The consumer can use the credit card 10 for purchasing a good or service from the merchant. That is, the consumer uses the credit card 10 to provide first data (i.e. payment credentials) for a transaction.
A typical transaction flow involving the system 50 can be described using steps S1-S8. At step S1, the consumer swipes the credit card 10 at the access device 11 to provide payment credentials for a transaction. At step S2, the access device 11 forwards the payment credentials to the merchant computer 12. At step S3, the merchant computer 12 sends an authorization request message including the payment credentials to the acquirer computer 13. At step S4, the acquirer computer 13 forwards the message to the payment processing network computer 14, and at step S5, the payment processing network computer 14 forwards the message to the issuer computer 15. At step S6, the issuer computer 15 authorizes the transaction and sends an authorization response message to the payment processing network computer 14. At step S7, the payment processor computer 14 stores a record of the transaction and forwards the authorization response message to the acquirer computer 13. At step S8, the acquirer computer 13 forwards the message to the merchant computer 12. The merchant then releases the purchased goods and services to the consumer, who then leaves the merchant's store. At a later time, a clearing and settlement process can occur.
Data such as data relating to fraudulent transactions conducted using fraudulent account numbers can be provided to the merchant operating the merchant computer 12. This may be in the form of chargebacks, or fraud reports. However, one problem with this conventional process is that the merchant receives this data after transactions are completed. If the merchant receives this data after the transaction is completed it is of little use. Another problem is the number of communications that may need to occur before the merchant can receive the data. For example, the merchant may need to request the data, and then the payment processing network may then need to provide the data to the merchant. These steps are in addition to the steps needed to perform the payment transaction.
Embodiments of the invention address these and other problems, individually and collectively.
One embodiment of the invention is directed to a method. The method comprises receiving, by a data processor in a first party mobile device, first data from a first data source, where the first data is beneficial for the first party. The method also comprises obtaining, by the data processor in the first party mobile device, second data from a second data source, where the second data is beneficial to the second party, and then generating, by the data processor in the first party mobile device, a single data element encoding the first data and the second data. Further, the method comprises providing, by the data processor in the first party mobile device, the single data element to a second party device. The second party device then decodes the single data element into the first data and the second data. The second party device is configured to process the first data separately from the second data.
Another embodiment of the invention is directed to a first party device configured to perform the above-described method.
Another embodiment of the invention is directed to a method comprising receiving, by a data processor in a second party device, a single data element from a first party mobile device. The single data element includes first data from a first data source and second data from a second data source, where the first data is beneficial for the first party and the second data is beneficial to the second party. The method also includes decoding, by the data processor in the second party device, the single data element into the first data and the second data, and processing, by the data processor in the second party device, the first data. The method further includes processing, by the data processor in the second party device, the second data separately from the first data.
Another embodiment of the invention is directed to a second party device configured to perform the above-described method.
Further details regarding embodiments of the invention can be found in the Detailed Description and the Figures.
Embodiments of the present invention are directed to providing second data (i.e. merchant-benefitting data) to a merchant at the initiation of a transaction. A consumer's mobile device requests and receives second data from a payment processing network before initiating a transaction. The mobile device also obtains first data (e.g., a payment token) from digital wallet provider. The mobile device creates a QR code containing both the first data and second data, and then initiates a transaction by providing the QR code to a merchant access device. The merchant separates the first data and second data, uses the first data to process the transaction, and benefits from the second data.
In embodiments of the invention, a payment processing network can generate several types of information that can be benefit a merchant. Instead of being limited to the merchant's own perspective, the merchant may be able to share in the payment processing network's more complete perspective of consumer activity. Thus, the merchant can use the data to gain a broader and more accurate understanding of consumer behavioral trends, and the merchant can then make better-informed business and marketing decisions.
The merchant can use the second data for a number of beneficial applications. For example, the second data may be a consumer loyalty score, and the merchant can provide a promotional offer to the consumer based on the loyalty score, thus improving the merchant's marketing practices. Because up-to-date second data is obtained by the mobile device just before the transaction, and because the up-to-date second data is provided to the merchant at the beginning of the transaction, the merchant is able to utilize accurate second data within the transaction timeframe.
Prior to discussing specific embodiments of the invention, some terms may be described in detail.
An “interaction” may include a communication, contact, or exchange between parties, devices, and/or entities. In some embodiments, data can be exchanged in an interaction between two devices (e.g., an interaction between a mobile device and an access device).
A “first party” may be a participant involved with another party. An example of a first party may be a consumer. The consumer may interact with another party, such as a merchant. The first party may operate a first party device such as a mobile phone.
A “second party” may include a participant involved with another party. An example of a second party is a merchant. The merchant may interact with another party, such as a consumer. The second party may operate a second party device such as an access device or a merchant computer.
“First data” may include any suitable information. In some embodiments, first data may be selected primarily based on the interests of the first party. An example of first data is a set of payment credentials provided by a consumer to a merchant for a transaction. Payment credentials are beneficial to a consumer because they allow the consumer to purchase a good or service. Another example of first data is authentication data that confirms the identity of the consumer (e.g., for a transaction or for gaining access to a restricted area). Another example of first data is VAS (Value Added Services) data. VAS data, such as a promotional offer or a loyalty identifier, is beneficial to a consumer because it can enable discounts or other additional services for the consumer.
“Second data” may include any suitable information. In some embodiments, second data may be selected primarily based on the interests of the second party. An example of second data is information that is specifically beneficial for a merchant. Second data may be generated by an entity such as a payment processing network, issuer, acquirer, social network, etc. In some embodiments, it may be provided to a merchant, for the merchant's benefit, via a consumer's mobile device. A payment processing network may have a broader perspective of consumer spending activity than a merchant, as the payment processing network can track consumer spending across multiple merchants, while a single merchant can typically only track consumer spending that takes place at that merchant. Accordingly, a merchant can gain greater perspective of consumer activity when provided with second data, and the merchant can utilize the second data in different ways. For example, the payment processing network can determine a loyalty score for the consumer at the merchant, and the merchant can provide promotional offers to the consumer based on the loyalty score.
Other types of second data that can be beneficial to a merchant include fraud risk information, consumer-habit information, real-time spending trends for a group of consumers, and information about consumer spending at competing merchants. Additionally, second data can include various forms of social media and social network data, such as a consumer's interests and travel plans as indicated on a social networking page. One of ordinary skill in the art would recognize that there are many other types of information that a payment processing network can determine, which a merchant could beneficially use. One of ordinary skill in the art would also recognize that a merchant could utilize different types of second data for various applications, such as marketing strategies, inventory adjustments, and a number of other beneficial activities.
A “first data source” may be an entity that provides first data. An example of a first data source is a digital wallet provider, a payment processing network, an issuer computer, a cloud storage system, a tokenization server or token vault, a mobile phone, etc.
A “second data source” may be an entity that provides second data. An example of a second data source may be a digital wallet provider, a payment processing network, a merchant system a third party system, a manufacturer's system, an issuer computer, etc. Any of these computers and systems may provide second data that can benefit the second party.
A “data element” may include a single packet of data. For example, a data element can include the first data and the second data. An example of a data element is a QR (quick response) code. Other examples of a data element include an NFC message, a programmed magnetic stripe, and any other suitable form of packaged data. A data element is typically transmitted in a single data transmission from a transmitter to a receiver.
A “value credential” may be evidence of worth. Examples of a value credential include payment credentials, promotional offers, etc.
An “affinity score” may be a value or assessment of one party's attraction or level of disengagement to another party. Examples of affinity scores include loyalty scores and attrition scores.
A “loyalty score” may be a value or assessment of one party's affinity to another party. In some embodiments, a higher loyalty score can indicate a higher level of loyalty. A higher level of loyalty can mean that there is a high probability that the first party will continue to interact with the second party in the future. A number of factors can be considered when determining a loyalty score. In one example, a consumer may considered loyal to a certain merchant or merchant category if the consumer regularly visits the merchant with a certain frequency, if the consumer spends a certain amount of money at the merchant, if the consumer spends more at the merchant than at a competitor, or the consumer displays any other suitable loyalty characteristic.
A loyalty score is typically calculated based on historical transaction data. In some embodiments, a merchant can determine a loyalty score for a consumer. In other embodiments, a payment processing network can determine a loyalty score and has access to a larger set of transaction data associated with the consumer, as the data typically includes transactions conducted at multiple different merchants. Accordingly, a loyalty score calculated at a payment processing network may be more accurate and informative, as it can be based on a more global perspective of consumer transactions. A payment processing network may be able to determine a loyalty score that represents a consumer's loyalty to a certain merchant or a certain merchant category.
An “attrition score” may be a value associated with a party's likelihood of disengagement with another party. For example, a high attrition score can indicate that there is a high probability that a consumer will discontinue shopping at a certain merchant. Similar to calculating a loyalty score, an attrition score can be calculated based on a consumer's historical transaction data by identifying behavioral trends and other indicators.
“Payment credentials” may include any suitable information associated with an account (e.g. a payment account and/or payment device associated with the account). Such information may be directly related to the account or may be derived from information related to the account. Examples of account information may include a PAN (primary account number or “account number”), user name, expiration date, CVV (card verification value), dCVV (dynamic card verification value), CVV2 (card verification value 2), CVC3 card verification values, etc. CVV2 is generally understood to be a static verification value associated with a payment device. CVV2 values are generally visible to a user (e.g., a consumer), whereas CVV and dCVV values are typically embedded in memory or authorization request messages and are not readily known to the user (although they are known to the issuer and payment processors). Payment credentials may be any information that identifies or is associated with a payment account. Payment credentials may be provided in order to make a payment from a payment account. Payment credentials can also include a payment token, a user name, an expiration date, a gift card number or code, and any other suitable information.
A “payment token” may include an identifier for a payment account that is a substitute for an account identifier, such as a primary account number (PAN). For example, a token may include a series of alphanumeric characters that may be used as a substitute for an original account identifier. For example, a token “4900 0000 0000 0001” may be used in place of a PAN “4147 0900 0000 1234.” In some embodiments, a token may be “format preserving” and may have a numeric format that conforms to the account identifiers used in existing payment processing networks (e.g., ISO 8583 financial transaction message format). In some embodiments, a token may be used in place of a PAN to initiate, authorize, settle or resolve a payment transaction or represent the original credential in other systems where the original credential would typically be provided. In some embodiments, a token value may be generated such that the recovery of the original PAN or other account identifier from the token value may not be computationally derived. Further, in some embodiments, the token format may be configured to allow the entity receiving the token to identify it as a token and recognize the entity that issued the token.
A “token service system” can include a system that services payment tokens. In some embodiments, a token service system can facilitate requesting, determining (e.g., generating) and/or issuing tokens, as well as maintaining an established mapping of tokens to primary account numbers (PANs) in a repository (e.g. token vault). In some embodiments, the token service system may establish a token assurance level for a given token to indicate the confidence level of the token to PAN binding. The token service system may support token processing of payment transactions submitted using tokens by de-tokenizing the token to obtain the actual PAN. In some embodiments, a token service system may include a token service computer alone, or in combination with other computers such as a payment processing network computer.
