Technology system for assisting financial institutions in debt collection

A computer implemented method for assisting financial institutions in debt collection, said method being performed in a digital processing system, said method comprising:

• maintaining in a memory of said digital processing system, an account data specifying account attributes of a plurality of accounts, said account data indicating a specific set of accounts of said plurality of accounts as being delinquent;
• receiving via a user interface module, a feature set comprising a set of account attributes of said account attributes;
• providing in said digital processing system a first machine learning (ML) approach and a second ML approach by execution of corresponding instructions;
• clustering, by an account segmentation module using said first ML approach, said plurality of accounts to determine a set of groups, wherein said first ML approach operates to group accounts based on said account attributes while giving higher weightage to said set of account attributes, each group of said set of groups being associated with a respective set of group qualifiers, each group qualifier specifying a corresponding range of values for a respective attribute of said account attributes;
• generating, by an agent assignment module using said second ML approach, a multi-classification model for assignment of a plurality of agents to respective accounts, wherein said second ML approach correlates a set of recovery attributes of each agent and said respective set of group qualifiers, while giving higher weightage to said set of account attributes contained in said feature set;
• identifying by said account segmentation module, a target group of said set of groups likely to present problems with debt collection, wherein said target group contains a material number of said specific set of accounts indicated to be delinquent and a subset of accounts which are indicated not to be delinquent in said account data;
• assigning, by said agent assignment module using said multi-classification model, a corresponding agent for each account in said subset of accounts;
• determining, by a strategy recommendation module, a recommended recovery strategy for each assignment of corresponding agent and account contained in said subset of accounts;
• and
• providing details of said subset of accounts, said corresponding agent assigned to each of said subset of accounts and said recommended recovery strategy for each assignment.

A digital processing system comprising:

• a random access memory (RAM) to store instructions for assisting financial institutions in debt collection;
• and
• one or more processors to retrieve and execute the instructions, wherein execution of the instructions causes the digital processing system to perform the actions of:
• maintaining an account data specifying account attributes of a plurality of accounts, said account data indicating a specific set of accounts of said plurality of accounts as being delinquent;
• receiving a feature set comprising a set of account attributes of said account attributes;
• clustering, using a first machine learning (ML) approach, said plurality of accounts to determine a set of groups, wherein said first ML approach operates to group accounts based on said account attributes while giving higher weightage to said set of account attributes, each group of said set of groups being associated with a respective set of group qualifiers, each group qualifier specifying a corresponding range of values for a respective attribute of said account attributes,
• wherein a first clustering ML approach is used as said first ML approach if a desired count of a number of groups in said set of groups is received with said feature set, and a second clustering ML approach is used if said desired count is not received;
• generating, using a second ML approach, a multi-classification model for assignment of a plurality of agents to respective accounts, wherein said second ML approach correlates a set of recovery attributes of each agent and said respective set of group qualifiers, while giving higher weightage to said set of account attributes contained in said feature set;
• identifying a target group of said set of groups containing a material number of said specific set of accounts indicated to be delinquent and a subset of accounts which are indicated not to be delinquent in said account data;
• assigning, using said multi-classification model, a corresponding agent for each account in said subset of accounts;
• determining a recommended recovery strategy for each assignment of corresponding agent and account contained in said subset of accounts;
• and
• providing details of said subset of accounts, said corresponding agent assigned to each of said subset of accounts and said recommended recovery strategy for each assignment.