U.S. patent application number 13/909496 was filed with the patent office on 2013-10-17 for automated loan risk assessment system and method.
The applicant listed for this patent is Interthinx, Inc.. Invention is credited to Steven C. Halper, Stephen M. Hourigan, Constance A. Wilson.
Application Number | 20130275293 13/909496 |
Document ID | / |
Family ID | 46280258 |
Filed Date | 2013-10-17 |
United States Patent
Application |
20130275293 |
Kind Code |
A1 |
Halper; Steven C. ; et
al. |
October 17, 2013 |
Automated Loan Risk Assessment System and Method
Abstract
An automated loan risk assessment system and method are
described. The system is adapted to receive information about a
loan or an insurance application requesting insurance to cover
same. The system calculates a risk score for the loan based on a
plurality of risk factors including at least two of a fraud risk
factor, a credit risk factor and a property valuation risk factor.
The risk score can be used by a loan service provider in deciding
whether or not to fund or insure the loan.
Inventors: |
Halper; Steven C.; (St.
Charles, MO) ; Wilson; Constance A.; (Lake St. Louis,
MO) ; Hourigan; Stephen M.; (Zionsville, IN) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Interthinx, Inc. |
Agoura Hills |
CA |
US |
|
|
Family ID: |
46280258 |
Appl. No.: |
13/909496 |
Filed: |
June 4, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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10046945 |
Jan 14, 2002 |
8458082 |
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13909496 |
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09993072 |
Nov 13, 2001 |
7689503 |
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10046945 |
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Current U.S.
Class: |
705/38 |
Current CPC
Class: |
G06Q 40/00 20130101;
G06Q 40/02 20130101; G06Q 40/025 20130101 |
Class at
Publication: |
705/38 |
International
Class: |
G06Q 40/02 20120101
G06Q040/02 |
Claims
1. An automated loan risk assessment system, comprising: means for
receiving information about a loan; and means for calculating a
risk score for the loan based on a plurality of risk factors
including at least two of a fraud risk factor, an underwriting risk
factor and a property valuation risk factor, whereby the risk score
can be used by a loan service provider in deciding whether or not
to fund or insure the loan.
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Description
CROSS REFERENCE TO RELATED APPLICATION
[0001] This is a continuation-in-part of application Ser. No.
09/993,072 entitled Predatory Lending Detection System and Method
Therefor filed Nov. 13, 2001.
FIELD OF THE INVENTION
[0002] This invention relates to an automated loan risk assessment
system and method and in particular, an automated system and method
of assessing risk with respect to a loan based on a plurality of
risk factors including at least two of a fraud risk factor, an
underwriting risk factor and a property valuation risk factor.
BACKGROUND OF THE INVENTION
[0003] One of the American dreams is home ownership. However,
according to the Mortgage Guaranty Insurance Company, "[r]elative
to the growth in home prices over the last century, Americans are
earning less and, as a result, saving less." As a result, the down
payment required to secure a mortgage often prevents young
individuals just "starting out" from buying a home. Consequently,
home mortgages having low down payments have become very popular.
The less money a borrower has invested in a home, however, the
greater the risk of default. Therefore, while there is some risk
that a borrower may default with a conventional mortgage which
typically requires a twenty percent (20%) down payment, this risk
is increased for borrowers who are only putting down five percent
(5%) or ten percent (10%). Low down payment mortgages, therefore,
often require that the borrower obtain some type of mortgage
insurance to protect the lender against loss if the borrower
defaults on the mortgage. However, even with such protection, the
lender typically is not able to recoup the entire amount of the
mortgage.
[0004] Lenders and mortgage insurers try to minimize their exposure
by obtaining information on borrowers indicative of their risk of
defaulting on a mortgage, such as through credit reports or
mortgage service systems such as The Mortgage Office, MORESERV and
TRAKKER. There are also several existing consumer and mortgage
scoring systems which generate underwriting scores to assist
mortgage insurers in this regard, such as for example, the Fair
Issac Consumer (FICO) score, the Private Mortgage Insurance (PMI)
aura score, the United Guaranty ACUscore, and the ARCS subprime
mortgage score.
