Note: Descriptions are shown in the official language in which they were submitted.
METHODS AND DEVICES FOR IDENTIFYING RELEVANT INFORMATION FOR A
FIRST ENTITY
TECHNICAL FIELD
[0001] The following relates generally to methods and devices for
identifying information
for entities based on information in data exchange records. More specifically,
the following
relates to methods and devices for identifying relevant information for
entities, and methods and
devices for determining, and identifying information to manage, levels of risk
for entities, based
on information in data exchange records.
BACKGROUND
[0002] Existing databases of various institutions contain data exchange
records for various
entities. For example, records of blood donations to a blood bank by various
entities or
individuals are tracked and maintained in digital format. Social media
networks and financial
institutions also retain large databases of data exchange records for various
entities. There
remains a need to effectively leverage the existing big data of institutions
to cultivate
relationships with entities (such as by identifying information of relevance
for the entities) and/or
to make informed decisions about possible interactions with entities based on
levels of risk for
the entities determined from the data.
SUMMARY
[0003] In an aspect of the present application there is provided a
computing device for
identifying relevant information for a first entity. The computing device
comprises: a memory
storing computer-executable instructions; a communication module for
communication with an
electronic device associated with the first entity over a network; and a
processor coupled to the
memory and the communication module. The instructions when executed by the
processor cause
the processor to: analyze records of data exchanges of the first entity stored
in a database
accessible to the processor; determine a sector with which the first entity is
associated by at least
one of: (i) analyzing the stored records of first entity data exchanges; and
(ii) analyzing input
received from the first entity, the input identifying the sector; analyze
records of data exchanges
of one or more second entities different from the first entity stored in the
database, to determine
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which of the one or more second entities data exchange records involve other
entities associated
with the sector, to determine sector associated one or more second entities
data exchanges;
analyze the stored records of the sector associated one or more second
entities data exchanges to
determine one or more data baselines; analyze the stored records of the first
entity data
exchanges to determine one or more first entity data baselines, at least one
of the one or more
first entity data baselines corresponding in type to a respective one of the
one or more data
baselines; compare one of the one or more data baseline(s) to a corresponding
one of the first
entity one or more data baseline(s); identify the relevant information based
on the comparison;
and notify, via the communication module, the electronic device associated
with the first entity
of the relevant information.
[0004] In another aspect of the present application there is provided a
computer-
implemented method for identifying relevant information for a first entity.
The method
comprises: analyzing records of data exchanges of the first entity stored in a
database accessible
to a processor of a computing device; determining a sector with which the
first entity is
associated by at least one of: (i) analyzing the stored records of first
entity data exchanges; and
(ii) analyzing input received from the first entity, the input identifying the
sector; analyzing
records of data exchanges of one or more second entities different from the
first entity stored in
the database, to determine which of the one or more second entities data
exchange records
involve other entities associated with the sector, to determine sector
associated one or more
second entities data exchanges; analyzing the stored records of the sector
associated one or more
second entities data exchanges to determine one or more data baselines;
analyzing the stored
records of the first entity data exchanges to determine one or more first
entity data baselines, at
least one of the one or more first entity data baselines corresponding in type
to a respective one
of the one or more data baselines; comparing one of the one or more data
baseline(s) to a
corresponding one of the first entity one or more data baseline(s);
identifying the relevant
information based on the comparing; and notifying, via a communication module
of the
computing device, over a network, an electronic device associated with the
first entity of the
relevant information.
[0005] In yet another aspect of the present application there is
provided a non-transitory
computer-readable medium comprising computer-executable instructions for
identifying relevant
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information for a first entity. The instructions when executed by a processor
of a computing
device cause the processor to: analyze records of data exchanges of the first
entity stored in a
database accessible to the processor; determine a sector with which the first
entity is associated
by at least one of: (i) analyzing the stored records of first entity data
exchanges; and (ii)
analyzing input received from the first entity, the input identifying the
sector; analyze records of
data exchanges of one or more second entities different from the first entity
stored in the
database, to determine which of the one or more second entities data exchange
records involve
other entities associated with the sector, to determine sector associated one
or more second
entities data exchanges; analyze the stored records of the sector associated
one or more second
entities data exchanges to determine one or more data baselines; analyze the
stored records of the
first entity data exchanges to determine one or more first entity data
baselines, at least one of the
one or more first entity data baselines corresponding in type to a respective
one of the one or
more data baselines; compare one of the one or more data baseline(s) to a
corresponding one of
the first entity one or more data baseline(s); identify the relevant
information based on the
.. comparison; and notify, via a communication module of the computing device,
over a network,
an electronic device associated with the first entity of the relevant
information.
BRIEF DESCRIPTION OF THE DRAWINGS
[0006] Aspects of the application will now be described by way of
example only with
reference to the appended drawings in which:
[0007] FIG. 1 depicts a schematic diagram of an exemplary aspect of a
system described
herein;
[0008] FIG. 2 depicts a schematic diagram of an exemplary aspect of a
computing device
described herein;
[0009] FIG. 3 depicts a flow diagram of an exemplary aspect of computer-
executable
instructions described herein; and
[0010] FIG. 4 depicts a flow diagram of another exemplary aspect of
computer-executable
instructions described herein.
