WSEAS Transactions on Information Science and Applications
Print ISSN: 1790-0832, E-ISSN: 2224-3402
Volume 23, 2026
Decision Support System (DSS) for Fraud Detection in Health Insurance Claims using Genetic Support Vector Machines (GSVMS)
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Abstract: Fraud in health insurance leads to huge financial losses and claim processing systems inefficiencies. In this paper, the proposed system to be used is a hybrid Genetic Support Vector Machine (GSVM) model of a Decision Support System that will be effective in detecting fraud. FIC-GSVM method combines Genetic Algorithms to select the most optimal features and Support Vector Machines to classify features. The model is tested with the National Health Insurance Scheme (NHIS) data on Ghana, which is a set of structured and coded healthcare claims. Experimental findings indicate that the proposed approach has a 90.5% accuracy, as well as high precision, recall, and reduced processing time as compared to the current approaches. The system facilitates automated, scalable, and near real-time fraud detection, which can be an effective solution to healthcare insurance analytics.
Keywords:
Health Insurance Fraud Detection, Decision Support System (DSS), Genetic Algorithm (GA), Support Vector Machine (SVM), Genetic Support Vector Machine (GSVM), Feature Selection, Machine Learning, Healthcare Analytics
Pages: 432-446
DOI: 10.37394/23209.2026.23.36