[0005] None of these scoring tools, however, assess risk
attributable to fraud (i.e., data integrity). For example, a lender
may manipulate the loan information to qualify an otherwise
unqualified borrower, or a borrower may falsify income or
employment information in order to obtain the loan. To the extent
fraudulent claims are not detected, the costs associated with
paying them are ultimately borne by the consumer. According to a
Sep. 26, 2001 article in Realty Times, reports of possible
fraudulent activity in connection with a mortgage increased
fifty-seven percent (57%) in the first quarter of this year.
[0006] Fraud can originate from numerous sources, such as lenders,
borrowers, appraisers, title agents, real estate agents and
builders. Fraud can be injected into the loan process in a number
of ways, such as through the use of false credit histories, false
income/employment information, falsified appraisals, inflated
property values and false identification. For example, loan
officers might fabricate pay stubs to help a borrower qualify for a
loan that the borrower might not otherwise qualify for so that he
or she can collect a commission. Likewise, a borrower might submit
falsified tax returns to ensure he or she qualifies for the
loan.
[0007] The potential for fraud increases as the number of parties
involved in the transaction increases. Increases in mortgage fraud
are also due to a number of other factors, such as (1) the creation
of new and creative forms of financing, coupled with automated
underwriting, (2) the increased availability of personal
information via the Internet, and (3) the low-cost of computer
equipment such as printers and copiers that produce high quality
copies such that one can fabricate authentic-looking documents
(i.e., pay stubs, tax returns).
[0008] Not only do fraudulent loans result in enormous financial
losses, misrepresenting information on a loan application is
illegal. Moreover, penalties for fraudulent lending violations
include substantial monetary penalties such as repayment of twice
the amount of all interest, fees, discounts and charges as well as
court and attorney fees to the borrower. In addition, such
violations can result in the temporary or permanent suspension of
business privileges of the lender, such as the ability to sell to
quasi-governmental agencies (e.g., Freddie Mac and Fannie Mae) or
in secondary markets, or the ability to sell certain types of
loans. In some cases, lenders can lose their licenses and face
imprisonment. In the secondary market, purchasers and assignees can
be held liable for all claims on loans in their possession. These
costs are then often passed on to consumers in the form of higher
loan costs, higher lending fees and higher interest rates.
[0009] Yet another risk associated with funding or insuring a loan
relates to the accuracy of the valuation of the subject property.
One of the most common problems associated with property valuations
is known as property flipping. This practice involves a property
that is bought and then resold (i.e., flipped) several times, each
time at a falsely inflated price. The property is then sold to an
unsuspecting mortgage company that pays much more for the property
than its market value that can result in a substantial loss to the
mortgage lender upon the reselling of the property. Typically,
lenders use internal or third party property valuation models or
tools such as AppIntell, Inc.'s ValVerify, Case Shiller Weiss'
CASA, Solimar's Basis100 or First American's product suite which
includes Value Point, Home Price Index, Assessed Value Model,
AREA's, and Value Point Plus to analyze the value of the property
provided in the loan documents and score it based on its accuracy.
Such an analysis looks at factors like the value of other
properties around the location of the subject property and the
selling prices of comparable properties. This score is usually in
the form of a value or grade representing a confidence level, which
corresponds to a range of predicated value. For example, in the
case of CASA, Grade A refers to a predicted value range within 6%,
Grade B refers to a predicted value range between 6% and 8%, Grade
C refers to a predicted value range of between 8% and 10%, Grade D
refers to a predicted value range between 10% and 14%, and Grade E
refers to a predicted value range between 14% and 20%. The bigger
the discrepancy between the property value provided in the loan
documents and the property value determined by such models or
tools, the greater the risk in funding or insuring the loan.
