METHOD AND APPARATUS FOR PREDICTING OUTCOMES OF A HOME EQUITY LINE OF CREDIT

• US 20080010188A1
• Filed: 07/02/2007
• Published: 01/10/2008
• Est. Priority Date: 06/30/2006
• Status: Active Grant

• Current Assignee: Corelogic Solutions LLC (CoreLogic Incorporated)
• Original Assignee: CoreLogic Information Solutions Incorporated (CoreLogic Incorporated)
• Inventors: Beardsell, Mark, Calem, Paul, Burgess, Harlow
• Granted Patent: US 7,958,048 B2
• Time in Patent Office: Days
• US Class Current: 705/038
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/02 Banking, e.g. interest calculation or account maintenance credit or loans G06Q40/03
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis

Abstract

A method and apparatus are described where account information is used to predict possible outcomes of a HELOC. To predict the possible outcomes, HELOC account state transition probabilities are modeled. The transition probabilities, determined by historic data regression analysis, provide the framework for a Monte Carlo simulation. The simulation is seeded with HELOC account information. A calculation engine takes the account information and simulates an elapse of time using a random number generator and the state transition probabilities. The simulation results in updated account information predicting a possible outcome over the elapsed time interval. The updated account information in turn may be used by the calculation engine to simulate the next elapse of time. This method may be iteratively repeated with the account information propagated forward until the end of the prediction period is reached.

Claims

1. A machine-readable medium comprising instructions for predicting outcomes of a home equity line of credit loan, wherein the instructions upon execution cause a machine to:

receive a plurality of account characteristics for a home equity line of credit loan;

generate an initial account state vector from the plurality of account characteristics;

receive a simulation parameter;

update the initial account state vector by propagating a state vector forward using a statistical transition model;

predict draw or payment events using the statistical transition model; and

generate probability distributions and compute account statistics using the statistical transition model.

2. The machine-readable medium of claim 1 wherein the plurality of account characteristics are selected from a group consisting of a location of a home, a loan origination date, a property value, an occupancy type, a junior ratio, a utilization at origination, a balance at origination, a term, a back end ratio, a prediction start date, an index rate, a margin, an interest rate, a home price index, and combinations thereof.

3. The machine-readable medium of claim 1 wherein the initial account state vector includes information that is used to determine at least one probability for each state transition.

4. The machine-readable medium of claim 1 wherein the simulation parameter is selected from a group consisting of a loan prediction period, a prediction interval, a number of Monte Carlo trials, and combinations thereof.

5. The machine-readable medium of claim 4 further comprising instructions that upon execution cause a machine to store an account state vector, the number of Monte Carlo trials, and the prediction interval.

6. The machine-readable medium of claim 5 further comprising instructions that upon execution cause a machine to store the initial account state vector as the account state vector, a 1 for the number of Monte Carlo trials, and a 0 for the prediction interval if no account state vector, trial number and prediction interval exist.

7. The machine-readable medium of claim 1 wherein the statistical transition model includes equations and coefficients to determine transition probabilities based on the information in the account state vector.

8. A computer-based method for predicting outcomes of a home equity line of credit loan comprising:

receiving a plurality of account characteristics for a home equity line of credit loan;

generating an initial account state vector from the plurality of account characteristics;

receiving a simulation parameter;

updating the initial account state vector by propagating a state vector forward using a statistical transition model;

predicting draw or payment events using the statistical transition model; and

generating probability distributions and compute account statistics using the statistical transition model.

9. The method of claim 8 wherein the plurality of account characteristics are selected from a group consisting of a location of a home, a loan origination date, a property value, an occupancy type, a junior ratio, a utilization at origination, a balance at origination, a term, a back end ratio, a prediction start date, an index rate, a margin, an interest rate, a home price index, and combinations thereof.

10. The method of claim 8 wherein the initial account state vector includes information that is used to determine at least one probability for each state transition.

11. The method of claim 8 wherein the simulation parameter is selected from a group consisting of a loan prediction period, a prediction interval, a number of Monte Carlo trials, and combinations thereof.

12. The method of claim 11 further comprising storing an account state vector, the number of Monte Carlo trials, and the prediction interval.

13. The method of claim 12 further comprising storing the initial account state vector as the account state vector, a 1 for the number of Monte Carlo trials, and a 0 for the prediction interval if no account state vector, trial number and prediction interval exist.

14. The method of claim 8 wherein the statistical transition model includes equations and coefficients to determine transition probabilities based on the information in the account state vector.

15. A computer-based method for forecasting possible outcomes of a home equity line of credit (HELOC) comprising:

generating a HELOC account simulation model having a plurality of possible account states;

receiving account information for seeding a simulation;

simulating an outcome by seeding the simulation with account information and iteratively predicting a next account state from the plurality of possible account states using the HELOC account simulation model;

generating an ensemble of simulated outcomes; and

aggregating the outcome ensemble into one or more probability statistics.

16. The method of claim 15 wherein the account information is selected from a group consisting of a loan balance, a CLTV ratio, an interest rate, a home price, a delinquency, and combinations thereof.

17. A method for estimating the expected return from a home equity line of credit (HELOC) account comprising:

generating a statistical model from historic HELOC data;

receiving account information about a prospective HELOC;

comparing the account information with the statistical model; and

predicting loan balance statistics from the comparison.

18. The method of claim 17 wherein the account information is selected from a group consisting of a loan balance, a CLTV ratio, an interest rate, a home price, a delinquency, and combinations thereof.

19. A method for calculating the utilization statistics of a home equity line of credit (HELOC) using Monte Carlo methods, comprising:

generating a statistical transition model of possible HELOC account states;

receiving HELOC account data;

simulating a plurality of possible account outcomes by seeding the statistical transition model with HELOC account data; and

generating one or more probability statistics from the plurality of possible account outcomes.

20. The method of claim 19 wherein the HELOC account data is selected from a group consisting of a loan balance, a CLTV ratio, an interest rate, a home price, a delinquency, and combinations thereof.