Method and system for predicting attrition customers

• US 20050097028A1
• Filed: 05/24/2004
• Published: 05/05/2005
• Est. Priority Date: 05/22/2003
• Status: Abandoned Application

• Current Assignee: Pershing Investments, LLC (Bank of New York Mellon Corporation)
• Original Assignee: Pershing Investments, LLC (Bank of New York Mellon Corporation)
• Inventors: Reddy, Praveen, Yip, Patrick, Watanabe, Larry
• Application Number:
  US10/851,646
• Publication Number:
  US 20050097028A1
• Time in Patent Office: Days
• US Class Current: 705/37
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
• CPC Class Codes: G06Q 40/12 Accounting

Abstract

A method and system predict customers/accounts that are likely to become attrited based on predefined classification rules and customer data/account information associated with the customers/accounts. The classification rules are generated by parsing through historical customer data/account information to identify attrition customers/accounts and their associated attributes. Unique algorithm is used to determine attrition statuses of the customers or accounts. After the classification rules are generated, the rules are applied to new customer data or account information to predict customers or accounts that are likely to become attrited.

Claims

1. A method for predicting attrition accounts comprising the steps of:

defining a base training time period;

accessing account information for each of a first plurality of accounts related to the base training time period;

identifying a target time period after the base training time period;

determining an attrition status of each of the first plurality of accounts in connection with the target time period;

classifying the first plurality of accounts based on the attrition status of each of the first plurality of accounts in connection with the target time period; and

generating a classification rule based on the account information for each of the first plurality of accounts related to the base training time period, and a result of the classifying step.

2. The method of claim 1 further comprising the steps of:

identifying a prediction time period;

identifying a base time period prior to the prediction time period;

accessing account information for each of the second plurality of accounts in connection with the base time period; and

classifying the second plurality of accounts by applying the classification rule to the accessed account information for each of the second plurality of accounts in connection with the base time period.

3. The method of claim 2 further comprising a step of generating an attrition prediction report based on a result of the classifying step, wherein the report includes a prediction of an attrition status for each of the second plurality of accounts.

4. The method of claim 3 further comprising a step of generating a warning message for at least one of the second plurality of accounts that has a predicted attrition status indicating that the account will become an attrition account in the prediction time period.

5. The method of claim 3 further comprising the steps of:

accessing profitability data of each of the second plurality of accounts or each of the at least one account that will become an attrition account;

comparing the profitability data of each of the second plurality of accounts or each of the at least one account that will become an attrition account with a predetermined profitability threshold; and

generating a profitability status for each of the second plurality of accounts or each of the at least one account that will become an attrition account, based on a result of the comparing step.

6. The method of claim 5 further comprising a step of classifying the second plurality of accounts based on the predicted attrition status and the profitability status of each of the second plurality of accounts.

7. The method of claim 6 further comprising a step of identifying at least one account that both has a predicted attrition status indicating that the account will become an attrition account in the prediction time period, and a profitability status exceeding the predetermined profitability threshold.

8. The method of claim 2, wherein the length of the base training time period is substantially equal to the length of the base time period.

45. A data processing system for calculating profitability of an account, comprising:

a processor for processing data; and

a data storage device coupled to the processor;

wherein the data storage device bearing instructions to cause the data processing system to perform the steps as in the method of claim 1.

49. A program comprising instructions, which may be embodied in a machine-readable medium, for controlling a data processing system to calculate profitability of an account, the instructions upon execution by the data processing system causing the data processing system to perform the steps as in the method of claim 1.

9. The method of 1, wherein the account information includes at least one of:

total assets of the account, total trade number in connection with the account, and total revenue associated with the account.

10. The method of 2, wherein the account information for each of the second plurality of accounts in connection with the base time period includes at least one of:

total assets of the account, total trade number in connection with the account, and total revenue associated with the account.

11. A method for predicting attrition customers comprising the steps of:

defining a base training time period;

accessing customer data for each of a first plurality of customers related to the base training time period, wherein the customer data includes account information of one or more accounts associated with each of the first plurality of customers;

identifying a target time period after the base training time period;

determining an attrition status of each of the first plurality of customers based on account activities of the one or more accounts related to each customer in connection with the target time period;

classifying the first plurality of customers based on the attrition status of each of the first plurality of customers in connection with the target time period; and

generating a classification rule based on the customer data for each of the first plurality of customers related to the base training time period, and a result of the classifying step.

