	US 11,704,669 B1
	Dynamic contactless payment processing based on real-time contextual information
Udaya Kumar Raju Ratnakaram, Telangana (IN); and Puneetha Polasa, Telangana (IN)
Assigned to Bank of America Corporation, Charlotte, NC (US)
Filed by Bank of America Corporation, Charlotte, NC (US)
Filed on Jan. 3, 2022, as Appl. No. 17/567,232.
Int. Cl. G06Q 40/00 (2023.01); G06Q 20/40 (2012.01)

CPC G06Q 20/4015 (2020.05)

21 Claims

1. A computing platform, comprising:

at least one processor;

a communication interface communicatively coupled to the at least one processor; and

a memory storing computer-readable instructions that, when executed by the at least one processor, cause the computing platform to:

receive historical data of a user;

train, using the historical data of the user, a machine learning model to identify patterns within user data to generate predicted pre-authorized amounts and recommendations;

retrieve contextual data for a user from at least one user source;

execute the machine learning model, wherein executing the machine learning model includes using, as inputs, the retrieved contextual data to output a pre-authorized amount for payment for an event using automatic payment processing;

receive, from an entity computing system, a request for payment and data associated with the event;

identify, from the data associated with the event, an amount for the event;

compare the identified amount to the pre-authorized amount output by the machine learning model;

responsive to determining that the identified amount is less than or equal to the pre-authorized amount:

request, from a user computing device and in real-time, current location data of the user;

receive, from the user computing device and in real-time, global positioning system (GPS) data of the user indicating the current location data of the user;

retrieve, from the contextual data, an expected location of the user;

compare the expected location of the user to the current location data of the user and location data from the data associated with the event;

responsive to determining that the current location data matches the expected location of the user and the data associated with the event;

authorize payment of the amount for the event; and

update the machine learning model based on the authorized payment; and

transmit, to the entity computing system, an instruction authorizing payment of the amount for the event;

responsive to determining that the current location data does not match the expected location of the user and the location data from the data associated with the event, generate and transmit, to the user computing device, a request to authorize payment of the amount for the event; and

responsive to determining that the identified amount is more than the pre-authorized amount, generate and transmit, to the user computing device, a request to authorize payment of the amount for the event.