[0010] Currently, fraud, underwriting and property valuation
scoring systems originate from different sources. As a result, they
are not compatible with each other. In other words, mortgage
service providers must go to one company to have a risk assessment
of the loan from an underwriting perspective, a different company
to have a risk assessment of the loan from a fraud perspective, and
possibly yet a different company to have a risk assessment of the
loan from a property valuation perspective. This cumbersome process
not only significantly delays the underwriting process, but also
increases its costs tremendously. In fact, the single largest
insurance policy acquisition cost in mortgage insurance is contract
underwriting. Approximately half of loan public filings by private
mortgage insurers in 2000 were referred to underwriters for manual
review after the loan was scored vis-a-vis the borrower's credit
history. Moreover, since the scores are not compatible, they cannot
be combined into an overall score reflecting the level of risk of
funding or insuring a loan based on at least two of the three
scores. The potential cost and time savings as well as value of an
automatic risk assessment system that takes into account risk from
at least two of a fraud, underwriting and property valuation
perspective all provided from one source is enormous.
[0011] There is, therefore, a need for an automated system and
method that assesses the risk associated with funding or insuring a
loan based on a plurality of risk factors.
BRIEF SUMMARY OF THE INVENTION
[0012] It is in view of the above problems that the present
invention was developed. In particular, an automated loan risk
assessment system is disclosed which comprises a mechanism for
receiving information about a loan, and a mechanism for calculating
a risk score for the loan based on a plurality of risk factors
including at least two of a fraud risk factor, an underwriting risk
factor and a property valuation risk factor, whereby the risk score
can be used by a loan service provider in deciding whether or not
to fund or insure the loan. In one embodiment, the risk score is
based on a combination of the fraud risk score factor, the
underwriting risk factor and the property valuation risk
factor.
[0013] The risk calculation mechanism may further comprise a
mechanism for calculating a fraud risk score, a mechanism for
calculating an underwriting risk score, and a mechanism for
calculating a property valuation score, wherein the risk score for
the loan is based on at least two of the fraud risk score, the
underwriting risk score and the property valuation risk score. The
fraud risk score calculation mechanism comprises a mechanism for
storing general information about borrowers and properties, and a
mechanism for detecting one or more variances among the loan
information or between the loan information and the general
information, each variance having a certain degree, such that the
fraud risk score is based on the detected variances and the degrees
thereof. The system may further comprise a mechanism for
determining one or more steps needed to resolve the one or more
detected variances, a mechanism for tracking the status of the one
or more detected variances, and/or a mechanism for assigning a risk
category to the loan based on the risk score.
[0014] The underwriting risk score calculation mechanism comprises
means for obtaining the underwriting risk score from an
underwriting risk score provider, the property valuation risk score
calculation mechanism comprises means for obtaining a property
valuation risk score from a property valuation score provider. The
system further comprises a mechanism for converting at least one of
the fraud risk score, the underwriting risk score and the property
valuation risk score. In one embodiment, the converting mechanism
comprises a mechanism for weighting at least one of the fraud risk
score, the underwriting risk score and the property valuation risk
score based on the level of risk associated therewith such that the
risk score is based on the weights assigned thereto. In another
embodiment, the mechanism for converting comprises a mechanism for
converting at least one of the fraud risk score, the underwriting
risk score and the property valuation risk score such that all of
the scores are compatible, and wherein the risk score represents an
average of the compatible scores.
[0015] The loan information may include insurance information
related to at least one insurance claim being asserted against an
insurance policy to which a loan is subject, such that the
mechanism for calculating a risk score comprises a mechanism for
calculating a risk score for the claim based on a plurality of risk
factors including at least one of a fraud risk factor, an
underwriting risk factor and a property valuation risk factor,
whereby the risk score can be used by a loan service provider in
deciding whether to allow or deny the claim.
[0016] The system may further comprise a mechanism for interfacing
at least one pricing scheme of a loan service provider such that a
loan or an insurance policy for a loan can be automatically priced
based on the risk score calculated therefor.
[0017] The present invention also discloses a computer-readable
medium whose contents cause a computer system to assess the risk
associated with funding or insuring a loan by performing the steps
of receiving information about a loan, and calculating a risk score
for the loan based on a plurality of risk factors including at
least two of a fraud risk factor, a credit risk factor and a
property valuation risk factor. The step of calculating the risk
score further comprises the steps of calculating a fraud risk
score, calculating an underwriting risk score, and calculating a
property valuation score, wherein the risk score for the loan is
based on the fraud risk score, the underwriting risk score and the
property valuation risk score. In one embodiment, the risk score is
based on a combination of the fraud risk score, the underwriting
risk score and the property valuation risk score.
