US 11,935,038 B2
Direct data share
Wesley Perkins, Henrico, VA (US); Venkata Satya Sriram Kalyan Namuduri, Glen Allen, VA (US); David Ross, Richmond, VA (US); Andrew Coulson, Washington, DC (US); and Hunter Roberts, Henrico, VA (US)
Assigned to Capital One Services, LLC, McLean, VA (US)
Filed by Capital One Services, LLC, McLean, VA (US)
Filed on Nov. 8, 2021, as Appl. No. 17/520,918.
Application 17/520,918 is a continuation of application No. 17/176,642, filed on Feb. 16, 2021, granted, now 11,182,797, issued on Nov. 23, 2021.
Prior Publication US 2022/0261811 A1, Aug. 18, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06Q 40/00 (2023.01); G06F 18/214 (2023.01); G06N 20/00 (2019.01); G06Q 20/38 (2012.01); G06Q 20/40 (2012.01)
CPC G06Q 20/3821 (2013.01) [G06F 18/2148 (2023.01); G06N 20/00 (2019.01); G06Q 20/4016 (2013.01)] 22 Claims
OG exemplary drawing
 
1. A computer-implemented method for supplementing payment authorization information, received from a payment processing service, corresponding to a financial transaction between a user and a merchant, the method comprising:
receiving, by a data share computing device, from a merchant device, and via a first application programming interface (API), supplemental transaction metadata comprising one or more data elements corresponding to one or more attributes of the financial transaction, wherein the supplemental transaction metadata is associated with a concurrent transmission of basic payment information, for the financial transaction, by the merchant device to the payment processing service, wherein the data elements are supplemental to the basic payment information sent to the payment processing service according to a pre-existing standard;
validating, by the data share computing device and based on a predicted processing time associated with processing, by the payment processing service, of the basic payment information, the supplemental transaction metadata based on one or more criteria, wherein validating the supplemental transaction metadata comprises at least validating a first data element of the supplemental transaction metadata, and wherein the one or more criteria are associated with one or more of: validity, consistency, or formatting of data elements of the supplemental transaction metadata;
receiving, by the data share computing device, from a computing device associated with the payment processing service, and via a second interface different from the first API, payment authorization information corresponding to the financial transaction, wherein the payment authorization information indicates whether the basic payment information, transmitted by the merchant device to the payment processing service, caused the financial transaction to be approved by the payment processing service, and wherein validating the supplemental transaction metadata received from the merchant device is performed prior to receiving the payment authorization information from the payment processing service;
matching, by the data share computing device, the validated supplemental transaction metadata for the financial transaction received from the merchant device with the payment authorization information received from the payment processing service for the financial transaction;
determining, by the data share computing device and using a machine learning model, an authorization result indicating whether the financial transaction is authorized based on the matched payment authorization information and the supplemental transaction metadata, wherein the machine learning model is trained to determine whether an input transaction is authentic based on data comprising financial transactions tagged based on their authenticity, and wherein the input transaction comprises payment authorization information and supplemental transaction metadata corresponding for a given payment transaction; and
sending to the merchant, by the data share computing device and based on an authorization timing requirement associated with the financial transaction and the payment processing service, the authorization result as determined by the machine learning model for the financial transaction.