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DETAILED DESCRIPTION
[0011] It will be appreciated that for simplicity and clarity of
illustration, where considered
appropriate, reference numerals may be repeated among the figures to indicate
corresponding or
analogous elements. In addition, numerous specific details are set forth in
order to provide a
thorough understanding of the exemplary aspects of the present application
described herein.
However, it will be understood by those of ordinary skill in the art that the
exemplary aspects
described herein may be practised without these specific details. In other
instances, well-known
methods, procedures and components have not been described in detail so as not
to obscure the
exemplary aspects described herein. Also, the description is not to be
considered as limiting the
.. scope of the exemplary aspects described herein. Any systems, method steps,
components, parts
of components, and the like described herein in the singular are to be
interpreted as also
including a description of such systems, method steps, components, parts of
components, and the
like in the plural, and vice versa.
[0012] The person of skill in the art will appreciate that there are
delays inherent to any
form of communication, including wired or wireless digital communication,
including over a
digital network, and as such, as used herein, the term "real-time" includes
real-time and
substantially real-time communication.
[0013] Institutions, such as blood banks, gather vast amounts of data
from various entities
(such as patrons, donators, volunteers, and any other personal or business
entity that may provide
.. information or data pertaining to the entity to an institution with which
it interacts). For
example, financial institutions, such as retail banks, gather vast amounts of
data on the data
exchanges, or financial transactions, of its various personal and business
entity customers.
Discussed below are methods and computing devices for identifying relevant
information for
entities, and methods and devices for determining, and identifying information
to manage, levels
of risk for entities, based on information in data exchange records.
[0014] With reference to FIG. 1 and FIG. 2, system 100 includes a
computing device 110
in digital communication with one or more entities 130 over a network 120.
Database 140 may
be co-located or form a part of the computing device 110, or otherwise be
accessible to a
processor of the computing device 110, such as over network 120.
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[0015] Computing device 110 may comprise memory 200, communication
module 210, a
display 220, one or more input devices 230, and at least one processor 240
coupled to the
memory 200, communication module 210, display 220, and input device(s) 230.
Communication module 210 enables computing device 110 to communicate with one
or more
.. other components of system 100, such as one or more entities 130 (such as
the first entity 130,
one or more second entities 130, or other entities 130 described below),
and/or an electronic
device 132 associated with any such entities 130, via a wired or wireless
communication
network, such as network 120. Network 120 may comprise a direct link between
communicating
components of system 100, or an indirect one, including but not limited to
communication by
Ethernet TM, BluetoothTM, WiFiTM, ZigBeeTM, ZWaveTM, 6LowPANTM, ThreadTm, NFC
(near-
field communication), SigFoxTM, infrared, WiMAXTm (fixed or mobile), RFID
(radio-frequency
identification), Neu1TM, L0RaWANTM, CoAP (Constrained Application Protocol),
MQTT
(Message Queue Telemetry Transport), and any suitable cellular communications
protocols
including, but not limited to, up to 5G protocols, such as GSM, GPRS, EDGE,
CDMA, UMTS,
LTE, LTE-A, IMS, for example, and any other communications protocols suitable
for the
method(s), system(s) and device(s) described herein, including any proprietary
protocols.
Network 120 may comprise a single network or more than one interconnected
network, of any
type suitable for the method(s), system(s) and device(s) described herein,
including but not
limited to wired or wireless PANs (personal area networks), LANs (local area
networks), WANs
(wide area networks), MANs (metropolitan area networks), mesh or ad hoc
networks, VPNs
(virtual private networks), the Internet, and any other suitable network type,
in any suitable
network configuration or topology (e.g., mesh, token ring, tree, star, etc.),
and any interconnected
combination of the foregoing. Although not shown in FIG. 1, system 100 may
further include
any components necessary to effect the communication and/or network type(s)
used, and may
also include components for increased network security, for example, access
points, routers, and
firewalls.
[0016] As used herein, the term "memory" (such as memory 200), or any
variation thereof,
may comprise a tangible and non-transitory computer-readable medium (i.e., a
medium which
does not comprise only a transitory propagating signal per se) comprising or
storing computer-
executable instructions, such as computer programs, sets of instructions,
code, software, and/or
data for execution of any method(s), step(s) or process(es) described herein
by any processor(s)
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described herein, including processor(s) 240. Memory may comprise one or more
of a local
and/or remote hard disk or hard drive, of any type, ROM (read-only memory)
and/or RAM
(random-access memory), buffer(s), cache(s), flash memory, optical memory
(e.g., CD(s) and
DVD(s)), and any other form of volatile or non-volatile storage medium in or
on which
information may be stored for any duration. Such computer-executable
instructions, when
executed by processor 240 of computing device 110, cause the processor to
perform any of the
methods described herein, such as methods for identifying relevant information
for a first entity,
and methods for determining, and identifying information to manage, a level of
risk of a first
entity (as further described below). It will be appreciated that the method
steps described herein
may be implemented in a variety of programming languages.
