A Data Mining with Hybrid Approach based Transaction Risk Score Generation Model (TRSGM) for Fraud Detection of Online Financial Transaction

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Provided by: International Journal of Computer Applications
Topic: Data Management
Format: PDF
In this paper, the authors propose a unique and hybrid approach containing data mining techniques, artificial intelligence and statistics in a single platform for fraud detection of online financial transaction, which combines evidences from current as well as past behavior. The proposed Transaction RiSk Generation Model (TRSGM) consists of five major components, namely, DBSCAN algorithm, linear equation, rules, data warehouse and Bayes theorem. DBSCAN algorithm is used to form the clusters of past transaction amounts of the customer, find out the deviation of new incoming transaction amount and finds cluster coverage.
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