EXPERT ENGINE TIER FOR ADAPTING TRANSACTION-SPECIFIC USER REQUIREMENTS AND TRANSACTION RECORD HANDLING

• US 20140129430A1
• Filed: 01/14/2014
• Published: 05/08/2014
• Est. Priority Date: 10/06/2005
• Status: Active Grant

• Current Assignee: Mastercard Mobile Transactions Solutions, Inc. (MasterCard Incorporated)
• Original Assignee: C-SAM Incorporated (MasterCard Incorporated)
• Inventors: Desai, Mehul, Pitroda, Satyan G., Maniar, Nehal
• Granted Patent: US 10,096,025 B2
• Time in Patent Office: Days
• US Class Current: 705/39
• CPC Class Codes: G06F 8/65 Updates security arrangements therefor G06F21/57
• CPC Class Codes: G06Q 20/08 Payment architectures
• CPC Class Codes: G06Q 20/105 involving programming of a portable memory device, e.g. IC cards, "electronic purses"
• CPC Class Codes: G06Q 20/322 Aspects of commerce using mobile devices [M-devices]
• CPC Class Codes: G06Q 20/36 using electronic wallets or electronic money safes
• CPC Class Codes: G06Q 20/3674 involving authentication
• CPC Class Codes: G06Q 20/382 insuring higher security of transaction
• CPC Class Codes: G06Q 20/3829 involving key management
• CPC Class Codes: G06Q 20/40 Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0641 Shopping interfaces

Abstract

In a platform comprising a service tier, an enabling tier, and a personalization tier, applying an expert engine to analyze one or more mobile device user and transaction environment requirements and configuring one or more platform features in accordance with the analysis.

Claims

1. A method, comprising:

accessing with an expert engine facility that is executing on a computer configuration data for at least one of a service tier and a personalization tier of a multi-tier platform configured with each of a service tier, a personalization tier, and an enabling tier, the platform adapted to perform secure personalized transactions in a multi-domain computing ecosystem comprising a plurality of service provider computers;

accessing with the expert engine one or more of user requirements and transaction environment requirements for a plurality of secure personalized transactions;

accessing with the expert engine service provider data representing service provider-specific aspects for a portion of the plurality of service providers;

analyzing with the expert engine the accessed configuration data, requirements, ecosystem data, and service provider data in context of one of the plurality of secure personalized transactions;

adapting with the expert engine a least one of a service tier and a personalization tier for the one of the plurality of secure personalized transactions to produce at least one of an expertly adapted service tier and an expertly adapted personalization tier based on a result of analyzing the accessed configuration data, requirements, ecosystem data, and service provider data; and

facilitating performance of the one of the plurality of secure personalized transactions with the at least one of an expertly adapted service tier and an expertly adapted personalization tier.

2. The method of claim 1, further comprising accessing with the expert engine computing ecosystem data representing at least one of ecosystem status and ecosystem size.

3. The method of claim 1, wherein the ecosystem comprises at least ten million participants and wherein the platform facilitates simultaneously performing at least one thousand secure personalized transactions.

4. The method of claim 1, wherein facilitating performance of the one of the plurality of secure personalized transactions comprises the expert engine ensuring the transaction seamlessly resumes operation following an ecosystem operational interruption.

5. The method of claim 4, wherein the ecosystem operational interruption comprises at least one of communication breakdown, server response delay, mobile device battery rundown, and mobile device signal drop.

6. The method of claim 1, wherein adapting at least one of a service tier and a personalization tier comprises accommodating one or more of user habits, user preferences, regional preferences, mobile device capabilities, and economic base differences of a user participating in the one of the plurality of secure personalized transactions.

7. The method of claim 1, wherein analyzing the accessed configuration data, requirements, ecosystem data, and service provider data includes determining usage patterns associated with at least one of the service tier and the personalization tier.

8. The method of claim 1, wherein analyzing the requirements includes analyzing transaction environment aspects, user history aspects, user environment aspects, historical transaction-related data aspects, and device related aspects.

9. The method of claim 1, wherein analyzing the ecosystem data comprises analyzing at least two of responsiveness within the ecosystem, stability of the ecosystem, a count of enrolled ecosystem participants, and a measure of ecosystem transaction activity.

10. A method comprising:

in a platform comprising a service tier, an enabling tier, and a personalization tier, applying an expert engine to analyze one or more mobile device user and transaction environment requirements; and

configuring one or more platform features in accordance with the analysis.

11. The method of claim 10, wherein configuring the one or more ecosystem features includes configuring a user interface based on one or more transaction requirements.

12. The method of claim 10, wherein the expert engine comprises an expert engine tier.

13. The method of claim 12, wherein the expert engine tier interacts with an experience framework to adapt at least one of the enabling tier, the service tier, and the personalization tier.

14. The method of claim 13, wherein applying the expert engine comprises applying the expert engine to analyze a user'"'"'s habits.

15. The method of claim 10, wherein configuring one or more ecosystem features comprises configuring one or more display features of a mobile device.

16. The method of claim 15, wherein the one or more display features are configured based, at least in part, upon a regional preference associated with a location of the mobile device.

17. The method of claim 15, wherein the one or more display features are configured based, at least in part, upon an identified client base.

18. The method of claim 17, wherein the one or more display features are configured based, at least in part, upon a regional preference of the identified client base.

19. The method of claim 17, wherein the one or more display features are configured based, at least in part, upon an economic aspect of the identified client base.