Claims
- 1. A method for managing financial accounts, comprising the steps of:
collecting account data for a plurality of financial accounts, where the account data are associated with a plurality of variables; establishing at least one control variable and at least one behavior variable based on the plurality of variables; determining a plurality of interval breakpoints for the at least one control variable and the at least one behavior variable; defining a plurality of account states based on the at least one control variable, the at least one behavior variable and the plurality of interval breakpoints; forming a transition matrix based at least in part on the account data and the plurality of account states; generating a Markov Decision Process (MDP) model based at least in part on the transition matrix; and using the Markov Decision Process model to effect a change in the at least one control variable resulting in a desired effect on the plurality of account states.
- 2. The method according to claim 1, where the plurality of financial accounts are bankcard accounts and the at least one control variable comprises at least one of:
(i) credit lines; or (ii) annual percentage rates (APRs).
- 3. The method according to claim 1, where the account data comprise time-series data on at least one of:
(i) credit bureau variables; (ii) credit bureau scores; and (iii) bankcard account performance.
- 4. The method according to claim 2, where the change in the at least one control variable for the desired effect comprises at least one of the following actions:
(i) change the credit line; (ii) change the annual percentage rate (APR); (iii) change both the credit line and the annual percentage rate (APR); or (iv) making no changes.
- 5. The method according to claim 2, where the desired effect is associated with at least one of the bankcard accounts':
(i) net cash flow (NCF); (ii) balance migration; or (iii) risk of credit losses.
- 6. The method according to claim 1, further comprising the steps of:
performing a regression tree analysis on the plurality of variables; establishing the at least one behavior variable based on the regression tree analysis; and determining the plurality of interval breakpoints for each of the at least one behavior variable based on the regression tree analysis.
- 7. The method according to claim 1, further comprising the steps of
applying business rules to an output of the Markov Decision Process model; and generating a policy lookup table based on the business rules and the output of the Markov Decision Process model.
- 8. The method according to claim 1, further comprising simplifying the transition matrix based on one or more of the following techniques:
(i) creating a rectangular transition matrix with rows for the at least one control variable and the at least one behavior variable, and columns for the at least one behavior variable only; (ii) combining at least one row of a transition matrix with an adjoining row, where the at least one row is characterized with low-frequency transitions; (iii) combining at least one column of a transition matrix with an adjoining column, where the at least one column is characterized with low-frequency transitions; and (iv) re-indexing a transition matrix to correctly capture all past and future account transitions.
- 9. The method according to claim 1, further comprising validating and supplementing the output of the Markov Decision Process model through a Monte Carlo simulation, where the Monte Carlo simulation is based at least partially on the account data.
- 10. A data structure for implementing a transition matrix computationally in a plurality of sizes, the data structure comprising:
a plurality of control branches, where each of the plurality of control branches is a member of a first bi-directionally linked list comprising: a plurality of control variables, a bi-directionally linked list of behavioral state nodes, and an array of action-specific destinations of the plurality of control variables; a plurality of behavior nodes, where each of the plurality of behavior nodes is a member of a second bi-directionally linked list comprising: a plurality of behavioral state variables, a plurality of arrays of financial metrics and simulation statistics, an array of action-specific destinations of the plurality of behavioral state variables, and a bi-directionally linked list of all behavioral transitions; and a plurality of transition probability nodes, where each of the plurality of transition probability nodes is a member of a third bi-directionally linked list comprising: a plurality of destination behavioral state variables, a list of destination pointers for behavior nodes that have non-zero transition probabilities, and a list of transition probability values of all destination points.
- 11. A computer readable medium having code for causing a processor to manage financial accounts, the computer readable medium comprising:
code adapted to collect account data for a plurality of financial accounts, where the account data are associated with a plurality of variables; code adapted to establish at least one control variable and at least one behavior variable based on the plurality of variables; code adapted to determine a plurality of interval breakpoints for the at least one control variable and the at least one behavior variable; code adapted to define a plurality of account states based at least in part on the at least one control variable, the at least one behavior variable and the plurality of interval breakpoints; code adapted to form a transition matrix based at least in part on the account data and the plurality of account states; code adapted to generate a Markov Decision Process (MDP) model based at least in part on the transition matrix; and code adapted to use the Markov Decision Process model to effect a change in the at least one control variable resulting in a desired effect on the plurality of account states.