“Value added services data” (or “VAS data”) can include data associated with a value added service. VAS data may be in any suitable form, and may include any suitable type of data. It may include strings of characters, image files, videos, etc. Each piece of value added data may have a tag value associated with it. The tag may be defined by the entity (e.g., a payment processing network) that originates or processes the value added services data. Table 1 below provides examples of value added services data.
A “mobile device” may comprise any electronic device that may be transported and operated by a user, which may also provide remote communication capabilities to a network. Examples of remote communication capabilities include using a mobile phone (wireless) network, wireless data network (e.g. 3G, 4G or similar networks), Wi-Fi, Wi-Max, or any other communication medium that may provide access to a network such as the Internet or a private network. Examples of mobile devices include mobile phones (e.g. cellular phones), PDAs, tablet computers, net books, laptop computers, personal music players, hand-held specialized readers, etc. Further examples of mobile devices include wearable devices, such as smart watches, fitness bands, ankle bracelets, rings, earrings, etc. A mobile device may comprise any suitable hardware and software for performing such functions, and may also include multiple devices or components (e.g. when a device has remote access to a network by tethering to another device—i.e. using the other device as a modem—both devices taken together may be considered a single mobile device). A mobile device may also comprise a verification token in the form of, for instance, a secured hardware or software component within the mobile device and/or one or more external components that may be coupled to the mobile device.
A mobile device may also include any suitable device that may be used to conduct a financial transaction, such as to provide payment information to a merchant. Such a mobile device may be in any suitable form. For example, suitable mobile devices can be hand-held and compact so that they can fit into a consumer's wallet and/or pocket (e.g., pocket-sized). They may include smart cards, magnetic stripe cards, keychain devices (such as the Speedpass™ commercially available from Exxon-Mobil Corp.), etc. Other examples of mobile devices include pagers, payment cards, security cards, access cards, smart media, transponders, and the like. If the mobile device is in the form of a debit, credit, or smartcard, the mobile device may also optionally have features such as magnetic stripes. Such devices can operate in either a contact or contactless mode.
“Short range communication” or “short range wireless communication” may comprise any method of providing short-range contact or contactless communications capability, such as RFID, Bluetooth™, infra-red, or other data transfer capability that can be used to exchange data between a mobile device and an access device. In some embodiments, short range communications may be in conformance with a standardized protocol or data transfer mechanism (e.g., ISO 14443/NFC). Short range communication typically comprises communications at a range of less than 2 meters. In some embodiments, it may be preferable to limit the range of short range communications (e.g., to a range of less than 1 meter, less than 10 centimeters, or less than 2.54 centimeters) for security, technical, and/or practical considerations.
An “application” may be computer code or other data stored on a computer readable medium (e.g. memory element or secure element) that may be executable by a processor to complete a task.
A “digital wallet” can include an electronic device that allows an individual to conduct electronic commerce transactions. A digital wallet may store user profile information, payment information, bank account information, one or more digital wallet identifiers and/or the like and can be used in a variety of transactions, such as but not limited to eCommerce, social networks, money transfer/personal payments, mobile commerce, proximity payments, gaming, and/or the like for retail purchases, digital goods purchases, utility payments, purchasing games or gaming credits from gaming websites, transferring funds between users, and/or the like. A digital wallet may be designed to streamline the purchase and payment process. A digital wallet may allow the user to load one or more payment cards onto the digital wallet so as to make a payment without having to enter an account number or present a physical card.
A “digital wallet provider” may include an entity, such as an issuing bank or third party service provider, that issues a digital wallet to a user that enables the user to conduct financial transactions. A digital wallet provider may provide standalone user-facing software applications that store account numbers, or representations of the account numbers (e.g., payment tokens), on behalf of a cardholder (or other user) to facilitate payments at more than one unrelated merchant, perform person-to-person payments, or load financial value into the digital wallet. A digital wallet provider may enable a user to access its account via a personal computer, mobile device or access device. Additionally, a digital wallet provider may also provide one or more of the following functions: storing multiple payment cards and other payment products on behalf of a user, storing other information including billing address, shipping addresses, and transaction history, initiating a transaction by one or more methods, such as providing a user name and password, NFC or a physical token, and may facilitate pass-through or two-step transactions.
A “consumer” may include an individual or a user that may be associated with one or more personal accounts and/or mobile devices. The consumer may also be referred to as a cardholder, account holder, or user.
An “issuer” may typically refer to a business entity (e.g., a bank) that maintains an account for a user.
A “merchant” may typically be an entity that engages in transactions and can sell goods or services, or provide access to goods or services.
An “acquirer” may typically be a business entity (e.g., a commercial bank) that has a business relationship with a particular merchant or other entity. Some entities can perform both issuer and acquirer functions. Some embodiments may encompass such single entity issuer-acquirers.
An “access device” may be any suitable device that provides access to a remote system. An access device may also be used for communicating with a merchant computer, a payment processing network, an authentication computer, or any other suitable system. An access device may generally be located in any suitable location, such as at the location of a merchant. An access device may be in any suitable form. Some examples of access devices include POS or point of sale devices (e.g., POS terminals), cellular phones, PDAs, personal computers (PCs), tablet PCs, hand-held specialized readers, set-top boxes, electronic cash registers (ECRs), automated teller machines (ATMs), virtual cash registers (VCRs), kiosks, security systems, access systems, and the like. An access device may use any suitable contact or contactless mode of operation to send or receive data from, or associated with, a user mobile device. In some embodiments, where an access device may comprise a POS terminal, any suitable POS terminal may be used and may include a reader, a processor, and a computer-readable medium. A reader may include any suitable contact or contactless mode of operation. For example, exemplary card readers can include radio frequency (RF) antennas, optical scanners, bar code readers, or magnetic stripe readers to interact with a payment device and/or mobile device. In the examples provided herein, an access device and merchant computer may be referred to as separate system components. It should be appreciated, however, that the access device and merchant computer may be a single component, for example, one merchant mobile device or POS device.
An “authorization request message” may be an electronic message that is sent to a payment processing network and/or an issuer of a payment card to request authorization for a transaction. An authorization request message according to some embodiments may comply with ISO 8583, which is a standard for systems that exchange electronic transaction information associated with a payment made by a consumer using a payment device or payment account. The authorization request message may include an issuer account identifier that may be associated with a payment device or payment account. An authorization request message may also comprise additional data elements corresponding to “identification information” including, by way of example only: a service code, a CVV (card verification value), a dCVV (dynamic card verification value), a PAN (primary account number or “account number”), a payment token, a user name, an expiration date, etc. An authorization request message may also comprise “transaction information,” such as any information associated with a current transaction, such as the transaction amount, merchant identifier, merchant location, acquirer bank identification number (BIN), card acceptor ID, etc., as well as any other information that may be utilized in determining whether to identify and/or authorize a transaction.
An “authorization response message” may be an electronic message reply to an authorization request message generated by an issuing financial institution or a payment processing network. The authorization response message may include, by way of example only, one or more of the following status indicators: Approval—transaction was approved; Decline—transaction was not approved; or Call Center—response pending more information, merchant must call the toll-free authorization phone number. The authorization response message may also include an authorization code, which may be a code that a credit card issuing bank returns in response to an authorization request message in an electronic message (either directly or through the payment processing network) to the merchant's access device (e.g. POS equipment) that indicates approval of the transaction. The code may serve as proof of authorization. As noted above, in some embodiments, a payment processing network may generate or forward the authorization response message to the merchant.
A “server computer” may include a powerful computer or cluster of computers. For example, the server computer can be a large mainframe, a minicomputer cluster, or a group of servers functioning as a unit. In one example, the server computer may be a database server coupled to a Web server. The server computer may be coupled to a database and may include any hardware, software, other logic, or combination of the preceding for servicing the requests from one or more client computers. The server computer may comprise one or more computational apparatuses and may use any of a variety of computing structures, arrangements, and compilations for servicing the requests from one or more client computers.
Each of the entities may communicate through any suitable communication channel or communications network. A suitable communications network may be any one and/or the combination of the following: a direct interconnection; the Internet; a Local Area Network (LAN); a Metropolitan Area Network (MAN); an Operating Missions as Nodes on the Internet (OMNI); a secured custom connection; a Wide Area Network (WAN); a wireless network (e.g., employing protocols such as, but not limited to a Wireless Application Protocol (WAP), I-mode, and/or the like); and/or the like.
In the system 50 described above with respect to
In embodiments of the invention, the mobile device 102 may be an example of a first party device and can provide a single data element (e.g., a QR code) comprising the first data and second data to the access device 104, which may be an example of a second party device. The second data may be relevant to the current transaction between the consumer and merchant. The mobile device 102 may receive the second data from the payment processing network computer 112 before the transaction is initiated, such that the mobile device 102 can provide the second data to the merchant at the initiation of the transaction. As a result, the merchant computer 106 can have sufficient time for processing the second data within the timeframe of the transaction. For example, there may be enough time to consider the second data (which might be a consumer's fraud risk score) when deciding whether or not to authorize the transaction. Thus, the system 100 allows for providing the merchant computer 106 with second data that is relevant to the current transaction and/or consumer in a timely manner.
In one embodiment, described in detail below, the second data is a loyalty score that represents the consumer's loyalty to the merchant. Since the loyalty score is provided to the merchant computer 106 at the beginning of the transaction, the merchant computer 106 may have sufficient time for selecting a promotional offer based on the loyalty score, and then providing the selected promotional offer to the consumer before the consumer leaves the transaction area. For example, the promotional offer can be provided along with a transaction receipt.
Embodiments of the invention can also be used in systems other than system 100, and for interaction scenarios other than a payment transaction. For example, supplementary data can be obtained and used for security access interactions (i.e., gaining access to a restricted area), for data exchange between two devices (e.g., “tapping” two mobile devices to exchange personal contact information), and for any other suitable interaction.
An example of the mobile device 102 used for providing the first data and second data to the access device 104, according to some embodiments of the invention, is shown in
The memory 102E may comprise a digital wallet application 102F, a geolocation module 102G, payment credentials 102H, VAS data 102J, and any other suitable module or data. The mobile device 102 may have any number of mobile applications installed or stored on the memory 102E and is not limited to that shown in
The digital wallet application 102F may provide a user interface for the user to provide input and initiate, facilitate, and manage transactions using the mobile device 102. The digital wallet application 102F may be able to store and/or access first data, such as payment credentials 102 and VAS data 102J. Further, the digital wallet application 102F may be able to generate payment tokens and/or obtain payment tokens from the digital wallet provider computer 116 or the tokenization service computer 122.
In some embodiments, the digital wallet application 102F may be able to obtain second data, such as a loyalty score. For example, the digital wallet application 102F may be able to generate and send a loyalty score request to the payment processing network computer 112. The loyalty score request may include consumer identification information, payment credentials 102H, merchant identification information, geolocation data obtained from the geolocation module 102G, and any other suitable information.
In some embodiments, the digital wallet application 102F may be able to generate a single data element including first data and second data. For example, the digital wallet application 102F may generate a QR code including a payment token, VAS data, a digital wallet identifier, a loyalty score, and any other suitable information.
