IP Library › Granted Patent US 11,915,246
Granted Patent B2
US 11,915,246 · App. 17/694,315 · Granted Feb 27, 2024

Methods and systems for providing a decision making platform

Inventor: John D. Chisholm (Ballwin, MO)
Assignee: MASTERCARD INTERNATIONAL INCORPORATED
G06Q20/4016G06Q20/04G06Q20/40G06Q40/02
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Quick Facts
Patent No.
US 11,915,246
App. No.
17/694,315
Granted
Feb 27, 2024
Kind
B2
Abstract

A computer-implemented method of providing enriched transaction data for a transaction requiring an authorization is provided, the transaction performed using a computer system having a processor and a memory device. The method includes storing transaction data received from an input channel, the transaction data including a transaction identifier. An execution plan is retrieved based at least in part on the transaction identifier. The transaction data is processed across an enrichment processor based on the execution plan to generate at least one fraud score for the transaction. The transaction data is enriched to include at least one of the fraud score and an enriched data object. The enriched data is transmitted to an authorizing party for authorization.

Claims (38)

1. A computer-implemented method for applying a plurality of computer-implemented prediction models to requests received via a plurality of input data streams, said method performed by a computer system comprising at least one processor and a memory device in communication with the at least one processor, the at least one processor in communication with a payment card processing network, said method comprising steps executed by the at least one processor of:

receiving the requests via the plurality of input data streams, wherein the plurality of input data streams includes at least two of a) real-time authorization requests routed individually from the payment card processing network, b) authorization advice messages routed individually from the payment card processing network after completion of an authorization process, and c) batch files of authorization advice messages received via a file transfer protocol;

creating, for each of the received requests, a corresponding data object having a common data structure across the received requests from the plurality of input data streams, wherein each data object contains transaction data extracted from the corresponding received request;

associating each data object with an execution plan specifying a corresponding at least one of the plurality of prediction models;

invoking, for each data object, the corresponding at least one of the prediction models specified by the execution plan, wherein each prediction model operates on the transaction data in the data object and returns output data;

converting, for each of the received requests, the output data returned from the corresponding at least one prediction model for the associated data object into compatible output data in a format appropriate for transmission to one or more intended recipients; and

transmitting the compatible output data for each received request to the one or more intended recipients.

2. The computer-implemented method of claim 1 , wherein the plurality of input data streams further includes authorization log files including previously unscored transactions routed from the payment processing network.

3. The computer-implemented method of claim 1 , further comprising invoking, for the corresponding data object for each of the received requests, a transform service that determines a message transformation plug-in corresponding to the specified at least one of the prediction models.

4. The computer-implemented method of claim 3 , further comprising generating, for each corresponding data object using the corresponding plug-in, a parsed transaction data object added to the corresponding data object and corresponding to an expected data input format of the specified at least one of the prediction models.

5. The computer-implemented method of claim 4 , further comprising invoking, for each corresponding data object subsequent to adding the parsed transaction data object, an execution plan builder that generates the execution plan for the received request and adds the execution plan to the corresponding data object.

6. The computer-implemented method of claim 1 , further comprising storing, for each received request, transaction data extracted from the request in an in-memory data grid.

7. The computer-implemented method of claim 6 , wherein invoking the specified at least one of the prediction models further comprises retrieving, from the in-memory data grid, at least one of historical transaction data associated with a payment card, summarized historical trends in the historical transaction data, results of off-line analytic analysis associated with a transaction data element, and issuer-specific preferences specified by an issuer of the payment card.

8. A computer system for applying a plurality of computer-implemented prediction models to requests received via a plurality of input data streams, said computer system comprising at least one processor and a memory device in communication with the at least one processor, the at least one processor in communication with a payment card processing network, said at least one processor programmed to:

receive the requests via the plurality of input data streams, wherein the plurality of input data streams includes at least two of a) real-time authorization requests routed individually from the payment card processing network, b) authorization advice messages routed individually from the payment card processing network after completion of an authorization process, and c) batch files of authorization advice messages received via a file transfer protocol;

create, for each of the received requests, a corresponding data object having a common data structure across the received requests from the plurality of input data streams, wherein each data object contains transaction data extracted from the corresponding received request;

associate each data object with an execution plan specifying a corresponding at least one of the plurality of prediction models;

invoke, for each data object, the corresponding at least one of the prediction models specified by the execution plan, wherein each prediction model operates on the transaction data in the data object and returns a output data;

convert, for each of the received requests, the output data returned from the corresponding at least one prediction model for the associated data object into compatible output data in a format appropriate for transmission to one or more intended recipients; and

transmit the compatible output data for each received request to the one or more intended recipients.