[0017] Input device(s) 230 provides a mechanism for a user of computing
device 110 to
provide input(s) to computing device 110, such as during the execution of
computer programs
stored in memory 200, for processing by processor 240. Input device(s) 230 may
include a
touch-sensitive display, physical or virtual keyboard, keypad, mouse,
microphone, trackpad,
.. scroll wheel or ball, or other suitable device capable of receiving or
detecting an input. Display
220 may comprise any screen suitable for displaying visual information,
including any suitable
touch-sensitive display (in which cases display 220 may also serve as an input
device 230 of
computing device 110), such as a touch-sensitive display based on capacitive,
resistive, infrared,
surface acoustic wave (SAW), strain gauge, optical imaging, acoustic pulse
recognition,
dispersive signal technology, or any other suitable technology known in the
art.
[0018] Computing device 110 may comprise a personal computer and/or one
or more
servers (such as for redundancy). Method steps described herein requiring user
input may be
carried out through a client interface of a software application executed by
processor 240 of
computing device 110, such as a web portal on computing device 110 or on any
networked
.. device, such as a tablet or desktop computer. Computing device 110 may
represent a system of
known components, including one or more servers, databases, I/O devices,
access terminals,
communications pathways, and any other components necessary in order for
computing
device(s) 110 to effect method step(s) described herein, as would be known to
the person of skill
in the art. As a non-limiting example, a computing device 110 may comprise a
financial server
hosting a financial software application of a financial institution, such as a
bank, and a user of
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computing device 110 (such as a bank employee) may have access to the
financial application
hosted by computing device 110, such as through an interface (e.g., web
portal, or a GUI of the
financial software application) on computing device 110 or via an "app" or web
browser on
another device communicatively coupled to computing device 110, such as a
smart phone, tablet,
or computer accessing the financial software over network 120, such as via a
secure connection
(e.g., VPN connection).
[0019] With reference to FIG. 3, in accordance with an exemplary aspect
of the present
application, instructions, when executed by processor 240, cause the processor
to carry out steps
of method 300 for identifying relevant information for a first entity. Method
300 may comprise
analyzing 302 records of data exchanges of first entity 130 stored in database
140 accessible to
processor 240; determining 304 a sector with which the first entity is
associated by at least one
of: (i) analyzing the stored records of first entity data exchanges; and (ii)
analyzing input
received from the first entity that identifies the sector; analyzing 306
records of data exchanges
of one or more second entities 130 different from the first entity stored in
database 140, to
determine which of the one or more second entities data exchange records
involve other entities
associated with the sector, to determine sector associated one or more second
entities data
exchanges; analyzing 308 the stored records of the sector associated one or
more second entities
data exchanges to determine one or more data baselines; analyzing 310 the
stored records of the
first entity data exchanges to determine one or more first entity data
baselines, at least one of
which corresponds in type to a respective one of the data baseline(s);
comparing 312 one of the
one or more data baseline(s) to a corresponding one of the first entity one or
more data
baseline(s); identifying 314 the relevant information based on the comparison;
and notifying 316
(e.g., via communication module 210) the first entity 130 of the relevant
information.
[0020] In accordance with some aspects, notifying 316 the first entity
of the relevant
information may be done in real-time, by push notification, upon identifying
the relevant
information. Alternatively, first entity 130 may request (such as by a
financial or banking app
configured to communicate with computing device 110, or which may comprise a
client instance
of computing device 110 having only informational or reporting features for
the user), over
network 120, the relevant information from computing device 110 and pull the
relevant
information. The notification may comprise, for example, an audible and/or
visual alert
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displayed on a display of another device (e.g., a mobile device, computer,
tablet, etc.) by which a
graphical user interface of an application hosted by the institution (such as
a financial or banking
app for a financial institution) is accessed by the first entity or a
representative of the first entity,
or a message sent via communication module to a digital address of such first
entity or first
entity representative (e.g., SMS, MMS, instant message, email, a proprietary
message type, etc.).
It will be appreciated by the person of ordinary skill in the art that any
suitable type of
notification message may be used.
[0021] In an exemplary aspect, computing device 110 comprises a
computing device of a
financial institution, and first entity 130 and the one or more second
entities 130 comprise
customers of the financial institution. In such aspects, the data exchanges
comprise financial
transactions of the financial institution's customers 130, which are received
over time by the
computing device 110 of the financial institution over network 120, and stored
in database 140.
In these aspects, the steps of analyzing 302 and 306 records of data exchanges
comprise analyses
of historical transaction or data exchange records of the customers of the
financial institution that
have been stored in the financial institution's database(s) 140. Further, in
such aspects, the first
entity comprises a customer of the financial institution for which the
computing device
determines the relevant information (or, with reference to method 400
described below, for
which the computing device determines, and identifies information to manage, a
level of risk),
and the one or more second entities that are different from the first entity
comprise all other
customers of the financial institution. In such aspects, at step 306, the
other entities associated
with the sector comprise other business customers of the financial institution
that are, e.g.,
identified by processor 240 as transacting parties in the analyzed data
exchange records that are
associated with the same sector as the first entity. Further, in such aspects,
the sector may
comprise a business sector with which the first entity is associated. For
example, the first entity
may be a retail coffee shop business customer, in which case the sector with
which the first entity
is associated may comprise "retail", "food and drink", and/or "retail coffee",
for example.