The geolocation module 102G may comprise code that causes the processor 102A to provide geo-location services (e.g., GPS). For example, the geolocation module 102G may contain logic that causes the processor 102A to determine the position of the mobile device 102. The geolocation module 102G may determine a set of coordinates or an address associated with the position of the mobile device 102. In some embodiments, the geolocation module 102G may locate or communicate with one or more satellites in a GPS network. The geolocation module 102G may determine the position of the mobile device 102 based on the relative positions of one or more satellites (e.g. using triangulation). In some embodiments, the geolocation module 102 may determine the position of the mobile device 102 based on communications with other systems, such as a cellular tower network or another network of local positioning beacons.
In some embodiments, the geolocation module 102G may be able to determine if the mobile device 102 is located at or near a merchant location. For example, the geolocation module 102G may store information about one or more merchant locations, such as one or more sets of coordinates or addresses associated with one or more merchant 120 locations. The geolocation module 102G may determine the position of the mobile device 102, and then determine whether the position of the mobile device 102G is at or within a predetermined distance of a merchant location (e.g. within 10, 20, 50, or 100 feet).
Referring back to
An example of the merchant computer 106, according to some embodiments of the invention, is shown in
The computer readable medium 106D may comprise a decoding module 106E, a transaction processing module 106F, a local VAS module 106G, a communication module 106H, a data analysis module 106J, an offer distribution module 106K, a receipt generation module 106L, a fraud risk module 106M, and any other suitable module. It may also comprise code, executable by the processor 106A for implementing a method comprising receiving a single data element from a first party mobile device, wherein the single data element includes first data from a first data and second data from a second data source, the first data being beneficial for the first party and the second data being beneficial to the second party; decoding the single data element into the first data and the second data; and processing the first data; and processing the second data separately from the first data.
The decoding module 106E may comprise code that causes the processor 106A to decode data. For example, the decoding module 106E may contain logic that causes the processor 106A to decode a QR code payload in order to identify and separate first data, such as a payment token and VAS data, from second data, such as a loyalty score.
The transaction processing module 106F may comprise code that causes the processor 106A to process transactions. For example, the transaction processing module 106F may contain logic that causes the processor 106A to generate an authorization request message including some or all of the first data (e.g. a payment token), transaction data, and any other relevant information, and then send the authorization request message to the acquirer computer 110. The transaction processing module 106F may also perform applicable value added services based on information from the local VAS module 106G and the external value added services computer 118.
The local VAS module 106G may comprise code that causes the processor 106A to identify and utilize relevant VAS data during a transaction. For example, the local VAS module 106G may contain logic that causes the processor 106A to redeem rewards points, track rewards points, process coupons, and provide any other value added services based on received VAS data.
The communication module 106H may comprise code that causes the processor 106A to generate messages and otherwise communicate with other entities. For example, the communication module 106H may contain logic that causes the processor 106A to obtain VAS information from the external value added services computer 118.
The data analysis module 106J may comprise code that causes the processor 106A to process second data during a transaction. For example, the data analysis module 106J may contain logic that causes the processor 106A to identify what types of information are included in the second data (e.g., loyalty score, competitor information, current consumer trends, etc.). The data analysis module 106J may also determine one or more actions to be taken based on the second data.
For example, data analysis module 106J may determine that a promotional offer should be provided to one or more consumers (e.g. provide an offer to a loyal consumer, distribute an offer for a good/service that many consumers are purchasing from competitor, etc.). Also, data analysis module 106J may determine that the merchant's inventory should be adjusted (e.g. increase the amount of certain goods that are selling well, decrease the amount of certain goods that consumers usually purchase from a competitor, start selling a second good if consumers typically buy it from another merchant after purchasing a first good here, etc.). A number of other actions that are beneficial to the merchant can be determined and executed based on various types of second data. Examples of additional modules are given below for performing certain actions based on second data. Additional modules could be included for performing other merchant-benefitting actions.
The offer distribution module 106K may comprise code that causes the processor 106A to identify and distribute promotional offers. For example, the offer distribution module 106K may contain logic that causes the processor 106A to determine a promotional offer based on received second data, and then provide the selected promotional offer to the consumer. One type of second data that can be used to select a promotional offer is a loyalty score. In some embodiments, different promotional offers may be provided to consumers with different loyalty scores. For example, a consumer with a high loyalty score may receive a more preferable promotional offer (e.g. a higher discount, or an offer for a preferred good or service).
In some embodiments, the offer distribution module 106K may distribute offers in a different manner, or based on other types of second data. For example, the merchant computer 106 may receive second data indicating that some consumers are choosing to shop at a competitor. In this case, the offer distribution module 106K may select an promotional offer for wide distribution. The promotional offer may be emailed to one or more consumers, shared on a social media website or application, made available to all consumers in a certain region, or otherwise distributed so that consumers are incentivized to shop at the merchant instead of the competitor.
The receipt generation module 106L may comprise code that causes the processor 106A to generate a receipt. For example, the receipt generation module 106L may contain logic that causes the processor 106A to generate an electronic receipt for an authorized transaction. A promotional offer (e.g. an offer selected by the offer distribution module 106K) can be included with a receipt or provided along with a receipt.
The fraud risk module 106M may comprise code that causes the processor 106A to assess the risk of fraud during a transaction. For example, the fraud risk module 106M may contain logic that causes the processor 106A to detect high-velocity transactions, check a “blacklist”, and otherwise check fraud/risk levels during a transaction. In some embodiments, the data analysis module 106J may identify that fraud risk information was received as second data. The fraud risk module 106M may determine whether or not to approve/reject the transaction based on the received information.
The promotional offer database 106C may include promotional offers. The merchant computer 106 may distribute promotional offers from the promotional offer database 106C at certain times, to certain consumers, or in any other suitable manner. In some embodiments, promotional offers may be distributed based on second data and/or VAS data, and promotional offers may be distributed by the offer distribution module 106K and/or the local VAS module 106G.
As described above, the merchant computer 106 may process VAS data when processing a transaction. Referring back to
Still referring to
As shown in
The payment processing network computer 112, the acquirer computer 110, and the issuer computer 114 may operate suitable routing tables to route authorization request messages using account identifiers such as PANs or tokens. Token routing data may be provided or maintained by the tokenization service computer 122, and may be communicated to any of the entities in
In addition to routing communications between the acquirer computer 110 and the issuer computer 114, the payment processing network computer 112 may be able to communicate with the mobile device 102. The payment processing network computer 112 may be able to provide various types of information to the mobile device 102, which the mobile device 102 may then include as second data during a transaction with the merchant.
An example of the payment processing network computer 112, according to some embodiments of the invention, is shown in
The computer readable medium 112E may comprise a communication module 112F, a consumer spending analysis module 112G, a global spending analysis module 112H, a consumer scoring module 112J, a fraud risk module 112K, and a consumer data preparation module 112L.
The communication module 112F may comprise code that causes the processor 112A to generate messages, forward messages, reformat messages, and/or otherwise communicate with other entities. For example, the communication module 112F may contain logic that causes the processor 112A to receive an authorization request message from the acquirer computer 110, de-tokenize a payment token by requesting associate payment credentials from the tokenization service computer 122, reformat the authorization request message so that a payment token is replaced with an associated set of payment credentials, and forward the authorization request message to the issuer computer 114.
The communication module 112F may also be able to provide information (e.g. various types of second data) to other entities, such as the mobile device 102. For example, the mobile device 102 may send a request for second data, and the communication module 112F may send a response including one or more types of second data.
The consumer spending analysis module 112G may comprise code that causes the processor 112A to analyze consumer data. For example, the consumer spending analysis module 112G may contain logic that causes the processor 112A to track purchases and trends associated with a consumer. Transaction records stored in the transaction database 112C can be used for consumer analysis. The payment processing network computer 112 may be involved in processing each transaction associated with a consumer's payment account, and thus the payment processing network computer 112 may be able to track the consumer's spending across different merchants. With such a global perspective of transactions, the consumer spending analysis module 112G may be able to determine a consumer's behavioral patterns, and the consumer spending analysis module 112G may be able to predict a consumer's future actions. For example, the consumer spending analysis module 112G may determine which types of products a consumer prefers, which merchants a consumer prefers, in which regions a consumer typically shops, whether a consumer is currently on a road trip or moving, if the consumer travels regularly, how much debt a consumer has, if the consumer has had a recent change in spending, if the consumer spends at certain predictable times, etc. Additionally, the consumer spending analysis module 112G may be able to compare one consumer's behavioral patterns with a general set of consumer behaviors that are based on a group of consumers.
The global spending analysis module 112H may comprise code that causes the processor 112A to analyze groups of consumers. For example, the global spending analysis module 112H may contain logic that causes the processor 112A to analyze trends from within consumers of a certain demographic, region, timeframe, etc. For example, the global spending analysis module 112H may be able to determine if consumers generally prefer a first merchant over a similar second merchant, what types of products consumers are buying more or less of, whether consumers tend to purchase certain products together, if there are currently consumers nearby that are not visiting a certain merchant's store, etc.
The consumer scoring module 112J may comprise code that causes the processor 112A to determine a consumer score. For example, the consumer scoring module 112J may contain logic that causes the processor 112A to determine an affinity score such as a loyalty score or an attrition score for a certain consumer. The payment processing network computer 112 may receive a request for second data, where the request includes consumer identifying information (e.g. payment credentials) and merchant identification information. Using historical spend data associated with the consumer (from the transaction database 112C) and merchant information (from the merchant database 112D), the consumer scoring module 112J may be able to determine a consumer's relationship with the merchant. For example, the consumer scoring module 112J may be able to determine whether the consumer frequently shops at the merchant, whether the consumer prefers the merchant over competitors, whether the consumer is likely to continue shopping at the merchant, whether the consumer is likely to purchase certain products at the merchant, etc. A consumer score, such as an affinity score, can be generated based on this type of analysis.
The fraud risk module 112K may comprise code that causes the processor 112A to assess risk for a certain consumer. For example, the fraud risk module 112K may contain logic that causes the processor 112A to analyze historical transaction data (from the transaction database 112C) associated with the consumer and identify indicators of possible fraud, such as high velocity transactions, declined transactions, disputed transactions, fraud/risk data provided by the issuer, etc. In some embodiments, the fraud risk module 112K may determine fraud/risk data generally associated with the consumer. In other embodiments, the fraud risk module 112K may determine the likelihood of the consumer attempting a fraudulent transaction at a specific merchant.
The consumer data preparation module 112L may comprise code that causes the processor 112A to compile second data for a consumer. For example, the consumer data preparation module 112L may contain logic that causes the processor 112A to gather consumer data from one or more modules (e.g. the consumer scoring module 112J) in response to a request for second data. A request for second data may indicate a certain consumer, a certain merchant, a certain type of second data, etc. In response to receiving a request, the consumer data preparation module 112L may prepare the relevant second data in order to provide the data to the requestor (e.g. the mobile device 102).
