Note: Descriptions are shown in the official language in which they were submitted.
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PATENT APPLICATION
MODULATING MOBILE-DEVICE DISPLAYS BASED ON AMBIENT SIGNALS TO
REDUCE THE LIKELIHOOD OF FRAUD
CROSS-REFERENCE TO RELATED APPLICATIONS
[001] This patent claims the benefit of U.S. Provisional Patent Application
62/160,811, titled
"Dynamic Gift Card Allocation," filed 13 May 2015. The entire content of this
earlier-filed
application is hereby incorporated by reference for all purposes.
BACKGROUND
1. Field
[002] The present invention relates generally to limiting access to
information on mobile
computing devices and, more specifically, to modulating mobile-device displays
based on
ambient signals to reduce the likelihood of fraud.
2. Description of the Related Art
[003] In some cases, people obtain valuable goods and services from others in
exchange for
drawing upon a balance in a stored value card, which includes the digital
equivalent. Examples
include open-loop stored value cards and closed-loop stored value cards, each
of which may take
various forms, such as gift cards, rebate cards, payroll cards, and the like.
In many cases, the
value stored on the card is spent by presenting to a retailer certain
information, such as a card
number and a pin number.
[004] Recently, online exchanges have arisen where those in possession of such
cards sell the
cards, often at a discount relative to the card balance. For example, a user
may receive a gift
card, as a birthday present, to a store that the user no longer favors, and
the user may sell the
card, in exchange for cash or another type of card, to the exchange or a
different user on such an
exchange. In some cases, access to the value of the card is conveyed by
sending the card and pin
numbers, without transferring possession of any physical token, like the card
itself. Thus, a
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buyer of a card may receive information, for example, an email, text, or in-
app data, that they can
present on their mobile device to a retailer to buy goods or services with the
value remaining on
the card. In some cases, the user may then re-sell or leave a remaining
balance on the card back
to an exchange, or the exchange may authorize the user to only use a portion
of the value stored
on the card.
[005] This approach, while relatively convenient for users, can give rise to
certain types of
fraud. One consequence of granting access to cards via networks, e.g., with
mobile computing
devices, without transferring a physical token, is that each party having
access to the card (e.g.,
the seller, the first buyer who spends part of the balance, the second buyer
who spends another
part, and so on) could potentially retain the information needed to spend the
remaining balance
on the card, even after the card has been sold on the exchange or returned to
the exchange. For
instance, there is a risk the first buyer could use part of the card's
balance, return the card to the
exchange, and then spend the remaining balance on the card before the card is
sold again on the
exchange (or after the card is sold but before it is used by the second
buyer).
SUMMARY
[006] The following is a non-exhaustive listing of some aspects of the present
techniques.
These and other aspects are described in the following disclosure.
[007] Some aspects include a process of classifying ambient signals to reduce
fraudulent use of
information, the process including: receiving, with the mobile computing
device, from a remote
server, balance-access information by which a stored value card balance can be
spent at a point
of sale terminal; storing, with the mobile computing device, the balance-
access information;
sensing, with one or more sensors of a mobile computing device, ambient
signals; classifying the
ambient signals as indicating the user is in a retail establishment; and in
response to the
classification, displaying, on a display screen of the mobile computing
device, the balance-access
information, such that the balance-access information can be input to a point-
of-sale terminal.
[008] Some aspects include a tangible, non-transitory, machine-readable medium
storing
instructions that when executed by a data processing apparatus cause the data
processing
apparatus to perform operations including the above-mentioned process.
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[009] Some aspects include a system, including: one or more processors; and
memory storing
instructions that when executed by the processors cause the processors to
effectuate operations of
the above-mentioned process.
BRIEF DESCRIPTION OF THE DRAWINGS
[0010] The above-mentioned aspects and other aspects of the present techniques
will be better
understood when the present application is read in view of the following
figures in which like
numbers indicate similar or identical elements:
[0011] Figure 1 illustrates the logical architecture of an example of a gift
card management
system in accordance with some of the present techniques;
[0012] Figure 2 illustrates an example of a gift card distribution process
that may be executed by
some embodiments of the system of Figure 1;
[0013] Figure 3 illustrates an example of a process for reducing fraudulent
use of gift cards that
may be executed by some embodiments of client devices communicating with the
system of
Figure 1; and
[0014] Figure 4 illustrates an example of a computer system by which the above
techniques may
be implemented.
[0015] While the invention is susceptible to various modifications and
alternative forms, specific
embodiments thereof are shown by way of example in the drawings and will
herein be described
in detail. The drawings may not be to scale. It should be understood, however,
that the drawings
and detailed description thereto are not intended to limit the invention to
the particular form
disclosed, but to the contrary, the intention is to cover all modifications,
equivalents, and
alternatives falling within the spirit and scope of the present invention as
defined by the
appended claims.
DETAILED DESCRIPTION OF CERTAIN EMBODIMENTS
[0016] To mitigate the problems described herein, the inventors had to both
invent solutions and,
in some cases just as importantly, recognize problems overlooked (or not yet
foreseen) by others
in the fields of computer security and payment processing systems. Indeed, the
inventors wish to
emphasize the difficulty of recognizing those problems that are nascent and
will become much
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more apparent in the future should trends in industry continue as the
inventors expect and
particularly those problems that cross the boundaries of distinct fields, as
is the case here.
Further, because multiple problems are addressed, it should be understood that
some
embodiments are problem-specific, and not all embodiments address every
problem with
traditional systems described herein or provide every benefit described
herein. That said,
improvements that solve various permutations of these problems are described
below.
[0017] It can be appreciated that while many retail establishments use gift
cards (e.g., prepaid
cards or vouchers that can be used for purchases at the establishment, also
referred to as stored
value cards), numerous inefficiencies exist. For example, individuals may own
gift cards from a
retailer from which they are not interested in purchasing anything.
[0018] Accordingly, described herein in various implementations are
technologies that enable
the centralized exchange of such gift cards. Such cards can be bought and sold
at a discount,
thereby providing liquidity to the original card owner as well as a discounted
purchase price (as
compared to the original retail price of an item being purchased) to the
buyer. Additionally, as
described herein, the referenced technologies can provide/maintain a gift card
repository and can
enable the efficient utilization of such cards in retail settings (both 'brick
and mortar' and
ecommerce). For example, using a mobile application executing on a mobile
device (in
conjunction with a central gift card repository/server), a user can utilize
gift cards to make retail
purchases (thereby benefitting from the discount associated with the
utilization of otherwise
unused gift cards) in substantially the same amount of time as a conventional
retail checkout
process would take. In doing so, the user can benefit from the discount
associated with gift card
utilization while maintaining an efficient/seamless checkout
process/experience.
[0019] However, as noted, in many Internet-based use cases, everyone who is
given access to a
gift card (e.g., the information needed to spend), or some other type of
stored-value card, and
then returns the card, is in position to double spend the balance. In many
cases, to use the gift
card, the mobile device displays the information used to authorize a
transaction on the gift card.
As a result, a nefarious user could write down that information, return the
card on an exchange,
and then use their own record of the information to draw down the card's
balance before another
authorized use by another person.
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[0020] This problem is unique to the Internet age because copies of the
information are shared,
potentially anonymously, over networks, and the ease of transacting results in
balances being
sliced more finely, putting the card information potentially in the possession
of several untrusted
parties. Further, users of these systems often expect a seamless experience,
and slow,
cumbersome authentication schemes are often not commercially feasible.
Compounding these
challenges, operators of gift card exchanges are often not in a position to
dictate technical
specifications of the point-of-sale terminals or transaction processing
systems by which the cards
are spent. As a result, efforts to mitigate fraud often need to accommodate
legacy point-of-sale
and transaction processing systems.
[0021] Some embodiments described below may limit the user's ability to obtain
the sensitive
card information, e.g., the card number or pin number. Some embodiments may
probabilistically
classify ambient signals as indicating whether the user is likely at a place
where there is a
legitimate use of the card, e.g., at a retail store that accepts the card, and
in some cases, at certain
types of retail stores. The result of the classification may be used to
determine whether to display
the card information on a display screen of a mobile computing device. For
instance, the card
information may remain un-displayed and encrypted on the user's mobile
computing device until
the user 1) requests to use the card; and 2) ambient signals are classified as
indicative of
legitimate use. In contrast, users who attempt to view the card information
when there is no
legitimate use likely, like viewing card numbers or pin numbers while at home
with a card only
usable for in-store transactions, may be prevented from viewing the card's
information.
[0022] Figure 1 depicts an illustrative system architecture 100, in accordance
with one
implementation of the present disclosure. The system architecture 100 includes
one or more user
devices 102, merchant devices 104, and server machine 120. These various
elements or
components can be connected to one another via network 110, which can be a
public network
(e.g., the Internet), a private network (e.g., a local area network (LAN) or
wide area network
(WAN)), or a combination thereof. Additionally, in certain implementations
various elements
may communicate and/or otherwise interface with one another (e.g., user device
102 with
merchant device 104). The various illustrated computing devices may be formed
with one or
more of the types of computer systems described below with reference to Figure
4.
