公开(公告)号：EP4236197A2

公开(公告)日：2023-08-30

申请号：EP23171107.8

申请日：2020-02-17

申请人： ADP, Inc.

发明人： SILVEIRA, Roberto ,  PEREIRA, Fabiano ,  SILVA, Leandro ,  FRANTZ, Matheus ,  CARVALHO, Daniel ,  HARTMANN, Julio ,  MOURA, Bruno ,  CASTRO, Iury ,  BOSCAINI, Lucas ,  PRIMAZ, Ezequiel

IPC分类号： H04L9/32

摘要： The invention is directed to a method for facilitating micro-loan transactions, comprising: aggregating human capital management information; scrubbing the dataset; dividing the data into training data and test data to be used for building and testing a predictive model; constructing the predictive model; using the predictive model to calculate predicted borrower-users and lender-users and populating a database with the predicted values; converting the predicted values into integrity scores to form an index representing predicted borrower-users and lender-users, wherein the integrity scores are updated based on user feedback; receiving (1720) a loan transaction request (228) from a borrower-user (210); determining (1730) a risk score (230) for the loan transaction based at least on the borrower-user (210)'s integrity score (222); identifying (1740) a set of lender-users (212) based on the determined risk score (230) and the lender-users (212)' integrity scores (222); facilitating (1750) a negotiation of transaction terms (238) between the borrower-user (210) and the set of lender-users (212) to determine the transaction terms (238); responsive to finalization of the transaction terms (238), recording (1760) the loan transaction and the transaction terms (238) in a blockchain, and remitting loan funds to the borrower-user (210); responsive to a subsequent repayment of the loan transaction according to the transaction terms (238), soliciting (1770) peer-submitted feedback (226) from at least one of the borrower-user (210) and the set of lender-users (212); and updating (1780) the integrity score (222) for the borrower-¬user (210) and the set of lender-users (212) based on received peer-submitted feedback (226) regarding the loan transaction.

公开(公告)号：EP4236197A3

公开(公告)日：2023-10-25

申请号：EP23171107.8

申请日：2020-02-17

申请人： ADP, Inc.

发明人： SILVEIRA, Roberto ,  PEREIRA, Fabiano ,  SILVA, Leandro ,  FRANTZ, Matheus ,  CARVALHO, Daniel ,  HARTMANN, Julio ,  MOURA, Bruno ,  CASTRO, Iury ,  BOSCAINI, Lucas ,  PRIMAZ, Ezequiel

IPC分类号： G06Q40/03 ,  H04L9/32 ,  G06N3/006 ,  G06N3/126 ,  G06N20/00 ,  G06N7/01

摘要： The invention is directed to a method for facilitating micro-loan transactions, comprising: aggregating human capital management information; scrubbing the dataset; dividing the data into training data and test data to be used for building and testing a predictive model; constructing the predictive model; using the predictive model to calculate predicted borrower-users and lender-users and populating a database with the predicted values; converting the predicted values into integrity scores to form an index representing predicted borrower-users and lender-users, wherein the integrity scores are updated based on user feedback; receiving (1720) a loan transaction request (228) from a borrower-user (210); determining (1730) a risk score (230) for the loan transaction based at least on the borrower-user (210)'s integrity score (222); identifying (1740) a set of lender-users (212) based on the determined risk score (230) and the lender-users (212)' integrity scores (222); facilitating (1750) a negotiation of transaction terms (238) between the borrower-user (210) and the set of lender-users (212) to determine the transaction terms (238); responsive to finalization of the transaction terms (238), recording (1760) the loan transaction and the transaction terms (238) in a blockchain, and remitting loan funds to the borrower-user (210); responsive to a subsequent repayment of the loan transaction according to the transaction terms (238), soliciting (1770) peer-submitted feedback (226) from at least one of the borrower-user (210) and the set of lender-users (212); and updating (1780) the integrity score (222) for the borrower-¬user (210) and the set of lender-users (212) based on received peer-submitted feedback (226) regarding the loan transaction.