[0018] The step of calculating the fraud risk score may comprise
storing general information about borrowers and properties, and
detecting one or more variances among the loan information or
between the loan information and the general information, each
variance having a certain degree, such that the fraud risk score is
based on the detected variances and the degrees thereof. In one
embodiment, the medium includes the step of calculating a variance
score for each detected variance based on the degree thereof,
wherein the fraud risk score represents the sum of the variance
scores. The medium may further include the steps of determining one
or more steps needed to resolve the one or more detected variances,
tracking the status of the one or more detected variances, and/or
assigning a risk category to the loan based on the risk score.
[0019] The step of calculating the underwriting risk score may
comprise obtaining the underwriting risk score from an underwriting
risk score provider, and the step of calculating the property
valuation risk score may comprise obtaining a property valuation
risk score from a property valuation score provider. The medium may
further comprise the step of converting at least one of the fraud
risk score, the underwriting risk score and the property valuation
risk score. In one embodiment, the step of converting comprises
weighting at least one of the fraud risk score, the underwriting
risk score and the property valuation risk score based on the level
or risk associated therewith such that the risk score is based on
the weights assigned thereto. In another embodiment, the step of
converting comprises converting at least one of the fraud risk
score, the underwriting risk score and the property valuation risk
score such that all of the scores are compatible, and averaging the
compatible scores.
[0020] The loan information includes insurance information related
to at least one insurance claim being asserted against an insurance
policy to which a loan is subject, such that the medium further
comprises the step of calculating a risk score for the claim based
on a plurality of risk factors including at least one of a fraud
risk factor, an underwriting risk factor and a property valuation
risk factor, whereby the risk score can be used by a loan service
provider in deciding whether to allow or deny the claim.
[0021] The medium may further comprise the step of interfacing at
least one pricing scheme of a loan service provider such that a
loan or an insurance policy can be automatically priced based on
the risk score calculated therefor.
[0022] The present invention also discloses a computer-implemented
method of assessing the risk associated with the funding or
insuring of a loan. The method comprises receiving information
about a loan, and calculating a risk score for the loan based on a
plurality of risk factors including at least two of a fraud risk
factor, an underwriting risk factor and a property valuation risk
factor. The step of calculating the risk score comprises the steps
of calculating a fraud risk score, calculating an underwriting risk
score, and calculating a property valuation score, wherein the risk
score for the loan is based on the fraud risk score, the
underwriting risk score and the property valuation risk score. In
one embodiment, the risk score is based on a combination of the
fraud risk score, the underwriting risk score, and the property
valuation risk score. The step of calculating the fraud risk score
comprises storing general information about borrowers and
properties, and detecting one or more variances among the loan
information or between the loan information and the general
information, each variance having a certain degree, such that the
fraud risk score is based on the detected variances and the degrees
thereof. In one embodiment, the method further comprises the step
of calculating a variance score for each detected variance based on
the degree thereof, wherein the fraud risk score represents the sum
of the variance scores. The method may further comprise the steps
of determining one or more steps needed to resolve the one or more
detected variances, tracking the status of the one or more detected
variances, and/or assigning a risk category to the loan based on
the risk score.
[0023] The step of calculating the underwriting risk score
comprises obtaining a credit risk score from a credit risk score
provider, and the step of calculating the property valuation risk
score comprises obtaining a property valuation risk score from a
property valuation score provider. The method may further comprise
the step of converting at least one of the fraud risk score, the
underwriting risk score and the property valuation risk score. In
one embodiment, the step of converting comprises weighting at least
one of the fraud risk score, the underwriting risk score and the
property valuation risk score based on the level of risk associated
therewith such that the risk score is based on the weights assigned
thereto. In another embodiment, the step of converting comprises
converting at least one of the fraud risk score, the underwriting
risk score and the property valuation risk score such that all of
the scores are compatible, and averaging the compatible scores.
