U.S. patent application number 14/170892 was filed with the patent office on 2014-05-29 for systems and methods for detecting fraud.
This patent application is currently assigned to LexisNexis Risk Solutions FL Inc.. The applicant listed for this patent is LexisNexis Risk Solutions FL Inc.. Invention is credited to Andrew John Bucholz, Monty Faidley, Mark Loizzo, Dermot O'Mahony, Jennifer Paganacci, Johannes Philippus de Villiers Prichard, Jesse CBD Shaw, Scott M. Straub, Marlene Thorogood, David Yeschek.
Application Number | 20140149304 14/170892 |
Document ID | / |
Family ID | 49879251 |
Filed Date | 2014-05-29 |
United States Patent
Application |
20140149304 |
Kind Code |
A1 |
Bucholz; Andrew John ; et
al. |
May 29, 2014 |
SYSTEMS AND METHODS FOR DETECTING FRAUD
Abstract
Certain embodiments of the disclosed technology may include
systems and methods for detecting fraud. According to an
implementation of the disclosed technology, a method is provided
that includes: receiving entity-supplied information including at
least a name, a social security number, and a mailing address
associated with a request for a payment or a benefit from a
government agency; querying one or more public or private databases
with the entity-supplied information; receiving a plurality of
independent information in response to the querying; determining,
based at least in part on a comparison of the entity-supplied
information with at least a portion of the plurality of independent
information, indicators of fraud; and outputting, for display, zero
or more indicators of fraud.
Inventors: |
Bucholz; Andrew John;
(Alexandria, VA) ; Straub; Scott M.; (Washington,
DC) ; Faidley; Monty; (Kennesaw, GA) ;
Prichard; Johannes Philippus de Villiers; (Boynton Beach,
FL) ; Shaw; Jesse CBD; (Saint Cloud, MN) ;
O'Mahony; Dermot; (Washington, DC) ; Yeschek;
David; (Boynton Beach, FL) ; Paganacci; Jennifer;
(Delray Beach, FL) ; Thorogood; Marlene; (Boca
Raton, FL) ; Loizzo; Mark; (Boca Raton, FL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
LexisNexis Risk Solutions FL Inc. |
Boca Raton |
FL |
US |
|
|
Assignee: |
LexisNexis Risk Solutions FL
Inc.
Boca Raton
FL
|
Family ID: |
49879251 |
Appl. No.: |
14/170892 |
Filed: |
February 3, 2014 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
|
|
13541157 |
Jul 3, 2012 |
8682755 |
|
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14170892 |
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Current U.S.
Class: |
705/325 |
Current CPC
Class: |
G06Q 50/265 20130101;
G06Q 40/00 20130101 |
Class at
Publication: |
705/325 |
International
Class: |
G06Q 50/26 20060101
G06Q050/26 |
Claims
1. A computer-implemented method for detecting fraud related to an
identity misrepresentation, identity creation or identity
usurpation, the method comprising: receiving entity-supplied
information comprising at least a name, a social security number,
and a mailing address associated with a request for a payment or a
benefit from a government agency; querying one or more public or
private databases with the entity-supplied information; receiving a
plurality of independent information in response to the querying,
wherein the plurality of independent information includes, as
applicable: an indication of whether or not the entity is deceased,
and a date of death when the entity is indicated as deceased;
independent address information associated with the entity; address
validity information associated with the entity-supplied
information; one or more records associated with the
entity-supplied information; or no information; and determining,
with one or more computer processors in communication with a
memory, based at least in part on a comparison of the
entity-supplied information with at least a portion of the
plurality of independent information, indicators of fraud,
comprising: entity deceased within a year of the request or died
within a timeframe of the year that would indicate a possible
non-fraud request for the payment or the benefit; the
entity-supplied mailing address does not match with any of the
independent address information; the entity-supplied mailing
address having no record of association with any independent
address information, including addresses of relatives or addresses
of associates; and the entity-supplied mailing address includes an
entity-supplied zip code having no record of association with one
or more zip codes associated with the independent address
information; and outputting, for display, zero or more indicators
of fraud, wherein zero indicators of fraud correspond to no fraud
determined.
2. The method of claim 1, further comprising: determining, based at
least in part on a comparison of the entity-supplied information
with the plurality of independent information, zero or more fraud
false positive indicators, wherein a false positive indicator
corresponds to a legitimate request for the payment or the benefit
from the government agency that appears fraudulent, the zero or
more fraud false positive indicators comprising one or more of: the
entity appears to be a minor based on one or more of the
entity-supplied information and the independent information,
wherein the entity-supplied social security number is valid and
issued within three to fifteen years; the entity is at least
twenty-four years old, and the independent information comprises no
information; the entity-supplied mailing address is invalid with a
record of association between a zip code of the entity-supplied
mailing address and one or more zip codes associated with the
independent address information; and outputting the zero or more
fraud false positive indicators.
3. The method of claim 1, wherein, the indication of whether or not
the entity is deceased comprises a length of time since the entity
has deceased when the entity is indicated as deceased.
4. The method of claim 1, wherein receiving the plurality of
independent information comprises receiving the one or more records
comprising one or more of housing records, vehicular records,
marriage records, divorce records, hospital records, death records,
court records, property records, incarceration records, tax
records, and utility records, wherein the utility records comprise
one or more of utility hookups, disconnects, and associated service
addresses.
5. The method of claim 1, wherein receiving the independent address
information or the address validity information comprises receiving
one or more addresses of relatives or associates of the entity.
6. The method of claim 1, wherein the one or more public or private
databases are independent of the government agency.
7. The method of claim 1, further comprising generating a quiz for
soliciting authentication input from the entity or from a requester
of the payment or benefit.
8. The method of claim 7, wherein the quiz is generated in response
to detecting one or more indicators of fraud.
9. A computer-implemented method for detecting fraud related to an
identity misrepresentation, identity creation or identity
usurpation, the method comprising: receiving entity-supplied
information comprising at least a name and a social security number
associated with a request for a payment or a benefit from a
government agency; querying one or more public or private databases
with the entity-supplied information; receiving, based at least on
the querying of the one or more public or private databases, data
comprising one or more of a second social security number or a
social security number variant associated with the entity-supplied
name, a second name associated with the entity-supplied social
security number, and a name variant associated with the
entity-supplied social security number; querying an accessible Do
Not Pay list with one or more combinations or variants of the
entity-supplied information and the received public or private
data; and outputting a fraud alert when the one or more
combinations or variants result in a match with at least one record
in the Do Not Pay list.
10. The computer-implemented method of claim 9, wherein querying
the Do Not Pay list with one or more combinations or variants
comprises querying the Do Not Pay list with one or more of the
entity-supplied name and the entity-supplied social security
number, the entity-supplied name and the second social security
number or the social security number variant, the second name or
the name variant and the entity supplied social security number, or
the second name or the name variant and the second social security
number or the social security number variant.
