the code are inspired by this article and this article, with some modification on the features and presentation. I also added comments and my understanding on the original ...
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An efficient Search Tool for an Anti-Money Laundering Application of an Multi-national Bank's Dataset Most of the financial institutions internationally have been implementing anti-money laundering solutions (AML) to fight investment fraud activities. In AML, ... NA Le-Khac,S Markos,M O'Neill,...
Then this data must be analyzed against the insurant's electronic health record (EHR) dataset to infer predictions on whether a given person may shortly need medical attention. The higher the risk, the higher the monthly or annual quote is.And this is a rather simplif...
interdependence nor the losses of other non-severe attacks. However, regardless of whether we calculate the losses of our dataset using extreme value distributions or simply extrapolate linearly, our results appear to be below those of other publications. We discuss this further in the following ...
imposed substantial changes to health insurer operations. We provide evidence of the presence of adverse selection following the enactment of the Patient Protection and Affordable Care Act of 2010. Using a unique dataset co...