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