System and method for evaluating future collateral risk quality of real estate

• US 20040153330A1
• Filed: 02/05/2003
• Published: 08/05/2004
• Est. Priority Date: 02/05/2003
• Status: Abandoned Application

• Current Assignee: Fidelity National Information Solutions Incorporated (Fidelity National Financial Incorporated)
• Original Assignee: Fidelity National Financial Incorporated
• Inventors: Miller, Norman, Hansen, Greg, Sklarz, Mike, Sennott, Mark
• Application Number:
  US10/358,280
• Publication Number:
  US 20040153330A1
• Time in Patent Office: Days
• US Class Current: 705/1
• CPC Class Codes: G06Q 40/03 Credit; Loans; Processing thereof
• CPC Class Codes: G06Q 40/06 Asset management; Financial planning or analysis
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G06Q 50/16 Real estate

Abstract

An apparatus and method is provided for evaluating default and foreclosure loss risk, both at time zero and for several years into the future, associated with a piece of real property on the basis of factors such as statistical home price trend information for a metropolitan statistical area (MSA) in which the real property is located and loan terms. An automated valuation estimate for the property is obtained and compared to the purchase price. A loan-to-value ratio is determined based on automated valuation estimate. A future home price is predicted based on statistical data obtained for a metropolitan statistical area (MSA) in which the real property is located. Based on the future home price and the LTV ratio, a probability that the real property will have negative equity is determined, and a risk score is generated based on the probability. Other features include generating base scores for each of a plurality of future years and obtaining a weighted average of the base scores; adjusting the risk score based on liquidity of real property values for the MSA in which the real property is located; adjusting the risk score based on reliability of data for the real property; adjusting the risk score based on price volatility for the MSA in which the real property is located; and using unemployment data in the MSA for which the real property is located in calculating the risk score.

Claims

1. A computer-assisted process for evaluating risks associated with real property, comprising the steps of, in a general-purpose computer:

(1) determining a probability of negative equity for the real property as a function of a future mortgage value and a future predicted value for the real property;

(2) establishing a base score for the real property for each of a plurality of future years as a function of the probability of negative equity determined in step (1); and

(3) generating a risk score indicative of future risk associated with the real property as a function of the base score established for each of the plurality of future years.

2. The computer-assisted process of claim 1, wherein step (1) comprises the step of determining the probability of negative equity as a function of variability of prices within a statistical grouping of properties.

3. The computer-assisted process of claim 2, wherein step (1) comprises the step of determining the probability of negative equity as a function of the variance of prices within a submarket.

4. The computer-assisted process of claim 1, wherein step (1) comprises the step of generating a cumulative normal density function based on a value estimate for the real property and the future mortgage value.

5. The computer-assisted process of claim 4, further comprising the step of using an automated valuation model (AVM) to generate a value estimate for a current year and using the value estimate for the current year to determine a probability of negative equity for the current year.

6. The computer-assisted process of claim 1, wherein the probability in step (1) is determined according to the following relation:

P(NE) at t=P(E<

0)=cndf{(log(V)−

log(M))/Square Root of Var of V}

where P=probability of NE, Negative Equity, at time t;

V=value estimate;

M=mortgage value based on the balance at time t;

the square root of the variance of V is based on the larger of the value estimate for the submarket or metropolitan market variance, whichever is larger; and

the cndf cumulative normal density function is the proportion of a normal distribution that falls into a negative equity range.

7. The computer-assisted process of claim 1, wherein step (1) comprises the step of determining the probability of negative equity as a function of a future price based on economic variables for a metropolitan statistical area in which the real property is located.

8. The computer-assisted process of claim 7, wherein step (1) comprises the step of determining a future price on the basis of a multiple regression analysis, where prices in time are a function of an affordable price and fundamental economic variables for a statistical area in which the real property is located.

9. The computer-assisted process of claim 8, wherein step (1) comprises the step of determining the future price on the basis of local employment statistics.

10. The computer-assisted process of claim 8, wherein step (1) comprises the step of determining the future price on the basis of median household income for a statistical area in which the real property is located.

11. The computer-assisted process of claim 1, wherein step (2) comprises the step of establishing a base score associated with a risk of default.

12. The computer-assisted process of claim 1, wherein step (3) comprises the step of generating the risk score as a weighted average of the base score established for each of the plurality of future years established in step (2) and using the weighted average to produce a score indicative of risks associated with the real property.

13. The computer-assisted process of claim 1, further comprising the step of:

(4) adjusting the risk score on the basis of how a price of the real property fits into a price range distribution for a submarket in which the real property is located.