The transaction database 112C may include records of previous transactions. Transaction records may indicate the involved consumer, payment credentials, merchant, mobile device, and any other suitable information. The merchant database 112D may include information about merchants. For example, the merchant database 112D may include merchant records with merchant names, merchant location data, merchant preferences for types of second data type, and any other suitable merchant information.
Referring back to
The tokenization service computer 122 may also be capable of de-tokenizing a token and providing payment credentials in response to receiving the token. For example, the tokenization service computer 122 may receive requests for payment credentials from the payment processing network computer 112 or the issuer computer 114. The tokenization service computer 122 may receive such a de-tokenization request including a token, identify payment credentials associated with the token, and then provide the payment credentials to the de-tokenization requestor.
As shown in
As shown in
The computer readable medium 116D may comprise a communication module 116E, a payment module 116F, a tokenization module 116G, and a value added services module 116H.
The communication module 116E may comprise code that causes the processor 116A to communicate with the mobile device 102, external value added services computer 118, cloud based payments platform 120, and any other suitable entity. For example, the communication module 116E may contain logic that causes the processor 116A to receive a request for a payment token from the mobile device 102, and then send a response including a payment token.
The payment module 116F may comprise code that causes the processor 116A to prepare payment credentials. For example, the payment module 116F may contain logic that causes the processor 116A to compile payment credentials (e.g., from the consumer information database 116C), such as a PAN or payment token, for providing to the mobile device 102. Payment credentials can be provided before each transaction, or payment credentials can be provisioned onto the mobile device 102.
The tokenization module 116G may comprise code that causes the processor 116A to obtain a payment token. For example, the tokenization module 116G may contain logic that causes the processor 116A to request a payment token from the cloud based payment platform 120 for a certain payment account on behalf of the consumer. In some embodiments, the tokenization module 116G may be able to generate payment tokens.
The value added services module 116H may comprise code that causes the processor 116A to prepare VAS data. For example, the value added services module 116H may contain logic that causes the processor 116A to compile VAS data associated with the consumer for a transaction. VAS data can be obtained from the consumer information database 116C, from the external value added services computer 118, and from any other suitable location. VAS data can be selected based on the merchant with which the consumer is transacting.
The consumer information database 116C may contain consumer information. For example, the consumer information database 116C may include payment credentials, VAS data, information about obtaining payment tokens, and any other suitable information associated with a consumer.
A method 700 according to embodiments of the invention can be described with respect to
The various messages in
In embodiments of the invention, a consumer's mobile device can provide a centrally-determined loyalty score to a merchant during a transaction. The mobile device receives a loyalty score generated by a payment processing network, combines payment credentials and the loyalty score into a single data element, and transmits the data element to a merchant access device. The merchant may use the loyalty score to provide targeted, tiered offers to the consumer within the timeframe of the transaction.
As described above, besides a loyalty score, several other types of merchant-benefitting second data can be provided, and the merchant can take a number of actions based on the data. The specific example of providing a loyalty score, and the merchant responding with a promotional offer, is described here for illustration purposes.
In order to initiate the method 700, the consumer may activate the mobile wallet application 102F on the mobile device 102, and may indicate a desire to make a payment (e.g., by selecting a “payment” option). The consumer may wish to purchase a good or service at the merchant via the mobile device 102. Further, the consumer may select a payment account within the mobile wallet application 102F (e.g., by selecting a visually displayed icon representing a payment account).
At step S702, the digital wallet application 102F may send a token request message to the digital wallet provider computer 116. The token request message can include payment credentials and any other suitable information. The digital wallet provider computer 116 can obtain a payment token that represents the payment credentials from the tokenization service computer 122.
At step S704, the digital wallet application 102F may receive a token response message including the payment token from the digital wallet provider computer 116. In addition to the payment token, the digital wallet provider computer 116 may transmit other information including one or more of a token expiration date, a token requestor ID, a digital wallet ID, and any other suitable information. The digital wallet provider computer 116 may also provide VAS data from the consumer information database 116C and/or the external value added services computer 118.
At step S706, the geolocation module 102G may determine the location of the mobile device 102 and provide the location data to the mobile wallet application 102F.
At step S708, the mobile wallet application 102F may send a second data request message to the payment processing network computer 112. The second data request message may include a mobile device identifier, a consumer identifier, location data, a merchant identifier, payment credentials, and any other suitable information.
At step S710, the payment processing network computer 112 may determine one or more types of second data for providing to the mobile device 102. Using one or more of the modules 112G-112L, the payment processing network computer 112 may determine suitable second data based on the consumer and the merchant. For example, the consumer scoring module 112J may determine a loyalty score associated with the consumer at the merchant. The consumer may be identified based on the mobile device 102 identifier or the payment credentials, and the merchant may be identified based a record in the merchant database 112D that is associated with the geolocation data. In some embodiments, the consumer data preparation module 112L may include any second data that is considered to be beneficial for the merchant. Although this example illustrates the payment processing network computer 112 as providing the second data, it is understood that any other computer (e.g., the issuer computer 114) may provide the second data. For example, the payment processing network 112 may generate a fraud or risk score based upon the payment credentials received in step S708.
At step S712, the mobile wallet application 102F may receive a second data response message including the loyalty score from the payment processing network computer 112.
At step S714, the mobile wallet application 102F may generate a transaction payload including the first data (e.g., the payment token and VAS data), the second data (e.g., the loyalty score), and any other suitable information. The transaction payload may be consolidated into a single data element, such as a QR code. In other embodiments, the single data element that is generated may be a single data packet that can be transmitted through a contact interface, a contactless medium (e.g., WiFi, NFC, etc.), etc.
At step S716, the mobile wallet application 102F may provide the transaction payload to the access device 104. For example, a QR code may be displayed (e.g., via display 102B), the consumer may hold the mobile device 102 within interaction range of the access device 104, and the access device may read the QR code. Any other suitable communication mechanism (e.g., a contactless mechanism) may be used to pass the transaction payload to the access device 104.
At step S718, the access device 104 may send the received information to the merchant computer 106.
At step S720, the merchant computer 106 may then convert the single data element into the original data that was used to form the single data element. For example, the merchant computer 106 may decode the QR code (e.g. via the decoding module 106E), thereby obtaining the payment token, the loyalty score, the VAS data, and any other data included in the QR code. It is noted that the access device 104 could perform the functions of the merchant computer 106 in other embodiments of the invention.
Once the merchant computer 106 has isolated the first data (e.g., payment credentials and VAS data) and the second data (e.g., loyalty score), the transaction can be processed (e.g. via the transaction processing module 106F). The merchant computer may first process the received VAS data, as well as retrieve any additional VAS data from the local VAS module 106G and/or the external value added services computer 118. For example, if there are any applicable coupons, the merchant computer 106 may reduce the amount of the transaction by the value of the coupon. In another example, if the second data is a fraud score for the consumer, then the merchant may take appropriate action based upon that fraud score. For example, if the fraud score is high, then the merchant may decide not to proceed with the transaction and/or may ask the consumer for additional authentication information or assurance of payment (e.g., an alternative source of funds).
At step S722, the merchant computer 106 may generate an authorization request message for the transaction, and send the authorization request message to the acquirer computer 110. The authorization request message may include the payment token, transaction information, and any other suitable information.
At step S724, the acquirer computer 110 may forward the authorization request message to the payment processing network computer 112.
The payment processing network computer 112 may de-tokenize the payment token in the authorization request message by obtaining the associated payment credentials from the tokenization service computer 122. At step S726, the payment processing network computer 112 may reformat the authorization request message to include the payment credentials (e.g., a real PAN or primary account number, a real CVV or card verification value, etc.), and then forward the authorization request message to the issuer computer 114.
At step S728, the issuer computer 114 then determines whether or not the transaction should be authorized. The issuer computer 114 may check the status of the payment account, conduct any appropriate fraud or credit checks, and perform any other suitable processing in order to determine whether or not to approve of the transaction. After this analysis occurs, the issuer computer 114 then generates and sends an authorization response message back to the payment processing network computer 112.
At step S730, the payment processing network computer 112 may reformat the authorization response message to include the payment token and remove the payment credentials, and then forward the authorization response message to the acquirer computer 110. The payment processing network computer 112 may also store a record of the transaction at the transaction database 112C.
At step S732, the acquirer computer 110 may forward the authorization response message to the merchant computer 106.
At step S734, the merchant computer 106 may process the second data. For example, the merchant computer 106 may determine that a loyalty score is included in the second data (e.g., via the data analysis module 106J). The merchant computer 106 may also analyze the loyalty score in order to determine one or more possible actions that may be beneficial for the merchant.
In some embodiments, the merchant computer 106 may determine that it would be beneficial to provide a promotional offer to the consumer. The merchant computer 106 may select a promotional offer based on the loyalty score (e.g., via the offer distribution module 106K). For example, a promotional offer that is preferred to the consumer may be selected if the loyalty score indicates higher than average loyalty to the merchant. The selected promotional offer may be sent to the communication module 106H, such that it may be provided to the consumer. In some embodiments, the promotional offer can be provided to the mobile device 102 in an electronic receipt.
As described above, there are several other types of second data that are beneficial to the merchant, and which may be provided in step S712. Further, the merchant computer 106 may be able to perform a number of alternative actions based on various types of second data.
In some embodiments, the merchant computer 106 may process the second data (e.g. loyalty score) in step S734 after receiving the authorization response message. However, the second data may alternatively be processed before or at the same time as processing the first data. Further, as noted above, in step S720, the second data may have been processed by the merchant computer 106 prior to sending an authorization request message to the issuer computer 114.
At step S736, the merchant computer 106 may forward the authorization response message to the access device 104. The merchant computer 106 may also generate and send an electronic receipt to the access device 104. In some embodiments, the promotional offer may be included in the electronic receipt.
At step S738, the access device 104 may inform the consumer that the transaction is approved, and the goods or services may be released to the consumer. Also, the electronic receipt and promotional offer may be transmitted to the mobile device 102 (e.g. via QR code, NFC, etc.). The promotional offer may beneficially persuade the consumer to return to the merchant at a later date for a future purchase, thus increasing commerce at the merchant.
Accordingly, the second data, which may not be necessary for conducting a transaction, can be provided during a transaction for the benefit of the merchant. The mobile device 102 obtains the loyalty score before the transaction begins, and thus the mobile device 102 can provide the loyalty score along with the payment token at the onset of the transaction. Since the merchant computer 106 receives the loyalty score right away, there may be sufficient time to identify the appropriate promotional offer while the transaction is being processed. As a result, the promotional offer can be provided to the mobile device 102 in an electronic receipt, such that the promotional offer is provided to the consumer before the consumer leaves the area.
At the end of the day or at some other predetermined interval of time, a clearing and settlement process between the issuer computer 114, the payment processing network computer 112, and the acquirer computer 110 may occur. In the clearing and settlement process, account information and token exchanges that are similar to those in the above-described authorization processing steps can occur.
Embodiments of the invention have a number of advantages. A merchant can have a more accurate understanding of a consumer's spending behaviors, as well as a more accurate picture of overall consumer/market activities. For example, a merchant can learn about how it is performing in relation to a competitor, and how consumer spending within the merchant category is changing. Essentially, a merchant can gain the perspective of a payment processing network. This can allow a merchant to make well-informed business and marketing decisions, leading to a competitive edge and better economic results.
