Abstract: A system, includes a non-transitory memory; and one or more hardware processors coupled to the non-transitory memory and configured to read instructions from the non-transitory memory to cause the system to perform operations comprising: transmitting a message from an application client to a service to request content from the service; ascertaining a failure of the service to provide the requested content; and in response to ascertaining the failure, applying data from the application client to an application in lieu of the requested content.

Abstract: Methods and systems are presented for predicting a likelihood of an occurrence of an event, such as a dispute or a chargeback, associated with an electronic transaction based on monitoring user interactions of a user with one or more computing systems after the electronic transaction has been conducted. The electronic transaction may involve a purchase of a product and/or service from a merchant. After the transaction is conducted, user interactions of the user with the one or more computer systems, such as a website of the merchant involved in the transaction, a website of another merchant, and a website of a payment service provider may be monitored. A machine learning model may then be used to predict whether the event associated with the transaction will occur in the future based on the monitored user interactions.

Abstract: A risk analysis system configures the decision engine to detect anomalous online activities by analyzing usage patterns associated with one or more user accounts across multiple frequencies. The risk analysis system obtains transaction log data representing transactions associated with one or more accounts, and extracts data from the transaction log data to generate time-series data along a time dimension. The time-series data may represent usage characteristics of one or more user accounts over a period of time. The risk analysis system derives pattern data representing usage patterns across multiple different frequencies based on the time-series data. The risk analysis system then configures the decision engine to detect anomalous account activities based on the derived pattern data.

Abstract: Systems and method for splitting a bill offline include detecting one or more local devices using local wireless communications provided by a peer-to-peer communication module. At least one payer device of the one or more local devices is selected for apportioning a primary bill. An offline payment authorization is then received from each at least one payer device through local wireless communications provided by the peer-to-peer communication module. When an Internet connection is later detected, the system provider connects to the Internet and sends the offline payment authorization received from each at least one payer device to a payment provider device over the Internet. The payment provider device may then transfer funds from account(s) of the at least one payer device to the account of the system provider.

Abstract: Methods and systems for using machine learning to determine an origin of an alphanumeric code are presented. The code is analyzed to determine a set of characteristics based on the values and the types of values within the code. The code and the set of characteristics may then be embedded into an image. To embed the code and the set of characteristics into an image, each of the code and the set of characteristics may be converted into a corresponding set of pixel values. The pixel values may then be combined to form the pixels in the image. The image is provided to a machine learning model as input. The machine learning model is configured to use the image to determine at least one entity that is associated with the code.

Abstract: A computer system receives a first information detailing a TLS fingerprint. A computer system determines an amount of bad transactions associated with the TLS fingerprint, wherein a bad transaction is a transaction involved in one or more fraudulent activities. The computer system determines whether the amount of bad transactions associated with the TLS fingerprint exceeds a threshold amount.

Abstract: A device may collect environmental information surrounding the device. Based on the collected environmental information, the device may automatically identify a potentially secured location that has lower security risk. When a potentially secured location is identified, the device may prompt the user to setup a security profile having reduced security requirement for the secured location. The device may store and associate the security profile with the secured location. The device may activate the security profile with reduced security requirement when the device is in the secured area. Further, the security profile may require that certain features of the device be disabled when the device is in the secured location.

Abstract: Techniques are disclosed relating to implementing a machine learning approach to cross-language translation and search. In certain embodiments, a method may include receiving a plurality of characters of a first language that are unsegmented and grouping the plurality of character into multiple groups. The method also includes determining a set of word tokens based on one or more transliterations of the multiple groups and one or more translations of the multiple groups to a second language. Further, the method includes generating one or more word token solution sets by querying an index file using the one or more word tokens. The method also includes determining whether the index file references an entity name corresponding to the plurality of characters of the first language based on comparing the one or more token solution sets with the index file.

Abstract: Systems and methods for a mixed deployment architecture are provided. A data center system may include a core compute grid system and a plurality of distributed compute grid systems. The core compute grid system may provide one or more non-distributable services for a payment service provider, such as a database service, and may include one or more isolated environment zones. Each distributed compute grid system provides one or more distributable services for the payment service provider, and each distributed compute grid system provides an identical set of distributable services. The data center system also includes a network coupling the core compute grid system and plurality of distributed compute grid systems. The plurality of distributed compute grid systems transmit queued writes generated by the distributable services to the database service provided by the core compute grid system.

Abstract: Operations may include providing, by an account management system of a first entity, a user interface to a third-party electronic device. The user interface may present an account access agreement that authorizes a second entity to access a third-party account managed by the account management system and owned by a third entity. The operations may further include generating, by the account management system, based on an indication that the third entity accepts the account access agreement, an account access token that is assigned to the third-party account and the second entity and that indicates that the third entity has authorized the second entity to access the third-party account. In addition, the operations may include communicating the account access token to a platform management system of the second entity such that the account access token provides the platform management system a mechanism to access the third-party account.

