IP Library › Granted Patent US 11,276,066
Granted Patent B2
US 11,276,066 · App. 16/505,397 · Granted Mar 15, 2022

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 11,276,066
App. No.
16/505,397
Granted
Mar 15, 2022
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 (43)

1. A computer-implemented method for providing enriched transaction data for real-time fraud scoring of a plurality of transactions by a plurality of scoring models, each scoring model having an expected data input format, each transaction requiring a real-time authorization decision by an authorizing third party, said method performed by a computer system comprising a processor and a memory device in communication with the processor, the computer system in communication with a payment card processing network, said method comprising:

receiving, from a plurality of computing devices of a plurality of requesting parties, scoring request messages each associated with a candidate transaction initiated by a customer, each scoring request message including transaction data for the candidate transaction;

creating, for each scoring request message, an internal message object;

invoking, for each internal message object, a transform service, wherein the transform service determines a message transformation plug-in corresponding to one of the plurality of scoring models;

generating, for each internal message object using the corresponding message transformation plug-in, a parsed transaction data object corresponding to the expected data input format of the corresponding scoring model, wherein the parsed transaction data object includes at least a portion of the transaction data and is added to the internal message object;

invoking, for each internal message object subsequent to adding the parsed transaction data object, an execution plan builder, wherein the execution plan builder generates an execution plan for the candidate transaction and adds the execution plan to the internal message object, wherein the execution plan specifies the corresponding scoring model;

invoking, for each internal message object subsequent to adding the execution plan, the scoring model specified by the execution plan, wherein the scoring model operates on the transaction data included in the parsed transaction data object and returns a fraud score;

enriching, for each transaction, the transaction data by adding the fraud score to the transaction data; and

transmitting, for each transaction, the enriched transaction data to the authorizing third party for making the real-time authorization decision.

2. The computer-implemented method of claim 1 further comprising storing, for each transaction, the transaction data in an in-memory data grid.

3. The computer-implemented method of claim 2 , wherein storing the transaction data in the in-memory data grid further comprises storing the transaction data including at least one of financial transaction data, healthcare transaction data, and personal identity transaction data.

4. The computer-implemented method of claim 2 , wherein storing the transaction data in the in-memory data grid further comprises storing financial transaction data including an account number and is associated with a purchase made by a cardholder using a payment card.

5. The computer-implemented method of claim 2 , wherein storing the transaction data in the in-memory data grid further comprises storing the transaction data in one of an in-memory object grid and an in-memory database.

6. The computer-implemented method of claim 2 , wherein storing the transaction data in the in-memory data grid further comprises storing the transaction data received from an input channel including at least one of an interchange network, and a web-based network such as the Internet.

7. The computer-implemented method of claim 2 , wherein invoking the scoring model 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 providing enriched transaction data for real-time fraud scoring of a plurality of transactions by a plurality of scoring models, each scoring model having an expected data input format, each transaction requiring a real-time authorization decision by an authorizing third party, the computer system comprising a processor and a memory device in communication with the processor, the computer system in communication with a payment card processing network, the computer system configured to:

receive, from a plurality of computing devices of a plurality of requesting parties, scoring request messages each associated with a candidate transaction initiated by a customer, each scoring request message including transaction data for the candidate transaction;

create, for each scoring request message, an internal message object;

invoke, for each internal message object, a transform service, wherein the transform service determines a message transformation plug-in corresponding to one of the plurality of scoring models;

generate, for each internal message object using the corresponding message transformation plug-in, a parsed transaction data object corresponding to the expected data input format of the corresponding scoring model, wherein the parsed transaction data object includes at least a portion of the transaction data and is added to the internal message object;

invoke, for each internal message object subsequent to adding the parsed transaction data object, an execution plan builder, wherein the execution plan builder generates an execution plan for the candidate transaction and adds the execution plan to the internal message object, wherein the execution plan specifies the corresponding scoring model;

invoke, for each internal message object subsequent to adding the execution plan, the scoring model specified by the execution plan, wherein the scoring model operates on the transaction data included in the parsed transaction data object and returns a fraud score;

enrich, for each transaction, the transaction data by adding the fraud score to the transaction data; and

transmit, for each transaction, the enriched transaction data to the authorizing third party for making the real-time authorization decision.

9. The computer system of claim 8 further configured to store, for each transaction, the transaction data in an in-memory data grid.

10. The computer system of claim 9 , wherein storing the transaction data in the in-memory data grid further comprises storing the transaction data including at least one of financial transaction data, healthcare transaction data, and personal identity transaction data.

11. The computer system of claim 9 , wherein storing the transaction data in the in-memory data grid further comprises storing financial transaction data including an account number and is associated with a purchase made by a cardholder using a payment card.

12. The computer system of claim 9 , wherein storing the transaction data in the in-memory data grid further comprises storing the transaction data in one of an in-memory object grid and an in-memory database.

13. The computer system of claim 9 , wherein storing the transaction data in the in-memory data grid further comprises storing the transaction data received from an input channel including at least one of an interchange network, and a web-based network such as the Internet.

14. The computer system of claim 8 , wherein invoking the scoring model 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.

15. One or more non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor, the computer-executable instructions cause the at least one processor to:

receive, from a plurality of computing devices of a plurality of requesting parties, scoring request messages each associated with a candidate transaction initiated by a customer, each scoring request message including transaction data for the candidate transaction;

create, for each scoring request message, an internal message object;

invoke, for each internal message object, a transform service, wherein the transform service determines a message transformation plug-in corresponding to one of a plurality of scoring models;

generate, for each internal message object using the corresponding message transformation plug-in, a parsed transaction data object corresponding to an expected data input format of the corresponding scoring model, wherein the parsed transaction data object includes at least a portion of the transaction data and is added to the internal message object;

invoke, for each internal message object subsequent to adding the parsed transaction data object, an execution plan builder, wherein the execution plan builder generates an execution plan for the candidate transaction and adds the execution plan to the internal message object, wherein the execution plan specifies the corresponding scoring model;

invoke, for each internal message object subsequent to adding the execution plan, the scoring model specified by the execution plan, wherein the scoring model operates on the transaction data included in the parsed transaction data object and returns a fraud score;

enrich, for each transaction, the transaction data by adding the fraud score to the transaction data; and

transmit, for each transaction, the enriched transaction data to an authorizing third party for making a real-time authorization decision.

16. The computer-readable storage media of claim 15 further configured to store, for each transaction, the transaction data in an in-memory data grid.

17. The computer-readable storage media of claim 16 , wherein storing the transaction data in the in-memory data grid further comprises storing the transaction data including at least one of financial transaction data, healthcare transaction data, and personal identity transaction data.

18. The computer-readable storage media of claim 16 , wherein storing the transaction data in the in-memory data grid further comprises storing financial transaction data including an account number and is associated with a purchase made by a cardholder using a payment card.

19. The computer-readable storage media of claim 16 , wherein storing the transaction data in the in-memory data grid further comprises storing the transaction data in one of an in-memory object grid and an in-memory database.

Assignments (1)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 8, 2019
From: CHISHOLM, JOHN D.
To: MASTERCARD INTERNATIONAL INCORPORATED
Reel/Frame 049692/0104 →
Continuity (4)
Continuation 14293734 · Jun 2, 2014
Continuation In Part 13364190 · Feb 1, 2012
Continuation 12271643 · Nov 14, 2008
Related Publication 20200005313A1 · Jan 2, 2020
Cited By (1)
US 12,393,949