Further, the mobile device to access device communication pathway, which is traditionally reserved for obtaining data beneficial to the consumer, is leveraged for providing a merchant with information that may benefit the merchant. As a result, the merchant can receive supplementary data (related to the consumer and/or market) in time to take action while the consumer is present and before a transaction is initiated. Also, by transmitting data beneficial to a merchant through a communication path normally used to transmit data beneficial to a consumer, a number of steps are reduced. For example, if the merchant wants to obtain a fraud or loyalty score from a payment processing network, then the merchant needs to separately communicate with the merchant and request that data. However, in embodiments of the invention, these extra steps and communications are advantageously not required.
As described, the inventive service may involve implementing one or more functions, processes, operations or method steps. In some embodiments, the functions, processes, operations or method steps may be implemented as a result of the execution of a set of instructions or software code by a suitably-programmed computing device, microprocessor, data processor, or the like. The set of instructions or software code may be stored in a memory or other form of data storage element which is accessed by the computing device, microprocessor, etc. In other embodiments, the functions, processes, operations or method steps may be implemented by firmware or a dedicated processor, integrated circuit, etc.
Any of the software components or functions described in this application may be implemented as software code to be executed by a processor using any suitable computer language such as, for example, Java, C++ or Perl using, for example, conventional or object-oriented techniques. The software code may be stored as a series of instructions, or commands on a computer-readable medium, such as a random access memory (RAM), a read-only memory (ROM), a magnetic medium such as a hard-drive or a floppy disk, or an optical medium such as a CD-ROM. Any such computer-readable medium may reside on or within a single computational apparatus, and may be present on or within different computational apparatuses within a system or network.
While certain exemplary embodiments have been described in detail and shown in the accompanying drawings, it is to be understood that such embodiments are merely illustrative of and not intended to be restrictive of the broad invention, and that this invention is not to be limited to the specific arrangements and constructions shown and described, since various other modifications may occur to those with ordinary skill in the art.
As used herein, the use of “a”, “an” or “the” is intended to mean “at least one”, unless specifically indicated to the contrary.
This application is a continuation of U.S. patent application Ser. No. 14/680,874, filed Apr. 7, 2015, which is a non-provisional application of and claims the benefit of the filing date of U.S. Provisional Application No. 61/976,989, filed on Apr. 8, 2014, which is herein incorporated by reference in its entirety for all purposes.
Number | Name | Date | Kind |
---|---|---|---|
5613012 | Hoffman et al. | Mar 1997 | A |
5781438 | Lee et al. | Jul 1998 | A |
5883810 | Franklin et al. | Mar 1999 | A |
5953710 | Fleming | Sep 1999 | A |
5956699 | Wong et al. | Sep 1999 | A |
6000832 | Franklin et al. | Dec 1999 | A |
6014635 | Harris et al. | Jan 2000 | A |
6044360 | Picciallo | Mar 2000 | A |
6163771 | Walker et al. | Dec 2000 | A |
6227447 | Campisano | May 2001 | B1 |
6236981 | Hill | May 2001 | B1 |
6267292 | Walker et al. | Jul 2001 | B1 |
6341724 | Campisano | Jan 2002 | B2 |
6385596 | Wiser et al. | May 2002 | B1 |
6422462 | Cohen | Jul 2002 | B1 |
6425523 | Shem-Ur et al. | Jul 2002 | B1 |
6592044 | Wong et al. | Jul 2003 | B1 |
6636833 | Flitcroft et al. | Oct 2003 | B1 |
6748367 | Lee | Jun 2004 | B1 |
6805287 | Bishop et al. | Oct 2004 | B2 |
6879965 | Fung et al. | Apr 2005 | B2 |
6891953 | DeMello et al. | May 2005 | B1 |
6901387 | Wells et al. | May 2005 | B2 |
6931382 | Laage et al. | Aug 2005 | B2 |
6938019 | Uzo | Aug 2005 | B1 |
6941285 | Sarcanin | Sep 2005 | B2 |
6980670 | Hoffman et al. | Dec 2005 | B1 |
6990470 | Hogan et al. | Jan 2006 | B2 |
6991157 | Bishop et al. | Jan 2006 | B2 |
7051929 | Li | May 2006 | B2 |
7069249 | Stolfo et al. | Jun 2006 | B2 |
7103576 | Mann, III et al. | Sep 2006 | B2 |
7113930 | Eccles et al. | Sep 2006 | B2 |
7136835 | Flitcroft et al. | Nov 2006 | B1 |
7177835 | Walker et al. | Feb 2007 | B1 |
7177848 | Hogan et al. | Feb 2007 | B2 |
7194437 | Britto et al. | Mar 2007 | B1 |
7209561 | Shankar et al. | Apr 2007 | B1 |
7264154 | Harris | Sep 2007 | B2 |
7287692 | Patel et al. | Oct 2007 | B1 |
7292999 | Hobson et al. | Nov 2007 | B2 |
7350230 | Forrest | Mar 2008 | B2 |
7353382 | Labrou et al. | Apr 2008 | B2 |
7379919 | Hogan et al. | May 2008 | B2 |
RE40444 | Linehan | Jul 2008 | E |
7415443 | Hobson et al. | Aug 2008 | B2 |
7444676 | Asghari-Kamrani et al. | Oct 2008 | B1 |
7469151 | Khan et al. | Dec 2008 | B2 |
7548889 | Bhambri et al. | Jun 2009 | B2 |
7567934 | Flitcroft et al. | Jul 2009 | B2 |
7567936 | Peckover et al. | Jul 2009 | B1 |
7571139 | Giordano et al. | Aug 2009 | B1 |
7571142 | Flitcroft et al. | Aug 2009 | B1 |
7580898 | Brown et al. | Aug 2009 | B2 |
7584153 | Brown et al. | Sep 2009 | B2 |
7593896 | Flitcroft et al. | Sep 2009 | B1 |
7606560 | Labrou et al. | Oct 2009 | B2 |
7627531 | Breck et al. | Dec 2009 | B2 |
7627895 | Gifford et al. | Dec 2009 | B2 |
7650314 | Saunders | Jan 2010 | B1 |
7685037 | Reiners et al. | Mar 2010 | B2 |
7702553 | Dickelman | Apr 2010 | B1 |
7702578 | Fung et al. | Apr 2010 | B2 |
7707120 | Dominguez et al. | Apr 2010 | B2 |
7712655 | Wong | May 2010 | B2 |
7734527 | Uzo | Jun 2010 | B2 |
7753265 | Harris | Jul 2010 | B2 |
7770789 | Oder, II et al. | Aug 2010 | B2 |
7784685 | Hopkins, III | Aug 2010 | B1 |
7793851 | Mullen | Sep 2010 | B2 |
7801826 | Labrou et al. | Sep 2010 | B2 |
7805376 | Smith | Sep 2010 | B2 |
7805378 | Berardi et al. | Sep 2010 | B2 |
7818264 | Hammad | Oct 2010 | B2 |
7828220 | Mullen | Nov 2010 | B2 |
7835960 | Breck et al. | Nov 2010 | B2 |
7841523 | Oder, II et al. | Nov 2010 | B2 |
7841539 | Hewton | Nov 2010 | B2 |
7844550 | Walker et al. | Nov 2010 | B2 |
7848980 | Carlson | Dec 2010 | B2 |
7849020 | Johnson | Dec 2010 | B2 |
7853529 | Walker et al. | Dec 2010 | B1 |
7853995 | Chow et al. | Dec 2010 | B2 |
7865414 | Fung et al. | Jan 2011 | B2 |
7873579 | Hobson et al. | Jan 2011 | B2 |
7873580 | Hobson et al. | Jan 2011 | B2 |
7890393 | Talbert et al. | Feb 2011 | B2 |
7891563 | Oder, II et al. | Feb 2011 | B2 |
7896238 | Fein et al. | Mar 2011 | B2 |
7908216 | Davis et al. | Mar 2011 | B1 |
7922082 | Muscato | Apr 2011 | B2 |
7931195 | Mullen | Apr 2011 | B2 |
7937324 | Patterson | May 2011 | B2 |
7938318 | Fein et al. | May 2011 | B2 |
7954705 | Mullen | Jun 2011 | B2 |
7959076 | Hopkins, III | Jun 2011 | B1 |
7996288 | Stolfo | Aug 2011 | B1 |
8025223 | Saunders et al. | Sep 2011 | B2 |
8046256 | Chien et al. | Oct 2011 | B2 |
8060448 | Jones | Nov 2011 | B2 |
8060449 | Zhu | Nov 2011 | B1 |
8074877 | Mullen et al. | Dec 2011 | B2 |
8074879 | Harris | Dec 2011 | B2 |
8082210 | Hansen et al. | Dec 2011 | B2 |
8095113 | Kean et al. | Jan 2012 | B2 |
8104679 | Brown | Jan 2012 | B2 |
RE43157 | Bishop et al. | Feb 2012 | E |
8109436 | Hopkins, III | Feb 2012 | B1 |
8121942 | Carlson et al. | Feb 2012 | B2 |
8121956 | Carlson et al. | Feb 2012 | B2 |
8126449 | Beenau et al. | Feb 2012 | B2 |
8171525 | Pelly et al. | May 2012 | B1 |
8175973 | Davis et al. | May 2012 | B2 |
8190523 | Patterson | May 2012 | B2 |
8196813 | Vadhri | Jun 2012 | B2 |
8205791 | Randazza et al. | Jun 2012 | B2 |
8219489 | Patterson | Jul 2012 | B2 |
8224702 | Mengerink et al. | Jul 2012 | B2 |
