REDUCING FALSE POSITIVES USING CUSTOMER FEEDBACK AND MACHINE LEARNING

A method of reducing a future amount of electronic fraud alerts includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that generates an electronic fraud alert, transmitting the alert to a mobile device of a customer, and receiving from the mobile dev...

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Bibliographische Detailangaben
Hauptverfasser: Valero, Miriam, Craig, Bradley A, Batra, Reena, Dua, Puneit, Kramme, Timothy, Phillips, Shanna L, Flowers, Elizabeth A, Ruestman, Russell
Format: Patent
Sprache:eng
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Zusammenfassung:A method of reducing a future amount of electronic fraud alerts includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that generates an electronic fraud alert, transmitting the alert to a mobile device of a customer, and receiving from the mobile device customer feedback indicating that the alert was a false positive or otherwise erroneous. The method also includes inputting the data detailing the financial transaction into a machine learning program trained to (i) determine a reason why the false positive was generated, and (ii) then modify the rules-based engine to account for the reason why the false positive was generated, and to no longer generate electronic fraud alerts based upon (a) fact patterns similar to fact patterns of the financial transaction, or (b) data similar to the data detailing the financial transaction, to facilitate reducing an amount of future false positive fraud alerts.