11. A system comprising: at least one memory for storing data and
computer-executable instructions; and at least one processor
configured to access the at least one memory and further configured
to execute the computer-executable instructions to: receive
entity-supplied information comprising at least a name, a social
security number, and a mailing address associated with a request
for a payment or a benefit from a government agency; query one or
more public or private databases with the entity-supplied
information; receive a plurality of independent information in
response to the querying, wherein the plurality of independent
information includes, as applicable: an indication of whether or
not the entity is deceased, and a date of death when the entity is
indicated as deceased; independent address information associated
with the entity; address validity information associated with the
entity-supplied information; one or more-records associated with
the entity-supplied information; and no information; and determine,
with the at least on processor, based at least in part on a
comparison of the entity-supplied information with at least a
portion of the plurality of independent information, indicators of
fraud, comprising one or more of: entity deceased within a year of
the request or died within a timeframe that would indicate a
possible non-fraud request for the payment or the benefit; the
entity-supplied mailing address does not match with any of the
independent address information; the entity-supplied mailing
address having no record of association with any independent
address information, including addresses of relatives or addresses
of associates; and the entity-supplied mailing address includes an
entity-supplied zip code having no record of association with one
or more zip codes associated with the independent address
information; and output, for display, zero or more indicators of
fraud, wherein zero indicators of fraud correspond to no fraud
determined.
12. The system of claim 11, wherein the at least one processor is
further configured to execute the computer-executable instructions
to: determine, based at least in part on a comparison of the
entity-supplied information with the plurality of independent
information, zero or more fraud false positive indicators, wherein
a false positive indicator corresponds to a legitimate request for
the payment or the benefit that appears fraudulent, the zero or
more fraud false positive indicators comprising one or more of: the
entity appears to be a minor based on one or more of the
entity-supplied information and the independent information,
wherein the entity-supplied social security number is valid and
issued within three to fifteen years; the entity is at least
twenty-four years old, and the independent information comprises no
information; and the entity-supplied mailing address is invalid
with a record of association between a zip code of the
entity-supplied mailing address and one or more zip codes
associated with the independent address information; and output the
zero or more fraud false positive indicators.
13. The system of claim 11, wherein, the indication of whether or
not the entity is deceased comprises a length of time since the
entity has deceased when the entity is indicated as deceased.
14. The system of claim 11, wherein the plurality of independent
information comprises one or more of housing records, vehicular
records, marriage records, divorce records, hospital records, death
records, court records, property records, incarceration records,
tax records, or utility records, wherein the utility records
comprise one or more of utility hookups, disconnects, and
associated service addresses.
15. The system of claim 11, wherein the independent address
information or the address validity information comprises one or
more addresses of relatives or addresses of associates of the
entity.
16. The system of claim 11, wherein the one or more public or
private databases are independent of the government agency.
17. The system of claim 11, wherein the at least one processor is
further configured to execute the computer-executable instructions
to generate a quiz for soliciting authentication input from the
entity or from a requester of the payment or benefit.
18. The method of claim 17, wherein the quiz is generated in
response to detecting one or more indicators of fraud.
19. A system comprising: at least one memory for storing data and
computer-executable instructions; and at least one processor
configured to access the at least one memory and further configured
to execute the computer-executable instructions to: receive
entity-supplied information comprising at least a name and a social
security number associated with a request for a payment or a
benefit from a government agency; query one or more public or
private databases with the entity-supplied information; receive,
based at least on the querying of the one or more public or private
databases, data comprising one or more of a second social security
number or a social security number variant associated with the
entity-supplied name, a second name associated with the
entity-supplied social security number, and a name variant
associated with the entity-supplied social security number; query
an accessible Do Not Pay list with one or more combinations or
variants of the entity-supplied information and the received public
or private data; and output a fraud alert when the one or more
combinations or variants result in a match with at least one record
in the Do Not Pay list.
20. The system of claim 19, wherein the one or more combinations or
variants of the entity-supplied information and the received public
data comprises one or more of the entity-supplied name and the
entity-supplied social security number, the entity-supplied name
and the second social security number or social security number
variant, the second name or name variant and the entity supplied
social security number, or the second name or the name variant and
the second social security number or the social security number
variant.
21. The system of claim 19, wherein the at least one processor is
further configured to execute the computer-executable instructions
to generate a quiz for soliciting authentication input from the
entity or from a requester of the payment or benefit.
22. The system of claim 21, wherein the quiz is generated in
response to detecting one or more indicators of fraud.
23. One or more computer readable media comprising
computer-executable instructions that, when executed by one or more
processors, configure the one or more processors to: receive
entity-supplied information comprising at least a name and a social
security number associated with a request for a payment or a
benefit from a government agency; query one or more public or
private databases with the entity-supplied information; receive a
plurality of independent information in response to the querying,
wherein the plurality of independent information includes, as
applicable: an indication of whether or not the entity is deceased,
and a date of death when the entity is indicated as deceased;
independent address information associated with the entity; address
validity information associated with the entity-supplied
information; one or more records associated with the
entity-supplied information; or no information; and determine, with
one or more computer processors in communication with a memory,
based at least in part on a comparison of the entity-supplied
information with at least a portion of the plurality of independent
information, indicators of fraud, comprising: entity deceased
within a year of the request or died within a timeframe that would
indicate a possible non-fraud request; the entity-supplied mailing
address does not match with any of the independent address
information; the entity-supplied mailing address having no record
of association with any independent address information, including
addresses of relatives or addresses of associates; and the
entity-supplied mailing address includes an entity-supplied zip
code having no record of association with one or more zip codes
associated with the independent address information; and output,
for display, zero or more indicators of fraud, wherein zero
indicators of fraud correspond to no fraud determined.
24. The computer readable media of claim 23, further comprising
computer-executable instructions that, when executed by one or more
processors, configure the one or more processors to: determine,
based at least in part on a comparison of the entity-supplied
information with the plurality of independent information, zero or
more fraud false positive indicators, wherein a false positive
indicator corresponds to a legitimate request for the payment or
the benefit from the government agency that appears fraudulent, the
zero or more fraud false positive indicators comprising one or more
of: the entity appears to be a minor based on one or more of the
entity-supplied information and the independent information,
wherein the entity-supplied social security number is valid and
issued within three to fifteen years; the entity is at least
twenty-four years old, and the independent information comprises no
information; the entity-supplied mailing address is invalid with a
record of association between a zip code of the entity-supplied
mailing address and one or more zip codes associated with the
independent address information; and output the zero or more fraud
false positive indicators.
