System and method for automated detection of never-pay data sets

US9251541B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9251541-B2
Application numberUS-201213718004-A
CountryUS
Kind codeB2
Filing dateDec 18, 2012
Priority dateMay 25, 2007
Publication dateFeb 2, 2016
Grant dateFeb 2, 2016

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  1. Title

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  2. Abstract

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  3. Assignees and inventors

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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  7. Citations and related patents

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Abstract

Official abstract text for this publication.

Data filters, models, and/or profiles for identifying and/or predicting the never-pay population (for example, those customers that make a request for credit and obtain the credit instrument but over the life of the account, never make a payment) can be useful to various commercial entities, such as those issuing mortgages, home equity lines of credit, consumer or business lines of credit, automobile loans, credit card accounts, or those entities providing services, such as utility services, phone services, and the like.

First claim

Opening claim text (preview).

What is claimed is: 1. A computerized method comprising: receiving, by a server computer through a communication link, data associated with application of a credit line during the application stage; analyzing, by the server computer, the data for predictive variables for use in a model for calculating a party fraud score, wherein the predictive variables include at least one of: previously unpaid debt obligation, recent bankruptcy, or high number of recent delinquencies on one or more credit lines; analyzing data associated with one or more previously flagged, existing credit lines for elements to be used in the model for calculating the first party fraud score; transmitting, from the server computer to a remote computer through a communication link that renders a graphical user interface on a display device of the remote computer, an electronic indication regarding the credit line when at least one or more of the predictive variables or the elements analyzed cause the first party fraud score to exceed a pre-described fraud likelihood threshold, wherein the first party fraud score is indicative of a propensity to never make payment on the credit line, and wherein the indication regarding the credit line is used to make a real-time decision regarding approval or denial of the credit line application. 2. The computerized method of claim 1 wherein the elements associated with analyzing data associated with one or more previously flagged, existing credit lines includes tradeline data. 3. The computerized method of claim 1 wherein analyzing data for predictive variables includes profiling of at least one entity associated with the application of the credit line. 4. The computerized method of claim 1 wherein the elements associated with analyzing data associated with one or more previously flagged, existing credit lines includes computed variables. 5. The computerized method of claim 1 wherein analyzing the data for predictive variables includes analyzing information provided by an entity applying for the credit line for false information. 6. The computerized method of claim 1 further comprising analyzing data associated with the credit line during a selected, initial time period after approving the credit line. 7. The computerized method of claim 6 wherein analyzing the data associated with the credit line during the selected, initial time period after approving the credit line includes analyzing a number of payments made on the credit line. 8. The computerized method of claim 6 wherein analyzing the data associated with the credit line during the selected, initial time period after approving the credit line includes analyzing a size of payments made on the credit line. 9. The computerized method of claim 6 wherein analyzing the data associated with the credit line during the selected, initial time period after approving the credit line includes analyzing information of associated credit and loan accounts. 10. The computerized method of claim 6 wherein analyzing the data associated with the credit line during the selected, initial time period after approving the credit line includes analyzing information associated with customers associated with the credit line. 11. The computerized method of claim 6 wherein analyzing the data associated with the credit line during the selected, initial time period after approving the credit line includes analyzing an amount of the credit. 12. The computerized method of claim 6 wherein analyzing the data associated with the credit line during the selected, initial time period after approving the credit line includes analyzing customer information. 13. The computerized method of claim 11 wherein a payment on the account has been received. 14. The computerized method of claim 11 wherein a payment on the account has been received, and the payment has not yet cleared. 15. The computerized method of claim 6 wherein analyzing data associated with the credit line during the selected, initial time period after approving the credit line includes analyzing the transactions associated with a customer and one or more credit lines. 16. The computerized method of claim 6 wherein analyzing data associated with the credit line during the selected, initial time period after approving the credit line includes creation of transaction profile variables associated with the credit line and customer profiles. 17. The computerized method of claim 1 further comprising attempting to electronically contact an entity associated with the credit line. 18. The computerized method of claim 1 further compromising merging the first party fraud score with a second first party fraud score associated with the application. 19. The computerized method of claim 1 wherein analyzing data associated with one or more previously flagged, existing credit lines includes searching for a condition where there is a request for an increase in a credit limit associated with the one or more credit lines.

Assignees

Inventors

Classifications

  • Buying, selling or leasing transactions · CPC title

  • G06Q40/03Primary

    Credit; Loans; Processing thereof · CPC title

  • G06Q40/00Primary

    Finance; Insurance; Tax strategies; Processing of corporate or income taxes · CPC title

  • specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems · CPC title

  • G06Q40/025Primary

    Physics · mapped topic

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Frequently asked questions

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What does patent US9251541B2 cover?
Data filters, models, and/or profiles for identifying and/or predicting the never-pay population (for example, those customers that make a request for credit and obtain the credit instrument but over the life of the account, never make a payment) can be useful to various commercial entities, such as those issuing mortgages, home equity lines of credit, consumer or business lines of credit, auto…
Who is the assignee on this patent?
Experian Inf Solutions Inc
What technology area does this patent fall under?
Primary CPC classification G06Q40/03. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Feb 02 2016 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 1 related publication on this page (citations in our corpus or others sharing the same primary CPC).