CLIAMS:We claim:
1. A method performed by a utility providing entity for optimizing debt collection from a customer, the method comprising:
identifying a customer with a debt;
classifying the customer with the debt into one of a plurality of predefined categories based on a profile of the customer;
retrieving one or more category specific collection actions capable of being taken against the customer based on the category associated with the customer;
determining a historic probability of success and/or failure for the one or more category specific collection actions;
generating, by a processor, a decision tree having a source node, one or more intermediate nodes, and one or more destination nodes, the source node, the one or more intermediate nodes, and the one or more destination nodes representing the one or more category specific collection actions, and the source node, the one or more intermediate nodes and the one or more destination nodes constituting one or more workflows;
determining an optimal workflow from the one or more workflows on basis of maximum expected value at the source node, the maximum expected value based on cost associated with the one or more category specific collection actions and probability of success and/or failure of the one or more category specific collection actions.

2. The method of claim 1, further comprising retrieving last collection action taken subsequent to the outstanding balance.

3. The method of claim 1, wherein the source node represents the last collection action taken.

4. The method of claim 1, wherein the maximum expected value at the source node is calculated by tracing backwards from the one or more destination nodes towards the source node.

5. The method of claim 1, wherein the expected value for the one or more intermediate nodes decreases while tracing backwards from the one or more destination nodes towards the source node.

6. The method of claim 1, wherein execution of the optimal workflow comprises moving from the source node to one of the one or more destination nodes.

7. The method of claim 1, wherein the profile of the customer is generated based on at least one of a payment history data, output of a collection action, time taken to clear previous bills, payment method, and a demographic data.

8. The method of claim 1, wherein sequence of the one or more collection actions against the customer is fixed based on one or more business and legal constraints.

9. The method of claim 1, wherein the predefined category associated with the customer is dynamic and is updated continuously.

10. A system for optimizing debt collection from a customer, the system comprising:
at least one processor;
a memory coupled to the at least one processor, the memory storing instructions which when executed by the processor causes the processor to:
identify a customer with a debt;
classify the customer with the debt into one of a plurality of predefined categories based on a profile of the customer;
retrieve one or more category specific collection actions capable of being taken against the customer based on the category associated with the customer;
determine a historic probability of success and/or failure for the one or more category specific collection actions;
generate a decision tree having a source node, one or more intermediate nodes, and one or more destination nodes, the source node, the one or more intermediate nodes, and the one or more destination nodes representing the one or more category specific collection actions, and the source node, the one or more intermediate nodes and the one or more destination nodes constituting one or more workflows;
determine an optimal workflow from the one or more workflows on basis of maximum expected value at the source node, the maximum expected value based on the cost associated with the one or more category specific collection actions and probability of success and/or failure of the one or more category specific collection actions.

11. The system of claim 10, wherein a last collection action taken is retrieved subsequent to the outstanding balance.

12. The system of claim 10, wherein the source node represents the last collection action taken.

13. The system of claim 10, wherein the maximum expected value at the source node is calculated by tracing backwards from the one or more destination nodes towards the source node.

14. The system of claim 10, wherein the expected value for the one or more intermediate nodes decreases while tracing backwards from the one or more destination nodes towards the source node.

15. The system of claim 10, wherein execution of the optimal workflow comprises moving from the source node to one of the one or more destination nodes.

16. The system of claim 10, wherein the profile of the customer is generated based on at least one of a payment history data, output of a collection action, time taken to clear previous bills, payment method, and a demographic data.

17. The system of claim 10, wherein sequence of the one or more collection actions against the customer is fixed based on one or more business and legal constraints.

18. The system of claim 10, wherein the predefined category associated with the customer is dynamic and is updated continuously.

Dated this 5th day of February 2014
R. Ramya Rao
Of K&S Partners
Agent for the Applicant
,TagSPECI:TECHNICAL FIELD
This disclosure relates generally to water utility entities, and more particularly to method and system for optimal debt collection from a customer.