12. The method of claim 11 further comprising the steps of:

identifying a prediction time period;

identifying a base time period prior to the prediction time period;

accessing customer data for each of the second plurality of accounts in connection with the base time period, wherein the customer data includes account information of one or more accounts associated with each of the second plurality of customers; and

classifying the second plurality of customers by applying the classification rule to the accessed customer data for each of the second plurality of customers in connection with the base time period.

13. The method of claim 12 further comprising a step of generating an attrition prediction report based on a result of the classifying step, wherein the report includes a prediction of an attrition status for each of the second plurality of customers.

14. The method of claim 13 further comprising a step of generating a warning message for at least one of the second plurality of customers that has a predicted attrition status indicating that the customer will become an attrition customer in the prediction time period.

15. The method of claim 13 further comprising the steps of:

accessing profitability data of each of the second plurality of customers or each of the at least one customer that will become an attrition customer;

comparing the profitability data of each of the second plurality of customers or each of the at least one customer that will become an attrition customer with a predetermined profitability threshold; and

generating a profitability status for each of the second plurality of customers or each of the at least one customer that will become an attrition customer, based on a result of the comparing step.

16. The method of claim 15 further comprising a step of classifying the second plurality of customers based on the predicted attrition status and the profitability status of each of the second plurality of customers.

17. The method of claim 16 further comprising a step of identifying at least one customer that both has a predicted attrition status indicating that the customer will become an attrition customer in the prediction time period, and a profitability status exceeding the predetermined profitability threshold.

18. The method of claim 12, wherein the length of the base training time period is substantially equal to the length of the base time period.

46. A data processing system for calculating profitability of an account, comprising:

a processor for processing data; and

a data storage device coupled to the processor;

wherein the data storage device bearing instructions to cause the data processing system to perform the steps as in the method of claim 11.

50. A program comprising instructions, which may be embodied in a machine-readable medium, for controlling a data processing system to calculate profitability of an account, the instructions upon execution by the data processing system causing the data processing system to perform the steps as in the method of claim 11.

19. The method of 11, wherein the customer data includes at least one of:

total assets of one or more accounts associated with a customer, total trade number in connection with one or more accounts associated with a customer, and total revenue associated with one or more accounts associated with a customer.

20. The method of 12, wherein the customer data for each of the second plurality of customers in connection with the base time period includes at least one of:

total assets of one or more accounts associated with a customer, total trade number in connection with one or more accounts associated with a customer, and total revenue associated with one or more accounts associated with a customer.

21. A method for predicting attrition accounts comprising the steps of:

defining a target time period;

determining an attrition status of each of a first plurality of accounts in connection with the target time period;

classifying the first plurality of accounts based on the attrition status of each of the first plurality of accounts in connection with the target time period;

selecting a base training time period prior to the target time period;

accessing account information for each of the first plurality of accounts related to the base training time period; and

generating a classification rule based on the account information for each of the first plurality of accounts related to the base training time period, and a result of the classifying step.

22. The method of claim 21 further comprising the steps of:

identifying a prediction time period;

identifying a base time period prior to the prediction time period;

accessing account information for each of the second plurality of accounts in connection with the base time period; and

classifying the second plurality of accounts by applying the classification rule to the accessed account information for each of the second plurality of accounts in connection with the base time period.

23. The method of claim 22 further comprising a step of generating an attrition prediction report based on a result of the classifying step, wherein the report includes a prediction of an attrition status for each of the second plurality of accounts.

24. The method of claim 23 further comprising a step of generating a warning message for at least one of the second plurality of accounts that has a predicted attrition status indicating that the account will become an attrition account in the prediction time period.

25. The method of claim 23 further comprising the steps of:

accessing profitability data of each of the second plurality of accounts or each of the at least one account that will become an attrition account;

comparing the profitability data of each of the second plurality of accounts or each of the at least one account that will become an attrition account with a predetermined profitability threshold; and

generating a profitability status for each of the second plurality of accounts or each of the at least one account that will become an attrition account, based on a result of the comparing step.

26. The method of claim 25 further comprising a step of classifying the second plurality of accounts based on the predicted attrition status and the profitability status of each of the second plurality of accounts.

27. The method of claim 26 further comprising a step of identifying at least one account that both has a predicted attrition status indicating that the account will become an attrition account in the prediction time period, and a profitability status exceeding the predetermined profitability threshold.