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[0023] User device 102 can be a rackmount server, a router computer, a
personal computer, a
portable digital assistant, a mobile phone, a laptop computer, a tablet
computer, a camera, a
video camera, a netbook, a desktop computer, a media center, a smartphone, a
watch, a
smartwatch, an in-vehicle computer/system, any combination of the above, or
any other such
computing device capable of implementing the various features described
herein. Various
applications, such as mobile applications ('apps'), web browsers, etc. (not
shown) may run on
the user device (e.g., on the operating system of the user device). It should
be understood that, in
certain implementations, user device 102 can also include and/or incorporate
various sensors
and/or communications interfaces (not shown). Examples of such sensors include
but are not
limited to: accelerometer, gyroscope, compass, GPS, haptic sensors (e.g.,
touchscreen, buttons,
etc.), microphone, camera, etc. Examples of such communication interfaces
include but are not
limited to cellular (e.g., 3G, 4G, etc.) interface(s), Bluetooth interface,
WiFi interface, USB
interface, NFC interface, etc.
[0024] Merchant device 104 can be a rackmount server, a router computer, a
personal computer,
a portable digital assistant, a mobile phone, a laptop computer, a tablet
computer, a camera, a
video camera, a netbook, a desktop computer, a media center, a smartphone, a
watch, a
smartwatch, an in-vehicle computer/system, a point of sale (POS) system,
device, and/or
terminal, any combination of the above, or any other such computing device
capable of
implementing the various features described herein. Various applications, such
as mobile
applications (apps'), web browsers, etc. (not shown) may run on the merchant
device (e.g., on
the operating system of the merchant device). It should be understood that, in
certain
implementations, merchant device 104 can also include and/or incorporate
various sensors and/or
communications interfaces (not shown). Examples of such sensors include but
are not limited to:
accelerometer, gyroscope, compass, GPS, haptic sensors (e.g., touchscreen,
buttons, etc.),
microphone, camera, barcode scanner, etc. Examples of such communication
interfaces include
but are not limited to cellular (e.g., 3G, 4G, etc.) interface(s), Bluetooth
interface, WiFi interface,
USB interface, NFC interface, etc. It should be understood that in certain
implementations
merchant device 104 may be a dedicated POS terminal (e.g., including an
integrated barcode
scanner) while in other implementations merchant device 104 may be a handheld
or personal
computing device (e.g., smartphone, tablet device, personal computer, etc.)
configured to provide
POS functionality (whether utilizing the functionality provided by the various
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components/sensors of the device or via one or more connected peripherals). It
should also be
understood that, in certain implementations, merchant device 104 can be a
server, such as a
webserver that provides an ecommerce site/service, such as may be accessed by
user device 102
via a website and/or dedicated application.
[0025] Server machine 120 can be a rackmount server, a router computer, a
personal computer, a
portable digital assistant, a mobile phone, a laptop computer, a tablet
computer, a camera, a
video camera, a netbook, a desktop computer, a smartphone, any combination of
the above, or
any other such computing device capable of implementing the various features
described herein.
Server machine 120 can include components such as gift card allocation engine
130, and gift
card repository 140. The components can be combined together or separated in
further
components, according to a particular implementation. It should be noted that
in some
implementations, various components of server machine 120 may run on separate
machines (for
example, gift card repository 140 can be a separate device). Moreover, some
operations of
certain of the components are described in more detail below.
[0026] Gift card repository 140 can be hosted by one or more storage devices,
such as main
memory, magnetic or optical storage based disks, tapes or hard drives, NAS,
SAN, and so forth.
In some implementations, gift card repository 140 can be a network-attached
file server, while in
other implementations gift card repository 140 can be some other type of
persistent storage such
as an object-oriented database, a relational database, and so forth, that may
be hosted by the
server machine 120 or one or more different machines coupled to the server
machine 120 via the
network 110, while in yet other implementations gift card repository 140 may
be a database that
is hosted by another entity and made accessible to server machine 120. Gift
card repository 140
can store information relating to various gift cards, such as codes, bar
codes, and/or any other
such identifiers, as well as information relating to such cards (e.g.,
monetary value, expiration
date, usage restrictions, etc.).
[0027] It should be understood that though Figure 1 depicts server machine 120
and devices 102
and 104 as being discrete components, in various implementations any number of
such
components (and/or elements/functions thereof) can be combined, such as within
a single
component/system. For example, in certain implementations devices 102 and/or
104 can
incorporate features of server machine 120.
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[0028] As described in detail herein, various technologies are disclosed that
enable dynamic gift
card allocation. In certain implementations, such technologies can encompass
operations
performed by and/or in conjunction with gift card allocation engine 130.
[0029] Figure 2 depicts a flow diagram of aspects of a method 200 for dynamic
gift card
allocation. The method is performed by processing logic that may comprise
hardware (circuitry,
dedicated logic, etc.), software (such as is run on a general purpose computer
system or a
dedicated machine), or a combination of both. In one implementation, the
method is performed
by one or more elements depicted and/or described in relation to Figure 1,
while in some other
implementations, one or more blocks of Figure 2 may be performed by another
machine or
machines.
[0030] For simplicity of explanation, methods are depicted and described as a
series of acts.
However, acts in accordance with this disclosure can occur in various orders
and/or concurrently,
and with other acts not presented and described herein. Furthermore, not all
illustrated acts may
be required to implement the methods in accordance with the disclosed subject
matter. In
addition, those skilled in the art will understand and appreciate that the
methods could
alternatively be represented as a series of interrelated states via a state
diagram or events.
Additionally, it should be appreciated that the methods disclosed in this
specification are capable
of being stored on an article of manufacture to facilitate transporting and
transferring such
methods to computing devices. The term article of manufacture, as used herein,
is intended to
encompass a computer program accessible from any computer-readable device or
storage media.
[0031] At block 210, a location of a device (e.g., user device 102) can be
determined. At block
220, a first gift card can be presented at the device, such as in a manner
described herein. In
certain implementations, such a gift card can be presented based on the
location (e.g., the
location of the device determined at block 210). At block 230, it can be
determined that the first
gift card has been utilized in a transaction. At block 240, a second gift card
can be provided at
the device. In certain implementations, such a gift card can be provided based
on a
determination that the first gift card (e.g., the gift card presented at block
220) has been utilized
in the transaction. Various aspects of the referenced operations are described
and illustrated in
greater detail herein.
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[0032] By way of further illustration, an application (app') executing on user
device 102 can
request or otherwise determine a current location of the device (e.g., based
on GPS coordinates,
etc.). Based on the determined location, information regarding one or more
retail establishments
(e.g., those within a defined proximity to the current location) can be
requested/retrieved and
presented at the device. In certain implementations, such information can
reflect those
proximate retail establishments with respect to which gift cards are available
(e.g., at gift card
repository 140 of server machine 120).
[0033] Upon receiving a selection (e.g., by the user) of a particular retail
establishment, one or
more gift cards (e.g., barcodes, etc., stored in gift card repository 140) can
be requested/received
by the user device. It should be noted, however, that in certain
implementations such gift card
information may be requested/received upon determining the location of the
device (e.g., by
requesting gift cards for those retail establishments that are proximate to
the device, maintaining
such cards in memory, and presenting them upon receiving a selection by the
user of a particular
establishment).
[0034] In certain implementations, an input can be received (e.g., as provided
by the user via the
device) that reflects a sale/purchase amount (e.g., the total amount charged
by the retailer for a
particular purchase, e.g., `$54.63'). Upon receiving such a selection, one or
more gift cards can
be received, requested, and/or selected (e.g., from those gift cards
previously received and stored
in the memory of the user device). In certain implementations, such gift cards
can be
selected/requested (e.g., from gift card repository 140) based on any number
of factors, such as
the degree to which the credit amount of the gift card
approximates/corresponds to the
sale/purchase amount. Moreover, in certain implementations the user may be
provided with the
option to select whether to utilize relatively more gift cards (e.g., of
smaller increments, together
which add up to the total purchase price, thereby receiving a larger
discount), or relatively fewer
gift cards (some of which may be of larger increments, thereby necessitating
the use of a smaller
number of gift cards and providing a more expedient check out process).
Additionally, in certain
implementations various predictions/projections can be computed with respect
to the
sale/purchase amount (e.g., based on the retail establishment, the user's
purchase history, the
amount of time the user has spent in the store, the distance the user has
traveled in the store, the
areas/departments of the store that the user has visited, etc.), and one or
more gift cards can be
selected/provided based on such predictions/projections.
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[0035] Moreover, in certain implementations a gift card having a value that
exceeds the total
sale/purchase amount may be selected/provided. Upon completion of the
transaction, the
remaining balance on the gift card can subsequently be provided (e.g., to
another user) with
respect to another transaction. By way of illustration, a first user may
initiate a transaction
totaling $60 and a gift card having $100 worth of credit may be
selected/provided (e.g., in a
manner described herein) in order to complete the transaction (leaving the
gift card with $40
worth of credit). Subsequently, a second user may, for example, initiate a
transaction totaling
$40 and the same gift card (now having $40 worth of credit) may be
selected/provided (e.g., in a
manner described herein) in order to complete the transaction (thereby
utilizing the entire
remaining value on the gift card). In doing so, a single gift card can be
utilized by different users
at different times for different transactions. Moreover, in certain
implementations each user will
only be required to pay or otherwise account for the portion/increment of the
gift card utilized for
his/her purchase. Additionally, in certain implementations, once a particular
gift card is utilized
in a first transaction, such a gift card may be temporarily held (e.g., for a
defined period of time
and/or until a confirmation of the original transaction and/or the current
balance of the card is
received/determined) prior to providing the card again for a subsequent
transaction. In doing so,
the remaining balance on the card can, for example, be confirmed prior to
providing it in another
transaction.