25. The computer readable media of claim 23, further comprising
computer-executable instructions that, when executed by one or more
processors, configure the one or more processors to generate a quiz
for soliciting authentication input from the entity or from a
requester of the payment or benefit.
26. The computer readable media of claim 23, wherein the quiz is
generated in response to detecting one or more indicators of
fraud.
27. One or more computer readable media comprising
computer-executable instructions that, when executed by one or more
processors, configure the one or more processors to: receive
entity-supplied information comprising at least a name and a social
security number associated with a request for a payment or a
benefit from a government agency; query one or more public or
private databases with the entity-supplied information; receive,
based at least on the querying of the one or more public or private
databases, data comprising one or more of a second social security
number or social security number variant associated with
entity-supplied name, a second name associated with the
entity-supplied social security number, or a name variant
associated with the entity-supplied social security number; query
an accessible Do Not Pay list with one or more combinations or
variants of the entity-supplied information and the received public
or private data; and output a fraud alert when the one or more
combinations or variants result in a match with at least one record
in the Do Not Pay list.
28. The computer readable media of claim 27, wherein the one or
more combinations or variants of the entity-supplied information
and the received data comprises one or more of the entity-supplied
name and the entity-supplied social security number, the
entity-supplied name and the second social security number or the
social security number variant, the second name or the name variant
and the entity supplied social security number, or the second name
or the name variant and the second social security number or the
social security number variant.
29. The computer readable media of claim 27, further comprising
computer-executable instructions that, when executed by one or more
processors, configure the one or more processors to generate a quiz
for soliciting authentication input from the entity or from a
requester of the payment or benefit.
30. The computer readable media of claim 29, wherein the quiz is
generated in response to detecting one or more indicators of fraud.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 13/541,157, filed Jul. 3, 2012, and published
as U.S. Patent Publication No. US20140012716, entitled "SYSTEMS AND
METHODS FOR DETECTING TAX REFUND FRAUD," the contents of which are
hereby incorporated by reference in its entirety.
FIELD
[0002] The disclosed technology generally relates to detecting
fraud, and in particular, to systems and methods for detecting
fraud related to a request for a payment or a benefit from a
government agency.
BACKGROUND
[0003] Federal and state revenue departments in the United States
face a number of problems associated with fraudulent requests for
payments, benefits, and/or refunds. Fraudsters can apply for
payments, benefits, and/or refunds by misrepresenting their
identity, by stealing and using identity information from another
individual, or by using an identity of a deceased person. The
associated revenue loss to the federal and state government agency
can be significant, and the process of verifying the legitimacy of
the requester's identity can create costly delays.
[0004] Technically well-informed fraud perpetrators with
sophisticated deception schemes are likely to continue targeting
governmental entities, particularly if fraud detection and
prevention mechanisms are not in place. Balancing the threats of
identity fraud with efficient service for legitimate requests
creates a significant challenge for governmental entities.
BRIEF SUMMARY
[0005] Some or all of the above needs may be addressed by certain
embodiments of the disclosed technology. Certain embodiments of the
disclosed technology may include systems and methods for detecting
fraud.
[0006] According to an exemplary embodiment of the disclosed
technology, a method is provided for detecting fraud related to an
identity misrepresentation, identity creation or identity
usurpation. The method includes receiving entity-supplied
information comprising at least a name, a social security number,
and a mailing address associated with a request for a payment or a
benefit from a government agency; querying one or more public or
private databases with the entity-supplied information; receiving a
plurality of independent information in response to the querying,
wherein the plurality of independent information includes, as
applicable: an indication of whether or not the entity is deceased,
and a date of death when the entity is indicated as deceased;
independent address information associated with the entity; address
validity information associated with the entity-supplied
information; one or more records associated with the
entity-supplied information; or no information. The method further
includes determining, with one or more computer processors in
communication with a memory, based at least in part on a comparison
of the entity-supplied information with at least a portion of the
plurality of independent information, indicators of fraud. The
indicators of fraud can include: the entity deceased within a year
of the request or died within a timeframe of the year that would
indicate a possible non-fraud request for the payment or the
benefit; the entity-supplied mailing address does not match with
any of the independent address information; the entity-supplied
mailing address having no record of association with any
independent address information, including addresses of relatives
or addresses of associates; and the entity-supplied mailing address
includes an entity-supplied zip code having no record of
association with one or more zip codes associated with the
independent address information. The method further includes
outputting, for display, zero or more indicators of fraud, wherein
zero indicators of fraud correspond to no fraud determined.
[0007] According to an exemplary embodiment of the disclosed
technology, another method is provided for detecting fraud related
to an identity misrepresentation, identity creation or identity
usurpation. The method can include receiving entity-supplied
information comprising at least a name and a social security number
associated with a request for a payment or a benefit from a
government agency; querying one or more public or private databases
with the entity-supplied information; receiving, based at least on
the querying of the one or more public or private databases, data
comprising one or more of a second social security number or a
social security number variant associated with the entity-supplied
name, a second name associated with the entity-supplied social
security number, and a name variant associated with the
entity-supplied social security number; querying an accessible Do
Not Pay list with one or more combinations or variants of the
entity-supplied information and the received public or private
data; and outputting a fraud alert when the one or more
combinations or variants result in a match with at least one record
in the Do Not Pay list.
[0008] According to an example implementation of the disclosed
technology, a system is provided. The system includes at least one
memory for storing data and computer-executable instructions; and
at least one processor configured to access the at least one memory
and further configured to execute the computer-executable
instructions to: receive entity-supplied information comprising at
least a name, a social security number, and a mailing address
associated with a request for a payment or a benefit from a
government agency; query one or more public or private databases
with the entity-supplied information; receive a plurality of
independent information in response to the querying. The plurality
of independent information includes, as applicable: an indication
of whether or not the entity is deceased, and a date of death when
the entity is indicated as deceased; independent address
information associated with the entity; address validity
information associated with the entity-supplied information; one or
more records associated with the entity-supplied information; and
no information. The at least one processor is further configured to
execute the computer-executable instructions to determine, with the
at least on processor, based at least in part on a comparison of
the entity-supplied information with at least a portion of the
plurality of independent information, indicators of fraud. The
indicators of fraud may include one or more of: (1) the entity
deceased within a year of the request or died within a timeframe
that would indicate a possible non-fraud request for the payment or
the benefit; (2) the entity-supplied mailing address does not match
with any of the independent address information; (3) the
entity-supplied mailing address having no record of association
with any independent address information, including addresses of
relatives or addresses of associates; and (4) the entity-supplied
mailing address includes an entity-supplied zip code having no
record of association with one or more zip codes associated with
the independent address information. The at least one processor is
further configured to execute the computer-executable instructions
to output, for display, zero or more indicators of fraud, wherein
zero indicators of fraud correspond to no fraud determined.
