MapReduce-iterative support vector machine classifier: novel fraud detection systems in healthcare insurance industry

<span>Fraud in healthcare insurance claims is one of the significant research challenges that affect growth services. The frauds are happening through subscribers, companies and providers. development a decision support to automate claim data from service provider offset patient’s challenges. In this paper, novel hybridized big statistical machine learning technique, named MapReduce based iterative vector (MR-ISVM) provide set sophisticated steps for automatic detection fraudulent health databases. experimental results have proven MR-ISVM classifier outperforms better classification than other (SVM) kernel classifiers. From results, positive impact seen declining computational time on processing without compromising accuracy achieved. proposed achieves 87.73% linear (75.3%) radial basis function (79.98%).</span>