[0036] Additionally, in certain implementations the referenced gift card(s)
can be provided to the
user device in advance of charging, debiting, etc., the requesting user for
the value of the card.
That is, as noted above, it can be appreciated that while a gift card of a
particular total value
(e.g., $100) may be selected/provided in order to complete the transaction, in
many scenarios the
user may only use a portion of the total value of the card (e.g., $60). As
such, in lieu of charging
the user the full value of the card (e.g., $100), the gift card can instead be
selected/provided (e.g.,
before the transaction has been completed and without initially
charging/debiting the requesting
user for the full value of the card), and once the transaction is complete the
user can be
charged/debited for the increment used during the transaction (e.g., based on
the total purchase
price as provided by the user, an independent verification of the gift card
balance, etc.) while the
remaining value on the gift card can be utilized in subsequent transaction(s)
(e.g., by other
users), such as in a manner described herein.
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[0037] The various selected/received gift cards can then be sequentially
presented/provided, e.g.,
on the screen of the user device. The user device (e.g., a smartphone) can be
placed or otherwise
oriented in relation to the merchant device (e.g., in relation to the barcode
scanner of a POS
terminal) such that the merchant device can scan, read, or otherwise perceive
or capture the
code/barcode of the gift card being presented. In doing so, the user can
complete the retail
transaction using gift cards originating at server machine 120. Moreover, in
certain
implementations a comparable/related technique can be employed with respect to
coupons. For
example, in certain implementations various coupons can be presented on the
screen of the
device in a sequence such that they can be received/processed by the merchant
device in
succession.
[0038] It should be understood that in scenarios in which multiple gift cards
are to be utilized,
such gift cards can be provided sequentially in any number of ways. For
example, in certain
implementations feedback can be provided/received (e.g., provided by the user
to the device,
such as by swiping a touch screen or pressing a button) which indicates that
another gift card is
to be presented. It should also be noted that, in certain implementations,
feedback may be
provided/received, indicating that a particular gift card did not work (in
which case a
replacement card can be retrieved/provided).
[0039] By way of further example, in certain implementations various sensory
inputs can be
received and processed by the user device which can be determined to indicate
that a presented
gift card has been processed and that a subsequent gift card is to be
presented (if
relevant/necessary). By way of illustration, in certain implementations
various audio inputs
(e.g., a 'beep' or tone emitted by the merchant device, indicating that a
barcode has been
scanned) can be received by the user device (e.g., by an integrated or
external microphone), and
such inputs can be processed to determine that the presented gift card has
been processed (and
that another gift card, if necessary, is to be presented). By way of further
illustration, in certain
implementations various visual/optical inputs (e.g., a flash or pulse of the
barcode scanner of the
merchant device, indicating that a barcode has been scanned) can be
received/perceived by the
user device (e.g., by an integrated 'front facing' camera), and such inputs
can be processed to
determine that the presented gift card has been processed (and that another
gift card, if necessary,
is to be presented). By way of yet further illustration, in certain
implementations various motion
inputs (e.g., a rotation/orientation of the user device, indicating that a
barcode has likely been
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scanned) can be identified by the user device (e.g., via an integrated
accelerometer, gyroscope,
etc.), and such inputs can be processed to determine that the presented gift
card has likely been
processed (and that another gift card, if necessary, is to be presented). It
should also be noted
that, in certain implementations, various aspects of the timing of the
presentation of the
referenced gift cards can also be accounted for, such that, for example, upon
presenting a
particular gift card for a defined time interval (e.g., 10 seconds), another
gift card can be
selected/requested and displayed.
[0040] As noted, certain users may attempt to fraudulently/improperly use the
described
technologies, such as by capturing/recording gift cards that are presented in
order to utilize them
at a later time. Accordingly, in order to ensure that presented gift cards are
likely to be utilized
in legitimate retail scenarios, various determinations can be made, based on
which a score can be
computed, reflecting the likelihood that the card is (or is not) being used
fraudulently. For
example, one or more inputs from various motion sensors (e.g., accelerometer,
gyroscope, etc.)
can be received and processed in order to determine the manner/pattern in
which the user device
is being maneuvered. A user device that is presenting the gift cards
legitimately (e.g., in a retail
setting) is likely to exhibit a consecutive series of movements/rotations
(e.g., placing the device
face down, followed by a rotation of the device such that it is face up,
followed by another
rotation to face down, etc.), while a device that is being used
inappropriately (such that, for
example, card numbers/codes are being recorded by the user) is less likely to
exhibit such motion
(as the user is likely to simply hold the device in place and cycling through
multiple cards).
Accordingly, in certain implementations the user device and/or the referenced
app executing
thereon can be configured to present/display the referenced gift
cards/barcodes while the device
is determined to be positioned in a particular orientation (e.g., face down,
as the device is likely
to be oriented when the barcode is being scanned), while not presenting (or
obscuring) such
cards/codes when the device is not so oriented. In doing so, the card/code can
be presented when
being legitimately used/scanned while not being presented in other
orientations which may
otherwise enable improper usage. By way of further example, one or more audio
inputs can be
received (e.g., by an integrated or external microphone) and processed in
order to determine an
amount/level of sound/noise (e.g., ambient noise) perceptible to the device.
In scenarios in
which the user device is presenting the gift cards legitimately (e.g., in a
retail setting), a certain
degree of ambient noise (and/or various sounds, talking, beeps, etc.) is
likely to be perceptible,
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while with respect to a device that is being used inappropriately (such that,
for example, card
numbers/codes are being recorded by the user), such audio inputs/noise are
less likely to be
perceived. By way of yet further example, one or more visual inputs can be
received (e.g., as
captured by one or more integrated cameras) and processed in order to
identify/determine
various aspects of the surroundings of the device. In scenarios in which the
user device is
presenting the gift cards legitimately (e.g., in a retail setting), various
elements, characteristics,
etc. (and changes thereto), are likely to be perceptible, while with respect
to a device that is being
used inappropriately (such that, for example, card numbers/codes are being
recorded by the
user), such visual elements, characteristics, etc. are relatively less likely
to be
perceived/identified. In yet other examples, various aspects of the location
of the user device can
be accounted for in determining the likelihood that the presented gift cards
are (or are not) being
used legitimately. For example, utilization of the referenced application in
an area that is
determined to be residential (and/or is not determined to be a retail
location) can indicate that the
usage is more likely to be improper.
[0041] Some embodiments may automatically check balances for sold and
surrendered cards to
ascertain whether a card that has been surrendered has had the card balance
change, possibly
indicating fraud by a user who copied the information on the card. In some
cases, the balance
checks may be performed through automated interaction with a telephone menu
(e.g., by
synthesizing appropriate key presses or voice responses and emitting
corresponding audio). In
some cases, the rate of such checks may be modulated responsive to use of a
card, e.g., the rate
of checks may be elevated for a threshold amount of time after a card is
returned. Some
embodiments may perform such checks while a user purports to be in a store,
e.g., in response to
the user requesting a card or crossing a geofence, to ascertain whether the
card was in fact used
for a purchase. In some cases, some embodiments may flag a transaction as
potentially
indicative of fraud in response to a user requesting a card and the balance
not changing within a
threshold duration of time.
[0042] Upon completion of the transaction (e.g., when enough gift cards have
been presented by
the user device to cover the cost of the purchase), feedback/input can be
received by the user
device (as provided, for example, by the user) indicating that the transaction
is complete (at
which point additional gift cards will not be displayed). Moreover, in certain
implementations,
various aspects of the location of the device can be used in determining that
the transaction is
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complete (and that additional gift cards are not to be displayed). For
example, upon determining
that the device has traveled beyond a certain distance (e.g., 50 feet) from
the area in which the
transaction was initiated (and/or from the location of the retail
establishment), it can be further
determined that the transaction is likely to be complete and additional gift
cards will not be
presented.
[0043] Some embodiments may limit access to a threshold amount of cards, or
cards having an
aggregate balance, based on statistical distribution of cart values for a
particular retail store. For
instance, some embodiments may obtain transaction records for each of a set of
stores, and for
each store, some embodiments may calculate population or sample statistics
indicative of a
measure of central tendency (e.g., mean, mode, or median) and a measure of
variability (e.g., a
variance, standard deviation, etc.). Some embodiments may infer a threshold
amount above
which cart values for a particular store are expected to be very unlikely,
e.g., accounting for less
than 1/100, less than 1/1,000, or less than 1/10,000 of the transactions at a
retail store. Some
embodiments may select cards to be sent to a user based on whether those
cards, either
individually or in the aggregate, contain a balance exceeding this threshold,
rejecting cards that
would cause the threshold to be exceeded.
[0044] As noted above, in order to prevent fraudulent/improper use of the
described
technologies, various forms of verification/authentication can be
incorporated. For example, in
certain implementations, in order to utilize the described technologies, the
user may be prompted
to log in or otherwise associate their gift card usage with a third party
login, service, account, etc.
