Method and apparatus for computing a loan quality score
A method of computing a loan quality score using user input data concerning a subject property and the proposed loan, The loan quality score is useful in determining the probability that fraud is involved in the property loan request being made to a lender.
1 . A computer-based method of computing a loan quality score for a subject property comprising the steps of:
using past loan data to develop at least one algorithm for use in predicting loan fraud;
obtaining subject property data; and
applying said at least one algorithm to said subject property data to thereby compute a loan quality score.
2 . A digital computer system programmed to perform the steps specified in the method of claim 1 .
3 . Computer-readable media containing programming designed to accomplish the method of claim 1 .
4 . The method of claim 1 wherein said past loan data includes at least one datum from a known fraudulent transaction.
5 . The method of claim 1 wherein said subject property data includes a determination as to whether the seller is a risky seller based on a string search for key words.
7 . The method of claim 1 wherein said subject property data includes the number of sales of said subject property within a predetermined period of time.
8 . The method of claim 1 wherein said subject property data includes data to determine whether the loan purpose is for purchase or refinancing.
9 . The method of claim 1 wherein said subject property data includes data to determine whether the borrower intends to occupy said subject property.
10 . The method of claim 1 wherein said subject property data includes data to determine whether the sale appears to be an arm's length transfer.
11 . The method of claim 1 wherein said subject property data includes the requested loan amount.
12 . The method of claim 1 wherein said subject property data includes the age of said subject property.
13 . The method of claim 1 wherein said subject property data includes the size of said subject property.
14 . The method of claim 1 wherein said subject property data includes at least one automated valuation model valuation of said subject property.
15 . The method of claim 1 wherein said subject property data includes an appreciation variance ratio.
16 . The method of claim 1 wherein said subject property data includes at least one user-submitted value of said subject property.
17 . The method of claim 1 , wherein said algorithm is:
Loan quality score=500−(33*Logit)
Where:
Logit
=
0.534
*
RS
+
0.637
*
TS
-
0.984
*
RF
+
0.979
*
AO
-
0.00000808
*
AVM
+
1.278
*
EX
+
1.301
*
EX
50
+
0.907
*
NARM
+
0.029
*
AG
+
0.0000136
*
LA
+
US
/
AVM
+
0.653
*
(
AV
/
AEST
)
^
2.25
-
0.000596
*
SF
-
3.738
Where:
Logit is the natural logarithm of the odds ratio, namely p/(1−p), where P is the probability that the loan is fraudulent.
RS is the risky seller binary variable.
TS is the number of times the property has been sold in the past three years.
RF is a binary variable for refinance loans.
AO is a binary variable for absentee owner.
AVM is the automated valuation model's estimate of value.
EX is the binary variable when user-submitted value exceeds automated valuation model valuation.
EX50 is the binary variable when user-submitted value exceeds automated valuation model valuation by 50% or more.
NARM is the binary variable for a non-arm's length transfer.
AG is the age of the target property.
LA is the loan amount.
AV is the appraised value.
US is the user-submitted value.
SF is the square footage of the target property.
18 . The method of claim 1 , wherein said algorithm is:
Loan quality score=500−(31*Logit)
Where:
Logit
=
0.077
*
PL
+
1.022
*
TS
-
1.174
*
RF
-
0.00001452
*
AVM
+
1.901
*
EX
+
0.012
*
AG
+
0.00002222
*
LA
+
0.459
*
AVR
-
5.007
Where:
Logit is the natural logarithm of the odds ratio, namely p/(1−p), where P is the probability that the loan is fraudulent;
PL is the percent of households earning less than a specified amount;
TS is the number of times the property has been sold in the past three years.
RF is a binary dummy variable for refinance loans-If the loan is a refinance, the binary variable is set to 1, otherwise it is set to 0;
AVM is the automated valuation model's estimate of value.
EX is the binary dummy variable when user-submitted value exceeds automated valuation model valuation;
AG is the age of the target property;
LA is the loan amount; and
AVR is the ratio of the appreciation in value, as given by the user, compared to the appreciation in value of the median home price in the predetermined geographic area.
19 . A method to be performed by a computer of determining a loan quality score for a subject property comprising the steps of:
using past loan data to develop at least one algorithm for use in predicting loan fraud;
obtaining subject property data;
obtaining an automated valuation model valuation of said subject property;
computing additional variables based upon said data and said automated valuation model valuation; and
applying said algorithm to said subject property data, said additional variables and said automated valuation model valuation to thereby compute a loan quality score.
20 . A computer-based apparatus for computing a loan quality score for a subject property comprising:
input means for receiving subject property data
computation means connected to said input means for computing a loan quality score and for computing algorithms for use in providing said loan quality score; and
output means connected to said computation means for providing the results.
21 . The apparatus of claim 20 , further comprising:
automated valuation model connection means connected to said input means for requesting and receiving automated valuation model valuations.
22 . The apparatus of claim 20 , further comprising:
temporary data storage means connected to said computation means for storing said property data and said loan quality score.
23 . The apparatus of claim 20 , further comprising: report-generation means connected to said computation means for creating reports based upon said property data and said loan quality score.
24 . The apparatus of claim 20 , further comprising:
database connection means connected to said input means for requesting and receiving data from at least one database.
25 . The apparatus of claim 20 , wherein said computation means uses the algorithm:
Loan quality score=500−(33*Logit)
Where:
Logit
=
0.534
*
RS
+
0.637
*
TS
-
0.984
*
RF
+
0.979
*
AO
-
0.00000808
*
AVM
+
1.278
*
EX
+
1.301
*
EX
50
+
0.907
*
NARM
+
0.029
*
AG
+
0.0000136
*
LA
+
US
/
AVM
+
0.653
*
(
AV
/
AEST
)
^
2.25
-
0.000596
*
SF
-
3.738
Where:
Logit is the natural logarithm of the odds ratio, namely p/(1−p), where P is the probability that the loan is fraudulent.
RS is the risky seller binary variable.
TS is the number of times the property has been sold in the past three years.
RF is a binary variable for refinance loans.
AO is a binary variable for absentee owner.
AVM is the automated valuation model's estimate of value.
EX is the binary variable when user-submitted value exceeds automated valuation model valuation.
EX50 is the binary variable when user-submitted value exceeds automated valuation model valuation by 50% or more.
NARM is the binary variable for a non-arm's length transfer.
AG is the age of the target property.
LA is the loan amount.
AV is the appraised value.
US is the user-submitted value.
SF is the square footage of the target property.
26 . The apparatus of claim 20 , wherein said computation means uses the algorithm:
Loan quality score=500−(31*Logit)
Where:
Logit
=
0.077
*
PL
+
1.022
*
TS
-
1.174
*
RF
-
0.00001452
*
AVM
+
1.901
*
EX
+
0.012
*
AG
+
0.00002222
*
LA
+
0.459
*
AVR
-
5.007
Logit is the natural logarithm of the odds ratio, namely p/(1−p), where P is the probability that the loan is fraudulent;
PL is the percent of households earning less than a specified amount;
TS is the number of times the property has been sold in the past three years.
RF is a binary dummy variable for refinance loans-If the loan is a refinance, the binary variable is set to 1, otherwise it is set to 0;
AVM is the automated valuation model's estimate of value.
EX is the binary dummy variable when user-submitted value exceeds automated valuation model valuation;
AG is the age of the target property;
LA is the loan amount; and
AVR is the ratio of the appreciation in value, as given by the user, compared to the appreciation in value of the median home price in the predetermined geographic area.