- 12. The computer readable medium according to claim 11, where the plurality of financial accounts are bankcard accounts and the at least one control variable comprises at least one of:
(i) credit lines; or (ii) annual percentage rates (APRs).
- 13. The computer readable medium according to claim 11, where the account data comprise time-series data on at least one of:
(i) credit bureau variables; (ii) credit bureau scores; and (iii) bankcard account performance.
- 14. The computer readable medium according to claim 12, where the change in the at least one control variable for the desired effect comprises at least one of the following actions:
(i) change the credit line; (ii) change the annual percentage rate (APR); (iii) change both the credit line and the annual percentage rate (APR); or (iv) making no changes.
- 15. The computer readable medium according to claim 12, where the desired effect is associated with at least one of the bankcard accounts':
(i) net cash flow (NCF); (ii) balance migration; or (iii) risk of credit losses.
- 16. The computer readable medium according to claim 11, further comprising:
code adapted to perform a regression tree analysis on the plurality of variables; code adapted to establish the at least one behavior variable based on the regression tree analysis; and code adapted to determine the plurality of interval breakpoints for each of the at least one behavior variable based on the regression tree analysis.
- 17. The computer readable medium according to claim 11, further comprising
code adapted to apply business rules to an output of the Markov Decision Process model; and code adapted to generate a policy lookup table based on the business rules and the output of the Markov Decision Process model.
- 18. The computer readable medium according to claim 11, further comprising code adapted to simplify the transition matrix based on one or more of the following techniques:
(i) creating a rectangular transition matrix with rows for the at least one control variable and the at least one behavior variable, and columns for the at least one behavior variable only; (ii) combining at least one row of a transition matrix with an adjoining row, where the at least one row is characterized with low-frequency transitions; (iii) combining at least one column of a transition matrix with an adjoining column, where the at least one column is characterized with low-frequency transitions; and (iv) re-indexing a transition matrix to correctly capture all past and future account transitions.
- 19. The computer readable medium according to claim 11, further comprising code adapted to validate and supplement the output of the Markov Decision Process model through a Monte Carlo simulation, where the Monte Carlo simulation is based at least partially on the account data.
- 20. A system for managing financial accounts, the system comprising
a data collection module for collecting account data for a plurality of financial accounts, where the account data are associated with a plurality of variables; an establishment module for establishing at least one control variable and at least one behavior variable based on the plurality of variables; a determination module for determining a plurality of interval breakpoints for the at least one control variable and the at least one behavior variable; a definition module for defining a plurality of account states based at least in part on the at least one control variable, the at least one behavior variable and the plurality of interval breakpoints; a formation module for forming a transition matrix based at least in part on the account data and the plurality of account states; a generation module for generating a Markov Decision Process (MDP) model based at least in part on the transition matrix; and a decision module for using the Markov Decision Process model to effect a change in the at least one control variable resulting in a desired effect on each of the plurality of account states.
- 21. The system according to claim 20, where the plurality of financial accounts are bankcard accounts and the at least one control variable comprises at least one of:
(i) credit lines; or (ii) annual percentage rates (APRs).
- 22. The system according to claim 20, where the account data comprise time-series data on at least one of:
(i) credit bureau variables; (ii) credit bureau scores; and (iii) bankcard account performance.
- 23. The system according to claim 21, where the change in the at least one control variable for the desired effect comprises at least one of the following actions:
(i) change the credit line; (ii) change the annual percentage rate (APR); (iii) change both the credit line and the annual percentage rate (APR); or (iv) making no changes.
- 24. The system according to claim 21, where the desired effect is associated with at least one of the bankcard accounts':
(i) net cash flow (NCF); (ii) balance migration; or (iii) risk of credit losses.
- 25. The system according to claim 20, further comprising:
an analysis module for performing a regression tree analysis on the plurality of variables; an establishment module for establishing the at least one behavior variable based on the regression tree analysis; and a determination module for determining the plurality of interval breakpoints for each of the at least one behavior variable based on the regression tree analysis.