Further, in such aspects, the "sector associated one or more second entities
data exchanges"
comprise data exchange or transaction records stored in the financial
institution's database 140
that involve personal or business customers other than the first entity (i.e.,
which do not include
the first entity as any of the transacting parties of the data exchange) and
which involve as a
transacting party a business customer other than the first entity associated
with the sector. For
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example, the sector associated one or more second entities data exchanges may
include a
transaction record between a patron and Retail Coffee Shop ABC in which the
patron purchased
a small coffee via a debit transaction (such as an Interac debit
transaction), and a transaction
record involving Retail Coffee Shop XYZ's purchase of chairs from a furniture
manufacturer;
both data exchange or transaction records involve other entities (Retail
Coffee Shop ABC and
Retail Coffee Shop XYZ) that are not the first entity (e.g., Retail Coffee
Shop 123) and belong to
the same sector as the first entity (e.g., "retail coffee").
[0022] Methods 300 and 400 may determine more than one relevant
information or level of
risk, by basing the respective analysis on more than one sector (i.e., sectors
of varying breadth,
as discussed above). The instructions executed by processor 240 may comprise
instructions
allowing for sectors to be pre-configured, such as in database 140, and/or
allowing for
configuration of sector breadth (e.g., a user of computing device 110, such as
a bank employee,
may configure the financial software comprising the instructions that cause
processor 240 to
execute methods 300 and 400 to set the sector breadth somewhere between a
broad (e.g.,
.. "retail") and narrow (e.g., "retail coffee") sector.
[0023] At step 304, the instructions when executed by processor 240
cause the processor to
determine 304 the sector with which the first entity is associated. Sector
determination may be
done by analyzing the stored records of first entity data exchanges. For
example, analysis of the
first entity data exchange records may show that the first entity regularly
buys coffee beans from
a supplier and sells coffee to customers, and processor 240 may then
accordingly determine the
first entity data exchange records to be associated with the "coffee retail"
sector. Sector
determination may also, or alternatively, be determined by reference to
sources of public
information. For example, the instructions when executed by processor 240 may
cause the
processor to look up, e.g., Starbuckse (where Starbuck is the first entity)
on the Internet to
determine that an appropriate sector is "coffee retail". Additionally, or
alternatively, sector
determination may be achieved via input from the first entity that identifies
the sector. This may
be done, e.g., when the first entity establishes a customer relationship with
the financial
institution (e.g., by opening one or more financial accounts) and identifies
itself as a company
operating in the "coffee", "food and drink" and/or "retail coffee" sector(s),
for example. The
instructions described herein may use artificial intelligence (AI) and/or
machine learning (ML) to
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carry out any suitable method steps described herein, including step 304
discussed above (e.g., to
appropriately analyze public information and/or the information contained in
data exchange
records). In accordance with an aspect, the instructions when executed by
processor 240 may
cause the processor to assign a unique code to the determined sector for
storage in database 140
as an attribute of, or related to, the data exchange records. The unique code
may be generated by
the processor, or may be based on a known standard for business sector
classification, such as a
Standard Industrial Classification (SIC) code.
[0024] At step 308, one or more data baselines are determined for the
sector associated one
or more second entities data exchange records. Such baselines (including the
first entity data
baselines, described below) may comprise or relate to, e.g., the transacting
merchant, data
exchange location, payment amount, and/or payment type (the payment type may
comprise, e.g.,
credit card, gift card, debit card, mobile payment, cash, and any other
suitable or known payment
types). Still with reference to FIG. 3., in accordance with a further aspect
of the present
application, method 300 may further comprise determining 318 which of the
sector associated
one or more second entities data exchanges comprises data exchanges of
personal (i.e., non-
business) entities, in which case the one or more data baselines determined at
step 308 (such as
the example baselines discussed above) may comprise one or more baselines for
the personal
entities. For example, one baseline related to the transacting merchants
identified in each of the
sector associated one or more second entities data exchange records may
comprise the
.. percentage of customers in the sector that transact with each merchant.
Another baseline may
comprise the percentage of customers that buy their coffee in region A (e.g.,
downtown
Toronto), region B (e.g., a suburb West of Toronto), and so on (more broad or
narrow
geographic regions could be used). Further baselines or values attributed
thereto, not described
herein, may be covered by the present application, and the types of baselines
and baseline values
are not intended to restrict the presently described aspects. For example, the
payment types
described above are not limiting on the presently described aspects, and yet
further payment
types, not presently in widespread use, known or contemplated, may be covered
by the presently
described aspects (such as blockchain-based payment systems, biometric based
payment
systems, and so on). At least one of the first entity data baselines
determined at step 310
corresponds in type to one of the data baseline(s) determined at step 308, so
that the step of
CA 3017014 2018-09-10
comparing 312 comprises comparing a data baseline to a first entity data
baseline of a
corresponding type.
