US 12,093,960 B2
Mitigation of fraudulent transactions conducted over a network
Basil Munir Abifaker, San Diego, CA (US); and Stephen Jones, Escondido, CA (US)
Assigned to FIRST DATA RESOURCES, LLC., Omaha, NE (US)
Filed by FIRST DATA RESOURCES, LLC, Omaha, NE (US)
Filed on Nov. 1, 2021, as Appl. No. 17/516,176.
Application 17/516,176 is a continuation of application No. 14/228,977, filed on Mar. 28, 2014, granted, now 11,188,916.
Prior Publication US 2022/0051255 A1, Feb. 17, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 20/40 (2012.01)
CPC G06Q 20/4016 (2013.01) 16 Claims
OG exemplary drawing
 
1. A non-transitory computer-readable media comprising computer-readable instructions stored thereon that when executed by one or more processors cause the one or more processors to:
receive one or more first data values associated with a buyer, one or more second data values associated with a recipient, and one or more third data values associated with payment information of the buyer, wherein the one or more first data values, the one or more second data values, and the one or more third data values are received in association with a request from the buyer during an online transaction to buy a good or service for the recipient;
determine a relationship between the buyer and the recipient based on the one or more first data values, the one or more first data values including one or more characteristics of a message associated with the online transaction;
compute an overall risk score based on at least one of the one or more first data values, the one or more second data values, or the one or more third data values and one or more fraud detection models, wherein the one or more fraud detection models comprise verifying the relationship between the buyer and the recipient by:
identifying a set of attributes of the buyer and the recipient based on the one or more first data values, the one or more second data values, and the one or more third data values;
searching the one or more separate sources to determine information about the buyer and the recipient;
comparing the set of attributes to the information about the buyer and the recipient to verify the set of attributes; and
assigning a score contribution of the fraud detection model to the overall risk score based on a number of the set of attributes that are verified based on the information determined from the one or more sources,
wherein the overall risk score represents a likelihood that the online transaction is fraudulent, and wherein the overall risk score is computed by applying a weight to each respective fraud detection model of the one or more fraud detection models, multiplying an output of the respective fraud detection model by the assigned weight to obtain a score contribution of the respective fraud detection model, and summing the score contributions of the one or more fraud detection models to compute the overall risk score;
compare the overall risk score with a threshold score; and
authorize or deny the online transaction based upon the comparison.