- 26. The system according to claim 20, further comprising:
a rule module for applying business rules to an output of the Markov Decision Process model; and a generation module for generating a policy lookup table based on the business rules and the output of the Markov Decision Process model.
- 27. The system according to claim 20, further comprising a simplification module for simplifying the transition matrix based on one or more of the following techniques:
(i) creating a rectangular transition matrix with rows for the at least one control variable and the at least one behavior variable, and columns for the at least one behavior variable only; (ii) combining at least one row of a transition matrix with an adjoining row, where the at least one row is characterized with low-frequency transitions; (iii) combining at least one column of a transition matrix with an adjoining column, where the at least one column is characterized with low-frequency transitions; and (iv) re-indexing a transition matrix to correctly capture all past and future account transitions.
- 28. The system according to claim 20, further comprising a simulation module for validating and supplementing the output of the Markov Decision Process model through a Monte Carlo simulation, where the Monte Carlo simulation is based at least partially on the account data.
- 29. A system for managing financial accounts, the system comprising:
means for collecting account data for a plurality of financial accounts, where the account data are associated with a plurality of variables; means for establishing at least one control variable and at least one behavior variable based at least in part on the plurality of variables; means for determining a plurality of interval breakpoints for the at least one control variable and the at least one behavior variable; means for defining a plurality of account states based at least in part on the at least one control variable, the at least one behavior variable and the plurality of interval breakpoints; means for forming a transition matrix based at least in part on the account data and the plurality of account states; means for generating a Markov Decision Process (MDP) model based at least in part on the transition matrix; and means for using the Markov Decision Process model to effect a change in the at least one control variable resulting in a desired effect on each of the plurality of account states.
- 30. The system according to claim 29, where the plurality of financial accounts are bankcard accounts and the at least one control variable comprises at least one of:
(i) credit lines; or (ii) annual percentage rates (APRs).
- 31. The system according to claim 29, where the account data comprise time-series data on at least one of:
(i) credit bureau variables; (ii) credit bureau scores; and (iii) bankcard account performance.
- 32. The system according to claim 30, where the change in the at least one control variable for the desired effect comprises at least one of the following actions:
(i) change the credit line; (ii) change the annual percentage rate (APR); (iii) change both the credit line and the annual percentage rate (APR); or (iv) making no changes.
- 33. The system according to claim 30, where the desired effect is associated with at least one of the bankcard accounts':
(i) net cash flow (NCF); (ii) balance migration; or (iii) risk of credit losses.
- 34. The system according to claim 29, further comprising:
means for performing a regression tree analysis on the plurality of variables; means for establishing the at least one behavior variable based on the regression tree analysis; and means for determining the plurality of interval breakpoints for each of the at least one behavior variable based on the regression tree analysis.
- 35. The system according to claim 29, further comprising:
means for applying business rules to an output of the Markov Decision Process model; and means for generating a policy lookup table based on the business rules and the output of the Markov Decision Process model.
- 36. The system according to claim 29, further comprising means for simplifying the transition matrix based on one or more of the following techniques:
(i) creating a rectangular transition matrix with rows for the at least one control variable and the at least one behavior variable, and columns for the at least one behavior variable only; (ii) combining at least one row of a transition matrix with an adjoining row, where the at least one row is characterized with low-frequency transitions; (iii) combining at least one column of a transition matrix with an adjoining column, where the at least one column is characterized with low-frequency transitions; and (iv) re-indexing a transition matrix to correctly capture all past and future account transitions.
- 37. The system according to claim 29, further comprising means for validating and supplementing the output of the Markov Decision Process model through a Monte Carlo simulation, where the Monte Carlo simulation is based at least partially on the account data.
- 38. A method for managing financial accounts, where a Portfolio Control and Optimization model is represented as:
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This patent application claims priority to U.S. Provisional Patent Application No. 60/426,799, filed Nov. 18, 2002, which is hereby incorporated by reference herein in its entirety.
Provisional Applications (1)
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Number |
Date |
Country |
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60426799 |
Nov 2002 |
US |