[0025] Still with reference to FIG. 3., in accordance with a further
aspect of the present
application, method 300 may further comprise: analyzing 320 the stored records
of the other
entities associated with the sector (which may comprise business entities);
and identifying 322,
from the analysis of the stored records of the other entities associated with
the sector, one or
more potential business-to-business opportunities for the first entity (which
may comprise a
business entity). The relevant information may then comprise the identified
one or more
potential business-to-business opportunities. For example, an analysis of the
data exchange
records of the other entities in the sector may reveal other suppliers of
products similar to those
purchased by the first entity, which suppliers supply the like products at
comparable or lower
prices than the prices paid by the first entity. As another example, such
analysis may reveal that
the first entity and another business entity in the sector sell complimentary
products and that
there may be efficiencies to be gained from a partnership between the
entities. As discussed
previously, this step, and any other suitable step discussed herein, may be
carried out using Al
and/or ML.
[0026] Still with reference to FIG. 3, in accordance with a further
aspect of the present
application, method 300 may further comprise: forming 324 one or more
recommendations for
the first entity from the analyzed records of the one or more second entities
data exchanges. In
this case, the relevant information may comprise the one or more
recommendations. The
recommendations may comprise, e.g., notifications of marketing opportunities.
For example, in
the case where the institution carrying out the analysis of the data exchange
records is a financial
institution, such as a retail bank, if the analysis of the one or more second
entities data exchanges
(i.e., all transaction records in database 140 other than the first entity's
transaction records)
reveals that there has been a spike in new, young adults carrying out
transactions in Region A, a
recommendation may be to cater marketing in Region A to young adults.
Conversely, a
recommendation may comprise an avoidance measure, such as where analysis of
the one or more
second entities data exchange records reveals a comparatively low population
for a retail location
of the first entity (e.g., as compared to an analysis of populations within
regions around locations
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of competitors of the first entity), in which case the recommendation may
comprise a warning of
low population and thus, low opportunities for sales, for example.
[0027] In another aspect of the present application, method 300 may
also comprise
extrapolating 326 from the analyzed records of the one or more second entities
data exchanges to
forecast one or more trends. In this case, the relevant information may
comprise the forecasted
one or more trends. The instructions when executed by processor 240 may cause
the processor
to analyze the one or more second entities data exchange records at different
points in time in
order to obtain different data points from which the extrapolation can be
made. Additionally, or
alternatively, reference may be made to the historical one or more second
entities data exchange
records in database 140, at one or more points in the past, in order to obtain
the various data
points from which the extrapolation can be made. Additionally, or
alternatively, reference may
be made to public sources of information, such as on the Internet, in order to
obtain data points
from which the extrapolation can be made (such as population statistics
available on the Internet
from public census records). For example, with reference to the population-
based
recommendation above, it may be forecasted, from an extrapolation from the
analyzed one or
more second entities data exchange records, that population for an area served
by a first entity
location is trending upward or downward. As another example, a forecast of an
increasing trend
in mobile payments may be determined.
[0028] As a further example of relevant information that may be
determined, method 300
may also comprise identifying 328 one or more instances of fraudulent data
exchanges from the
analyzed records of the one or more second entities data exchanges. The
relevant information
may then comprise the identified one or more instances of fraudulent data
exchanges. Step 328
may comprise analysis of data exchange/transaction records, and/or may
comprise analysis of
data derived from public sources and/or interactions with the one or more
second entities (e.g.,
when customers of a financial institution report instances of fraud to a
bank).
[0029] Still with reference to FIG. 3, in accordance with a further
aspect of the present
application, method 300 may further comprise, after the step of analyzing 320
the stored records
of the other entities associated with the sector, determining 330 a benchmark
index for the sector
and an index for the first entity based on respective one or more factors of
the other entities and
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the first entity. The relevant information may comprise the sector benchmark
index and/or the
first entity index. The one or more factors may comprise, for a time period:
revenues, profits,
and/or volume of product sold, for example. The time period for the analyzed
factor(s) may be
pre-configured by a user of computing device 110 via input device 230, and/or
the instructions
may include a default time period which may be overwritten by the user input.
Further factors
not described herein may be covered by the present application, and the types
of factors are not
intended to restrict the presently described aspects. Method 300 may further
comprise
comparing 332 the first entity index to the sector benchmark index and ranking
334 the first
entity against the other entities based on the comparison. In such cases, the
relevant information
may comprise the rank, and it is expected that the rank (identifying for the
first entity its ranking
against its competitors, for example, based on one or more factors) would
provide yet a further
source of useful information to the first entity from the data exchange
records of the institution.
For example, it may be of use for marketing purposes that the first entity
knows how it ranks
against the other entities in the sector in terms of revenues by region. It
may also be of use to the
first entity to know how it ranks against the other entities in the sector
based on a combination of
factors that are combined to determine the benchmark index and first entity
index. The various
factors may be combined to derive the respective indexes by known mathematical
formulas for
benchmarking based on a plurality of factors, as would be known in the art. In
accordance with a
further aspect, rather than determining 330 a single benchmark index based on
multiple factors,
.. separate benchmark indexes may be determined, each based on a respective
one of the factors,
and respective indexes may also be determined for the first entity. In this
case, the steps of
comparing 332 and ranking 334 may be based on separate comparisons and
rankings for each
such factor and the related indexes for the sector and the first entity.
