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Abstract

A system and method for improving the accuracy of fraud detection in transactions for a more effective fraud response. First and second models each receive transaction request data, evaluate the transaction request data for fraud, and produce first and second initial fraud results, respectively. The first model includes a first set of features which is relevant to detecting fraud and which includes one or more dominant features. The second model includes a second set of features which excludes the one or more dominant features. A score generator receives and combines the first and second initial results to generate a final fraud score. A response module takes an action based on the final score, such as rejecting or allowing the transaction request. The first and second models may use the same or different machine learning or other modeling technologies. The score generator may be a combination module or a combination model.

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First Claim