Adverse action methodology for credit risk models
US11475515B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Oct 11, 2019 |
| Grant date | Oct 18, 2022 |
| Priority date | — |
| Expiry date | Oct 11, 2039 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06Q30/0201
- WIPO fieldIT methods for management
- WIPO sectorElectrical engineering
Abstract
A computer-based credit evaluation system is described that uses a machine learning-based credit risk model with an adverse action methodology to assess applicant credit profiles and identify adverse action factors for credit request denials. The credit risk model is trained to assess an applicant's credit profile based on characteristics. In the case of a denial, the system compares applicant values of the characteristics against anchor values for the characteristics determined based on values from a top scoring credit profile. The system uses the credit risk model to calculate a replacement score for each of the characteristics by replacing the applicant value for the characteristic with an anchor value for the characteristic. The system ranks the characteristics based on the replacement scores, and identifies the top ranked characteristics as the adverse action factors for the denial.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.