[0045] In certain implementations, server machine 120 and/or gift card
allocation engine 130 can
be configured to select/provide various gift cards based on any number of
factors. For example,
with respect to gift card sellers that have been determined to be relatively
more likely to
sell/provide gift cards that may not work, gift cards that are provided by
such sellers can be
prioritized (e.g., provided to a requesting user as soon as possible), as the
more time elapses from
the time of sale of the card, the greater the likelihood that the card may not
work. By way of
further example, with respect to new gift card sellers, gift cards that are
provided by such sellers
can be prioritized (e.g., provided to a requesting user as soon as possible),
in order to provide
such sellers with quicker payment for the cards they provide.
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[0046] It should also be noted that while the much of the foregoing
description has illustrated
various aspects of the described technologies in relation to utilizing mobile
devices in retail
transactions (e.g., in conjunction with a POS terminal), in certain
implementations the referenced
technologies can also be implemented in ecommerce settings (e.g., in
conjunction with a web
browser). For example, via a browser plugin (and/or any other such
application, module, etc.),
upon determining that a user is checking out of an ecommerce site (e.g.,
finalizing/executing an
ecommerce transaction), various aspects of the webpage/' shopping cart' can be
processed/analyzed. In doing so, the final purchase price can be determined
and one or more gift
cards can be provided/presented within the checkout interface. In doing so,
the user can complete
the ecommerce transaction while availing themselves of savings attendant with
paying via gift
cards.
[0047] It should also be noted that while the technologies described herein
are illustrated
primarily with respect to dynamic gift card allocation, the described
technologies can also be
implemented in any number of additional or alternative settings or contexts
and towards any
number of additional objectives.
[0048] Figure 3 illustrates an example of a process 300 to selectively
determine whether to
display balance-access information for stored value cards based on the output
of classifiers that
determine whether the mobile computing device executing the process 300 is
likely in a retail
store. As noted, in some cases, some gift card exchanges may send buyers of
gift cards balance
access information for those gift cards, such as a gift card number and a pin
number. In some
cases, users may attempt to engage in fraudulent transactions by purchasing
gift cards, recording
in their personal records the balance-access information, and then returning
the gift card back to
the exchange, for instance, by selling the gift card back to the exchange or
by only using a
portion of the balance of a gift card that is automatically returned. Such
users, wishing to engage
in fraud, may then use the balance-access information to engage in a
subsequent transaction,
before the subsequent legitimate user of the gift card can use the remaining
balance. For
instance, the user may present online or in person the information in their
personal record of the
balance-access information to spend gift-card value that they surrendered to
the exchange. To
make such endeavors less attractive, some embodiments may selectively display
the balance-
access information in response to determining that the user is likely in a
location at which they
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would have a legitimate reason for accessing such information, for example, at
a point-of-sale
terminal in a retail store that accepts the card.
[0049] In some cases, access may be granted in response to determining that
the user has crossed
a geo-fence associated with a retail store. However, such techniques, while
consistent with some
embodiments, may leave open some relatively easy avenues for exploitation, for
instance, by
accessing the information while in the user's car in the parking lot of the
store. In some cases,
satellite navigation and geolocation services available on mobile devices are
often unreliable and
imprecise for indoor positioning, particularly for determining whether the
user is within a
relatively close distance to point-of-sale terminal, like within 3 to 5
meters, or less. Accordingly,
some embodiments may use signals from a variety of sensors to ascertain, based
on the mobile
computing device's current environment, whether the mobile computing device is
likely being
used in a legitimate transaction, or whether the mobile computing device is
likely being accessed
simply to view and record the balance-access information improperly. Some
embodiments may
engage in this routine in a relatively battery-friendly way, using a
combination of ambient
signals that collectively yield a relatively low false positive and low false
negative rate, thereby
providing a relatively seamless experience for the end-user. Further, some
embodiments may
accommodate a diverse array of types of point-of-sale terminals, including
legacy systems that
are not specifically configured to address these problems.
[0050] In some embodiments, the process 300 may be executed by a mobile
computing device,
such as a tablet computer, wearable computing device, cell phone, or the like,
for instance, a
hand-held mobile computing device having a battery. In some embodiments, the
mobile
computing device may have a suite of sensors, such as a microphone, one or
more cameras, a
light-intensity sensor, a time-of-flight sensor, an inertial measurement unit,
a magnetometer, a
satellite navigation signal receiver, and one or more radios, like a Bluetooth
radio, a near-field
communication radio, a Wi-Fi TM radio, and a cellular radio. Certain
combinations of these
sensors may produce signals that can be relatively reliably classified as
indicating whether a user
is in particular a retail store near a point-of-sale terminal. In some
embodiments, the mobile
computing device may have the features of the computing device described below
with reference
to Figure 4, and in some embodiments, the mobile computing device may
communicate via the
net Internet with the above-described gift card management service, for
instance, in the course of
performing the process 200 of Figure 2.
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[0051] In some embodiments, the process 300 begins with receiving balance-
access information
by which a stored value card balance (also referred to as a gift card, but not
limited to gift cards)
can be spent at a point-of-sale terminal, as indicated by block 302. In some
cases, this
information may be obtained upon (e.g., in response to) a user requesting with
a web browser or
native mobile application a gift card usable at a particular retailer, for
instance, from the above-
described gift card management service of Figure 1.
[0052] In some embodiments, this information may be received via email, text,
or an API
response, like an HTTP request. In some cases, the received balance-access
information is
received in encrypted form, for instance, as an additional layer of encryption
underneath
encryption used to convey the information over the Internet, such as a layer
under SSL or TLS
encryption. For example, the balance-access information may be stored in an
ABS 256 encrypted
blob that is sent over the Internet via a TLS encrypted communication. In some
embodiments,
the balance-access information may be stored in encrypted form, such that a
user interrogating
program state or memory of the mobile computing device is unable to view the
balance-access
information. In some embodiments, the balance-access information is sent as a
string, for
example, a gift card number and a pin number. In some embodiments, the balance-
access
information is sent in the form of an image, such as a barcode image or QR
code image that,
upon being displayed on a display screen of the mobile computing device, can
be scanned by a
scanner at a point-of-sale terminal to enter the gift card information.
[0053] Next, some embodiments may store the received balance-access
information, as indicated
by block 304. As noted above, in some cases, this information may be stored in
encrypted form
on the client mobile computing device, for instance, after decrypting a TLS
encrypted
communication, leaving the encrypted blob in memory, without yet decrypting
the ABS 256
encryption. In some cases, decryption keys may be stored in obfuscated memory
of the mobile
computing device, for instance, distributed among several variables of source
code by which a
native mobile application is written, such that efforts to decompile or
otherwise analyze
compiled source code are less likely to reveal the decryption keys.
[0054] Next, some embodiments may determine whether the user requests to use
the card, as
indicated by block 306. In some cases, a user may request the card before step
302, and it should
be generally noted that the steps described herein are not limited to the
order in which the steps
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are displayed or described. In some embodiments, the user may request to use
the gift card
through multiple steps, for instance, by requesting gift cards for a
particular retailer in a first
request, for example, in a request to a native mobile application or webpage
that secures
responsive balance-access information from the gift card management service,
and then later by
the user selecting an input in a user interface of the webpage or native
mobile application that
indicates the user wishes to display the information for entry to a point-of-
sale terminal. In some
cases, a native mobile application or web page may have an event handler
associated with a
region of a display screen, and that event handler may detect an on-press
event and, in response,
advance the routine to additional steps of process 300, for instance, in a
press-to-display user
interface.
[0055] In some cases, a multi-region press may be requested or required, for
instance, with two
fingers of the user's left hand on one side of the screen and two fingers of
the user's right hand on
the other side of the screen, such that some inferences about the likely
orientation of the screen
relative to the user may be drawn by the native mobile application,
particularly when combined
with readings from an inertial measurement unit, as described below. For
example, in some
cases, the native mobile application may respond to such a multitouch input
upon determining
that the orientation of the screen is vertical, as would be the case when a
user is holding the
screen between their left and right fore fingers and thumbs vertically, with
the screen oriented
away from the user, toward a retail sales clerk viewing the screen to enter
the balance access
information into a point-of-sale terminal. Or, in some cases, a user may
merely engage in input
indicating the user wishes to use the card, and upon the user releasing a
touch, the process may
proceed.
[0056] Upon determining that the user does not yet request to use the card,
some embodiments
may continue to wait, or, upon determining that the user does request use the
card, embodiments
may proceed to the next step.
[0057] Next, some embodiments may sense ambient signals, as indicated by block
308. In some
cases, waiting to sense ambient signals until the user requests to use the
card may reduce battery
drain associated with constantly monitoring such signals, for instance, even
when the user is
nowhere near a retail store or has shown no intent to use a gift card. (Or
some embodiments may
constantly monitor such signals to provide a more responsive experience at the
expense of power
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consumption.) In some cases, sensing ambient signals may be triggered by one
of the two stages
of a request to use the card described above, for instance, in response to a
user requesting gift
cards associated with a given retailer. In some embodiments, sensing of
ambient signals may
have a timeout threshold at which point sensing may cease to protect the
battery of the mobile
computing device, and a user may be presented with an input by which the user
can indicate an
intent to continue attempting to use a gift card.
