发明名称 METHODS AND SYSTEMS FOR AUTOMATICALLY GENERATING HIGH QUALITY ADVERSE ACTION NOTIFICATIONS
摘要 This invention relates generally to the personal finance and banking field, and more particularly to the field of lending and credit notification methods and systems. Preferred embodiments of the present invention provide systems and methods for automatically generating high quality adverse action notifications based on identifying variations between a declined borrower's profile and that of approved applicants, both with simple and sophisticated credit scoring systems, using specific algorithms.
申请公布号 US2016155193(A1) 申请公布日期 2016.06.02
申请号 US201514954825 申请日期 2015.11.30
申请人 ZESTFINANCE, INC. 发明人 Merrill John W.L.;Budde Shawn M.;Candido John;Gu Lingyun;Kheiri Farshad;McGuire James P.;Merrill Douglas C.;Pinnamaneni Manoj;Sinay Marick
分类号 G06Q40/02 主分类号 G06Q40/02
代理机构 代理人
主权项 1. A central computer server communicatively coupled to a public network, the central computer server having a non-transitory computer-usable medium with a sequence of instructions which, when executed by a processor, causes said processor to execute an electronic process that automatically generates high quality adverse action notifications, said process comprising: collecting an electronic dataset for a borrower which contains a credit score and a plurality of variables and meta-variables that describe specific aspects of the borrower to generate a borrower profile; independently and collectively processing the plurality of variables and meta-variables in the borrower dataset against a lender's criteria for creditworthiness; identifying sets of variables and meta-variables in the borrower profile that, when changed, result in an improved measure of creditworthiness, wherein the identifying step includes analyzing at least one shortest path between the borrower dataset and the dataset of at least one of: (i) a perfect applicant and (ii) an average approved applicant; and generating a report that interprets the at least one shortest path, and variables and meta-variables therein, into plain language through which the borrower may understand how to improve the borrower's credit score.
地址 Los Angeles CA US