[0009] According to another exemplary embodiment, a system is
provided that includes at least one memory for storing data and
computer-executable instructions; and at least one processor
configured to access the at least one memory and further configured
to execute the computer-executable instructions to: receive
entity-supplied information comprising at least a name and a social
security number associated with a request for a payment or a
benefit from a government agency; query one or more public or
private databases with the entity-supplied information; receive,
based at least on the querying of the one or more public or private
databases, data comprising one or more of a second social security
number or a social security number variant associated with the
entity-supplied name, a second name associated with the
entity-supplied social security number, and a name variant
associated with the entity-supplied social security number; query
an accessible Do Not Pay list with one or more combinations or
variants of the entity-supplied information and the received public
or private data; and output a fraud alert when the one or more
combinations or variants result in a match with at least one record
in the Do Not Pay list.
[0010] Exemplary embodiments of the disclosed technology can
include one or more computer readable media comprising
computer-executable instructions that, when executed by one or more
processors, configure the one or more processors to perform a
method. The method includes receiving entity-supplied information
comprising at least a name, a social security number, and a mailing
address associated with a request for a payment or a benefit from a
government agency; querying one or more public or private databases
with the entity-supplied information; receiving a plurality of
independent information in response to the querying, wherein the
plurality of independent information includes, as applicable: an
indication of whether or not the entity is deceased, and a date of
death when the entity is indicated as deceased; independent address
information associated with the entity; address validity
information associated with the entity-supplied information; one or
more records associated with the entity-supplied information; or no
information. The method further includes determining, with one or
more computer processors in communication with a memory, based at
least in part on a comparison of the entity-supplied information
with at least a portion of the plurality of independent
information, indicators of fraud. The indicators of fraud can
include: the entity deceased within a year of the request or died
within a timeframe of the year that would indicate a possible
non-fraud request for the payment or the benefit; the
entity-supplied mailing address does not match with any of the
independent address information; the entity-supplied mailing
address having no record of association with any independent
address information, including addresses of relatives or addresses
of associates; and the entity-supplied mailing address includes an
entity-supplied zip code having no record of association with one
or more zip codes associated with the independent address
information. The method further includes outputting, for display,
zero or more indicators of fraud, wherein zero indicators of fraud
correspond to no fraud determined.
[0011] Exemplary embodiments of the disclosed technology can
include one or more computer readable media comprising
computer-executable instructions that, when executed by one or more
processors, configure the one or more processors to perform a
method. The method includes receiving entity-supplied information
comprising at least a name and a social security number associated
with a request for a payment or a benefit from a government agency;
querying one or more public or private databases with the
entity-supplied information; receiving, based at least on the
querying of the one or more public or private databases, data
comprising one or more of a second social security number or a
social security number variant associated with the entity-supplied
name, a second name associated with the entity-supplied social
security number, and a name variant associated with the
entity-supplied social security number; querying an accessible Do
Not Pay list with one or more combinations or variants of the
entity-supplied information and the received public or private
data; and outputting a fraud alert when the one or more
combinations or variants result in a match with at least one record
in the Do Not Pay list.
[0012] Other embodiments, features, and aspects of the disclosed
technology are described in detail herein and are considered a part
of the claimed disclosed technologies. Other embodiments, features,
and aspects can be understood with reference to the following
detailed description, accompanying drawings, and claims.
BRIEF DESCRIPTION OF THE FIGURES
[0013] Reference will now be made to the accompanying figures and
flow diagrams, which are not necessarily drawn to scale, and
wherein:
[0014] FIG. 1 is a block diagram of various illustrative scenarios
associated with a request for payment or benefit, according to
exemplary embodiments of the disclosed technology.
[0015] FIG. 2 is a block diagram of an illustrative fraud detection
system 200 according to an exemplary embodiment of the disclosed
technology.
[0016] FIG. 3 is a block diagram of an illustrative fraud detection
system architecture 300 according to an exemplary embodiment of the
disclosed technology.
[0017] FIG. 4 is a flow diagram of a method 400 according to an
exemplary embodiment of the disclosed technology.
[0018] FIG. 5 is a flow diagram of a method 500 according to an
exemplary embodiment of the disclosed technology.
DETAILED DESCRIPTION
[0019] Embodiments of the disclosed technology will be described
more fully hereinafter with reference to the accompanying drawings,
in which embodiments of the disclosed technology are shown. This
disclosed technology may, however, be embodied in many different
forms and should not be construed as limited to the embodiments set
forth herein; rather, these embodiments are provided so that this
disclosure will be thorough and complete, and will fully convey the
scope of the disclosed technology to those skilled in the art.
[0020] In the following description, numerous specific details are
set forth. However, it is to be understood that embodiments of the
disclosed technology may be practiced without these specific
details. In other instances, well-known methods, structures and
techniques have not been shown in detail in order not to obscure an
understanding of this description. The term "exemplary" herein is
used synonymous with the term "example" and is not meant to
indicate excellent or best. References to "one embodiment," "an
embodiment," "exemplary embodiment," "various embodiments," etc.,
indicate that the embodiment(s) of the disclosed technology so
described may include a particular feature, structure, or
characteristic, but not every embodiment necessarily includes the
particular feature, structure, or characteristic. Further, repeated
use of the phrase "in one embodiment" does not necessarily refer to
the same embodiment, although it may.
[0021] As used herein, unless otherwise specified the use of the
ordinal adjectives "first," "second," "third," etc., to describe a
common object, merely indicate that different instances of like
objects are being referred to, and are not intended to imply that
the objects so described must be in a given sequence, either
temporally, spatially, in ranking, or in any other manner.
[0022] Certain embodiments of the disclosed technology may enable
the detection of possible, probable, and/or actual fraud associated
with a request for a payment or a benefit to a governmental agency.
Embodiments disclosed herein may provide systems and methods for
detecting identity misrepresentation, identity creation or identity
usurpation related to the request. According to an example
implementation of the disclosed technology, information supplied by
a requester, together with information obtained from other sources,
such as public or private databases, may be utilized to determine
if the request is likely to be fraudulent or legitimate.
[0023] Certain embodiments of the disclosed technology may enable
detection of various requests for payment, benefit, service,
refund, etc. from a government agency or entity. The government
agency, as referred to herein, may include any government entity or
jurisdiction, including but not limited to federal, state,
district, county, city, etc. Embodiments of the disclosed
technology may be utilized to detect fraud associated with
non-government entities. For example, embodiments of the disclosed
technology may be utilized by various businesses, corporations,
non-profits, etc., to detect fraud.
[0024] In one example application of the disclosed technology,
suspect or fraudulent tax returns refund requests may be detected.