8225385 | Chow et al. | Jul 2012 | B2 |
8229852 | Carlson | Jul 2012 | B2 |
8265993 | Chien et al. | Sep 2012 | B2 |
8280777 | Mengerink et al. | Oct 2012 | B2 |
8281991 | Wentker et al. | Oct 2012 | B2 |
8328095 | Oder, II et al. | Dec 2012 | B2 |
8336088 | Raj et al. | Dec 2012 | B2 |
8346666 | Lindelsee et al. | Jan 2013 | B2 |
8376225 | Hopkins, III | Feb 2013 | B1 |
8380177 | Laracey | Feb 2013 | B2 |
8387873 | Saunders et al. | Mar 2013 | B2 |
8401539 | Beenau et al. | Mar 2013 | B2 |
8401898 | Chien et al. | Mar 2013 | B2 |
8402555 | Grecia | Mar 2013 | B2 |
8403211 | Brooks et al. | Mar 2013 | B2 |
8412623 | Moon et al. | Apr 2013 | B2 |
8412837 | Emigh et al. | Apr 2013 | B1 |
8417642 | Oren | Apr 2013 | B2 |
8433116 | Butler et al. | Apr 2013 | B2 |
8442894 | Blackhurst et al. | May 2013 | B2 |
8447699 | Batada et al. | May 2013 | B2 |
8453223 | Svigals et al. | May 2013 | B2 |
8453925 | Fisher et al. | Jun 2013 | B2 |
8458487 | Palgon et al. | Jun 2013 | B1 |
8484134 | Hobson et al. | Jul 2013 | B2 |
8485437 | Mullen et al. | Jul 2013 | B2 |
8494959 | Hathaway et al. | Jul 2013 | B2 |
8498908 | Mengerink et al. | Jul 2013 | B2 |
8504475 | Brand et al. | Aug 2013 | B2 |
8504478 | Saunders et al. | Aug 2013 | B2 |
8510816 | Quach et al. | Aug 2013 | B2 |
8533860 | Grecia | Sep 2013 | B1 |
8538845 | Liberty | Sep 2013 | B2 |
8555079 | Shablygin et al. | Oct 2013 | B2 |
8566168 | Bierbaum et al. | Oct 2013 | B1 |
8567670 | Stanfield et al. | Oct 2013 | B2 |
8571939 | Lindsey et al. | Oct 2013 | B2 |
8577336 | Mechaley, Jr. | Nov 2013 | B2 |
8577803 | Chatterjee et al. | Nov 2013 | B2 |
8577813 | Weiss | Nov 2013 | B2 |
8578176 | Mattsson | Nov 2013 | B2 |
8583494 | Fisher | Nov 2013 | B2 |
8584251 | McGuire et al. | Nov 2013 | B2 |
8589237 | Fisher | Nov 2013 | B2 |
8589271 | Evans | Nov 2013 | B2 |
8589291 | Carlson et al. | Nov 2013 | B2 |
8595098 | Starai et al. | Nov 2013 | B2 |
8595812 | Bomar et al. | Nov 2013 | B2 |
8595850 | Spies et al. | Nov 2013 | B2 |
8606638 | Dragt | Dec 2013 | B2 |
8606700 | Carlson et al. | Dec 2013 | B2 |
8606720 | Baker et al. | Dec 2013 | B1 |
8615468 | Varadarajan | Dec 2013 | B2 |
8620754 | Fisher | Dec 2013 | B2 |
8635157 | Smith et al. | Jan 2014 | B2 |
8646059 | Von Behren et al. | Feb 2014 | B1 |
8651374 | Brabson et al. | Feb 2014 | B2 |
8656180 | Shablygin et al. | Feb 2014 | B2 |
8751391 | Freund | Jun 2014 | B2 |
8762263 | Gauthier et al. | Jun 2014 | B2 |
8762283 | Gerber et al. | Jun 2014 | B2 |
8793186 | Patterson | Jul 2014 | B2 |
8838982 | Carlson et al. | Sep 2014 | B2 |
8856539 | Weiss | Oct 2014 | B2 |
8887308 | Grecia | Nov 2014 | B2 |
9065643 | Hurry et al. | Jun 2015 | B2 |
9070129 | Sheets et al. | Jun 2015 | B2 |
9100826 | Weiss | Aug 2015 | B2 |
9160741 | Wentker et al. | Oct 2015 | B2 |
9229964 | Stevelinck | Jan 2016 | B2 |
9245267 | Singh | Jan 2016 | B2 |
9249241 | Dai et al. | Feb 2016 | B2 |
9256871 | Anderson et al. | Feb 2016 | B2 |
9280765 | Hammad | Mar 2016 | B2 |
9530137 | Weiss | Dec 2016 | B2 |
10026087 | Salmon et al. | Jul 2018 | B2 |
20010029485 | Brody et al. | Oct 2001 | A1 |
20010034720 | Armes | Oct 2001 | A1 |
20010054003 | Chien et al. | Dec 2001 | A1 |
20020007320 | Hogan et al. | Jan 2002 | A1 |
20020016749 | Borecki et al. | Feb 2002 | A1 |
20020029193 | Ranjan et al. | Mar 2002 | A1 |
20020035548 | Hogan et al. | Mar 2002 | A1 |
20020073045 | Rubin et al. | Jun 2002 | A1 |
20020116341 | Hogan et al. | Aug 2002 | A1 |
20020128977 | Nambiar et al. | Sep 2002 | A1 |
20020133467 | Hobson et al. | Sep 2002 | A1 |
20020147913 | Lun Yip | Oct 2002 | A1 |
20030028481 | Flitcroft et al. | Feb 2003 | A1 |
20030130955 | Hawthorne | Jul 2003 | A1 |
20030191709 | Elston et al. | Oct 2003 | A1 |
20030191945 | Keech | Oct 2003 | A1 |
20040010462 | Moon et al. | Jan 2004 | A1 |
20040030659 | Gueh | Feb 2004 | A1 |
20040044379 | Holsheimer | Mar 2004 | A1 |
20040050928 | Bishop et al. | Mar 2004 | A1 |
20040059682 | Hasumi et al. | Mar 2004 | A1 |
20040093281 | Silverstein et al. | May 2004 | A1 |
20040139008 | Mascavage, III | Jul 2004 | A1 |
20040143532 | Lee | Jul 2004 | A1 |
20040158532 | Breck et al. | Aug 2004 | A1 |
20040210449 | Breck et al. | Oct 2004 | A1 |
20040210498 | Freund | Oct 2004 | A1 |
20040232225 | Bishop et al. | Nov 2004 | A1 |
20040260646 | Berardi et al. | Dec 2004 | A1 |
20050037735 | Coutts | Feb 2005 | A1 |
20050080730 | Sorrentino | Apr 2005 | A1 |
20050108178 | York | May 2005 | A1 |
20050199709 | Linlor | Sep 2005 | A1 |
20050246293 | Ong | Nov 2005 | A1 |
20050269401 | Spitzer et al. | Dec 2005 | A1 |
20050269402 | Spitzer et al. | Dec 2005 | A1 |
20060235795 | Johnson et al. | Oct 2006 | A1 |
20060237528 | Bishop et al. | Oct 2006 | A1 |
20060278704 | Saunders et al. | Dec 2006 | A1 |
20070084913 | Weston | Apr 2007 | A1 |
20070107044 | Yuen et al. | May 2007 | A1 |
20070129955 | Dalmia et al. | Jun 2007 | A1 |
20070136193 | Starr | Jun 2007 | A1 |
20070136211 | Brown et al. | Jun 2007 | A1 |
20070170247 | Friedman | Jul 2007 | A1 |
20070179885 | Bird et al. | Aug 2007 | A1 |
20070208671 | Brown et al. | Sep 2007 | A1 |
20070245414 | Chan et al. | Oct 2007 | A1 |
20070288377 | Shaked | Dec 2007 | A1 |
20070291995 | Rivera | Dec 2007 | A1 |
20080015988 | Brown et al. | Jan 2008 | A1 |
20080029607 | Mullen | Feb 2008 | A1 |
20080035738 | Mullen | Feb 2008 | A1 |
20080052226 | Agarwal et al. | Feb 2008 | A1 |
20080054068 | Mullen | Mar 2008 | A1 |
20080054079 | Mullen | Mar 2008 | A1 |
20080054081 | Mullen | Mar 2008 | A1 |
20080065554 | Hogan et al. | Mar 2008 | A1 |
20080065555 | Mullen | Mar 2008 | A1 |
20080201264 | Brown et al. | Aug 2008 | A1 |
20080201265 | Hewton | Aug 2008 | A1 |
20080228646 | Myers et al. | Sep 2008 | A1 |
20080243702 | Hart et al. | Oct 2008 | A1 |
20080245855 | Fein et al. | Oct 2008 | A1 |
20080245861 | Fein et al. | Oct 2008 | A1 |
20080283591 | Oder, II et al. | Nov 2008 | A1 |
20080302869 | Mullen | Dec 2008 | A1 |
20080302876 | Mullen | Dec 2008 | A1 |
20080313264 | Pestoni | Dec 2008 | A1 |
20090006262 | Brown et al. | Jan 2009 | A1 |
20090010488 | Matsuoka et al. | Jan 2009 | A1 |
20090037333 | Flitcroft et al. | Feb 2009 | A1 |
20090037388 | Cooper et al. | Feb 2009 | A1 |
20090043702 | Bennett | Feb 2009 | A1 |
20090048971 | Hathaway et al. | Feb 2009 | A1 |
20090063345 | Erikson | Mar 2009 | A1 |
20090106112 | Dalmia et al. | Apr 2009 | A1 |
20090106160 | Skowronek | Apr 2009 | A1 |
20090134217 | Flitcroft et al. | May 2009 | A1 |
20090157555 | Biffle et al. | Jun 2009 | A1 |
20090159673 | Mullen et al. | Jun 2009 | A1 |
20090159700 | Mullen et al. | Jun 2009 | A1 |
20090159707 | Mullen et al. | Jun 2009 | A1 |
20090173782 | Muscato | Jul 2009 | A1 |
20090200371 | Kean et al. | Aug 2009 | A1 |
20090248583 | Chhabra | Oct 2009 | A1 |
20090276347 | Kargman | Nov 2009 | A1 |
20090281948 | Carlson | Nov 2009 | A1 |
20090294527 | Brabson et al. | Dec 2009 | A1 |
20090307139 | Mardikar et al. | Dec 2009 | A1 |
20090308921 | Mullen | Dec 2009 | A1 |
20090327131 | Beenau et al. | Dec 2009 | A1 |
20100008535 | Abulafia et al. | Jan 2010 | A1 |
20100088237 | Wankmueller | Apr 2010 | A1 |
20100094755 | Kloster | Apr 2010 | A1 |
20100106644 | Annan et al. | Apr 2010 | A1 |
20100120408 | Beenau et al. | May 2010 | A1 |
20100133334 | Vadhri | Jun 2010 | A1 |
20100138347 | Chen | Jun 2010 | A1 |
20100145860 | Pelegero | Jun 2010 | A1 |
20100161433 | White | Jun 2010 | A1 |
20100185545 | Royyuru et al. | Jul 2010 | A1 |
20100211505 | Saunders et al. | Aug 2010 | A1 |
20100223186 | Hogan et al. | Sep 2010 | A1 |
20100228668 | Hogan et al. | Sep 2010 | A1 |
20100235284 | Moore | Sep 2010 | A1 |
20100258620 | Torreyson et al. | Oct 2010 | A1 |
20100291904 | Musfeldt et al. | Nov 2010 | A1 |
20100299267 | Faith et al. | Nov 2010 | A1 |
20100306076 | Taveau et al. | Dec 2010 | A1 |
20100325041 | Berardi et al. | Dec 2010 | A1 |
20110010292 | Giordano et al. | Jan 2011 | A1 |
20110016047 | Wu et al. | Jan 2011 | A1 |
