Abstract: Arrangements for adjusting a movable display portion of a self-service kiosk are provided. In some aspects, sensor data may be received from one or more sensors associated with a self-service kiosk. The sensor data may be analyzed to determine one or more dimensions of the vehicle. Based on the analyzed sensor data, a position to which a movable display portion of the self-service kiosk should be adjusted may be identified. In some examples, an instruction causing the movable display portion to adjust from a first, current position to the identified adjusted position may be generated and executed. The user may then initiate the transaction using one or more components of the self-service kiosk in the adjusted, second position. The transaction may be processed by the self-service kiosk. When the transaction is completed, an instruction causing the movable display portion to return to the first position may be generated and executed.

Abstract: Arrangements for controlling transaction processing via linked devices are provided. In some aspects, customer linking data may be received from a user. For instance, a user may identify one or more user computing devices, as well as one or more payment devices, such as credit cards, debit cards, and the like. The customer linking data may include an indication to link the user computing devices to the payment devices in order to execute one or more rules limiting transaction processing associated with the payment devices. A request to process a transaction and transaction details may be received from an external entity computing system. The request for transaction and transaction details may be analyzed to determine whether the user computing device is linked to the payment device. If so, the transaction may be authorized and processed. If not, additional authentication data may be requested.

Abstract: An apparatus is configured to receive a complaint initiation signal that includes an indication that a card reader may be compromised, and initiation date and time of the complaint, and geolocation data related to the reporting party. The apparatus is further configured to identify a street address closest to the geolocation data in the complaint using a geolocation application programming interface and the set of geolocation data. The apparatus is also configured to determine that the identified street address is associated with an entity. The apparatus then calculates a confidence interval as to whether that entity is the type of entity that uses a card reader. The apparatus is further configured to determine that the confidence interval exceeds a threshold. The apparatus is also configured to determine an identifier of the entity. Further, the apparatus is configured to publish an alert to a data feed.

Abstract: Systems for dynamically detecting and controlling unauthorized events are presented. In some examples, data may be received from one or more computing systems. In some examples, the computing systems may each be associated with an enterprise unit within an enterprise organization. The data may include, in some examples, processed unauthorized activity event data, such as account takeover event data. The data received may be aggregated and analyzed (e.g., using machine learning) to identify potential threats and threat outputs. In some examples, the threat output may include a user interface indicating the threat or potential threat, systems or applications potentially impacted, enterprise units impacted, and the like. Based on the threat output, one or more mitigation actions may be identified and executed. The mitigation actions may include modifying operation of one or more systems, modifying authentication requirements, and the like.

Abstract: A device that is configured to capture biometric information for a user using a first biometric sensor that is configured to capture biometric information that identifies physical characteristics of the user. The device is further configured to capture device information for a user device that is associated with the user. The device is further configured to generate an authentication fingerprint for the user based on a combination of the biometric information and the device information. The device is further configured to obtain vital sign information using a second biometric sensor that is configured to capture vital sign information that identifies a physical state of the user. The device is further configured to generate an authentication request that includes the authentication fingerprint and the vital sign information and to send the authentication request to a network device.

Abstract: A device that is configured to receive an authentication request for a first user. The authentication request includes a first authentication fingerprint and a first vital sign information. The device is further configured to identify a second authentication fingerprint from a memory that matches the first authentication fingerprint and to identify a second vital sign information that is associated with the second authentication fingerprint. The device is further configured to compare the first vital sign information from the authentication request to a tolerance threshold value. The device is further configured to generate an authentication response based on the comparison and to send the authentication response to a network device.

Abstract: An apparatus is configured to receive a complaint initiation signal that includes an indication that a card reader may be compromised, and initiation date and time of the complaint, and geolocation data related to the reporting party. The apparatus is further configured to identify a street address closest to the geolocation data in the complaint using a geolocation application programming interface and the set of geolocation data. The apparatus is also configured to determine that the identified street address is associated with an entity. The apparatus then calculates a confidence interval as to whether that entity is the type of entity that uses a card reader. The apparatus is further configured to determine that the confidence interval exceeds a threshold. The apparatus is also configured to determine an identifier of the entity. Further, the apparatus is configured to publish an alert to a data feed.

Abstract: Arrangements for dynamic system control evaluation and issue identification and mitigation are provided. In some examples, data may be received from a plurality of sources. The data may be received in batches at predetermined intervals or time periods, and/or as streaming data. In some examples, a first system control may be identified and a first system control value may be determined for the first system control. A plurality of threshold ranges associated with the first system control may be identified and the first system control value may be compared to the plurality of threshold ranges. Based on the comparing, the first system control value may be mapped to an objective score on a cyber health scale. The objective score may then be evaluated to determine whether an issue is occurring or is likely to occur. If so, one or more mitigation actions may be identified and implemented.

Abstract: An apparatus is configured to receive a data feed. The data feed includes location data of a first card reader that may be compromised and an identifier of the party that initiated the alert. The apparatus is further configured to determine that the location data of the first card reader matches a location identifier associated with a first card reader owner profile. The apparatus is also configured to determine that the owner of the card reader is not the entity receiving the alert. The apparatus then determines that there is not a match between the identifier of the party that initiated the alert and a user identifier from a plurality of user account profiles. The apparatus is further configured to transmit a message to the card reader owner indicating that the card reader may be compromised.

Abstract: Systems for dynamically detecting and controlling unauthorized events are presented. In some examples, data may be received from one or more computing systems. In some examples, the computing systems may each be associated with an enterprise unit within an enterprise organization. The data may include, in some examples, processed unauthorized activity event data, such as account takeover event data. The data received may be aggregated and analyzed (e.g., using machine learning) to identify potential threats and threat outputs. In some examples, the threat output may include a user interface indicating the threat or potential threat, systems or applications potentially impacted, enterprise units impacted, and the like. Based on the threat output, one or more mitigation actions may be identified and executed. The mitigation actions may include modifying operation of one or more systems, modifying authentication requirements, and the like.

Abstract: Arrangements for dynamic system control evaluation and issue identification and mitigation are provided. In some examples, data may be received from a plurality of sources. The data may be received in batches at predetermined intervals or time periods, and/or as streaming data. In some examples, a first system control may be identified and a first system control value may be determined for the first system control. A plurality of threshold ranges associated with the first system control may be identified and the first system control value may be compared to the plurality of threshold ranges. Based on the comparing, the first system control value may be mapped to an objective score on a cyber health scale. The objective score may then be evaluated to determine whether an issue is occurring or is likely to occur. If so, one or more mitigation actions may be identified and implemented.