For example, the disclosed technology may utilize information
supplied by the refundee together with information obtained from
other sources, such as public or private databases, to determine if
the refund request is likely to be fraudulent or legitimate.
[0025] Certain example implementations of the disclosed technology
may utilize an authentication process in response to the detection
of a possible fraudulent request. For example, in response to the
detection of one or more indicators of a fraudulent request for
payment or benefit, a quiz may be generated and the requester may
be required to provide correct answers before receiving the payment
or benefit. In one example implementation, the quiz may be utilized
to authenticate the person(s) requesting the payment or
service.
[0026] According to an example implementation, if a payment or
service (such as a tax refund, for example) is requested and if the
associated request information is analyzed by the system and found
to have questionable validity (such as a low score, for example),
the quiz may be generated for the requester to complete. According
to an example implementation, the quiz may be generated from
information derived from one or more databases, and may take the
form of a set of questions. In one example implementation, one or
more of the questions associated with the generated quiz may be
multiple choice. In another example implementation, one or more of
the questions associated with the quiz may require specific input.
In an example implementation, if the requester passes the quiz,
then the requested payment or benefit may be processed so that the
requester may receive the payment or benefit. Conversely, if the
requester fails the quiz, then the requested payment or benefit may
not be processed and the requester may not receive the funds
without further authentication. Embodiments utilizing the quiz may
help reduce the number requests that have been incorrectly flagged
as fraudulent.
[0027] Various exemplary embodiments of the disclosed technology
will now be described with reference to the accompanying
figures.
[0028] FIG. 1 shows a block diagram illustrating various scenarios
associated with a request for payment or benefit, according to
exemplary embodiments of the disclosed technology. In one example
scenario, a legitimate requester 102 may submit request for payment
or benefit to a governmental entity 108. In another example
implementation, the request may be submitted to a private or public
entity, such as a company 110. The request, in one example
implementation, may be in the form of a tax return to the
governmental entity 108, for example, the Internal Revenue Service
(IRS) or a State Revenue Department.
[0029] In one example implementation, the legitimate requester 102
may have a legitimate social security number 104 associated with
their name. In certain exemplary embodiments, the legitimate
requester 102 may also have a legitimate address 106 associated
with their name and/or social security number 104. According to
certain exemplary embodiments, one or more databases 138 may be
utilized, for example, to verify that the name, social security
number 104, and/or address 106 match the identity of the legitimate
requester 102. In a typical normal scenario, the legitimate
requester 102 may submit the request for payment or benefit, and
governmental entity 108 may provide the payment or benefit 112. For
example, the payment or benefit, in one example implementation may
be a tax refund. Accordingly, in certain example implementation,
the payment or benefit 112 may be dispersed to the legitimate
requester 102 by one or more of: (1) a check mailed to the
legitimate address 106; (2) a debit card 116 mailed to the
legitimate address 106; or (3) electronic funds transferred 113 to
the legitimate taxpayer's 102 bank account 114. In other example
implementations, the payment or benefit 112 may dispersed or
provided according to the normal procedures of the providing
entity. In such a scenario, the system 100 may work quickly and
efficiently to provide payment or service (for example a refund tax
overpayment) to the legitimate requester 102.
[0030] Unfortunately, there exists other scenarios, as depicted in
FIG. 1, where a fraudster 124 may apply for payment or benefit 112
using misrepresented or stolen identity information. In one
exemplary scenario, the fraudster 124 may apply for payment or
benefit 112 using a social security number 120 and name associated
with a deceased person 118. In certain scenarios, the fraudster 124
may open a bank account 114 in the name of the deceased person 118
and request the payment or benefit 112 in the form of an electronic
deposit 113. In another scenario, the fraudster 124 may request the
payment or benefit 112 in the form of a debit card. Each of these
scenarios may result in the fraudster 124 obtaining the payment or
benefit 112 without having to present positive identification, for
example, as is typically needed to cash a check.
[0031] In certain scenarios, the fraudster 124 may actually reside
at a first address 132, or even in jail 130, but may submit a
request for payment or benefit using a second address 128 to avoid
being tracked down. In certain scenarios, the fraudster 124 may
provide a fabricated social security number 126 in requesting the
payment or benefit. In yet another scenario, the fraudster 126 may
steal the real social security number 136 associated with a child
134 to obtain payment or benefit.
[0032] Exemplary embodiments of the disclosed technology may be
utilized to detect a potential fraudulent requests for payment or
benefits, and may be utilized to cancel a payment or benefit to a
potential fraudster 124. Other exemplary embodiments of the
disclosed technology may be utilized to detect false positive
situations and allow payment or benefit for scenarios that may
otherwise be flagged as being suspicious. For example, a legitimate
scenario that can appear as fraudulent involves taxable income from
a first job. Typically, such taxpayers in this category may be
minors with no public record associated with a residence or prior
income. Embodiments of the disclosed technology may utilize social
security number patterns, blocks, etc., and/or the age of the
requester 102 124 to determine legitimacy of the request and/or the
legitimacy of the requester's identity.
[0033] According to certain exemplary embodiments of the disclosed
technology, a requester 102 124 may provide certain entity-supplied
information with a request for payment or benefit 112 that includes
at least a name, social security number, and mailing address. In an
exemplary embodiment, one or more databases 138 may be queried with
the entity-supplied information. For example, the one or more
databases 138 may include public or private databases. In
accordance with certain exemplary embodiments, one or more public
records may be utilized verify entity-supplied information or
retrieve additional information based on the entity-supplied
information. According to exemplary embodiments, the public records
may include one or more of housing records, vehicular records,
marriage records, divorce records, hospital records, death records,
court records, property records, incarceration records, or utility
records. In exemplary embodiments, the utility records can include
one or more of utility hookups, disconnects, and associated service
addresses.
[0034] According to exemplary embodiments, a plurality of
independent information may be received in response to the querying
of the public or private database(s). In accordance with exemplary
embodiments, the independent information may include, but is not
limited to (1) an indication of whether or not the entity is
deceased; (2) independent address information associated with the
entity; (3) address validity information associated with the
entity-supplied information; (3) one or more public records
associated with the entity-supplied information; or (4) no
information.
[0035] Exemplary embodiments of the disclosed technology may make a
comparison of the entity-supplied information with the plurality of
independent information to determine zero or more indicators of
fraud. For example, embodiments of the disclosed technology may
compare the entity-supplied information with the plurality of
independent information to determine if the entity associated with
the request for payment or benefit died within a timeframe that
would indicate a possible non-fraud request, but with no record of
association between the entity-supplied mailing address and the
address information obtained via the independent information. Such
a scenario may represent a situation where a fraudster 124 has
obtained a name and social security information 120 from a deceased
person 118, but where the address provided does not correspond with
the known residence address 122 of the deceased person 118, or with
any known relatives or associates of the deceased person 118. This
scenario may be an indicator of a attempt by a fraudster 124 to
have a deceased person's 118 payment or benefit 112 sent to a post
office box or other address that can be monitored by the fraudster
124 without any direct tie to the fraudster 124. Exemplary
embodiments of the disclosed technology may include a length of
time entity has been deceased (if the entity is deceased) in the
determination of fraud indicators. For example, a request for
payment or benefit listing a person known to be dead for 10 years
is very likely a fraudulent refund request.
