Systems and methods for determining thin-file records and determining thin-file risk levels

• US 8,271,378 B2
• Filed: 09/19/2011
• Issued: 09/18/2012
• Est. Priority Date: 04/12/2007
• Status: Active Grant

• Current Assignee: Experian Marketing Solutions, LLC (Experian plc)
• Original Assignee: Experian Marketing Solutions Incorporated (Experian plc)
• Inventors: Chaudhuri, Anamitra, Hadenfeldt, Nancy A., Hjermstad, Erik
• Primary Examiner(s): Kyle, Charles
• Assistant Examiner(s): MADAMBA, CLIFFORD B
• Application Number:
  US13/236,555
• Publication Number:
  US 20120158575A1
• Time in Patent Office: 365 Days
• Field of Search: 705/36, 705/38, 705/39
• US Class Current: 705/38
• CPC Class Codes: G06Q 20/10 specially adapted for electronic funds transfer [EFT] systems; specially adapted for home banking systems
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/08 Insurance

Abstract

In some embodiments, systems and methods are disclosed for generating filters to determine whether a consumer is likely to have a scoreable credit record based on non-credit data, and to determine a potential risk level associated with an unscoreable credit record based on non-credit data. Existing scoreable and unscoreable records are compared to determine factors correlated with having an unscoreable record, and a multi-level filter is developed. Unscoreable records having at least one entry are compared to determine whether they are “good” or “bad” risks, factors correlated with either condition are determined, and a filter is developed. The filters can be applied to records comprising demographic data to determine consumers that are likely to have unscoreable records but represent good risks.

Claims

1. A computing system, comprising:

a computer processor configured to access a plurality of records and configured to select a first one or more records that include less than a predetermined amount of credit data;

a thin-file propensity module executing in the computer processor and configured to;

access the selected records;

determine first demographic characteristics that are correlated to the selected records based at least on a likelihood that other records that are also associated with one or more of the first demographic characteristics include less than the predetermined amount of credit data; and

determine that a first record likely includes less than the predetermined amount of credit data based at least on matching of one or more demographic characteristics associated with the first record to the first demographic characteristics; and

a risk assessment module executing in the computer processor and configured to determine a risk score associated with the first record based at least on a demographic characteristic associated with the first record.

2. The computing system of claim 1,

wherein the first demographic characteristics comprise one or more of residence address data, age data, household data, marital status data, delinquent data for consumers in a geographic area, and data related to length of residency.

3. The computing system of claim 1,

wherein one or more of the first demographic characteristics are the same as the demographic characteristic associated with the first record that the risk score determination is based on.

4. The computing system of claim 1,

wherein each of the first demographic characteristics is different than the demographic characteristic associated with the first record that the risk score determination is based on.

5. The computing system of claim 1,

wherein the demographic characteristic associated with the first record that the risk score determination is based on is one of residence address data, age data, household data, marital status data, delinquent data for consumers in a geographic area, or data related to length of residency.

6. A method of identifying a level of risk associated with a thin-file credit record, comprising:

accessing a first set of records to select a first one or more records which include less than a predetermined amount of credit data;

determining first demographic characteristics that are correlated to the selected records based at least on a likelihood that other records that are also associated with one or more of the first demographic characteristics include less than the predetermined amount of credit data;

determining, by at least one computer processor, that a first record likely includes less than the predetermined amount of credit data based at least on matching of one or more demographic characteristics associated with the first record to the first demographic characteristics; and

determining, by at least one computer processor, a risk score associated with the first record based at least on a demographic characteristic associated with the first record.

7. The method of claim 6,

wherein each of the first demographic characteristics is different than the demographic characteristic associated with the first record that the risk score determination is based on.

8. The method of claim 6,

wherein the demographic characteristic associated with the first record that the risk score determination is based on is one of residence address data, age data, household data, marital status data, delinquent data for consumers in a geographic area, or data related to length of residency.

9. The method of claim 6,

wherein one or more of the first demographic characteristics are the same as the demographic characteristic associated with the first record that the risk score determination is based on.

10. The method of claim 6,

wherein the first demographic characteristics comprise one or more of residence address data, age data, household data, marital status data, delinquent data for consumers in a geographic area, and data related to length of residency.

11. A tangible computer-readable medium having instructions stored thereon, the instructions configured for execution by a computing system having one or more computer processors in order to cause the computing system to:

access a first set of records to select a first one or more records that include less than a predetermined amount of credit data;

determine first demographic characteristics that are correlated to the selected records based at least on a likelihood that other records that are also associated with one or more of the first demographic characteristics include less than the predetermined amount of credit data;

determine that a first record likely includes less than the predetermined amount of credit data based at least on matching of one or more demographic characteristics associated with the first record to the first demographic characteristics; and

determine a risk score associated with the first record based at least on a demographic characteristic associated with the first record.