[0058] A variety of different types of signals may be sensed with a variety of
different types of
sensors on the mobile computing device. In some cases, some of the signals or
sensed without
regard to whether the user request use the gift card, while other signals,
particularly more battery
intensive sensors are engaged responsive to a user request. In some
embodiments, the sensor is a
radio of the mobile computing device, and the signal is a wireless beacon,
such as a Wi-Fi
beacon or a Bluetooth beacon, or an NFC identifier. In some embodiments, a
beacon identifier
encoded in the beacon may be compared against a list of identifiers associated
with retail stores
at which the gift card may be legitimately used, and a wireless environment
score may be
calculated based on the result of this comparison. For instance, a binary
score of one may be
output in response to detecting a match, indicating the user is within range
of a beacon known to
be in a store at which a gift card in memory is usable. In some cases,
different scores may be
calculated for different gift card stored in memory, as different gift cards
may be associated with
different types of retail stores and associated ambient environments.
[0059] In some cases, users may attempt to spoof such beacons, for instance,
by programming
the SSID of their home wireless router to match that broadcast at a store to
trick systems relying
on WiFi TM beacon information, or by configuring Bluetooth TM beacons to
broadcast spoofed
UUIDs. To frustrate such attacks, some embodiments may sense a rolling
encrypted code
broadcast in the beacon and determine whether that rolling encrypted code
matches an expected
current state for a beacon associated with such a retailer. In some cases,
wireless beacons may
broadcast a rolling encrypted code with a linear shift register algorithm, or
with other techniques,
like with a KeeLoq TM code. In some embodiments, matching of codes may be
determined with
one or more remote computing devices, such as via a request to the gift card
management service
described above, which may compare beacon identifiers to an index of beacon
identifiers and
respond with a store identifier or binary signal indicating a match. Or in
some cases, the gift card
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management service or the mobile computing device may send a rolling encrypted
beacon
identifier to a third party server, which may respond with a store identifier.
[0060] In some embodiments, wireless radio signals may generally determine the
geolocation of
the mobile computing device, and classifiers for one or more other types of
signals may be
obtained in response. For example, classifiers for a set of features known to
be associated with a
given retail store may be downloaded and stored in cache memory in response to
the mobile
computing device crossing a geo-fence associated with that store. In another
example, a set of
classifiers may be sent to, and stored by, the mobile computing device in
response to a particular
gift card being sent to the device, for instance, a set of classifiers
corresponding to a particular
retailer at which the sent gift card is usable. As a result, relatively
granular and store specific
classifiers may be configured without storing such classifiers for every store
to which a user may
visit. In some embodiments, the techniques described in U.S. Patent
Application 14/839,058,
titled "REDUCING THE SEARCH SPACE FOR RECOGNITION OF OBJECTS IN AN
IMAGE BASED ON WIRELESS SIGNALS," filed 28 August 2015 may be used to this
effect.
[0061] In another example, the sensed ambient signals may be audio signals
sensed with a
microphone of the mobile computing device. In some cases, the sensed signals
may be time-
series signals, such as an amplitude of audible signals that varies over time.
In some cases,
multiple microphones on the mobile computing device may sense multiple audio
feeds, and those
audio feeds may be used in subsequent steps to determine a directionality of
signals.
[0062] In another example, a light intensity sensor on the mobile computing
device may sense
time varying light intensity in the environment of the mobile computing
device, for instance,
from overhead lighting. In some cases, location signals may be embedded in
these fluctuations in
the intensity of overhead lighting, or in some cases, different types of
lighting may emit useful
signals, like 120 Hz oscillations of fluorescent lights, that provide an
additional signal by which
location may be determined.
[0063] In another example, a camera of the mobile computing device may capture
an image or
sequence of images. In some embodiments, both a front facing and rear facing
camera of the
mobile computing device may capture images, for instance, to ascertain whether
a screen of the
mobile computing device is pointed towards a point-of-sale terminal and that a
rear facing
camera is pointed to a face of the user, thereby demonstrating that the user
is less likely to be
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able to view information on the screen. In some cases, an array of cameras on
one face of the
mobile computing device may capture images, and computational photography
techniques may
be used to ascertain spatial information based upon a light field impending
upon the mobile
computing device. In another example, the mobile computing device may have a
time-of-flight
sensor by which a scan of 3-D surfaces is obtained, for instance, providing in
combination with
an image sensor, both a pixel intensity and pixel distance.
[0064] In another example, the mobile computing device may have a
magnetometer, which may
sense a time varying magnetic field and orientation of the magnetic field,
such as the user moves
through the store, or as may occur due to electromagnetic signals emitted by
the operation of
circuitry in a point-of-sale scanner. Variations in such signals, either in
time or space, may be
classified as indicating presence at a point of sale terminal.
[0065] In some cases, the mobile computing device may include an inertial
measurement unit,
such as a six axis accelerometer operative to sense changes in rotational
velocity at about three
orthogonal axes and the changes in linear translation speed about three
orthogonal axes. In some
cases, the inertial measurement unit may be operative to sense a downward
direction due to
acceleration from gravity. In some cases, the inertial measurement unit may
output a
multidimensional time series, such as a sequence of six dimensional values
indicating sensor
readings at each of six dimensions at each instance the inertial measurement
unit is polled by a
native mobile application.
[0066] Next, some embodiments may classify the ambient signals as indicating
the user is in a
retail establishment by determining a classification score, as indicated by
block 310. In some
cases, the classification score is a weighted combination of a plurality,
e.g., two, three, four, five
or more, sensor-specific classification scores. In some cases, these weights
may be dynamically
adjusted over time, for instance, in response to detected miss classifications
to reduce a
misclassification rate. For example, some embodiments may implement a
stochastic gradient
descent algorithm to reduce an amount of error on a training set of sensor
signals labeled with
values indicating whether the collection of signals correspond to a fraudulent
use or a legitimate
use for instance at a given retail store, such that store-specific sets of
parameters may be
downloaded upon determining that the user has crossed a geo-fence associated
with the store.
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[0067] In some embodiments, audio signals may be classified by calculating an
audio
classification score. In some cases, the audio signal may be normalized, for
instance, by
amplifying or suppressing the signal to reach a target root mean square value
or maximum value
in amplitude. In some embodiments, features may be extracted from the
normalized signal. A
variety of different types of features may be extracted. For instance, some
embodiments may
pass the normalized signal through one or more bandpass filters, and responses
exceeding a
threshold amplitude output from the bandpass filters may be designated as a
feature. In some
cases, the features may be two-dimensional features corresponding to both a
duration and an
indication that an output exceeding the threshold occurred. In some cases,
such a feature may
correspond to a beep sound emitted by a point-of-sale terminal known to be
used by the
merchant, for example, as the sales clerk scans items and the system beeps. In
some cases, the
sound of these beeps may be used as a signal indicative of the presence of a
point-of-sale
terminal. In another example, some embodiments may extract features by
executing a Fourier
analysis on the audio signal and extracting features from portions of the
output that exceed some
threshold duration or amplitude. In another example, some stores may embed
location identifiers
in in-store audio, and some embodiments may extract those identifier from the
audio, for
example, by time or frequency demultiplexing the audio signal. In some cases,
classification
models for the different audio signals may be store specific, and those models
may be
downloaded based on crossing a geo-fence associated with the store or
downloading a card
associated with the store. In another example, certain signals of relatively
constant duration may
be detected with a convolution layer of a neural net that convolve a kernel
over time to classify
whether a trailing duration of the audio signal includes a beep of a point-of-
sale terminal (or
other indicative signal). In some cases, such models may be trained by
sampling audio and
labeling sample audio as indicating a legitimate transaction or a fraudulent
transaction, for
example, based on logged sensor data and subsequent reported fraudulent uses
or legitimate uses.
Similar techniques may be used to capture signals from a magnetometer, for
instance signals
indicating variations in an electromagnetic field arising from operation of a
point-of-sale
terminal or related equipment, for instance, emitted due to circuitry within
an a handheld scanner
or theft detection system of the store. Or in some cases, variations in a
magnetic field (and IMU)
may be integrated to infer a user's geolocation more precisely.
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[0068] In some embodiments, image signals may be classified, for instance,
based on whether
the image contains a point-of-sale terminal. In some embodiments, a training
set of such images
may be captured and manually labeled as including such a point-of-sale
terminal. Some
embodiments may train a neural network based on the labeled training set, for
example, a
convolution neural network having a convolution layer corresponding to the
portion of the image
depicting the point-of-sale terminal. In some cases, a particular part of the
point-of-sale terminal
may be detected, for instance, a hand-held scanner, which often includes a
black screen that is
relatively reliably detected in images or a display of a balance that may be
relatively reliably
detected, both with a relatively bandwidth sensitive classifier model. In some
cases, the
convolution layer may be applied multiple times across an image at different,
overlapping
portions of the image to determine whether output neuron of the convolution
layer fires,
indicating a point-of-sale terminal.