20110016320 | Bergsten et al. | Jan 2011 | A1 |
20110040640 | Erikson | Feb 2011 | A1 |
20110047076 | Carlson et al. | Feb 2011 | A1 |
20110083018 | Kesanupalli et al. | Apr 2011 | A1 |
20110087596 | Dorsey | Apr 2011 | A1 |
20110093397 | Carlson et al. | Apr 2011 | A1 |
20110125597 | Oder, II et al. | May 2011 | A1 |
20110153437 | Archer et al. | Jun 2011 | A1 |
20110153496 | Royyuru | Jun 2011 | A1 |
20110153498 | Makhotin et al. | Jun 2011 | A1 |
20110154466 | Harper et al. | Jun 2011 | A1 |
20110161233 | Tieken | Jun 2011 | A1 |
20110178926 | Lindelsee et al. | Jul 2011 | A1 |
20110191244 | Dai | Aug 2011 | A1 |
20110191252 | Dai | Aug 2011 | A1 |
20110238511 | Park et al. | Sep 2011 | A1 |
20110238573 | Varadarajan | Sep 2011 | A1 |
20110246317 | Coppinger | Oct 2011 | A1 |
20110258111 | Raj et al. | Oct 2011 | A1 |
20110272471 | Mullen | Nov 2011 | A1 |
20110272478 | Mullen | Nov 2011 | A1 |
20110276380 | Mullen et al. | Nov 2011 | A1 |
20110276381 | Mullen et al. | Nov 2011 | A1 |
20110276424 | Mullen | Nov 2011 | A1 |
20110276425 | Mullen | Nov 2011 | A1 |
20110295745 | White et al. | Dec 2011 | A1 |
20110302081 | Saunders et al. | Dec 2011 | A1 |
20120023567 | Hammad | Jan 2012 | A1 |
20120028609 | Hruska | Feb 2012 | A1 |
20120030047 | Fuentes et al. | Feb 2012 | A1 |
20120035998 | Chien et al. | Feb 2012 | A1 |
20120041881 | Basu et al. | Feb 2012 | A1 |
20120047237 | Arvidsson et al. | Feb 2012 | A1 |
20120066078 | Kingston et al. | Mar 2012 | A1 |
20120072350 | Goldthwaite et al. | Mar 2012 | A1 |
20120078735 | Bauer et al. | Mar 2012 | A1 |
20120078798 | Downing et al. | Mar 2012 | A1 |
20120078799 | Jackson et al. | Mar 2012 | A1 |
20120095852 | Bauer et al. | Apr 2012 | A1 |
20120095865 | Doherty et al. | Apr 2012 | A1 |
20120116902 | Cardina et al. | May 2012 | A1 |
20120123882 | Carlson et al. | May 2012 | A1 |
20120123940 | Killian et al. | May 2012 | A1 |
20120129514 | Beenau et al. | May 2012 | A1 |
20120130898 | Snyder et al. | May 2012 | A1 |
20120136780 | El-Awady et al. | May 2012 | A1 |
20120143767 | Abadir | Jun 2012 | A1 |
20120143772 | Abadir | Jun 2012 | A1 |
20120158580 | Eram et al. | Jun 2012 | A1 |
20120158593 | Garfinkle et al. | Jun 2012 | A1 |
20120173431 | Ritchie et al. | Jul 2012 | A1 |
20120185386 | Salama et al. | Jul 2012 | A1 |
20120197807 | Schlesser et al. | Aug 2012 | A1 |
20120203664 | Torossian et al. | Aug 2012 | A1 |
20120203666 | Torossian et al. | Aug 2012 | A1 |
20120215688 | Musser et al. | Aug 2012 | A1 |
20120215696 | Salonen | Aug 2012 | A1 |
20120221421 | Hammad | Aug 2012 | A1 |
20120226582 | Hammad | Sep 2012 | A1 |
20120231844 | Coppinger | Sep 2012 | A1 |
20120233004 | Bercaw | Sep 2012 | A1 |
20120244885 | Hefetz | Sep 2012 | A1 |
20120246070 | Vadhri | Sep 2012 | A1 |
20120246071 | Jain et al. | Sep 2012 | A1 |
20120246079 | Wilson et al. | Sep 2012 | A1 |
20120265631 | Cronic et al. | Oct 2012 | A1 |
20120271770 | Harris et al. | Oct 2012 | A1 |
20120297446 | Webb et al. | Nov 2012 | A1 |
20120300932 | Cambridge et al. | Nov 2012 | A1 |
20120303503 | Cambridge et al. | Nov 2012 | A1 |
20120303961 | Kean et al. | Nov 2012 | A1 |
20120304273 | Bailey et al. | Nov 2012 | A1 |
20120310725 | Chien et al. | Dec 2012 | A1 |
20120310831 | Harris et al. | Dec 2012 | A1 |
20120310836 | Eden et al. | Dec 2012 | A1 |
20120316992 | Oborne | Dec 2012 | A1 |
20120317035 | Royyuru et al. | Dec 2012 | A1 |
20120317036 | Bower et al. | Dec 2012 | A1 |
20130017784 | Fisher | Jan 2013 | A1 |
20130018757 | Anderson et al. | Jan 2013 | A1 |
20130019098 | Gupta et al. | Jan 2013 | A1 |
20130030934 | Bakshi et al. | Jan 2013 | A1 |
20130031006 | McCullagh et al. | Jan 2013 | A1 |
20130054337 | Brendell et al. | Feb 2013 | A1 |
20130054466 | Muscato | Feb 2013 | A1 |
20130054474 | Yeager | Feb 2013 | A1 |
20130073463 | Dimmick et al. | Mar 2013 | A1 |
20130081122 | Svigals et al. | Mar 2013 | A1 |
20130091028 | Oder, II et al. | Apr 2013 | A1 |
20130110658 | Lyman et al. | May 2013 | A1 |
20130111599 | Gargiulo | May 2013 | A1 |
20130117185 | Collison et al. | May 2013 | A1 |
20130124290 | Fisher | May 2013 | A1 |
20130124291 | Fisher | May 2013 | A1 |
20130124364 | Mittal | May 2013 | A1 |
20130138525 | Bercaw | May 2013 | A1 |
20130144888 | Faith et al. | Jun 2013 | A1 |
20130145148 | Shablygin et al. | Jun 2013 | A1 |
20130145172 | Shablygin et al. | Jun 2013 | A1 |
20130159178 | Colon et al. | Jun 2013 | A1 |
20130159184 | Thaw | Jun 2013 | A1 |
20130166402 | Parento et al. | Jun 2013 | A1 |
20130166450 | Pama | Jun 2013 | A1 |
20130166456 | Zhang et al. | Jun 2013 | A1 |
20130173736 | Krzeminski et al. | Jul 2013 | A1 |
20130185202 | Goldthwaite et al. | Jul 2013 | A1 |
20130191286 | Cronic et al. | Jul 2013 | A1 |
20130191289 | Cronic et al. | Jul 2013 | A1 |
20130198071 | Jurss | Aug 2013 | A1 |
20130198080 | Anderson et al. | Aug 2013 | A1 |
20130200146 | Moghadam | Aug 2013 | A1 |
20130204787 | Dubois | Aug 2013 | A1 |
20130204793 | Kerridge et al. | Aug 2013 | A1 |
20130212007 | Mattsson et al. | Aug 2013 | A1 |
20130212017 | Bangia | Aug 2013 | A1 |
20130212019 | Mattsson et al. | Aug 2013 | A1 |
20130212024 | Mattsson et al. | Aug 2013 | A1 |
20130212026 | Powell et al. | Aug 2013 | A1 |
20130212666 | Mattsson et al. | Aug 2013 | A1 |
20130218698 | Moon et al. | Aug 2013 | A1 |
20130218769 | Pourfallah et al. | Aug 2013 | A1 |
20130226799 | Raj | Aug 2013 | A1 |
20130226813 | Voltz | Aug 2013 | A1 |
20130246199 | Carlson | Sep 2013 | A1 |
20130246202 | Tobin | Sep 2013 | A1 |
20130246203 | Laracey | Sep 2013 | A1 |
20130246258 | Dessert | Sep 2013 | A1 |
20130246259 | Dessert | Sep 2013 | A1 |
20130246261 | Purves et al. | Sep 2013 | A1 |
20130246267 | Tobin | Sep 2013 | A1 |
20130254028 | Salci | Sep 2013 | A1 |
20130254052 | Royyuru et al. | Sep 2013 | A1 |
20130254102 | Royyuru | Sep 2013 | A1 |
20130254117 | Von Mueller et al. | Sep 2013 | A1 |
20130262296 | Thomas et al. | Oct 2013 | A1 |
20130262302 | Lettow et al. | Oct 2013 | A1 |
20130262315 | Hruska | Oct 2013 | A1 |
20130262316 | Hruska | Oct 2013 | A1 |
20130262317 | Collinge et al. | Oct 2013 | A1 |
20130268776 | Motoyama | Oct 2013 | A1 |
20130275300 | Killian et al. | Oct 2013 | A1 |
20130275307 | Khan | Oct 2013 | A1 |
20130275308 | Paraskeva et al. | Oct 2013 | A1 |
20130282502 | Jooste | Oct 2013 | A1 |
20130282575 | Mullen et al. | Oct 2013 | A1 |
20130282588 | Hruska | Oct 2013 | A1 |
20130297501 | Monk et al. | Nov 2013 | A1 |
20130297504 | Nwokolo et al. | Nov 2013 | A1 |
20130297508 | Belamant | Nov 2013 | A1 |
20130304649 | Cronic et al. | Nov 2013 | A1 |
20130308778 | Fosmark et al. | Nov 2013 | A1 |
20130311382 | Fosmark et al. | Nov 2013 | A1 |
20130317886 | Kiran | Nov 2013 | A1 |
20130317982 | Mengerink et al. | Nov 2013 | A1 |
20130332344 | Weber | Dec 2013 | A1 |
20130339253 | Sincai | Dec 2013 | A1 |
20130346314 | Mogollon et al. | Dec 2013 | A1 |
20140007213 | Sanin et al. | Jan 2014 | A1 |
20140013106 | Redpath | Jan 2014 | A1 |
20140013114 | Redpath | Jan 2014 | A1 |
20140013452 | Aissi et al. | Jan 2014 | A1 |
20140019352 | Shrivastava | Jan 2014 | A1 |
20140025581 | Calman | Jan 2014 | A1 |
20140025585 | Calman | Jan 2014 | A1 |
20140025958 | Calman | Jan 2014 | A1 |
20140032417 | Mattsson | Jan 2014 | A1 |
20140032418 | Weber | Jan 2014 | A1 |
20140040137 | Carlson et al. | Feb 2014 | A1 |
20140040139 | Brudnicki et al. | Feb 2014 | A1 |
20140040144 | Plomske et al. | Feb 2014 | A1 |
20140040145 | Ozvat et al. | Feb 2014 | A1 |
20140040628 | Fort et al. | Feb 2014 | A1 |
20140041018 | Bomar et al. | Feb 2014 | A1 |
20140046853 | Spies et al. | Feb 2014 | A1 |
20140047551 | Nagasundaram et al. | Feb 2014 | A1 |
20140052532 | Tsai et al. | Feb 2014 | A1 |
20140052620 | Rogers et al. | Feb 2014 | A1 |
20140052637 | Jooste et al. | Feb 2014 | A1 |
20140068706 | Aissi | Mar 2014 | A1 |
20140074637 | Hammad | Mar 2014 | A1 |
20140074724 | Gordon et al. | Mar 2014 | A1 |
20140095331 | Wong | Apr 2014 | A1 |
20140108172 | Weber et al. | Apr 2014 | A1 |