[0030] In aspects described herein, methods steps involving the sharing
of information
obtained from data exchange records may involve the anonymizing of such
information prior to
its dissemination, in order to comply with applicable laws (e.g., privacy
laws).
[0031] The presently described aspects are expected to allow an
institution (such as a
financial institution) to identify relevant information for entities (such as
the first entity described
herein, which may, e.g., be a business customer of the financial institution)
from its existing data
exchange records, to thereby leverage its data (which may be extensive, and
thus comprise "big
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data") to cultivate relationships with any such first entity. For example, the
identified relevant
information may comprise information on the number of coffee shop customers
that purchase
coffee from Retail Coffee Shop ABC versus the first entity (Retail Coffee Shop
123). As
another example, where the baselines compared comprise coffee bean suppliers,
the analysis of
the data exchange records may reveal that merchants with greater sales than
the sales of the first
entity are supplied by a particular coffee bean supplier, and so the relevant
information may
comprise an indication of the coffee bean supplier supplying the more
successful coffee retailers.
The first entity may then, for example, use the relevant information to
conduct further analysis
(such as by investigating the bean quality and taste of the beans supplied to
the more successful
retailers), or may make a determination to switch bean suppliers based solely
on the relevant
information. As described herein, the presently described aspects may use AT
and/or ML in
carrying out any of the method steps described herein that are suitable for
implementation using
Al and/or ML, and may use information from both the data exchange records in
database 140
and public sources of digital information (such as the Internet) to determine
relevant information
(or other information required in the described method steps) to allow the
first entity to make
informed decisions about its business and/or data exchanges. As described
above, the relevant
information may comprise, e.g., trends or forecasts, recommendations, warnings
of fraudulent
transactions, rankings, and other information derived from the described
comparisons and/or
from analysis of the data exchange records, and in that manner, the presently
described aspects
leverage existing data to cultivate relationships with entities.
[00321 With reference to FIG. 4, in accordance with a further exemplary
aspect of the
present application, the instructions when executed by processor 240 cause the
processor to carry
out steps of method 400 for determining, and identifying information to
manage, a level of risk
of a first entity. For example, where the institution collecting the data on
the first entity and the
one or more second entities comprises a financial institution, the financial
institution may use the
information from the data exchange records to determine, in accordance with
method 400, one or
more risk levels associated with the first entity in order to inform its
decision to, e.g., invest in or
provide a monetary loan to the first entity. The financial institution may
also use the information
gleaned from the data exchange records to provide feedback to the first entity
(e.g., in the form
goal(s)) to help the first entity manage its risk level(s) and perhaps improve
(i.e. lower) its
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level(s) of risk), and the financial institution may use that revised risk
level to reassess its
decision to grant a monetary loan or to adjust the loan amount.
[0033] With reference to FIGs. 3 and 4, method 400 may comprise steps
302, 304, 306,
320, 330, 332, and 334 of method 300, and transition at "A" from step 334 to
the remaining steps
of method 400 shown in FIG. 4. With reference to FIG. 4, method 400 may
further comprise:
determining 402 the level of risk for the first entity based on the rank
determined at step 334;
determining 404 an amount of a contribution to the first entity based on the
determined level of
risk; if it is determined 405 that the rank is below (and/or the level of risk
is above) a threshold,
determining 406 one or more goals over a time period for the first entity for
increasing the rank,
the goal(s) corresponding respectively to the factor(s) from step 330 (for
determining 330 the
sector benchmark index and the first entity index) and relating to respective
one or more
measurable metrics of the first entity; measuring 408 the one or more metrics
at or before expiry
of the time period; determining 410 an updated first entity index based on the
measured
metric(s); determining 412 an updated benchmark index for the sector based on
the one or more
factors of the other entities; comparing 414 the updated first entity index to
the updated sector
benchmark index; determining 416 an updated rank against the updated benchmark
index for the
first entity based on the comparison; determining 418 an updated level of risk
for the first entity
based on the determined updated rank; and adjusting 420 the amount of the
contribution to the
first entity based on the determined updated risk.
[0034] The risk(s) determined at steps 402 and/or 418 may be determined in
accordance
with any proprietary or known method(s) for quantifying risks based on one or
more factors, and
the method employed for determining 402 and/or 418 the risk and/or updated
risk is not to be
considered as limiting the scope of the presently described aspects. In the
financial context,
"risk" may comprise a risk of the first entity's business failing (which may
also include, e.g., a
risk of the first entity being unable to pay loans, and/or a risk of a poor
return on an investment
in the first entity). At step 406, the threshold and the time period may be
pre-configured by a
user of computing device 110 via input device 230, and/or the instructions may
include a default
threshold or time period which may be overwritten by user input. Further,
method 400 may
employ a threshold for the rank (in which case the threshold comprises a lower
threshold), the
level of risk (in which case the threshold comprises an upper threshold), or
both. If at step 405 it
CA 3017014 2018-09-10
is determined, after ranking 334 the first entity that the rank is below a
lower threshold, method
400 may proceed to step 402 to determine the level of risk before proceeding
to step 404 to
determine the amount of the contribution. Alternatively, method 400 may
comprise determining
402 the level of risk prior to the determination made at step 405, in which
case, if at step 405 it is
determined that the level of risk is above an upper threshold, method 400 may
proceed to step
404 to determine the amount of the contribution.
