Q-Fraud Detector is an industrial application of data mining, business rules implementation, and machine learning. The proposed solution defines the build and deployment of a custom ruleset and a machine-learning model for online transactions to detect fraudulent transactions.

Q-Fraud Detector consists of the following components:

The transaction scoring database, to enable the integration with the fraud system
The machine learning model to detect fraudulent transactions
An auto-train mechanism to auto-train the model in predefined timeframes

Machine Learning

Q-Fraud Detector uses ML to create models and improve them in the future as operations continue.

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