[0069] In some embodiments, multiple images may be captured. For example,
facial features of
the user may be captured in an image taken when setting up an account on a
native mobile
application, and later, using the techniques discussed above. Some embodiments
may determine
whether an image taken with a rear facing camera of the mobile computing
device includes the
user in the frame, while another image taken with another camera facing in the
same direction as
the screen, includes an image of a point-of-sale terminal. In another example,
light signals
emitted by a point-of-sale terminal in a scanning process may be detected,
either with a light
sensor or with a camera. For example, a barcode scanner or QR code scanner may
emit a laser of
a particular frequency (either or both in electromagnetic frequency and
scanning frequency) that
may be detected. In some cases, sensed light intensity may be passed through
serial bandpass
filters, such that light flickering at the scan rate of a barcode scanner, of
a color of a scanner
laser, is passed through the filters, and a resulting averaged image intensity
over a duration of
time including multiple scans may be compared to a threshold to classify the
image sensor output
as indicating the presence of a point-of-sale terminal.
[0070] Similar techniques may be used to classify image and time-of-flight
sensor outputs. For
example, a three-dimensional shape of a portion of a point-of-sale terminal,
like a handheld
scanner, may be detected in time-of-flight data, for instance, again, using a
convolution layer of a
trained neural network to account for translation invariant aspects of the
signal captured by the
mobile computing device.
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[0071] In some embodiments, a multidimensional time series from the inertial
measurement unit
may be classified as indicating a particular gesture has occurred or that the
mobile computing
device is oriented in a particular direction. For instance, to determine
whether the mobile
computing device is oriented in a particular direction, some embodiments may
determine
whether the signal corresponding to a particular axis of the inertial
measurement unit (e.g.,
averaged over some trailing duration of time, like one second) exceeds a
threshold, indicating the
consistent pull of gravity in a particular direction, like when the phone is
oriented vertically right
side up or upside down or horizontally right side up or upside down.
[0072] In some embodiments, a time series of such data may be used to
determine whether a
particular gesture has occurred, for instance, indicating that the user has
rotated and translated
the phone through space in a manner consistent with how a user typically
presents a display
screen to another person entering the information into a point-of-sale
terminal, like when a user
takes a phone facing towards their face, spins the phone 180 about a vertical
axis, translates the
phone downward, spins the phone 180 about a horizontal axis, and then tilts
the phone away
from themselves (spinning about an orthogonal horizontal axis), and holds the
phone static. In
some cases, users may engage in such motions at different speeds, through
different distances
and angular changes over time. Accordingly, some embodiments may classify such
time series as
including a qualifying gesture with a dynamic time warp analysis. For example,
a training set of
users may be asked to engage in the gesture, and a template for a dynamic time
warp algorithm
may be trained, for instance with dynamic programming and tuned constraints,
based on the
sensor data from the training exercise. Later, this template may be compared
against sensor data
obtained when a user request to use a gift card, and the sensor data may be
classified as
indicating a gesture associated with legitimate use.
[0073] Next, some embodiments may determine whether the classification score
exceeds a
threshold, as indicated by block 312. In some cases, this threshold may be
modulated with the
techniques described above by which the weights for combining the various
classification scores
are combined. Upon determining that the score does not exceed the threshold,
some
embodiments may continue to sense ambient signals, returning the step 308, in
some cases until
a timeout determination is made to preserve the battery life of the mobile
computing device.
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[0074] Alternatively, upon determining that the score exceeds a threshold,
some embodiments
may cause the mobile computing device to display the balance-access
information, as indicated
by block 314. In some cases, the balance access information may be decrypted
and displayed on
a display screen of the mobile computing device. In some embodiments, a
barcode may be
formed from string balance-access information, such as a linear barcode or a
QR code, and a
resulting image may be displayed, such that the image may be scanned to enter
the information
into a point-of-sale terminal. Or in some cases, the information may be
displayed in human-
readable form, such that a salesclerk can type the information into a point-of-
sale terminal. Or, in
some cases, the image of the barcode or QR code may be formed on the remote
server, and the
image may be downloaded, though this use is expected to be higher bandwidth
relative to
systems that compose such images on the mobile computing device, as the string
data encoded
therein is often much less data intensive.
[0075] A variety of techniques may be executed to impede users from capturing
the displayed
information. Some embodiments may instruct a mobile computing device to block
the mobile
computing device from performing a screen capture. Some embodiments may
display the
balance-access information for a threshold amount of time that is relatively
short (e.g., less than
five seconds, less than one second, or less than one-half of one second), such
that the information
may be captured by a machine, but is too quickly removed to be reliably
captured by human
being. Some embodiments may flash the information on the screen repeated
times, such that the
scanner has multiple opportunities to capture the information, while a human
would find it
difficult to record the information. Some embodiments may animate movement of
the code on
the screen to bring the code in and out of focus of a user camera attempting
to capture an image
of the code, e.g., exceeding a tracking rate of typical autofocus mechanisms
in consumer
cameras, while staying within a tracking rate that can be accommodated by
point of sale
scanners. Some embodiments may compose a plurality of scannable codes, like
barcodes, some
of which are internally inconsistent and invalid (e.g., dummy codes), and one
of which contains
the balance-access information in an internally consistent scannable code. In
some cases, formats
for some scannable codes include redundancy for purposes of error detection
and correction, like
parity bits. Some embodiments may flash a sequence of scannable codes in which
all but one of
the scannable codes in the sequence, for example, a randomized one in the
sequence, contain
invalid codes in which the error detection and correction rules are violated,
for instance, with an
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incorrect parity bit. As a result, it is expected that a point-of-sale
terminal scanning the flashing
codes will reject all but the legitimate code, while a user attempting to
write down the codes will
not know which one is legitimate without a much more laborious effort. In some
cases, an entire
screen may be varied in intensity in synchronicity with a scanning rate of a
barcode scanner,
such that the lightness or darkness of the screen varies according to what a
barcode scanner
would sense while transiting across a barcode, thereby conveying a signal to
the barcode scanner
that matches what would be perceived by a static one or two dimensional
barcode without
presenting a static image that a user can readily visually parse.
[0076] Thus, with various combinations of the above techniques, users may be
deterred from
engaging in fraud.
[0077] In some embodiments, the gift card management system of Figure 1 may
execute various
routines to further reduce the likelihood of fraud. For instance, some
embodiments may infer
register balances and select gift cards to match the inferred balance to
expedite gift card
exhaustion. For instance, some embodiments may estimate a register balance
based on a
distribution of previous know balances for a given retailer and for users
deemed to have a profile
similar to that of the user requesting cards. Some embodiments may then obtain
a set of
candidate cards and select among the candidate cards based on 1) a current
balance of the
candidate card; 2) a risk score determined for each candidate card (e.g.,
based on an amount of
users who have had access to the card and whether those users have a
relatively long history of
non-fraudulent card use recorded in the system). Some embodiments may select
the card closest
to the inferred register balance having a risk score above a threshold. Some
embodiments may
calculate a weighted combination of the risk score and an inverse of the
difference between the
inferred register balance (or an actual balance) and the card balance. Some
embodiments may
rank the cards based on this weighted combined score and select a highest
scoring card. Some
embodiments may select a riskiest card having a balance expected to be
exhausted by the
inferred register balance.
[0078] Similarly, some embodiments may suppress the number of cards a user
accesses in a
transaction. For instance, a user may combine two or three or more gift card
balances to pay a
register balance. The more cards consumed and not exhausted, the greater the
risk of fraud.
Accordingly, some embodiments may rate limit a number of cards a user is
allowed to access or
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rate limit an aggregate balance of cards a user can access. Similarly, some
embodiments may
select among candidate cards to reduce the number provided to a given users,
e.g., by favoring
cards close to the inferred (or actual) register balance.
[0079] Further, some embodiments may distribute cards geographically to
enhance the power of
the purchase location to signal fraud. In some cases, a card may be sent to a
first geographic area
and returned with a balance. Later, a user in a different geographic area
(e.g., more than a
threshold distance, or having less than a threshold co-occurrence rate among
users between the
two locations) may request a card for the same retailer. The card for the
later user may be
selected in response to determining that this geographic threshold is
satisfied. A different later
user in the first geographic location may not be provided the card upon
determining that the
geographic locations are the same. Later, if fraud occurs, the location of the
fraud is expected to
be indicative of which user holding a given card engaged in fraud, as it is
expected to be less
likely that a user will travel to a relatively distant geographic location to
spend a card they
previously surrendered, rather than attempt to use the same card in their same
area.
[0080] Figure 5 is a diagram that illustrates an exemplary computing system
1000 in accordance
with embodiments of the present technique. Various portions of systems and
methods described
herein, may include or be executed on one or more computer systems similar to
computing
system 1000. Further, processes and modules described herein may be executed
by one or more
processing systems similar to that of computing system 1000.
[0081] Computing system 1000 may include one or more processors (e.g.,
processors 1010a-
1010n) coupled to system memory 1020, an input/output I/0 device interface
1030, and a
network interface 1040 via an input/output (I/0) interface 1050. A processor
may include a
single processor or a plurality of processors (e.g., distributed processors).
