Systems and methods for automated fraud detection and analytics using aggregated payment vehicles and devices

1. A method, implemented by a computing system using a memory and a processor, for automated fraud detection and analytics using aggregated payment vehicles and devices, the method comprising:

receiving, by the computing system over a computer network, an authorization request for a payment transaction, using a first payment vehicle;

receiving, by the computing system over the computer network, device information of a first device owned by an individual and used in the payment transaction;

retrieving, at the computing system from a transaction database of transaction data aggregated for a plurality of individuals and indexed to individuals using identifying information associated with a transaction, transaction data and identifying information associated with one or more of the authorization request, the first payment vehicle, or the first device before the authorization request is routed to a financial institution;

determining, by the computing system, whether an individual fraud detection profile associated with the retrieved identifying information exists in a profile database including identifiers of payment vehicles associated with an individual and any known devices associated with an individual;

searching, by the computing system in the transaction database, for one or more of a second payment vehicle or a second device associated with the identifying information, using the identifying information at the transaction database, based on determining the individual fraud detection profile does not exist in the profile database;

generating profile data for an individual associated with the identifying information according to aggregated transaction data associated with one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device;

automatically analyzing, using a trained aggregated fraud scoring system, the payment transaction against the generated profile data, wherein the trained aggregated fraud scoring system is trained to detect fraudulent transactions using the transaction database;

automatically determining, using the trained aggregated fraud scoring system, whether the payment transaction is a fraudulent activity based on the analyzing the payment transaction against the generated profile data, as a fraudulent activity analysis report to improve a prediction of a fraudulent transaction relative to a system that monitors buying behavior of a cardholder at an individual card level; and

responding to the authorization request for the payment transaction based on a result of the determining whether the payment transaction is a fraudulent activity.

2. The method of claim 1 , further comprising:

sending, over the computer network, as a result of determining that the payment transaction is a fraudulent activity, a notification to the financial institution for the fraudulent activity.

3. The method of claim 1 , further comprising:

storing, at a transaction database, as a result of determining that the individual's fraud detection profile does not exist, transaction data with other transaction data associated with the first payment vehicle or the first device;

aggregating, by the computing system, transaction data associated with one or more of: the first payment vehicle, the second payment vehicle, the first device, or the second device, from the transaction database;

retrieving, from the financial institution, reported fraudulent activities pertaining to the one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device; and

generating, by the computing system, a unique hash value for the generated profile data associated with the individual,

wherein the profile data for the individual is further generated according to at least one of the identifying information associated with the authorization request, personally identifiable information (PII) of the individual, and reported fraudulent activities on the one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device.

4. The method of claim 3 , further comprising, generating, at the computing system, a multidimensional score for the at least one transaction associated with the one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device.

5. The method of claim 3 , wherein the individual's profile data includes at least one of the individual's spending irregularities and fraud analysis according to the reported fraudulent activities associated with the one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device.

6. The method of claim 3 , wherein the individual's spending irregularities are calculated based on at least one of the individual's spending habits, geographic area, and type of payment vehicle.

7. The method of claim 3 , wherein the personally identifiable information (PII) comprises at least one of name, physical address, email address, or biometric information.

8. The method of claim 3 , wherein the first and second payment vehicles are debit or credit cards issued by the financial institution.

9. The method of claim 1 , further comprising, identifying, by the computing system, any fraudulent suspicion pertaining to the payment transaction to the financial institution.

10. The method of claim 1 , the transaction data comprises of at least one of a merchant's ID, transaction location and terminal information, source IP address, data and time, device information, transaction amount, and payment vehicle information.

11. The method of claim 1 , wherein the searching whether the individual fraud detection profile associated with the retrieved identifying information associated with the authorization request exists includes searching for a unique hash value associated with an individual fraud detection profile for the retrieved identifying information associated with the authorization request in the profile database.

12. The method of claim 1 , wherein the device information comprises, one or more of: an identifier of the device, passwords, user names and accounts, IP addresses, browser settings, browser history, cookies, font preferences, language preferences, and typing data.

13. A method, implemented by a computing system using a memory and a processor, for automated fraud detection and analytics using aggregated payment vehicles and devices for a household, the method comprising:

receiving, by the computing system over a computer network, an authorization request for a payment transaction, using a first payment vehicle;

receiving, by the computing system over the computer network, device information of a first device owned by a household and used in the payment transaction;

retrieving, at the computing system from a transaction database of transaction data aggregated for a plurality of individuals and indexed to individuals using identifying information associated with a transaction, transaction data and identifying information associated with one or more of the authorization request, the first payment vehicle, or the first device before the authorization request is routed to a financial institution;

searching and determining, by the computing system, whether a household fraud detection profile associated with the retrieved identifying information exists in a profile database for an individual and including identifiers of payment vehicles associated with the household and any known devices associated with the household;