[0024] The loan information includes insurance information related
to at least one insurance claim being asserted against an insurance
policy to which the loan is subject, such that the step of
calculating a risk score comprises calculating a risk score for the
claim based on a plurality of factors including at least one of a
fraud risk factor, an underwriting risk factor, and a property
valuation risk factor, whereby the risk score can be used by a loan
service provider in deciding whether to allow or deny the
claim.
[0025] The method may further comprise the step of interfacing at
least one pricing scheme of a loan service provider such that a
loan or insurance policy can be automatically priced based on the
risk score calculated therefor.
BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS
[0026] The accompanying drawings, which are incorporated in and
form a part of the specification, illustrate the embodiments of the
present invention and together with the description, serve to
explain the principles of the invention. In the drawings:
[0027] FIG. 1 is a block diagram of a loan risk assessment system
in accordance with one embodiment of the present invention.
[0028] FIG. 2 is a flowchart illustrating one embodiment of the
steps for assessing the risk associated with a loan based on fraud
using the system of FIG. 1.
[0029] FIG. 3 shows one embodiment of an input screen display
generated by the system and method of the present invention.
[0030] FIG. 4 is a flowchart illustrating one embodiment of the
steps for assessing the risk associated with a loan based on a
combination of fraud, underwriting and property valuation risk
factors using the system of FIG. 1.
[0031] FIG. 5 shows one embodiment of a report generated by the
system and method of the present invention.
DETAILED DESCRIPTION OF THE INVENTION
[0032] FIG. 1 shows a block diagram of a system 10 in accordance
with one embodiment of the present invention; namely the assessment
of risk associated with insuring a mortgage based on a plurality of
risk factors including without limitation a fraud risk factor, an
underwriting risk factor and a property valuation risk factor.
While the system 10 will be described in connection with the
insurance of a mortgage, it can be appreciated that the system 10
can be applied to the funding or insuring of any type of loan. The
system 10 consists of a plurality of databases for storing a
plurality of different types of information. In particular, a
database 12 stores a variety of specific information related to the
loan, including without limitation information about the borrower
and the subject property. Such information may come from a variety
of documents including without limitation an insurance application
1, an Escrow Waiver 3, an Adjustable Rate Note 5, an Itemization of
Amount Financed 7, a U.S. Department of Housing and Urban
Development (HUD) I Settlement statement 9, an Adjustable Rate Note
11, a Special Closing Instructions document 13, a Truth-in-Lending
statement 15, a loan document worksheet 17, a Deed of Trust 19, and
a residential loan application 21 (also known as a "1003"). To the
extent the system 10 is also or alternatively being used to assess
the risk associated with insuring a loan, the loan information may
include information related to the insurance of the loan. Such
information may come from the insurer and the insurance
application.
[0033] A database 14 stores general information related to
borrowers, lenders, insurers, properties and any other aspect of
the loan. Borrower information may include personal information
about the borrower such as his or her name, address, and Social
Security number. Lender information may include the lender's name,
address and lending history. Property information may include
addresses and appraisal values. This general information can come
internally from the operator of the system 10, and/or from one or
more third party or external database sources. For example,
property information could come from such third party sources as
International Data Management Corporation (IDM), Data Quick and
Management Risk Assessment Corporation (MRAC), and Accumail United
States Postal Service National Database. Borrower and lender
information could come from third party sources, such as Trans
Union, Equifax, Lexis Nexis, Acxiom, Info USA and Dunn and
Bradstreet.
[0034] The loan information and the general information are stored
in a database server 16, which includes communication software for
communicating with third party or external databases not stored
therein. It can be appreciated, however, that the loan information
and the general information could be each stored in a separate
database server or stored in various combinations thereof as
needed. In one embodiment, the server database 16 is a Dell
Power-Edge 2400 running Sequel Server 2000 software in a Windows
2000 operating system environment. In a preferred embodiment, two
database servers are provided for load balancing and
redundancy.
