A Study of Hybrid Learning Methodologies in Insurance Fraud Detection Techniques
- Author Surya Susan Thomas
- Co-Author Ananthi Sheshasaayee
- DOI
- Country : India
- Subject : Computer Science
Keywords : Insurance, Fraud detection, Datamining methods, Supervised, Unsupervised, Hybrid
learning
Abstract
Insurance fraud is a false misinterpretation of a matter of fact to obtain a financial gain from an insurance claim process. This result when a claimant attempts to achieve some financial boost which he/she is not supposed to obtain. Nowadays, the scenario has changed in such a way that in a developing country like India, the realization to get insured has substantially increased over the period of twenty to thirty years. The increase in insurance claims also led to an increase in the fraudulent claims which led to the necessity to detect these claims at the earliest so as to reduce financial losses to the insurance companies. Data mining methods helps in detecting frauds to a great extent. An overview of the supervised, unsupervised and hybrid learning methodologies for insurance fraud detection is discussed in this paper.
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