[0035] As discussed above, the first entity and the one or more second
entities may
comprise customers of a financial institution, and the contribution may
comprise a monetary loan
from the financial institution to the first entity. The contribution could
also comprise an
.. investment from an investing entity, such as a VC firm or personal
investor, where, e.g., the first
entity has given permission to the financial institution to release the
determined rank and/or level
of risk to prospective investors (or where the first entity itself provides
this information to
prospective investors). It will be appreciated that the step of determining
404 an amount of a
contribution to the first entity based on the determined level of risk may
also comprise a decision
as to whether or not to make a contribution at all; in the context of step
404, if it is determined
that a contribution is not to be made, the determined contribution amount
would be zero.
[0036] Further, if it is determined, at step 405, that the rank is
below (and/or the level of
risk is above) the threshold, method 400 may proceed to step 404, where the
determined
contribution amount may be zero, or some initial amount which may be adjusted
later at step 420
(depending on the updated level of risk determined at step 418).
Alternatively, method 400 may
proceed from step 405 directly to step 406 (which path is not shown in FIG.
4).
[0037] The one or more metrics for measuring the goal(s) determined at
step 406 may
comprise accounts receivable, accounts payable, revenues, net profits,
employee retention,
and/or any other measurable metrics not described herein, such as other types
of financial data
capable of being monitored and measured. The types of measurable metrics are
not intended to
restrict the presently described aspects. The metrics may be directly measured
from the data
exchange records or may be derived therefrom. For example, employee retention
may be
determined by, e.g., monitoring the number of data exchange records comprising
payroll deposits
made by the first entity.
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[0038] As an example, a financial institution may decide that it will
not loan money to a
first entity that ranks below a lower threshold of, e.g., 7 (out of a maximum
ranking of, e.g., 10),
as determined by perhaps a proprietary ranking methodology employed by the
financial
institution. First entities that comprise small businesses or sole
proprietorships, while pursuing
potentially lucrative endeavours, may not have a level of sophistication or
knowledge that would
allow them to otherwise come well-equipped with the financial data (e.g. sales
figures and
forecasts) that would help to secure the loans being sought. A financial
institution may use
method 400 to, e.g., provide a further opportunity to such first entities, by
setting measurable
goals for the entities which have associated metrics that may be measured 408
at or before expiry
of the established time period. The time period for the first entity to
achieve the goals may be
set, e.g., to 90, 120, 150, or 365 days, or any other time period. Method 400
therefore provides
financial institutions with an option to monitor, via data exchange records in
database 140 of the
financial institution, first entities in order to conduct due diligence on the
first entities and to
make an informed decision regarding whether to make a contribution (e.g., a
loan) to such
entities where, e.g., the first entity in question may show promise, but may
have initially lacked
the information necessary to secure a loan.
[0039] In accordance with further aspects of the present application,
method 400 may
further comprise steps for providing the first entity with feedback on whether
goal(s) have been
accomplished, as well as on whether the first entity is on track to accomplish
the goal(s). For
example, method 400 may further comprise determining 426, upon measuring the
one or more
metrics at the expiry of the time period, and notifying 424 the first entity
of, via communication
module 210, which of the one or more goals have been achieved and/or missed.
The financial
institution may then use the results of the first entity's performance over
the time period toward
achieving the goals as a basis for further discussions with the first entity
about securing a loan, or
the financial institution may decide to refuse, grant or adjust the
contribution or loan on the basis
of the determination made at step 426 (such as in accordance with steps 410-
420, or based solely
on the determination made at step 426 (the path from 426 to 420 not being
shown in FIG. 4)).
[0040] As described above, method 400 may also comprise determining 428,
upon
measuring 408 the one or more metrics, and notifying 424 the first entity of,
via communication
module 210, progress of the first entity toward achieving the one or more
goals by expiry of the
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time period. The determined progress may include, e.g., indications of percent
of goal achieved
(e.g., 55% of target revenue for time period achieved), or any other suitable
manner of conveying
progress, as would be understood by the person of ordinary skill in the art.
[0041] Method 400 may also comprise, upon determining 428 the progress
of the first
entity toward achieving the goal(s) by expiry of the time period,
extrapolating 430 from the
determined progress a forecast of whether the one or more goals are achievable
by expiry of the
time period, and notifying 424, via the communication module, the first entity
of the forecast.
Extrapolation may comprise any known method or technique for extrapolating and
forecasting or
projecting data based on known data, as would be known to the person of
ordinary skill in the
art. The notification may comprise an indication that the first entity is on
track to achieve the
goal(s) or at risk of missing the goal(s) by expiry of the time period.