[0035] The loan information may be input into system 10 for storage
in loan database 12 via input devices 18. While input devices 18 as
shown are personal computers, they can be any type of device that
allows the input of data. Specifically, the insurer logs on to
system 10 through an input device 18, whereupon several screens
such as screen 50 shown in FIG. 3, are displayed. Each screen 50
may include one or more fields in which the loan information can be
input. For example, screen 50 includes a General Information
section 52 in which general information about the borrower can be
input, such as last name, middle name, first name, Social Security
number, phone number, age and citizenship. Current residence
section 54 allows the insurer to input information related to the
borrower's current residence. Employer Information sections 56 and
58 allow the insurer to input information related to a borrower's
current and previous employers. Once the information has been
input, the insurer can save it by clicking on the "Save Data"
button 60. If the insurer does not wish to save the information, he
or she can simply click the "Cancel" button 62. Similar screens are
displayed to the insurer until all of the necessary loan
information has been input. Once input, the loan information can be
downloaded to loan database 12.
[0036] Input devices 18 are shown as being located at the insurer's
establishment such that the loan information is input directly by
the insurer and then simply downloaded to database server 16 for
storage in the loan database 12. The insurer may in turn use a
document preparation company or rely on the lender to input and
download some or all of the loan information directly for storage
in loan database 12. Alternatively, the loan information can be
sent to the operator of the system 10 to be input via one or more
input devices 20 connected either directly or remotely to an
application server 22. Such input devices 20 may then also be used
to input any general information to be stored in general database
14. The loan information may be input to system 10 by a lender in
the same manner as described above with respect to the insurer. One
or more of the input devices 18 or 20 may be connected to a printer
24 for printing reports generated by the system 10.
[0037] Application server 22 is responsible for processing the loan
information associated with each loan or insurance application to
assess the level of risk associated with the funding and/or
insuring of the loan, respectively. Application server 22 includes
memory (not shown) for storing the program or programs necessary
for assessing such risk as will be further discussed herein.
Application server 22 interfaces with the input devices 18,
underwriting scoring systems 30, and property valuation systems 32
through server 28. The connection between server 28 and input
devices 18, underwriting scoring systems 30, and property valuation
systems 32 can be via any communication network such as the
telephone network, a satellite network, a cable network or any
other communications network capable of transmitting information
across it. Server 28 includes communication software to allow it to
communicate with input devices 18, underwriting scoring systems 30,
and property valuation systems 32. In one embodiment, application
server 22 and server 28 are Dell Power-Edge 1550 servers running
Microsoft Internet Information Services (IIS) Server v5.0 software
under a Windows 2000 advanced server operating system. In a
preferred embodiment, server 28 is a web server that allows system
10 to be implemented through a website accessible via the Internet.
However, it can be appreciated that any type of server having the
necessary processing capabilities and storage capacity may be used.
In a preferred embodiment, application server 22 and server 28 are
provided in duplicate for load balancing and redundancy.
[0038] The process of assessing the level of risk associated with
insuring a loan will be described with reference to FIGS. 2, 4 and
5. For exemplary purposes, this process will be discussed in
connection with a system 10 that is web-based and accessed by a
mortgage insurer. It can be appreciated, however, that the system
10 need not be web-based to operate, and any loan service provider
with authorized access to the system 10 and who desires the ability
to automatically assess the risk associated with the funding and/or
insuring of a loan may use the system 10.
[0039] FIG. 2 illustrates the process of assessing the risk of
insuring a mortgage based on the fraud risk factor. At 100,
information about the loan requesting to be insured is input. At
102, application server 22 checks this loan information to
determine if there are any variances or differences among the loan
information stored in loan database 12 or between the loan
information stored in loan database 12 and the general information
stored in general information database 34. For example, in the case
of falsified identity, the social security number provided is
checked to see if it corresponds to someone who has died, if it has
been reported stolen, if it was issued prior to the borrower's
birth year, or it if does not match the borrower's age. If no
variances are found, at 105 the system 10 scores the loan
accordingly.