[0036] According to another exemplary embodiment of the disclosed
technology, a comparison may be made with the entity-supplied
mailing address and the independent information to determine if the
entity-supplied mailing address is invalid with no record of
association between a zip code of the entity-supplied mailing
address and one or more zip codes associated with the independent
address information. For example, situations exist where a
legitimate taxpayer 102 may abbreviate or include a typographical
error their return mailing address, but they may provide a correct
zip code that could be verified with the independent information.
However, a fraudster 124 may be likely to use a completely
different zip code, and in such situations, embodiments of the
disclosed technology may utilize the inconsistent zip code
information to flag a possible fraudulent tax return request.
[0037] According to another exemplary embodiment of the disclosed
technology, a comparison may be made with the entity-supplied
mailing address and the independent information to determine
whether or not there is any record of association between the
entity-supplied mailing address and any independent address
information, such as the address of a relative, or associate.
According to an exemplary embodiment, if there is no association
between the entity-supplied mailing address and any independent
address information, then there is a high likelihood that the
payment or benefit request is fraudulent.
[0038] In accordance with certain exemplary embodiments of the
disclosed technology, fraud false positive indicators may
determined, based at least in part on a comparison of the
entity-supplied information with the plurality of independent
information. Absent of exemplary embodiments of the disclosed
technology, certain situations may be incorrectly flagged as
fraudulent, and may create costly and unnecessary delays related to
the disbursement of the payment or benefit. In one exemplary
embodiment, a fraud false positive indicator may be based on an
analysis to detect if the entity-supplied mailing address is
invalid, but with a record of association between a zip code of the
entity-supplied mailing address and one or more zip codes
associated with the independent address information. This
represents a situation where a legitimate requester 102 has
abbreviated their address or included a typographical error in the
address, but the zip code corresponds with one known to be
associated with the legitimate requester 102.
[0039] According to another exemplary embodiment, a fraud false
positive indicator may be based on the entity-supplied social
security number when there is no independent information available.
For example, in one exemplary embodiment, the entity-supplied
social security number may be checked to determine if it is valid
and issued within 3 to 15 years, and the independent information
can be checked to see if it includes information. If no independent
information is available and if the entity-supplied social security
number is valid and issued within 3 to 15 years, then this
information may provide an indication that the requesting entity is
a minor. In another exemplary embodiment, the social security
number may be checked to determine if the entity is at least 24
years old with a valid social security number issued within 3 to 15
years, and the obtained independent information includes no
information. In this scenario, exemplary embodiments of the
disclosed technology may provide an indication that the requesting
entity is an immigrant.
[0040] According to exemplary embodiments of the disclosed
technology, one or more public or private databases 138 may be
accessed to receive independent information. For example, one or
more public records may be provide housing records, vehicular
records, marriage records, divorce records, hospital records, death
records, court records, property records, incarceration records, or
utility records. In exemplary embodiments, the utility records may
include one or more of utility hookups, disconnects, and associated
service addresses. According to exemplary embodiments of the
disclosed technology, such public records may be searched by social
security number and/or name to provide independent information that
can be utilized to verify entity-supplied information. For example,
entity-supplied address information can be checked to determine if
it corresponds to any addresses of relatives or associates of the
entity.
[0041] According to certain exemplary embodiments of the disclosed
technology, fraud associated with a request for payment or benefit
may be detected by querying a Do Not Pay list with a combination of
entity-supplied information and independent information obtained
from one or more public records. For example, a person may be
listed on a Do Not Pay list for a number of reasons, including
being incarcerated, not paying child support, having liens, etc.
Persons on the Do Not Pay list may supply an incorrect social
security number or a slight misspelling of a name to avoid being
matched with the information on the Do Not Pay list.
[0042] An example implementation of the disclosed technology may
include receiving entity-supplied information that includes at
least a name and a social security number and querying one or more
public records with the entity-supplied information. Certain
exemplary embodiments of the disclosed technology may receive,
based at least on the querying, public data that includes one or
more of a second social security number or variant of a social
security number associated with entity-supplied name, a second name
associated with the entity-supplied social security number, or a
name variant associated with the entity-supplied social security
number. For example, a variant may include information such as a
name, a number, or an address, etc. that approximately matches real
or legitimate information. A social security number variant, for
example, may be nearly identical to a legitimate social security
number, but with one or more numbers changed, transposed, etc.
[0043] According to exemplary embodiments of the disclosed
technology, a Do Not Pay list may be queried with one or more
combinations and/or variants of the entity-supplied information and
the received public data, and a fraud alert may be output if the
one or more combinations and/or variants result in a match with at
least one record in the Do Not Pay list. Thus, in certain example
implementations, the entity-supplied information may be compared
with variations of information on the Do Not Pay list (and/or other
public or private information) to determine a possible match.
Conversely, in other example implementations, information obtained
from the Do Not Pay list (and/or other public or private sources)
may be compared with variations of the entity-supplied information
to determine possible matches.
[0044] According to certain exemplary embodiments, the Do Not Pay
list may be queried with one or more combinations of the
entity-supplied name and entity-supplied social security number,
the entity-supplied name and a second social security number or a
variant of the social security number, the second name or name
variant and the entity supplied social security number, or the
second name or name variant and the second social security number
or variant of the social security number. According to exemplary
embodiments, if one of the combinations or variants matches the
information on the Do Not Pay list, then a fraud alert may be
output.
[0045] FIG. 2 depicts a block diagram of an illustrative fraud
detection system 200 according to an exemplary embodiment of the
disclosed technology. The system 200 includes a controller 202 that
includes a memory 204, one or more processors 206, an input/out
interface 208 for communicating with a local monitor 218 and input
devices, and one or more network interfaces 210 for communicating
with local or remote servers or databases 222, which may be
accessed through a local area network or the internet 220.
According to exemplary embodiments, the memory may included an
operating system 212, data 214, and one or more fraud analysis
modules 216.
[0046] Various embodiments of the communication systems and methods
herein may be embodied in non-transitory computer readable media
for execution by a processor. An exemplary embodiment may be used
in an application of a mobile computing device, such as a
smartphone or tablet, but other computing devices may also be used.