28. The method of claim 22, wherein the length of the base training time period is substantially equal to the length of the base time period.

31. The method of claim 21, wherein the base time period is selected based on the attrition status of each account.

32. The method of claim 31, wherein:

for an attrition account, the base time period is selected to be a predetermined time period prior to the account becomes attrited; and

for a non-attrition account, the base time period is selected to be the predetermined time period prior to the target time period.

47. A data processing system for calculating profitability of an account, comprising:

a processor for processing data; and

a data storage device coupled to the processor;

wherein the data storage device bearing instructions to cause the data processing system to perform the steps as in the method of claim 21.

51. A program comprising instructions, which may be embodied in a machine-readable medium, for controlling a data processing system to calculate profitability of an account, the instructions upon execution by the data processing system causing the data processing system to perform the steps as in the method of claim 21.

29. The method of 21, wherein the account information includes at least one of:

total assets of the account, total trade number in connection with the account, and total revenue associated with the account.

30. The method of 22, wherein the account information for each of the second plurality of accounts in connection with the base time period includes at least one of:

total assets of the account, total trade number in connection with the account, and total revenue associated with the account.

33. A method for predicting attrition customers comprising the steps of:

defining a target time period;

determining an attrition status of each of a first plurality of customers in connection with the target time period based on account activities of one or more accounts related to each customer in connection with the target time period;

classifying the first plurality of customers based on the attrition status of each of the first plurality of customers in connection with the target time period;

selecting a base training time period prior to the target time period;

accessing customer data for each of the first plurality of customers related to the base training time period, wherein the customer data includes account information of one or more accounts associated with each of the first plurality of customers; and

generating a classification rule based on the customer data for each of the first plurality of customers related to the base training time period, and a result of the classifying step.

34. The method of claim 33 further comprising the steps of:

identifying a prediction time period;

identifying a base time period prior to the prediction time period;

accessing customer data for each of the second plurality of accounts in connection with the base time period, wherein the customer data includes account information of one or more accounts associated with each of the second plurality of customers; and

classifying the second plurality of customers by applying the classification rule to the accessed customer data for each of the second plurality of customers in connection with the base time period.

35. The method of claim 34 further comprising a step of generating an attrition prediction report based on a result of the classifying step, wherein the report includes a prediction of an attrition status for each of the second plurality of customers.

36. The method of claim 35 further comprising a step of generating a warning message for at least one of the second plurality of customers that has a predicted attrition status indicating that the customer will become an attrition customer in the prediction time period.

37. The method of claim 35 further comprising the steps of:

accessing profitability data of each of the second plurality of customers;

comparing the profitability data of each of the second plurality of customers with a predetermined profitability threshold; and

generating a profitability status for each of the second plurality of customers based on a result of the comparing step.

38. The method of claim 37 further comprising a step of classifying the second plurality of customers based on the predicted attrition status and the profitability status of each of the second plurality of customers.

39. The method of claim 38 further comprising a step of identifying at least one customer that both has a predicted attrition status indicating that the customer will become an attrition customer in the prediction time period, and a profitability status exceeding the predetermined profitability threshold.

40. The method of claim 34, wherein the length of the base training time period is substantially equal to the length of the base time period.

43. The method of claim 33, wherein the base time period is selected based on the attrition status of each customer.

44. The method of claim 43, wherein:

for an attrition customer, the base time period is selected to be a predetermined time period prior to the customer becomes attrited; and

for a non-attrition customer, the base time period is selected to be the predetermined time period prior to the target time period.

48. A data processing system for calculating profitability of an account, comprising:

a processor for processing data; and

a data storage device coupled to the processor;

wherein the data storage device bearing instructions to cause the data processing system to perform the steps as in the method of claim 33.

52. A program comprising instructions, which may be embodied in a machine-readable medium, for controlling a data processing system to calculate profitability of an account, the instructions upon execution by the data processing system causing the data processing system to perform the steps as in the method of claim 33.

41. The method of 33, wherein the customer data includes at least one of:

total assets of one or more accounts associated with a customer, total trade number in connection with one or more accounts associated with a customer, and total revenue associated with one or more accounts associated with a customer.

42. The method of 34, wherein the customer data for each of the second plurality of customers in connection with the base time period includes at least one of:

total assets of one or more accounts associated with a customer, total trade number in connection with one or more accounts associated with a customer, and total revenue associated with one or more accounts associated with a customer.