TRANSACTION RISK ASSESSMENT USING MACHINE-TRAINED MODELS

TRANSACTION RISK ASSESSMENT USING MACHINE-TRAINED MODELS

Systems and methods are directed to assessing risk and triggering a mitigation action prior to executing an offer based on a level of risk. Risk models are trained with data extracted from past transactions, whereby the risk models are configured to determine levels of risk for potential transaction...

Ausführliche Beschreibung

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Bibliographische Detailangaben
Hauptverfasser: Kannusami, Om Prakash, Sharp, Scott David, Muthuraman, Alagu, Hameed, Shakul
Format: Patent
Sprache:eng
Schlagworte:
CALCULATING
COMPUTING
COUNTING
DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FORADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORYOR FORECASTING PURPOSES
PHYSICS
SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE,COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTINGPURPOSES, NOT OTHERWISE PROVIDED FOR
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Beschreibung
Zusammenfassung:Systems and methods are directed to assessing risk and triggering a mitigation action prior to executing an offer based on a level of risk. Risk models are trained with data extracted from past transactions, whereby the risk models are configured to determine levels of risk for potential transactions. A request to make an offer on a listing representing an item is received. In response, the system identifies one or more account attributes associated with the user account and determines a level of risk by applying the one or more account attributes to one or more of the risk models. If the level of risk transgresses a threshold, the system triggers the automatic payment flow prior to executing the offer, which includes causing display of an information request user interface through which payment and shipping information is received. Responsive to receiving the payment and shipping information, the offer is executed.