FIG. 3 illustrates schematic diagram of internal architecture of an
exemplary mobile computing device 300. It will be understood that
the architecture illustrated in FIG. 3 is provided for exemplary
purposes only and does not limit the scope of the various
embodiments of the communication systems and methods.
[0047] FIG. 3 depicts a block diagram of an illustrative computer
system architecture 300 according to an exemplary embodiment of the
disclosed technology. Certain aspects of FIG. 3 may also be
embodied in the controller 202, as shown in FIG. 2. Various
embodiments of the communication systems and methods herein may be
embodied in non-transitory computer readable media for execution by
a processor. It will be understood that the architecture
illustrated in FIG. 3 is provided for exemplary purposes only and
does not limit the scope of the various embodiments of the
communication systems and methods.
[0048] The architecture 300 of FIG. 3 includes a central processing
unit (CPU) 302, where computer instructions are processed; a
display interface 304 that acts as a communication interface and
provides functions for rendering video, graphics, images, and texts
on the display; a keyboard interface 306 that provides a
communication interface to a keyboard; and a pointing device
interface 308 that provides a communication interface to a pointing
device or touch screen. Exemplary embodiments of the architecture
300 may include an antenna interface 310 that provides a
communication interface to an antenna; a network connection
interface 312 that provides a communication interface to a network.
In certain embodiments, a camera interface 314 is provided that
acts as a communication interface and provides functions for
capturing digital images from a camera. In certain embodiments, a
sound interface 316 is provided as a communication interface for
converting sound into electrical signals using a microphone and for
converting electrical signals into sound using a speaker. According
to exemplary embodiments, a random access memory (RAM) 318 is
provided, where computer instructions and data are stored in a
volatile memory device for processing by the CPU 302.
[0049] According to an exemplary embodiment, the architecture 300
includes a read-only memory (ROM) 320 where invariant low-level
systems code or data for basic system functions such as basic input
and output (I/O), startup, or reception of keystrokes from a
keyboard are stored in a non-volatile memory device. According to
an exemplary embodiment, the architecture 300 includes a storage
medium 322 or other suitable type of memory (e.g. such as RAM, ROM,
programmable read-only memory (PROM), erasable programmable
read-only memory (EPROM), electrically erasable programmable
read-only memory (EEPROM), magnetic disks, optical disks, floppy
disks, hard disks, removable cartridges, flash drives), where the
files include an operating system 324, application programs 326
(including, for example, a web browser application, a widget or
gadget engine, and or other applications, as necessary) and data
files 328 are stored. According to an exemplary embodiment, the
architecture 300 includes a power source 330 that provides an
appropriate alternating current (AC) or direct current (DC) to
power components. According to an exemplary embodiment, the
architecture 300 includes and a telephony subsystem 332 that allows
the device 300 to transmit and receive sound over a telephone
network. The constituent devices and the CPU 302 communicate with
each other over a bus 334.
[0050] In accordance with exemplary embodiments, the CPU 302 has
appropriate structure to be a computer processor. In one
arrangement, the computer CPU 302 is more than one processing unit.
The RAM 318 interfaces with the computer bus 334 to provide quick
RAM storage to the CPU 302 during the execution of software
programs such as the operating system application programs, and
device drivers. More specifically, the CPU 302 loads
computer-executable process steps from the storage medium 322 or
other media into a field of the RAM 318 in order to execute
software programs. Data is stored in the RAM 318, where the data is
accessed by the computer CPU 302 during execution. In one exemplary
configuration, the device 300 includes at least 128 MB of RAM, and
256 MB of flash memory.
[0051] The storage medium 322 itself may include a number of
physical drive units, such as a redundant array of independent
disks (RAID), a floppy disk drive, a flash memory, a USB flash
drive, an external hard disk drive, thumb drive, pen drive, key
drive, a High-Density Digital Versatile Disc (HD-DVD) optical disc
drive, an internal hard disk drive, a Blu-Ray optical disc drive,
or a Holographic Digital Data Storage (HDDS) optical disc drive, an
external mini-dual in-line memory module (DIMM) synchronous dynamic
random access memory (SDRAM), or an external micro-DIMM SDRAM. Such
computer readable storage media allow the device 300 to access
computer-executable process steps, application programs and the
like, stored on removable and non-removable memory media, to
off-load data from the device 300 or to upload data onto the device
300. A computer program product, such as one utilizing a
communication system may be tangibly embodied in storage medium
322, which may comprise a machine-readable storage medium.
[0052] An exemplary method 400 will now be described with reference
to the flowchart of FIG. 4 The method may be utilized for detecting
fraud related to an identity misrepresentation, identity creation
or identity usurpation. The method 400 starts in block 402, and
according to an exemplary embodiment of the disclosed technology
includes receiving entity-supplied information comprising at least
a name, a social security number, and a mailing address associated
with a request for a payment or a benefit from a government agency.
In block 404, the method 400 querying one or more public or private
databases with the entity-supplied information. In block 406, the
method 400 includes receiving a plurality of independent
information in response to the querying.
[0053] According to certain example embodiments, the plurality of
independent information can include one or more of (1) an
indication of whether or not the entity is deceased, and a date of
death when the entity is indicated as deceased; (2) independent
address information associated with the entity; (3) address
validity information associated with the entity-supplied
information; (4) one or more records associated with the
entity-supplied information; or (5) no information.
[0054] In block 408, the method 400 includes determining, with one
or more computer processors in communication with a memory, based
at least in part on a comparison of the entity-supplied information
with at least a portion of the plurality of independent
information, one or more indicators of fraud. For example, the
indicators of fraud may include one or more of (1) the entity is
indicated as deceased within a year of the request or died within a
timeframe of the year that would indicate a possible non-fraud
request for the payment or the benefit; (2) the entity-supplied
mailing address does not match with any of the independent address
information; (3) the entity-supplied mailing address having no
record of association with any independent address information,
including addresses of relatives or addresses of associates; and
(4) the entity-supplied mailing address includes an entity-supplied
zip code having no record of association with one or more zip codes
associated with the independent address information.
[0055] In block 410, the method 400 includes outputting, for
display, zero or more indicators of fraud, wherein zero indicators
of fraud correspond to no fraud determined.
[0056] Another exemplary method 500 for detecting fraud related to
an identity misrepresentation, identity creation or identity
usurpation will now be described with reference to the flowchart of
FIG. 5. The method 500 starts in block 502, and according to an
exemplary embodiment of the disclosed technology includes receiving
entity-supplied information comprising at least a name and a social
security number associated with a request for a payment or a
benefit from a government agency. In block 504, the method 500
includes querying one or more public or private databases with the
entity-supplied information. In block 506, the method 500 includes
receiving, based at least on the querying of the one or more public
or private databases, data comprising one or more of a second
social security number or a social security number variant
associated with the entity-supplied name, a second name associated
with the entity-supplied social security number, and a name variant
associated with the entity-supplied social security number. In
block 508, the method 500 includes querying an accessible Do Not
Pay list with one or more combinations or variants of the
entity-supplied information and the received public or private
data. In block 510, the method 500 includes outputting a fraud
alert when the one or more combinations or variants result in a
match with at least one record in the Do Not Pay list
[0057] According to exemplary embodiments, certain technical
effects can be provided, such as creating certain systems and
methods that detect fraud related to a request for payment or
benefit. Exemplary embodiments of the disclosed technology can
provide the further technical effects of providing systems and
methods for determining and eliminating false positives with
respect to fraud.