14. The computer-assisted process of claim 13, wherein step (4) comprises the step of adjusting downwardly the risk score if a price of the real property is in an upper tier of the price range distribution and adjusting upwardly the risk score if the price of the real property is in a lower tier of the price range distribution.

15. The computer-assisted process of claim 1, further comprising the step of:

(4) adjusting the risk score on the basis of how long properties in a statistical market in which the real estate is located have been on the market.

16. The computer-assisted process of claim 1, further comprising the steps of:

(4) adjusting the risk score on the basis of relative pricing in the local market; and

(5) adjusting the risk score on the basis of relative liquidity in the local market.

17. The computer-assisted process of claim 1, further comprising the step of adjusting the risk score on the basis of a creditworthiness score of a loan applicant associated with the real property.

18. The computer-assisted process of claim 1, wherein step (1) comprises the step of determining the probability of negative equity as a function of local market conditions.

19. A computer-assisted process for evaluating real property, comprising the steps of, in a general-purpose computer:

(1) establishing an automated valuation estimate for the real property;

(2) predicting a future price for the real property based on statistical data pertinent to an area in which the real property is located;

(3) determining, based on steps (1) and (2), a probability that the real property will have a negative equity in a future time period; and

(4) generating a risk score for the real property using the probability determined in step (3).

20. The computer-assisted process of claim 19,

wherein step (3) comprises the step of determining a standard deviation of property prices for a metropolitan statistical area (MSA) in which the real property is located.

21. The computer-assisted process of claim 19,

wherein step (2) comprises the step of predicting the future price over a plurality of future years;

and

wherein step (3) comprises the step of determining a probability for each of the plurality of future years and using each said probability to generate the risk score.

22. The computer-assisted process of claim 19, wherein step (4) comprises the step of generating a base score for each of the plurality of future years and weighting each base score to generate the risk score.

23. The computer-assisted process of claim 19, further comprising the step of adjusting the risk score based on liquidity of real estate values for a submarket in which the real property is located.

24. The computer-assisted process of claim 19, further comprising the step of adjusting the risk score based on a median time on the market for properties located in a submarket in which the real property is located.

25. The computer-assisted process of claim 19, further comprising the step of adjusting the risk score based on availability of data for the real property.

26. The computer-assisted process of claim 19, wherein step (2) comprises the step of using unemployment data for the MSA in which the real property is located.

27. The computer-assisted process of claim 19, wherein step (2) comprises the step of using household incomes for the MSA in which the real property is located.

28. The computer-assisted process of claim 19, wherein step (1) comprises the step of obtaining a plurality of automated valuation model (AVM) value estimates for the real property and weighting each of the plurality of AVM value estimates in accordance with regression coefficients based on actual data obtained for a submarket in which the real property is located.

29. The computer-assisted process of claim 19, further comprising the step of weighting the risk score according to a creditworthiness score of a mortgage applicant associated with the real property.

30. The computer-assisted process of claim 19, wherein step (2) comprises the step of predicting a future home price on the basis of the following multiple regression relation:

HP_t=β

₁(AP)_t+β

₂(FE)_t+β

₃(HP)<sub>t−

n</sub>+ε

Where AP=HHMI_msa/M/AMC_i,n/LTV where HHMI is the local MSA median household income;

M is the inverse of an allowable portion of household income for mortgage loan purchases;

AMC is an annualized mortgage constant equal to the monthly mortgage constant times 12 for the current mortgage interest rate, i, and term, n; and

LTV is the loan to value ratio;

Where FE represents local economic conditions;

Where HP represents historical house price data;

Where β

₁,β

₂,β

₃ represent regression coefficients; and

Where ε

is an error parameter.

31. A computer programmed to carry out the process of claim 19.

32. A computer-implemented process for evaluating risks associated with real property, comprising the steps of, in a general-purpose computer:

(1) generating a plurality of automated valuation estimates for the real property;

(2) weighting each of the plurality of automated valuation (AVM) price estimates according to regression coefficients reflecting data for a submarket in which the real property is located, and generating a weighted AVM price estimate for a current year;

(3) generating a predicted future price for each of a plurality of future years for the real property using a regression model that takes into account local economic conditions in a submarket in which the real property is located;

(4) determining for each of the plurality of future years a probability that the real property will have a negative equity on the basis of the predicted future price;

a mortgage balance for each future year; and

a variance of prices for the submarket in which the real property is located;

(5) generating a risk score for the real property using the probability determined in step (4); and

(6) adjusting the risk score to account for liquidity in the submarket.