Correlating Medi-Claim Service by Deep Learning Neural Networks

2023/08/08 by Jayanthi Vajiram, Vajiram, Jayanthi, Negha Senthil +3
Computer Science · #Artificial Intelligence (cs.AI) #FOS: Computer and information sciences #Imbalanced Data Classification Techniques #Machine Learning (cs.LG)

paper · pdf · doi:10.48550/arxiv.2308.04469

openalex publication_date 2023/08/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Medical insurance claims are of organized crimes related to patients, physicians, diagnostic centers, and insurance providers, forming a chain reaction that must be monitored constantly. These kinds of frauds affect the financial growth of both insured people and health insurance companies. The Convolution Neural Network architecture is used to detect fraudulent claims through a correlation study of regression models, which helps to detect money laundering on different claims given by different providers. Supervised and unsupervised classifiers are used to detect fraud and non-fraud claims.

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