Abstract: Systems and methods for preventing fraud using behavioral biometrics may include a server with memory and a processor. The processor may be configured to create a behavioral biometric use-print for a user based on a plurality of observed and recorded user interactions and then monitor one or more behavioral biometrics of the user while the user accesses a user account. These monitored behavioral biometrics may be compared against the behavioral biometric use-print to determine if there are material deviations indicating that the user is under stress. When the server determines that the user is under stress, it may provide an intervention to help safeguard against potential in-process fraud.

Abstract: The present embodiments disclose systems and methods for authenticating a user with behavioral biometrics associated with a card. The card includes an accelerometer configured to measure the orientation of the card body. The system includes the card and a software application. The software application generates a user profile based on observed card biometrics, then determines whether a recent transaction significantly deviates from the profile.

Abstract: Methods and systems for estimating a vehicle status using interaction data are disclosed. An exemplary method can include obtaining, via at least one processor, information associated with a vehicle; obtaining, via the at least one processor, a set of interaction data of an individual associated with the vehicle; and accessing, via the at least one processor and on a memory, a framework indicative of an association between interaction data and vehicles status. An exemplary method may further include generating, via the at least one processor and by applying the framework to the set of interaction data and the information associated with the vehicle, an estimate of the vehicle status; generating, via the at least one processor and based on the estimate of the vehicle status, at least one evaluation for the vehicle; and outputting the at least one evaluation.

Abstract: Various embodiments are directed to a system or platform with machine learning capabilities configured to accurately predict in real-time a depreciation factor of a vehicle associated with a customer and further accurately predict a present value of the vehicle based at least in part on card transaction data associated with the customer. Based on one or more factors, such as a determination that the present value of the vehicle falls below a predefined threshold value, one or more auto financing products may be generated and provided to the customer by the system.

Abstract: Provided are compact transaction cards. In some approaches, a body of the card includes first and second sections rotatably coupled together, wherein the first and second sections define a first main side opposite a second main side, an insertion end perimeter opposite a second end perimeter, and a first side perimeter opposite a second side perimeter. The body may include a chip along the first main side, the chip being located on the first section of the body. A magnetic stripe may be provided along the second main side of the body, wherein the magnetic stripe is located on the second section, wherein the magnetic stripe extends parallel to the insertion end perimeter when the first and second sections are in a first configuration, and wherein the magnetic stripe extends perpendicular to the insertion end perimeter when the first and second sections are in a second configuration.

Abstract: Systems and methods for secure prediction can include a memory and a processor that is configured to retrieve location information associated with a user account and calculate an average spend over one or more route options for a first period of time based on the location information. The processor can be configured to apply a predictive model to the average spend to determine a predicted utilization amount, identify one or more users that have a user utilization amount exceeding the predicted utilization amount, transmit one or more notifications to adjust the user utilization amount from a first value to a second value for a second period of time, and receive one or more responses that are responsive to the one or more notifications. The processor can be configured to adjust the user utilization amount to the second value and revert the user utilization amount back to the first value.

Abstract: Provided are compact transaction cards. In some approaches, a body of the card includes first and second sections rotatably coupled together, wherein the first and second sections define a first main side opposite a second main side, an insertion end perimeter opposite a second end perimeter, and a first side perimeter opposite a second side perimeter. The body may include a chip along the first main side, the chip being located on the first section of the body. A magnetic stripe may be provided along the second main side of the body, wherein the magnetic stripe is located on the second section, wherein the magnetic stripe extends parallel to the insertion end perimeter when the first and second sections are in a first configuration, and wherein the magnetic stripe extends perpendicular to the insertion end perimeter when the first and second sections are in a second configuration.

Abstract: Embodiments discussed herein are generally directed to systems, devices, methods, and techniques to perform authentication and payment operations with a contactless card to provide items and services.

Abstract: Provided are compact transaction cards. In some approaches, a transaction card may include a body having first and second main sides, a first and second end perimeter perimeters, and first and second side perimeters, wherein a first axis extending between the first and second side perimeters defines a first section of the body and a second section of the body. The card may further include an identification chip along the first main side and a magnetic stripe along the second main side, wherein the magnetic stripe extends between the first and second side perimeters, and wherein the magnetic stripe and the identification chip are located on the first section of the body. The card may further include a textured grip along at least one of the first main side and the second main side, wherein the textured grip is positioned only on the second section of the body.

Abstract: Various embodiments are directed to a system or platform with machine learning capabilities configured to accurately predict in real-time a depreciation factor of a vehicle associated with a customer and further accurately predict a present value of the vehicle based at least in part on card transaction data associated with the customer. Based on one or more factors, such as a determination that the present value of the vehicle falls below a predefined threshold value, one or more auto financing products may be generated and provided to the customer by the system.