A processor may be
any suitable processor capable of executing or otherwise performing
instructions. A processor
may include a central processing unit (CPU) that carries out program
instructions to perform the
arithmetical, logical, and input/output operations of computing system 1000. A
processor may
execute code (e.g., processor firmware, a protocol stack, a database
management system, an
operating system, or a combination thereof) that creates an execution
environment for program
instructions. A processor may include a programmable processor. A processor
may include
general or special purpose microprocessors. A processor may receive
instructions and data from
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a memory (e.g., system memory 1020). Computing system 1000 may be a uni-
processor system
including one processor (e.g., processor 1010a), or a multi-processor system
including any
number of suitable processors (e.g., 1010a-1010n). Multiple processors may be
employed to
provide for parallel or sequential execution of one or more portions of the
techniques described
herein. Processes, such as logic flows, described herein may be performed by
one or more
programmable processors executing one or more computer programs to perform
functions by
operating on input data and generating corresponding output. Processes
described herein may be
performed by, and apparatus can also be implemented as, special purpose logic
circuitry, e.g., an
FPGA (field programmable gate array) or an ASIC (application specific
integrated circuit).
Computing system 1000 may include a plurality of computing devices (e.g.,
distributed computer
systems) to implement various processing functions.
[0082] I/0 device interface 1030 may provide an interface for connection of
one or more I/0
devices 1060 to computer system 1000. I/0 devices may include devices that
receive input (e.g.,
from a user) or output information (e.g., to a user). I/0 devices 1060 may
include, for example,
graphical user interface presented on displays (e.g., a cathode ray tube (CRT)
or liquid crystal
display (LCD) monitor), pointing devices (e.g., a computer mouse or
trackball), keyboards,
keypads, touchpads, scanning devices, voice recognition devices, gesture
recognition devices,
printers, audio speakers, microphones, cameras, or the like. I/0 devices 1060
may be connected
to computer system 1000 through a wired or wireless connection. I/0 devices
1060 may be
connected to computer system 1000 from a remote location. I/0 devices 1060
located on remote
computer system, for example, may be connected to computer system 1000 via a
network and
network interface 1040.
[0083] Network interface 1040 may include a network adapter that provides for
connection of
computer system 1000 to a network. Network interface may 1040 may facilitate
data exchange
between computer system 1000 and other devices connected to the network.
Network interface
1040 may support wired or wireless communication. The network may include an
electronic
communication network, such as the Internet, a local area network (LAN), a
wide area network
(WAN), a cellular communications network, or the like.
[0084] System memory 1020 may be configured to store program instructions 1100
or data
1110. Program instructions 1100 may be executable by a processor (e.g., one or
more of
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processors 1010a-1010n) to implement one or more embodiments of the present
techniques.
Instructions 1100 may include modules of computer program instructions for
implementing one
or more techniques described herein with regard to various processing modules.
Program
instructions may include a computer program (which in certain forms is known
as a program,
software, software application, script, or code). A computer program may be
written in a
programming language, including compiled or interpreted languages, or
declarative or
procedural languages. A computer program may include a unit suitable for use
in a computing
environment, including as a stand-alone program, a module, a component, or a
subroutine. A
computer program may or may not correspond to a file in a file system. A
program may be
stored in a portion of a file that holds other programs or data (e.g., one or
more scripts stored in a
markup language document), in a single file dedicated to the program in
question, or in multiple
coordinated files (e.g., files that store one or more modules, sub programs,
or portions of code).
A computer program may be deployed to be executed on one or more computer
processors
located locally at one site or distributed across multiple remote sites and
interconnected by a
communication network.
[0085] System memory 1020 may include a tangible program carrier having
program
instructions stored thereon. A tangible program carrier may include a non-
transitory computer
readable storage medium. A non-transitory computer readable storage medium may
include a
machine readable storage device, a machine readable storage substrate, a
memory device, or any
combination thereof Non-transitory computer readable storage medium may
include non-
volatile memory (e.g., flash memory, ROM, PROM, EPROM, EEPROM memory),
volatile
memory (e.g., random access memory (RAM), static random access memory (SRAM),
synchronous dynamic RAM (SDRAM)), bulk storage memory (e.g., CD-ROM and/or DVD-
ROM, hard-drives), or the like. System memory 1020 may include a non-
transitory computer
readable storage medium that may have program instructions stored thereon that
are executable
by a computer processor (e.g., one or more of processors 1010a-1010n) to cause
the subject
matter and the functional operations described herein. A memory (e.g., system
memory 1020)
may include a single memory device and/or a plurality of memory devices (e.g.,
distributed
memory devices). Instructions or other program code to provide the
functionality described
herein may be stored on a tangible, non-transitory computer readable media. In
some cases, the
entire set of instructions may be stored concurrently on the media, or in some
cases, different
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parts of the instructions may be stored on the same media at different times,
e.g., a copy may be
created by writing program code to a first-in-first-out buffer in a network
interface, where some
of the instructions are pushed out of the buffer before other portions of the
instructions are
written to the buffer, with all of the instructions residing in memory on the
buffer, just not all at
the same time.
[0086] 1/0 interface 1050 may be configured to coordinate I/0 traffic between
processors 1010a-
1010n, system memory 1020, network interface 1040, I/0 devices 1060, and/or
other peripheral
devices. I/0 interface 1050 may perform protocol, timing, or other data
transformations to
convert data signals from one component (e.g., system memory 1020) into a
format suitable for
use by another component (e.g., processors 1010a-1010n). I/0 interface 1050
may include
support for devices attached through various types of peripheral buses, such
as a variant of the
Peripheral Component Interconnect (PCI) bus standard or the Universal Serial
Bus (USB)
standard.
[0087] Embodiments of the techniques described herein may be implemented using
a single
instance of computer system 1000 or multiple computer systems 1000 configured
to host
different portions or instances of embodiments. Multiple computer systems 1000
may provide
for parallel or sequential processing/execution of one or more portions of the
techniques
described herein.
[0088] Those skilled in the art will appreciate that computer system 1000 is
merely illustrative
and is not intended to limit the scope of the techniques described herein.
Computer system 1000
may include any combination of devices or software that may perform or
otherwise provide for
the performance of the techniques described herein. For example, computer
system 1000 may
include or be a combination of a cloud-computing system, a data center, a
server rack, a server, a
virtual server, a desktop computer, a laptop computer, a tablet computer, a
server device, a client
device, a mobile telephone, a personal digital assistant (PDA), a mobile audio
or video player, a
game console, a vehicle-mounted computer, or a Global Positioning System
(GPS), or the like.
Computer system 1000 may also be connected to other devices that are not
illustrated, or may
operate as a stand-alone system. In addition, the functionality provided by
the illustrated
components may in some embodiments be combined in fewer components or
distributed in
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additional components. Similarly, in some embodiments, the functionality of
some of the
illustrated components may not be provided or other additional functionality
may be available.
[0089] Those skilled in the art will also appreciate that while various items
are illustrated as
being stored in memory or on storage while being used, these items or portions
of them may be
transferred between memory and other storage devices for purposes of memory
management and
data integrity. Alternatively, in other embodiments some or all of the
software components may
execute in memory on another device and communicate with the illustrated
computer system via
inter-computer communication. Some or all of the system components or data
structures may
also be stored (e.g., as instructions or structured data) on a computer-
accessible medium or a
portable article to be read by an appropriate drive, various examples of which
are described
above. In some embodiments, instructions stored on a computer-accessible
medium separate
from computer system 1000 may be transmitted to computer system 1000 via
transmission media
or signals such as electrical, electromagnetic, or digital signals, conveyed
via a communication
medium such as a network or a wireless link. Various embodiments may further
include
receiving, sending, or storing instructions or data implemented in accordance
with the foregoing
description upon a computer-accessible medium. Accordingly, the present
invention may be
practiced with other computer system configurations.
[0090] In block diagrams, illustrated components are depicted as discrete
functional blocks, but
embodiments are not limited to systems in which the functionality described
herein is organized
as illustrated. The functionality provided by each of the components may be
provided by
software or hardware modules that are differently organized than is presently
depicted, for
example such software or hardware may be intermingled, conjoined, replicated,
broken up,
distributed (e.g. within a data center or geographically), or otherwise
differently organized. The
functionality described herein may be provided by one or more processors of
one or more
computers executing code stored on a tangible, non-transitory, machine
readable medium. In
some cases, third party content delivery networks may host some or all of the
information
conveyed over networks, in which case, to the extent information (e.g.,
content) is said to be
supplied or otherwise provided, the information may provided by sending
instructions to retrieve
that information from a content delivery network.
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[0091] The reader should appreciate that the present application describes
several inventions.
Rather than separating those inventions into multiple isolated patent
applications, applicants have
grouped these inventions into a single document because their related subject
matter lends itself
to economies in the application process. But the distinct advantages and
aspects of such
inventions should not be conflated. In some cases, embodiments address all of
the deficiencies
noted herein, but it should be understood that the inventions are
independently useful, and some
embodiments address only a subset of such problems or offer other, unmentioned
benefits that
will be apparent to those of skill in the art reviewing the present
disclosure. Due to costs
constraints, some inventions disclosed herein may not be presently claimed and
may be claimed
in later filings, such as continuation applications or by amending the present
claims. Similarly,
due to space constraints, neither the Abstract nor the Summary of the
Invention sections of the
present document should be taken as containing a comprehensive listing of all
such inventions or
all aspects of such inventions.
