公开(公告)号：US20240354786A1

公开(公告)日：2024-10-24

申请号：US18305483

申请日：2023-04-24

申请人： HIGHRADIUS CORPORATION

发明人： Anupam Kunwar ,  Apoorva Shrivastava ,  Sayanta Mukherjee ,  Rohit Haldar ,  Maitreya Mohapatra ,  Vineet Kumar Gupta

IPC分类号： G06Q30/0202 ,  G06N5/022

CPC分类号： G06Q30/0202 ,  G06N5/022

摘要： A system and method for predicting financial transaction patterns is disclosed. The method includes receiving invoice data of one or more customers. The method further includes receiving granularity levels, thereby generating a set granularity level instances based on various invoice data attributes. The method further computes payment frequency bucket features for all the generated set of granularity level instances and assigns invoices to clusters based on the set of payment frequency bucket features. The set of payment frequency bucket features assigns a customer to be one of: a weekly payer, alternative weekly payer, a monthly payer, a bi-monthly, a quarterly payer, a half yearly payer and an annual payer. The method further includes the generation of a set of payment pattern features based on the set of payment frequency bucket features of the cluster. Further, the method includes selection of an optimal pattern with highest probability of adherence.

公开(公告)号：US20230342793A1

公开(公告)日：2023-10-26

申请号：US18306278

申请日：2023-04-25

申请人： HIGHRADIUS CORPORATION

发明人： Anupam Kunwar ,  Glen George ,  Apoorva Shrivastava ,  Sayanta Mukherjee ,  Shailly Shailja

IPC分类号： G06Q30/0201

CPC分类号： G06Q30/0201

摘要： A Machine Learning (ML)-based computing system and method for financial transaction based customer worklist generation is disclosed. A data determination module configured to obtain a credit sale amount, an account receivable as of a run date of the module (RD), a disputed invoice amount and a skipped invoice amount using an Machine Learning (ML) model. A DSO component calculation module configured to calculate the obtained DSO components for each entity corresponding to a grouping category at a given point of time period. A DSO impact score generation module configured to generate a DSO impact score based on the estimated open amount reduction, desired number of days in period and the credit sale amount. A Machine Learning insight module configured to calculate the generated DSO impact score based on historical customer information associated with one or more customers. A data output module configured to output the DSO impact score.

公开(公告)号：US20230342738A1

公开(公告)日：2023-10-26

申请号：US18306281

申请日：2023-04-25

申请人： HIGHRADIUS CORPORATION

发明人： Anupam Kunwar ,  Glen George ,  Apoorva Shrivastava ,  Sayanta Mukherjee ,  Shailly Shailja

IPC分类号： G06Q20/10 ,  G06Q30/04

CPC分类号： G06Q20/102 ,  G06Q30/0204 ,  G06Q40/03 ,  G06Q30/04 ,  G06Q10/0635

摘要： A Machine Learning (ML)-based computing system and method for customer segmentation and collections worklist generation is disclosed. The method includes data receiver module configured to receive one or more open invoices from one or more electronic devices associated with a user. Further, the method includes data processing module configured to process the received one or more open invoices. Further, the method includes segment clustering module configured to determine a payment behaviour and customer risk. Further, the method includes worklist generation module configured to generate a customer worklist. Further, the method includes action recommendation module configured to recommend one or more collection strategies. Further, the method includes prioritization module configured to rank each of the one or more customers in the generated worklist. Furthermore, the method includes the data output module configured to output the one or more collection strategies and the ranked one or more customers.