[0040] If one or more variances are found, at 106, the system 10
preferably scores each variance based on the degree thereof. In one
embodiment, the score is a numeric value such that the higher the
degree of variance, the lower the score. For example, a discrepancy
in the borrower's address may be scored lower (i.e., worse) than a
discrepancy in the employer's address. It can be appreciated,
however, that a reverse scoring system could be used whereby a
higher degree of variance results in a higher score. It can also be
appreciated that any type of scoring system indicative of the
severity of the risk associated with the detected variance,
including a non-numeric one, could be used. For example, each
detected variance can be assigned a specific weight or grade based
on its severity. Likewise, the system 10 can calculate a fraud
score (as discussed below) based on the type, number and severity
of the detected variances rather than scoring each variance
separately.
[0041] At 108, the system 10 calculates a fraud score based on the
sum of the scores of each detected variance and at 110, assigns the
loan a risk category based on the fraud score. In one embodiment, a
total score ranging between 600 and 1000 results in a "Pass" score,
a total score ranging between 401 and 599 results in a "High"
score, and a total score ranging between 0 and 400 results in an
"Investigate" score. A Pass score means that there were no or
minimal variances detected in connection with the loan information
and that therefore, there is no actual fraud detected in connection
with this loan. A High score means that the variances detected
indicate a potential for fraud and that therefore while there is a
relatively low level of risk of insuring the loan vis-a-vis fraud,
the insurer may nevertheless want to further scrutinize the loan
information. An Investigate score means that there is some aspect
of the loan that is potentially fraudulent, but a greater level of
risk than in the case of a High score. Again, any type of scoring
system indicative of the risk associated with the loan information
at issue may be used.
[0042] At 112, the system 10 determines what step or steps are
needed to resolve any detected variances, and at 114, the system 10
notifies the user of the results. FIG. 5 shows one embodiment of
how system 10 may notify a user of its results. Specifically, a
screen 70 is displayed to the user on his or her input device 18.
In section 72, identifying information about the loan is displayed,
such as the name of the borrower and the loan number. In section
74, more detailed loan information is provided, such as for example
the loan amount, the purchase price and the estimated/appraised
value. Section 76 provides information from the insurance
application. Section 76 provides a summary of the results of the
insurance application as processed by system 10. At 78, the total
fraud score is displayed, and at 80, the risk category (i.e., Pass,
High or Investigate) is identified.
[0043] In the case of an Investigate status, section 82 identifies
each variance or transgression and at 84, provides a description of
the variance. In the example shown, the first transgression
indicates that the property value exceeds its expected range. The
second transgression indicates that the effective date on the
insurance application does not reflect the loan closing date. At
86, the system 10 identifies any action that can be taken to
resolve the transgression. A section 88 is also preferably provided
which allows any additional comments regarding the transgression,
as well as a section 90 which allows the user to track the status
of a transgression and if and when it has been resolved.
Alternatively, in the case where the insurance application is not
being processed in real-time, notification can be sent to the user
via e-mail, facsimile, telephone or any other known notification
method.
[0044] FIG. 4 illustrates the process of assessing the level of
risk associated with insuring a loan vis-a-vis a combination of the
fraud, underwriting and property value risk factors. In particular,
at 200, information about the loan requesting to be insured is
input into system 10. At 202, application server 22 checks this
loan information to determine if there are any variances among the
loan information stored in loan database 12 or between the loan
information stored in loan database 12 and the general information
stored in general database 34. If no variances are detected, at 204
the system 10 scores the loan. If one or more variances are
detected, at 206, the system 10 scores each variance based on the
degree thereof. As stated previously herein, any scoring mechanism
may be used. At 208, the system 10 calculates a fraud score for
each insurance application based on the sum of the scores of each
detected variance. As previously mentioned, in the case where each
detected variance is not individually scored, the fraud score is
based on the number, type and severity of detected variances. At
210, the system 10 obtains an underwriting score from an
underwriting scoring system 30. At 212, the system 10 obtains a
property valuation score from a property valuation system 32. At
214, the system 10 calculates a combined score based on a
combination of the fraud, underwriting and property valuation
scores.
[0045] Step 214 is performed by combining the three scores based on
each individual score and the level of risk associated therewith.