20140108265 | Hayhow et al. | Apr 2014 | A1 |
20140114857 | Griggs et al. | Apr 2014 | A1 |
20140143137 | Carlson | May 2014 | A1 |
20140164243 | Aabye et al. | Jun 2014 | A1 |
20140188586 | Carpenter et al. | Jul 2014 | A1 |
20140294701 | Dai et al. | Oct 2014 | A1 |
20140297534 | Patterson | Oct 2014 | A1 |
20140310183 | Weber | Oct 2014 | A1 |
20140330721 | Wang | Nov 2014 | A1 |
20140330722 | Laxminarayanan et al. | Nov 2014 | A1 |
20140331265 | Mozell et al. | Nov 2014 | A1 |
20140337236 | Wong et al. | Nov 2014 | A1 |
20140344153 | Raj et al. | Nov 2014 | A1 |
20140372308 | Sheets | Dec 2014 | A1 |
20150019443 | Sheets et al. | Jan 2015 | A1 |
20150032625 | Dill et al. | Jan 2015 | A1 |
20150032626 | Dill et al. | Jan 2015 | A1 |
20150032627 | Dill et al. | Jan 2015 | A1 |
20150046338 | Laxminarayanan et al. | Feb 2015 | A1 |
20150046339 | Wong et al. | Feb 2015 | A1 |
20150052064 | Karpenko et al. | Feb 2015 | A1 |
20150088756 | Makhotin et al. | Mar 2015 | A1 |
20150106239 | Gaddam et al. | Apr 2015 | A1 |
20150112870 | Nagasundaram et al. | Apr 2015 | A1 |
20150112871 | Kumnick | Apr 2015 | A1 |
20150120472 | Aabye et al. | Apr 2015 | A1 |
20150127529 | Makhotin et al. | May 2015 | A1 |
20150127547 | Powell et al. | May 2015 | A1 |
20150140960 | Powell et al. | May 2015 | A1 |
20150142673 | Nelsen et al. | May 2015 | A1 |
20150161597 | Subramanian et al. | Jun 2015 | A1 |
20150178721 | Pandiarajan | Jun 2015 | A1 |
20150178724 | Ngo et al. | Jun 2015 | A1 |
20150180836 | Wong et al. | Jun 2015 | A1 |
20150186864 | Jones et al. | Jul 2015 | A1 |
20150193222 | Pirzadeh et al. | Jul 2015 | A1 |
20150195133 | Sheets et al. | Jul 2015 | A1 |
20150199679 | Palanisamy et al. | Jul 2015 | A1 |
20150199689 | Kumnick et al. | Jul 2015 | A1 |
20150220917 | Aabye et al. | Aug 2015 | A1 |
20150269566 | Gaddam et al. | Sep 2015 | A1 |
20150287037 | Salmon et al. | Oct 2015 | A1 |
20150312038 | Palanisamy | Oct 2015 | A1 |
20150319158 | Kumnick | Nov 2015 | A1 |
20150319161 | Dimmick | Nov 2015 | A1 |
20150332262 | Lingappa | Nov 2015 | A1 |
20150339664 | Wong et al. | Nov 2015 | A1 |
20150356560 | Shastry et al. | Dec 2015 | A1 |
20160028550 | Gaddam et al. | Jan 2016 | A1 |
20160042263 | Gaddam et al. | Feb 2016 | A1 |
20160065370 | Le Saint et al. | Mar 2016 | A1 |
20160092696 | Guglani et al. | Mar 2016 | A1 |
20160092872 | Prakash et al. | Mar 2016 | A1 |
20160103675 | Aabye et al. | Apr 2016 | A1 |
20160119296 | Laxminarayanan et al. | Apr 2016 | A1 |
20160140545 | Flurscheim et al. | May 2016 | A1 |
20160148197 | Dimmick | May 2016 | A1 |
20160148212 | Dimmick | May 2016 | A1 |
20160171479 | Prakash et al. | Jun 2016 | A1 |
20160173483 | Wong et al. | Jun 2016 | A1 |
20160224976 | Basu et al. | Aug 2016 | A1 |
20170046696 | Powell et al. | Feb 2017 | A1 |
20170103387 | Weber | Apr 2017 | A1 |
20170220818 | Nagasundaram et al. | Aug 2017 | A1 |
20170228723 | Taylor et al. | Aug 2017 | A1 |
Number | Date | Country |
---|---|---|
2156397 | Feb 2010 | EP |
0135304 | May 2001 | WO |
0135304 | May 2002 | WO |
2004042536 | May 2004 | WO |
2006113834 | Oct 2006 | WO |
2009032523 | May 2009 | WO |
2010078522 | Jul 2010 | WO |
2012068078 | May 2012 | WO |
2012098556 | Jul 2012 | WO |
2012142370 | Oct 2012 | WO |
2012167941 | Dec 2012 | WO |
2013048538 | Apr 2013 | WO |
2013056104 | Apr 2013 | WO |
2013119914 | Aug 2013 | WO |
2013179271 | Dec 2013 | WO |
2015168334 | Nov 2015 | WO |
2015179637 | Nov 2015 | WO |
Entry |
---|
R. K. Balan and N. Ramasubbu, “The Digital Wallet: Opportunities and Prototypes,” in Computer, vol. 42, No. 4, pp. 100-102, Apr. 2009, doi: 10.1109/MC.2009.134. (Year: 2009). |
“Petition for Inter Partes Review of U.S. Pat. No. 8,533,860 Challenging Claims 1-30 Under 35 U.S.C. § 312 and 37 C.F.R. § 42.104”, USPTO Patent Trial and Appeal Board, IPR 2016-00600, Feb. 17, 2016, 65 pages. |
U.S. Appl. No. 14/600,523, Secure Payment Processing Using Authorization Request, filed Jan. 20, 2015, 42 pages. |
U.S. Appl. No. 14/680,874 , Non-Final Office Action, dated Aug. 4, 2017, 13 pages. |
U.S. Appl. No. 14/680,874 , “Notice of Allowability”, dated Jun. 14, 2018, 5 pages. |
U.S. Appl. No. 14/680,874 , Notice of Allowance, dated Mar. 19, 2018, 9 pages. |
U.S. Appl. No. 14/719,014 , “Restriction Requirement”, dated May 26, 2016, 6 pages. |
U.S. Appl. No. 14/952,444 , Tokenization Request via Access Device, filed Nov. 25, 2015, 78 pages. |
U.S. Appl. No. 14/952,514 , Systems Communications With Non-Sensitive Identifiers, filed Nov. 25, 2015, 72 pages. |
U.S. Appl. No. 14/955,716 , Provisioning Platform for Machine-To-Machine Devices, filed Dec. 1, 2015, 61 pages. |
U.S. Appl. No. 14/966,948 , Automated Access Data Provisioning, filed Dec. 11, 2015, 52 pages. |
U.S. Appl. No. 15/004,705 , Cloud-Based Transactions With Magnetic Secure Transmission, filed Jan. 22, 2016, 161 pages. |
U.S. Appl. No. 15/008,388 , Methods for Secure Credential Provisioning, filed Jan. 27, 2016, 90 pages. |
U.S. Appl. No. 15/011,366 , Token Check Offline, filed Jan. 29, 2016, 60 pages. |
U.S. Appl. No. 15/019,157 , Token Processing Utilizing Multiple Authorizations, filed Feb. 9, 2016, 62 pages. |
U.S. Appl. No. 15/041,495 , Peer Forward Authorization of Digital Requests, filed Feb. 11, 2016, 63 pages. |
U.S. Appl. No. 15/265,282 , Self-Cleaning Token Valut, filed Sep. 14, 2016, 52 pages. |
U.S. Appl. No. 15/462,658 , Replacing Token on a Multi-Token User Device, filed Mar. 17, 2017, 58 pages. |
U.S. Appl. No. 61/738,832 , Management of Sensitive Data, filed Dec. 18, 2012, 22 pages. |
U.S. Appl. No. 61/751,763 , Payments Bridge, filed Jan. 11, 2013, 64 pages. |
U.S. Appl. No. 61/879,632 , Systems and Methods for Managing Mobile Cardholder Verification Methods, filed Sep. 18, 2013, 24 pages. |
U.S. Appl. No. 61/892,407 , Issuer Over-The-Air Update Method and System, filed Oct. 17, 2013, 28 pages. |
U.S. Appl. No. 61/894,749 , Methods and Systems for Authentication and Issuance of Tokens in a Secure Environment, filed Oct. 23, 2013, 67 pages. |
U.S. Appl. No. 61/926,236 , Methods and Systems for Provisioning Mobile Devices With Payment Credentials and Payment Token Identifiers, filed Jan. 10, 2014, 51 pages. |
U.S. Appl. No. 62/000,288 , Payment System Canonical Address Format, filed May 19, 2014, 58 pages. |
U.S. Appl. No. 62/003,717 , Mobile Merchant Application, filed May 28, 2014, 58 pages. |
U.S. Appl. No. 62/024,426 , Secure Transactions Using Mobile Devices, filed Jul. 14, 2014, 102 pages. |
U.S. Appl. No. 62/037,033 , Sharing Payment Token, filed Aug. 13, 2014, 36 pages. |
U.S. Appl. No. 62/038,174 , Customized Payment Gateway, filed Aug. 15, 2014, 42 pages. |
U.S. Appl. No. 62/042,050 , Payment Device Authentication and Authorization System, filed Aug. 26, 2014, 120 pages. |
U.S. Appl. No. 62/053,736 , Completing Transactions Without a User Payment Device, filed Sep. 22, 2014, 31 pages. |
U.S. Appl. No. 62/054,346 , Mirrored Token Vault, filed Sep. 23, 2014, 38 pages. |
U.S. Appl. No. 62/103,522 , Methods and Systems for Wallet Provider Provisioning, filed Jan. 14, 2015, 39 pages. |
U.S. Appl. No. 62/108,403 , Wearables With NFC HCE, filed Jan. 27, 2015, 32 pages. |
U.S. Appl. No. 62/117,291 , Token and Cryptogram Using Transaction Specific Information, filed Feb. 17, 2015, 25 pages. |
U.S. Appl. No. 62/128,709 , Tokenizing Transaction Amounts, filed Mar. 5, 2015, 30 pages. |
Fitzgerald , “Report: 3-D Secure not What Name Suggests”, American Banker, Feb. 3, 2010, 3 pages. |
Application No. PCT/US2015/028365 , International Search Report and Written Opinion, dated Jul. 30, 2015, 14 pages. |
Application No. PCT/US2015/031968 , International Search Report and Written Opinion, dated Jul. 27, 2015, 7 pages. |
Number | Date | Country | |
---|---|---|---|
20180293585 A1 | Oct 2018 | US |
Number | Date | Country | |
---|---|---|---|
61976989 | Apr 2014 | US |
Number | Date | Country | |
---|---|---|---|
Parent | 14680874 | Apr 2015 | US |
Child | 16008960 | US |