[0058] Example implementations of the disclosed technology may
utilize an authentication quiz process in response to the detection
of a possible fraudulent request. For example, in response to the
detection of one or more indicators of a fraudulent request for
payment or benefit, the requester may be required to provide
correct answers to a custom quiz before receiving the payment or
benefit.
[0059] According to an example implementation, information
associated with the request may be analyzed by the system (for
example, the computer system architecture or device 300 as shown in
FIG. 3), and if it is found to have questionable validity (such as
a low score, for example) a customized quiz may be generated for
the requester to complete correctly before proceeding with any
release of payment or benefit. Certain embodiments may utilize such
quiz to reduce or eliminate requests that are flagged as fraudulent
but actually legitimate.
[0060] According to an example implementation, the quiz may include
one or more questions that are generated from information derived
from the one or more databases. In one example implementation, the
generated quiz may be multiple choice. In another example
implementation, one or more of the questions associated with the
quiz may require specific input. In an example implementation, if
the requester passes the quiz, then the requested payment or
benefit may be processed so that the requester may receive the
payment or benefit. Conversely, if the requester fails the quiz,
then the requested payment or benefit may not be processed and the
requester may not receive the funds without further authentication.
Embodiments utilizing the quiz may help reduce the number requests
that have been incorrectly flagged as fraudulent
[0061] In exemplary embodiments of the disclosed technology, the
fraud detection system 200 and/or the fraud detection system
architecture 300 may include any number of hardware and/or software
applications that are executed to facilitate any of the operations.
In exemplary embodiments, one or more I/O interfaces may facilitate
communication between the fraud detection system 200 and/or the
fraud detection system architecture 300 and one or more
input/output devices. For example, a universal serial bus port, a
serial port, a disk drive, a CD-ROM drive, and/or one or more user
interface devices, such as a display, keyboard, keypad, mouse,
control panel, touch screen display, microphone, etc., may
facilitate user interaction with the fraud detection system 200
and/or the fraud detection system architecture 300. The one or more
I/O interfaces may be utilized to receive or collect data and/or
user instructions from a wide variety of input devices. Received
data may be processed by one or more computer processors as desired
in various embodiments of the disclosed technology and/or stored in
one or more memory devices.
[0062] One or more network interfaces may facilitate connection of
the fraud detection system 200 and/or the fraud detection system
architecture 300 inputs and outputs to one or more suitable
networks and/or connections; for example, the connections that
facilitate communication with any number of sensors associated with
the system. The one or more network interfaces may further
facilitate connection to one or more suitable networks; for
example, a local area network, a wide area network, the Internet, a
cellular network, a radio frequency network, a Bluetooth.TM.
enabled network, a Wi-Fi.TM. enabled network, a satellite-based
network any wired network, any wireless network, etc., for
communication with external devices and/or systems.
[0063] As desired, embodiments of the disclosed technology may
include the fraud detection system 200 and/or the fraud detection
system architecture 300 with more or less of the components
illustrated in FIG. 2 and FIG. 3.
[0064] Certain embodiments of the disclosed technology are
described above with reference to block and flow diagrams of
systems and methods and/or computer program products according to
exemplary embodiments of the disclosed technology. It will be
understood that one or more blocks of the block diagrams and flow
diagrams, and combinations of blocks in the block diagrams and flow
diagrams, respectively, can be implemented by computer-executable
program instructions. Likewise, some blocks of the block diagrams
and flow diagrams may not necessarily need to be performed in the
order presented, or may not necessarily need to be performed at
all, according to some embodiments of the disclosed technology.
[0065] These computer-executable program instructions may be loaded
onto a general-purpose computer, a special-purpose computer, a
processor, or other programmable data processing apparatus to
produce a particular machine, such that the instructions that
execute on the computer, processor, or other programmable data
processing apparatus create means for implementing one or more
functions specified in the flow diagram block or blocks. These
computer program instructions may also be stored in a
computer-readable memory that can direct a computer or other
programmable data processing apparatus to function in a particular
manner, such that the instructions stored in the computer-readable
memory produce an article of manufacture including instruction
means that implement one or more functions specified in the flow
diagram block or blocks. As an example, embodiments of the
disclosed technology may provide for a computer program product,
comprising a computer-usable medium having a computer-readable
program code or program instructions embodied therein, said
computer-readable program code adapted to be executed to implement
one or more functions specified in the flow diagram block or
blocks. The computer program instructions may also be loaded onto a
computer or other programmable data processing apparatus to cause a
series of operational elements or steps to be performed on the
computer or other programmable apparatus to produce a
computer-implemented process such that the instructions that
execute on the computer or other programmable apparatus provide
elements or steps for implementing the functions specified in the
flow diagram block or blocks.
[0066] Accordingly, blocks of the block diagrams and flow diagrams
support combinations of means for performing the specified
functions, combinations of elements or steps for performing the
specified functions and program instruction means for performing
the specified functions. It will also be understood that each block
of the block diagrams and flow diagrams, and combinations of blocks
in the block diagrams and flow diagrams, can be implemented by
special-purpose, hardware-based computer systems that perform the
specified functions, elements or steps, or combinations of
special-purpose hardware and computer instructions.
[0067] While certain embodiments of the disclosed technology have
been described in connection with what is presently considered to
be the most practical and various embodiments, it is to be
understood that the disclosed technology is not to be limited to
the disclosed embodiments, but on the contrary, is intended to
cover various modifications and equivalent arrangements included
within the scope of the appended claims. Although specific terms
are employed herein, they are used in a generic and descriptive
sense only and not for purposes of limitation.
[0068] This written description uses examples to disclose certain
embodiments of the disclosed technology, including the best mode,
and also to enable any person skilled in the art to practice
certain embodiments of the disclosed technology, including making
and using any devices or systems and performing any incorporated
methods. The patentable scope of certain embodiments of the
disclosed technology is defined in the claims, and may include
other examples that occur to those skilled in the art. Such other
examples are intended to be within the scope of the claims if they
have structural elements that do not differ from the literal
language of the claims, or if they include equivalent structural
elements with insubstantial differences from the literal language
of the claims.
* * * * *