For discussion purposes only, it will be assumed that the fraud and
property valuation scores are Pass, High or Investigate, and the
underwriting score is one generated from a Fannie Mae underwriting
system which includes the following: approve/eligible,
approve/ineligible, refer/eligible, refer/ineligible, refer with
caution or out of scope (i.e., reject). It will also be assumed
that the combined score calculated by the system 10 will be the
same as that used by the underwriting scoring system.
[0046] In one embodiment, the incompatible scores are "converted"
by system 10 by assigning a weight to each individual score
vis-a-vis the other scores and its corresponding level of risk. For
example, a fraud score of Investigate will always be weighted such
that the combined score will always be an Out of Scope score
regardless of the underwriting and property valuation scores.
Likewise, a property valuation score of Investigate will also
always be weighted such that the combined score will always be an
Out of Scope score regardless of the fraud and property valuation
scores. In the case where there are no Investigate scores but at
least one of the fraud or property valuation scores is High, the
combined score will be Refer with Caution. In general, the less
risk associated with each score, the better the combined score.
[0047] Alternatively, one or more of the scores are converted into
a score that is compatible with the other. For example, the numeric
fraud score can be used as the scoring system for the combined
score and the underwriting and property valuation scores can be
converted to a similar numeric value representative thereof. One
advantage of using the numeric scores is that the level of risk is
more specific. For instance, while a score of 401 and a score of
599 would both be High, the score 401 represents a higher risk than
the score 599. Under such a system, an approve/eligible score will
have a higher (i.e., better) score than a refer with caution score.
Each score can then be added together and an average score
computed. It can be appreciated, that any scoring system can be
used for the combined score and that any fraud, underwriting and/or
property valuation scores not compatible therewith would need to be
"converted" by system 10 before the combined score could be
calculated.
[0048] At 216, the system 10 assigns a risk category to the loan
based on the combined score. In a preferred embodiment, at 218, the
system 10 determines the steps needed to resolve any detected
variances. At 220, the system 10 notifies the user of the results,
and at 222 the process ends.
[0049] While the system and method have been described with respect
to the assessment of risk based on the fraud score by itself, and a
combination of the fraud, underwriting and property valuation
scores, it can be appreciated that the system and method of the
present invention can incorporate any combination of these scores
(i.e., fraud score plus underwriting score, fraud score plus
property valuation score, or underwriting plus property valuation
score). With such a system and method, a loan service provider can
better assess the level of risk involved with funding or insuring
the loan through one source.
[0050] The system and method of the present invention can also be
used to assist insurers with the processing of claims associated
with their insurance policies. The system is the same in structure
as system 10 shown in FIG. 1, except that the loan database 12
includes information input by the insurer related to the claims and
corresponding insurance policies at issue and each insured's
payment history for the policy. An insurer can determine whether to
accept or deny a claim depending on at least one of a fraud risk
score, and underwriting risk score, a property valuation risk score
or a combined score calculated by the system for the claim at
issue.
[0051] Finally, the system and method of the present invention can
also be used as an automatic risk-pricing tool to assist loan
service providers with the pricing of loans and insurance policies,
respectively. Specifically, since the combined score is
representative of the risk associated with the loan or insurance
application, it can be used to price the loan or insurance policy
covering it. In particular, server 28 of FIG. 1 interfaces the
lender's or insurer's pricing scheme (not shown), such that the
loan or insurance policy at issue can be automatically priced out
based on the combined score calculated therefor.
[0052] In view of the foregoing, it will be seen that the several
advantages of the invention are achieved and attained. The
embodiments were chosen and described in order to best explain the
principles of the invention and its practical application to
thereby enable others skilled in the art to best utilize the
invention in various embodiments and with various modifications as
are suited to the particular use contemplated. As various
modifications could be made in the constructions and methods herein
described and illustrated without departing from the scope of the
invention, it is intended that all matter contained in the
foregoing description or shown in the accompanying drawings shall
be interpreted as illustrative rather than limiting. Thus, the
breadth and scope of the present invention should not be limited by
any of the above-described exemplary embodiments, but should be
defined only in accordance with the following claims appended
hereto and their equivalents.
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