if a household fraud detection profile associated with the retrieved identifying information does not exist in the profile database, storing, at the transaction database, transaction data with other transaction data associated with the first payment vehicle or first device;

searching and determining, by the computing system using the transaction database, second payment vehicles and devices associated with members of the household using retrieved identifying information associated with the authorization request in the transaction database;

generating profile data for each member of the household according to aggregated transaction data associated with one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device;

automatically analyzing, using a trained aggregated fraud scoring system, the payment transaction against the generated profile data associated with each member of the household, wherein the trained aggregated fraud scoring system is trained to detect fraudulent transactions using the transaction database;

automatically determining, using the trained aggregated fraud scoring system, whether the payment transaction is a fraudulent activity based on the analyzing the payment transaction against the generated profile data, as a fraudulent activity analysis report to improve a prediction of a fraudulent transaction relative to a system that monitors buying behavior of a cardholder at an individual card level; and

responding to the authorization request for the payment transaction based on a result of the determining whether the payment transaction is a fraudulent activity.

14. The method of claim 13 , further comprising:

aggregating, by the computing system, transaction data associated with the payment vehicles and devices from the transaction database;

retrieving, from the financial institution, reported fraudulent activities pertaining to the payment vehicles and devices;

generating, by the computing system, a unique hash value for the generated profile data associated with the members of household;

linking, by the computing system, the unique hash value for the profile data associated with the members of the household to a unique hash value for a household; and

sending, over the computer network, as a result of determining that the payment transaction is a fraudulent activity, a notification to the financial institution reporting the fraudulent activity,

wherein the profile data for each member of the household is further generated according to at least one of the identifying information associated with the authorization request, personally identifiable information (PII) of one or more members of the household, and reported fraudulent activities on the payment vehicles and devices.

15. The method of claim 14 , further comprising, generating, at the computing system, a multidimensional score to the payment transaction according to the at least one payment vehicle and at least one device associated with the household profile.

16. The method of claim 14 , further comprising, generating the household profile presenting the household member's spending irregularities and suspicious activities associated with the at least one payment vehicle or at least one device linked to the household profile.

17. A system for automated fraud detection and analytics using aggregated payment vehicles and devices, comprising:

a memory having processor-readable instructions stored therein; and

a processor configured to access the memory and execute the processor-readable instructions, which when executed by the processor configures the processor to perform a plurality of functions, including functions to:

receive, over a computer network, an authorization request for a payment transaction, using a first payment vehicle;

receive, over the computer network, device information of a first device owned by an individual and used in the payment transaction;

retrieve, from a transaction database of transaction data aggregated for a plurality of individuals and indexed to individuals using identifying information associated with a transaction, transaction data and identifying information associated with one or more of the authorization request, the first payment vehicle, or the first device, before the authorization request is routed to a financial institution;

determine whether an individual fraud detection profile associated with the retrieved identifying information exists in a profile database including identifiers of payment vehicles associated with an individual and any known devices associated with an individual;

search, in the transaction database, for one or more of a second payment vehicle or a second device associated using the identifying information at the transaction database, using the identifying information at the transaction database, based on determining the individual fraud detection profile does not exist in the profile database;

generate profile data for an individual according to aggregated transaction data associated with one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device;

automatically analyze, using a trained aggregated fraud scoring system, the payment transaction against the generated profile data, wherein the trained aggregated fraud scoring system is trained to detect fraudulent transactions using the transaction database;

automatically determine, using the trained aggregated fraud scoring system, whether the payment transaction is a fraudulent activity based on the analyzing the payment transaction against the generated profile data, as a fraudulent activity analysis report to improve a prediction of a fraudulent transaction relative to a system that monitors buying behavior of a cardholder at an individual card level; and

respond to the authorization request for the payment transaction based on a result of the determining whether the payment transaction is a fraudulent activity.

18. The system of claim 17 , wherein the processor is further configured to:

aggregate transaction data associated with one or more of: the first payment vehicle, the second payment vehicle, the first device, or the second device, from the transaction database;

retrieve, from the financial institution, reported fraudulent activities pertaining to the one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device;

generate a unique hash value for the generated profile data associated with the individual; and

send, over the computer network, as a result of determining that the payment transaction is a fraudulent activity, a notification to a web server associated with the financial institution reporting the fraudulent activity,

wherein the profile data for the individual is further generated according to at least one of the identifying information associated with the authorization request, personally identifiable information (PII) of the individual, and reported fraudulent activities on the first and the second payment vehicles.

19. The system of claim 18 , wherein the processor is further configured to generate a multidimensional score for the payment transaction associated with the one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device.

20. The system of claim 18 , wherein the analysis of the payment transaction against the profile data is according to the individual's spending irregularities and suspicious activities associated with the one or more of the first payment vehicle, the second payment vehicle, the first device, or the second device.