Abstract: The disclosure generally relates to the field of graphical user interfaces and particular it relates to a method of deleting a graphical user interface object, and to a corresponding electronic device and computer program. In particular the disclosure relates to a method, at an electronic device with a touch display and at least one user feedback mechanism for deleting a user interface object, wherein user feedback is provided, in response to the, facilitated by one of the at least one of the user feedback mechanisms.

Abstract: Methods and systems for detecting passive malicious network-mapping software on a computer network are disclosed. An expected location within a computer system for storing a received data packet may be determined. An actual storage location of the received data packet may be identified and compared to the expected storage location. In the event that the expected location does not match the actual storage location of the received data packet on the computer system, the presence of passive malicious network-mapping software such as a sniffer may be detected.

Abstract: Methods and systems are presented for providing concurrent data retrieval and risk processing while evaluating a risk source of an online service provider. Upon receiving a request to evaluate the risk source, a risk analysis module may initiate one or more risk evaluation sub-processes to evaluate the risk source. Each risk evaluation sub-process may require different data related to the risk source to perform the evaluation. The risk analysis module may simultaneously retrieve the data related to the risk source and perform the one or more risk evaluation sub-processes such that the risk analysis module may complete a risk evaluation sub-process whenever the data required by the risk evaluation sub-process is made available.

Abstract: A system and method for preventing hidden data being passed using steganography by performing additional steganography to obscure the hidden data such that the hidden data is unrecoverable without information regarding the method of the additional steganography. This system and method allows for preventing hidden data without having to decipher the hidden data.

Abstract: A method for offering at least one credit product by at least one credit issuer to a consumer at a point-of-sale between a merchant and the consumer. The method includes the steps of: providing a credit issuer data set including a plurality of data fields to a central database; initiating a transaction between the consumer and the merchant at the point-of-sale; offering, to the consumer at the point-of-sale, the at least one credit product; and presenting, to the consumer at the point-of-sale, at least one data field in the credit issuer data set. The at least one data field presented to the consumer is populated with data directed to the credit product, the credit issuer, or any combination thereof. An apparatus and system are also disclosed.

Abstract: Systems and methods are provided for online transactions using pattern recognition. A user of a payment provider may create and register patterns drawn by the user on a pattern entry image. The user may register the patterns by associating transaction options with each drawn pattern. Each pattern may be used to execute a particular transaction such as a purchase transaction, a payment of a specific amount, a payment to a specific recipient, or a sales transaction. When the user wishes to execute a transaction such as an online payment to a particular recipient for a particular amount, the user can redraw the registered pattern associated with payments to that recipient for that amount. A pattern can be drawn at a particular location on the pattern entry image. Different transactions can be associated with patterns drawn at different locations.

Abstract: Methods and systems for providing information to a user are described. Multiple mobile devices can individually collect data and feed the data to beacons in a location. The information can include sound data, light data, motion data, health and wellness related data, humidity data, and/or temperature data. The beacons receive this data from multiple users and transmit it to a service provider. The service provider collects the data from the beacons and provides the data to one or more users.

Abstract: Embodiments of systems and methods are provided for an authentication device that enables transactions with a payment instrument at different limitations, restrictions and/or use conditions. In an embodiment, a system comprises a receiver configured to receive, through an authentication device, authentication information associated with a user of the authentication device or with a payment instrument, wherein the payment instrument communicates with the authentication device, and the payment instrument has a first limitation that does not need pre-authorization.

Abstract: There are provided systems and methods for transportation check-in and payment using beacons. A service provider, such as a transportation, payment, or other service provider, may utilize short range wireless beacons at or near a transportation service that provide automated check-in with a user device. When the user device is in proximity to the beacon, the user may be checked-in and provide payments for use of the transportation service, such as payment for a transportation fare. The user may receive scheduling and/or updates for the transportation service. Additionally, while the user is travelling with the transportation service, the user may purchase extra fare if the user realizes that current travel coverage of the purchased transportation fare does not cover an expected cost of the trip. The extra fare may be automatically purchased if the user device loses power or the user is unaware of the trip cost.

Abstract: Techniques are disclosed relating to scoring partial matches between words. In certain embodiments, a method may include receiving a request to determine a similarity between an input text data and a stored text data. The method also includes determining, based on comparing one or more words included in the input text data with one or more words included in the stored text data, a set of word pairs and a set of unpaired words. Further, in response to determining that the set of unpaired words passes elimination criteria, the method includes calculating a base similarity score between the input text data and the stored text data based on the set of word pairs. The method also includes determining a scoring penalty based on the set of unpaired words and generating a final similarity score between the input text data and the stored text data by modifying the base similarity score based on the scoring penalty.