9. The computer system of claim 8 , wherein the plurality of input data streams further includes authorization log files including previously unscored transactions routed from the payment processing network.

10. The computer system of claim 8 , wherein said at least one processor is further programmed to invoke, for the corresponding data object for each of the received requests, a transform service that determines a message transformation plug-in corresponding to the specified at least one of the prediction models.

11. The computer system of claim 10 , wherein said at least one processor is further programmed to generate, for each corresponding data object using the corresponding plug-in, a parsed transaction data object added to the corresponding data object and corresponding to an expected data input format of the specified at least one of the prediction models.

12. The computer system of claim 11 , wherein said at least one processor is further programmed to invoke, for each corresponding data object subsequent to adding the parsed transaction data object, an execution plan builder that generates the execution plan for the received request and adds the execution plan to the corresponding data object.

13. The computer system of claim 8 , wherein said at least one processor is further programmed to store, for each received request, transaction data extracted from the request in an in-memory data grid.

14. The computer system of claim 13 , wherein said at least one processor is further programmed to, in association with invoking the specified at least one of the prediction models, retrieve, from the in-memory data grid, at least one of historical transaction data associated with a payment card, summarized historical trends in the historical transaction data, results of off-line analytic analysis associated with a transaction data element, and issuer-specific preferences specified by an issuer of the payment card.

15. At least one non-transitory computer-readable medium including instructions embodied thereon for applying a plurality of computer-implemented prediction models to requests received via a plurality of input data streams, the instructions executable by at least one processor in communication with a payment card processing network to cause the at least one processor to:

receive the requests via the plurality of input data streams, wherein the plurality of input data streams includes at least two of a) real-time authorization requests routed individually from the payment card processing network, b) authorization advice messages routed individually from the payment card processing network after completion of an authorization process, and c) batch files of authorization advice messages received via a file transfer protocol;

create, for each of the received requests, a corresponding data object having a common data structure across the received requests from the plurality of input data streams, wherein each data object contains transaction data extracted from the corresponding received request;

associate each data object with an execution plan specifying a corresponding at least one of the plurality of prediction models;

invoke, for each data object, the corresponding at least one of the prediction models specified by the execution plan, wherein each prediction model operates on the transaction data in the data object and returns a output data;

convert, for each of the received requests, the output data returned from the corresponding at least one prediction model for the associated data object into compatible output data in a format appropriate for transmission to one or more intended recipients; and

transmit the compatible output data for each received request to the one or more intended recipients.

16. The at least one non-transitory computer-readable medium of claim 15 , wherein the plurality of input data streams further includes authorization log files including previously unscored transactions routed from the payment processing network.

17. The at least one non-transitory computer-readable medium of claim 15 , wherein the instructions are executable to further cause the at least one processor to invoke, for the corresponding data object for each of the received requests, a transform service that determines a message transformation plug-in corresponding to the specified at least one of the prediction models.

18. The at least one non-transitory computer-readable medium of claim 17 , wherein the instructions are executable to further cause the at least one processor to generate, for each corresponding data object using the corresponding plug-in, a parsed transaction data object added to the corresponding data object and corresponding to an expected data input format of the specified at least one of the prediction models.

19. The at least one non-transitory computer-readable medium of claim 18 , wherein the instructions are executable to further cause the at least one processor to invoke, for each corresponding data object subsequent to adding the parsed transaction data object, an execution plan builder that generates the execution plan for the received request and adds the execution plan to the corresponding data object.

20. The at least one non-transitory computer-readable medium of claim 15 , wherein the instructions are executable to further cause the at least one processor to store, for each received request, transaction data extracted from the request in an in-memory data grid.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Mar 14, 2022
From: CHISHOLM, JOHN D.
To: MASTERCARD INTERNATIONAL INCORPORATED
Reel/Frame 059259/0545 →
Continuity (5)
Continuation 16505397 · Jul 8, 2019
Continuation 14293734 · Jun 2, 2014
Continuation In Part 13364190 · Feb 1, 2012
Continuation 12271643 · Nov 14, 2008
Related Publication 20220222672A1 · Jul 14, 2022
Cited By (1)
US 12,393,949