公开(公告)号：US20160189293A1

公开(公告)日：2016-06-30

申请号：US14979736

申请日：2015-12-28

Applicant: LexisNexis Risk Solutions FL Inc.

Inventor： James Christiansen ,  Eric Graves ,  Lea Smith ,  Darrin Udean

IPC: G06Q40/02

CPC classification number: G06Q40/025

Abstract: Certain implementations of the disclosed technology may include systems, methods, and apparatus for inferring the performance of rejected credit applicants using non-tradeline data. According to an example implementation, a method is provided for evaluating factors that may indicate financial distress and/or future credit performance associated with an applicant. In an example implementation, the method may include receiving applicant information associated with an applicant of a credit application. Responsive to a query, the method may include receiving by at least one processor, non-tradeline data related to the applicant. The method includes scoring, using a predictive scoring model, and based at least in part on the non-tradeline data, a prediction of the applicant's future credit performance. The method includes generating, based on the scoring, an estimated credit performance of the applicant over a predetermined period; and outputting an indication of the estimated credit performance.

Abstract translation: 所公开技术的某些实现可以包括用于使用非交易数据推断拒绝的信用申请人的表现的系统，方法和装置。 根据示例实现，提供了一种用于评估可能指示与申请人相关联的财务困境和/或未来信用绩效的因素的方法。 在示例实现中，该方法可以包括接收与信用申请的申请人相关联的申请人信息。 响应于查询，该方法可以包括由至少一个处理器接收与申请人相关的非业务数据。 该方法包括评分，使用预测评分模型，并且至少部分地基于非交易数据，预测申请人未来的信用绩效。 该方法包括基于得分，在预定时间内生成申请人的估计信用表现; 并输出所估计的信用表现的指示。

公开(公告)号：US10223746B2

公开(公告)日：2019-03-05

申请号：US14979736

申请日：2015-12-28

Applicant: LexisNexis Risk Solutions FL Inc.

Inventor： James Christiansen ,  Eric Graves ,  Lea Smith ,  Darrin Udean

IPC: G06Q40/02

Abstract: Certain implementations of the disclosed technology may include systems, methods, and apparatus for inferring the performance of rejected credit applicants using non-tradeline data. According to an example implementation, a method is provided for evaluating factors that may indicate financial distress and/or future credit performance associated with an applicant. In an example implementation, the method may include receiving applicant information associated with an applicant of a credit application. Responsive to a query, the method may include receiving by at least one processor, non-tradeline data related to the applicant. The method includes scoring, using a predictive scoring model, and based at least in part on the non-tradeline data, a prediction of the applicant's future credit performance. The method includes generating, based on the scoring, an estimated credit performance of the applicant over a predetermined period; and outputting an indication of the estimated credit performance.