[0092] It should be understood that the description and the drawings are not
intended to limit the
invention to the particular form disclosed, but to the contrary, the intention
is to cover all
modifications, equivalents, and alternatives falling within the spirit and
scope of the present
invention as defined by the appended claims. Further modifications and
alternative embodiments
of various aspects of the invention will be apparent to those skilled in the
art in view of this
description. Accordingly, this description and the drawings are to be
construed as illustrative
only and are for the purpose of teaching those skilled in the art the general
manner of carrying
out the invention. It is to be understood that the forms of the invention
shown and described
herein are to be taken as examples of embodiments. Elements and materials may
be substituted
for those illustrated and described herein, parts and processes may be
reversed or omitted, and
certain features of the invention may be utilized independently, all as would
be apparent to one
skilled in the art after having the benefit of this description of the
invention. Changes may be
made in the elements described herein without departing from the spirit and
scope of the
invention as described in the following claims. Headings used herein are for
organizational
purposes only and are not meant to be used to limit the scope of the
description.
[0093] As used throughout this application, the word "may" is used in a
permissive sense (i.e.,
meaning having the potential to), rather than the mandatory sense (i.e.,
meaning must). The
words "include", "including", and "includes" and the like mean including, but
not limited to. As
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used throughout this application, the singular forms "a," "an," and "the"
include plural referents
unless the content explicitly indicates otherwise. Thus, for example,
reference to "an element" or
"a element" includes a combination of two or more elements, notwithstanding
use of other terms
and phrases for one or more elements, such as "one or more." The term "or" is,
unless indicated
otherwise, non-exclusive, i.e., encompassing both "and" and "or." Terms
describing conditional
relationships, e.g., "in response to X, Y," "upon X, Y,", "if X, Y," "when X,
Y," and the like,
encompass causal relationships in which the antecedent is a necessary causal
condition, the
antecedent is a sufficient causal condition, or the antecedent is a
contributory causal condition of
the consequent, e.g., "state X occurs upon condition Y obtaining" is generic
to "X occurs solely
upon Y" and "X occurs upon Y and Z." Such conditional relationships are not
limited to
consequences that instantly follow the antecedent obtaining, as some
consequences may be
delayed, and in conditional statements, antecedents are connected to their
consequents, e.g., the
antecedent is relevant to the likelihood of the consequent occurring.
Statements in which a
plurality of attributes or functions are mapped to a plurality of objects
(e.g., one or more
processors performing steps A, B, C, and D) encompasses both all such
attributes or functions
being mapped to all such objects and subsets of the attributes or functions
being mapped to
subsets of the attributes or functions (e.g., both all processors each
performing steps A-D, and a
case in which processor 1 performs step A, processor 2 performs step B and
part of step C, and
processor 3 performs part of step C and step D), unless otherwise indicated.
Further, unless
otherwise indicated, statements that one value or action is "based on" another
condition or value
encompass both instances in which the condition or value is the sole factor
and instances in
which the condition or value is one factor among a plurality of factors.
Unless otherwise
indicated, statements that "each" instance of some collection have some
property should not be
read to exclude cases where some otherwise identical or similar members of a
larger collection
do not have the property, i.e., each does not necessarily mean each and every.
Limitations as to
sequence of recited steps should not be read into the claims unless explicitly
specified, e.g., with
explicit language like "after performing X, performing Y," in contrast to
statements that might be
improperly argued to imply sequence limitations, like "performing X on items,
performing Y on
the X'ed items," used for purposes of making claims more readable rather than
specifying
sequence. Unless specifically stated otherwise, as apparent from the
discussion, it is appreciated
that throughout this specification discussions utilizing terms such as
"processing," "computing,"
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"calculating," "determining" or the like refer to actions or processes of a
specific apparatus, such
as a special purpose computer or a similar special purpose electronic
processing/computing
device.
[0094] In this patent, certain U.S. patents, U.S. patent applications, or
other materials (e.g.,
articles) have been incorporated by reference. The text of such U.S. patents,
U.S. patent
applications, and other materials is, however, only incorporated by reference
to the extent that no
conflict exists between such material and the statements and drawings set
forth herein. In the
event of such conflict, the text of the present document governs.
[0095] The present techniques will be better understood with reference to the
following
enumerated embodiments:
1. A tangible, non-transitory machine-readable media storing instructions to
classify ambient
signals to reduce fraudulent use of stored value card information, wherein the
instructions, when
executed by one or more processors of a mobile computing device effectuate
operations
comprising; receiving, with the mobile computing device, from a remote server,
balance-access
information by which a stored value card balance can be spent at a point of
sale terminal; storing,
with the mobile computing device, the balance-access information; sensing,
with one or more
sensors of a mobile computing device, ambient signals; classifying the ambient
signals as
indicating the user is in a retail establishment; and in response to the
classification, displaying,
on a display screen of the mobile computing device, the balance-access
information, such that
the balance-access information can be input to a point-of-sale terminal.
2. The media of embodiment 1, wherein: sensing ambient signals comprises:
sensing audio;
sensing an image; sensing an orientation; and sensing a wireless beacon; and
classifying the
ambient signals as indicating the user is in a retail establishment comprises:
calculating a score
based on a weighted combination of a classification of the sensed audio, a
classification of the
image, a classification of the orientation, and a classification of the
wireless beacon; and
determining that the score satisfies a threshold.
3. The media of any of embodiments 1-2, comprising: determining a geolocation
of the mobile
computing device; requesting from a remote server parameters of an ambient
signal classifier
pertinent to the geolocation; receiving the parameters; and wherein
classifying the ambient
signals comprises classifying the ambient signals based on the parameters.
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4. The media of embodiment 3, wherein determining a geolocation of the mobile
computing
device comprises: receiving an encrypted rolling code emitted by a wireless
beacon; and
validating that the encrypted rolling code corresponds to wireless beacon of a
retailer.
5. The media of any of embodiments 1-4, wherein sensing ambient signals
comprises sensing
audio with a microphone of the mobile computing device.
6. The media of embodiment 5, wherein classifying the ambient signals
comprises: normalizing
the audio; extracting a feature vector from the normalized audio; and scoring
the feature vector
with a value indicating a likelihood of whether the user is in a retail
establishment.
7. The media of any of embodiments 5-6, wherein classifying the ambient
signals comprises:
extracting a feature by passing a representation of the audio through a band-
pass filter.
8. The media of any of embodiments 5-7, wherein classifying the ambient
signals comprises:
extracting a feature by determining a Fourier transform of a representation of
the audio.
9. The media of any of embodiments 5-9, wherein the features comprise: an
audio signal within
a range of frequencies; and duration of the audio signals within the range of
frequencies.
10. The media of embodiment 9, wherein the range of frequencies is selected
from among a
plurality of ranges of frequencies based on a geolocation sensed by the mobile
computing device.
11. The media of any of embodiments 1-10, wherein sensing ambient signals
comprises
receiving a reading from an inertial measurement unit (IMU) of the mobile
computing device.
12. The media of embodiment 11, wherein classifying the ambient signals
comprises:
determining an orientation of the mobile computing device with respect to
gravity.
13. The media of any of embodiments 11-12, wherein classifying the ambient
signals comprises:
classifying a multi-dimensional time series of readings from the IMU as
indicating a gesture.
14. The media of embodiment 13, wherein classifying a multi-dimensional time
series of
readings from the IMU as indicating a gesture comprises dynamic time warping
the multi-
dimensional time series.
15. The media of any of embodiments 1-14, wherein sensing, with one or more
sensors of a
mobile computing device, ambient signals comprises: sensing an image with a
camera of the
mobile computing device.
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16. The media of embodiment 15, wherein classifying the ambient signals
comprises:
classifying the image as containing at least part of a point-of-sale terminal.
17. The media of any of embodiments 15-16, wherein classifying the ambient
signals comprises:
classifying the image as containing at least part of a point-of-sale terminal
by detecting
translation invariant features in the image corresponding to the point-of-sale
terminal with a
convolution layer of a neural network.
18. The media of any of embodiments 15-17, wherein classifying the ambient
signals comprises:
classifying two images from two cameras of the mobile computing device by
determining that
one image from a camera facing in a direction opposite the display screen
contains the user's
face, such that the display screen is oriented away from the user.
19. The media of any of embodiments 1-18, wherein classifying the ambient
signals comprises
performing steps for classifying the ambient signals.
20. The media of any of embodiments 1-19, wherein displaying, on a display
screen of the
mobile computing device, the balance-access information comprises: receiving
an input from a
touchscreen of the mobile computing device indicating a user input; in
response to the user input,
displaying the balance-access information; determining that the user input has
ceased and, in
response, ceasing to display the balance access information.
21. The media of any of embodiments 1-20, the instructions comprising:
determining a
geolocation of the mobile computing device; presenting at the mobile computing
device and
based on the geolocation, a first gift card; determining that the first gift
card has been utilized in
a transaction; and based on a determination that the first gift card has been
utilized in the
transaction, providing a second gift card at the mobile computing device.
22. A method, comprising: the operations of any of embodiments 1-21.
23. A system, comprising: one or more processors; and memory storing
instructions that
when executed by the processors cause the processors to effectuate operations
comprising: the
operations of any of embodiments 1-21.
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