Invention Grant
- Patent Title: Enhancing delinquent debt collection using statistical models of debt historical information and account events
- Patent Title (中): 使用债务历史信息和账户事件的统计模型加强违规收债
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Application No.: US11683976Application Date: 2007-03-08
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Publication No.: US07536348B2Publication Date: 2009-05-19
- Inventor: Min Shao , Scott Zoldi , Gordon Cameron , Ron Martin , Radu Drossu , Jenny (Guofeng) Zhang , Daniel Shoham
- Applicant: Min Shao , Scott Zoldi , Gordon Cameron , Ron Martin , Radu Drossu , Jenny (Guofeng) Zhang , Daniel Shoham
- Applicant Address: US MN Minneapolis
- Assignee: Fair Isaac Corporation
- Current Assignee: Fair Isaac Corporation
- Current Assignee Address: US MN Minneapolis
- Agency: Mintz Levin Cohn Ferris Glovsky and Popeo, P.C.
- Main IPC: G06Q40/00
- IPC: G06Q40/00

Abstract:
A predictive model, for example, a neural network, evaluates individual debt holder accounts and predicts the amount that will be collected on each account based on learned relationships among known variables. The predictive model is generated using historical data of delinquent debt accounts, the collection methods used to collect the debts in the accounts, and the success of the collection methods. In one embodiment, the predictive model is generated using profiles of delinquent debt accounts summarizing patterns of events in the accounts, and the success of the collection effort in each account. In another embodiment, the predictive model includes a mathematical representation of the collector's notes created during the collection period for each account.
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