Further, notifying 424 the
first entity of the forecast may be done in real-time upon determining the
forecast. The first
entity may then use the provided information to adjust marketing tactics,
supplier relationships,
and any other facet of the business that may help the first entity to meet the
set goal(s) by expiry
of the time period, and to thereby achieve a higher determined 416 updated
rank and a higher
determined 418 updated level of risk, which in turn may result in the
financial institution
adjusting 420 the amount of the contribution (such as by deciding to increase
a monetary loan
amount, or deciding to offer a loan where no loan was previously being
offered).
[0042] Conversely, where the updated level of risk is above the
previously determined 402
level of risk for the first entity (such as where the measured metric(s) show
that coffee sales have
dropped to 50% from 35% less than competitors' average sales), the financial
institution may
adjust the amount of a contribution (e.g., a monetary loan) to the first
entity to a lesser amount,
or decide not to offer a loan at all. Providing the first entity with an
indication of progress
toward achieving the goal(s), and particularly in real-time, may help the
first entity to avoid a
failed loan application, and may also help the financial institution to avoid
missing out on what
may be a sound loan transaction.
[0043] In accordance with a further aspect of the present application,
method 400 may
comprise a mechanism for adjusting one or more of the goals where, e.g., it is
determined that
the goals initially established were insufficient (due, e.g., to an error in
goal setting by the
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financial institution, new information received from the first entity that
impacts the goals, or for
any other reason), which may be determined at, e.g., step 428, such as where
it is determined 428
that the first entity has met the goals with relative ease and well before
expiry of the time period,
in which case it may be determined, by both the financial institution and the
first entity, that a
larger contribution should be sought, and that the goals should be adjusted
accordingly (or,
alternatively, the original loan amount may be granted without adjusting the
goals). As such,
method 400 may further comprise (such as upon measuring 408 the metric(s)),
determining 422
one or more adjustments to the one or more goals, and notifying 424, via
communication module
210, the first entity of the adjusted one or more goals. Method 400 may then
carry on from the
step of measuring 408 the (now adjusted) metric(s).
[0044] In accordance with a further aspect of the present application,
the institution having
the data exchange records in database 140 may decide to offer products and/or
services to the
first entity based on any of the analyses of the data exchange records
described herein. For
example, method 400 may further comprise determining 432 one or more product
and/or service
offerings based on the level of risk or the level of updated risk determined
at steps 402 and 418,
respectively, and notifying 424 the first entity, via communication module
210, of the one or
more product and/or service offerings. For example, upon determining that the
level of risk or
updated level of risk for a first entity is acceptable (e.g., in accordance
with its own standards), a
financial institution may decide to offer the first entity a term deposit
product, a line of credit, or
any other product or service.
[0045] The step of notifying 424 may be as described above for the step
of notifying 316,
in that it may be done in real-time, by push notification, upon any of the
steps of method 400
producing information which the institution (e.g., financial institution) may
share with the first
entity, such as upon execution of steps 404, 406, 416, 420, 422, 426, 428,
430, and/or 432.
Alternatively, first entity 130 may request (such as by a financial or banking
app configured to
communicate with computing device 110, or which may comprise a client instance
of computing
device 110 having only informational or reporting features for the user), over
network 120 from
computing device 110, information from any of the steps of method 400
producing information
which may be shared with the first entity, such as the information from steps
404, 406, 416, 420,
422, 426, 428, 430, and/or 432, and pull the relevant information. Further,
notifying 424 may
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occur after any other step of method 400 producing information which the
institution (e.g.,
financial institution) may share with the first entity, such as after steps
402 and/or 418 (to share
the determined risk or updated level of risk), for example. As described
above, the notification
may comprise, for example, an audible and/or visual alert displayed on a
display of another
.. device (e.g., a mobile device, computer, tablet, etc.) by which a graphical
user interface of an
application hosted by the institution (such as a financial or banking app for
a financial
institution) is accessed by the first entity or a representative of the first
entity, or a message sent
via communication module 210 to a digital address of such first entity or
first entity
representative (e.g., SMS, MMS, instant message, email, a proprietary message
type, etc.). It
will be appreciated by the person skilled in the art that any suitable type of
notification message
may be used.
[0046] Any of the steps of notifying 316 or 424 described herein may
comprise notifying
an electronic device 132 associated with any entities 130 (such as first
entity 130, one or more
second entities 130, or other entities 130, as described above), as shown in
FIG. 1.
[0047] While the foregoing has been described in some detail for purposes
of clarity and
understanding, it will be appreciated by those skilled in the relevant arts,
once they have been
made familiar with this disclosure that various changes in form and detail can
be made without
departing from the true scope of the appended claims. The present application
is therefore not to
be limited to the exact components or details of methodology or construction
set forth above.
.. Except to the extent necessary or inherent in the processes themselves, no
particular order to
steps or stages of methods or processes described in this disclosure,
including in the Figures, is
intended or implied. In many cases the order of process or method steps may be
varied, and/or
made sequential or parallel, without changing the purpose, effect, or import
of the method(s)
described.
CA 3017014 2018-09-10
