Abstract: Disclosed are systems and methods for mitigation of fraudulent transactions. In some embodiments, a server is communicatively coupled to a user device, and is configured to receive a proposed transaction from a merchant device communicatively coupled to the server, apply a dynamic classification algorithm to the proposed transaction to determine if the proposed transactions appears to be fraudulent, generate a user verification request when the proposed transaction appears to be fraudulent, transmit the user verification request to a user computing device communicatively coupled to the server, receive an approval or a refusal of the proposed transaction based on the user verification request, and process the proposed transaction based on the received approval or refusal of the proposed transaction.

Abstract: Disclosed are systems and methods for mitigation of fraudulent transactions. In some embodiments, a server is communicatively coupled to a user device, and is configured to receive a proposed transaction from a merchant device communicatively coupled to the server, apply a dynamic classification algorithm to the proposed transaction to determine if the proposed transactions appears to be fraudulent, generate a user verification request when the proposed transaction appears to be fraudulent, transmit the user verification request to a user computing device communicatively coupled to the server, receive an approval or a refusal of the proposed transaction based on the user verification request, and process the proposed transaction based on the received approval or refusal of the proposed transaction.

Abstract: Disclosed are systems and methods for mitigation of fraudulent transactions. In some embodiments, a server is communicatively coupled to a user device, and is configured to receive a proposed transaction from a merchant device communicatively coupled to the server, apply a dynamic classification algorithm to the proposed transaction to determine if the proposed transactions appears to be fraudulent, generate a user verification request when the proposed transaction appears to be fraudulent, transmit the user verification request to a user computing device communicatively coupled to the server, receive an approval or a refusal of the proposed transaction based on the user verification request, and process the proposed transaction based on the received approval or refusal of the proposed transaction.

Abstract: Various embodiments described herein are generally directed to techniques for identifying the availability of an enterprise to provide products, for example, banking products and/or services. Embodiments may include using an availability manager informed by resource status data to determine if an enterprise facility is available to provide at least one product. In some embodiments, at least some data used to determine the availability of an enterprise facility may be collected from sensors and/or transducers associated with the enterprise facility. Various embodiments may include using a machine learning model to analyze enterprise resource availability to determine enterprise facility availability to provide products. In some aspects described herein, at least one record may be updated with resource status information, facility availability, available product set information, and/or estimated lead time information.

Abstract: Systems, methods, apparatuses, and computer program products to determine delivery times based on a delivery address. A request may be from an application executing on a mobile device specifying a delivery address for delivery of an item. A plurality of delivery times may be received from a plurality of delivery services, the plurality of delivery times based on a time at the delivery address. Selection of a first delivery time may be received from the application. A pickup location and a pickup time may be determined. A request to deliver the item to the delivery address may be transmitted to a first delivery service. Acceptance of the request may be received from the first delivery service. A confirmation may be transmitted to the application. An indication of the order may be stored in a database.

Abstract: Various embodiments described herein are generally directed to techniques for identifying the availability of an enterprise to provide products, for example, banking products and/or services. Embodiments may include using an availability manager informed by resource status data to determine if an enterprise facility is available to provide at least one product. In some embodiments, at least some data used to determine the availability of an enterprise facility may be collected from sensors and/or transducers associated with the enterprise facility. Various embodiments may include using a machine learning model to analyze enterprise resource availability to determine enterprise facility availability to provide products. In some aspects described herein, at least one record may be updated with resource status information, facility availability, available product set information, and/or estimated lead time information.

Abstract: Various embodiments described herein are generally directed to techniques for identifying the availability of an enterprise to provide products, for example, banking products and/or services. Embodiments may include using an availability manager informed by resource status data to determine if an enterprise facility is available to provide at least one product. In some embodiments, at least some data used to determine the availability of an enterprise facility may be collected from sensors and/or transducers associated with the enterprise facility. Various embodiments may include using a machine learning model to analyze enterprise resource availability to determine enterprise facility availability to provide products. In some aspects described herein, at least one record may be updated with resource status information, facility availability, available product set information, and/or estimated lead time information.

Abstract: Disclosed are systems and methods for mitigation of fraudulent transactions. In some embodiments, a server is communicatively coupled to a user device, and is configured to receive a proposed transaction from a merchant device communicatively coupled to the server, apply a dynamic classification algorithm to the proposed transaction to determine if the proposed transactions appears to be fraudulent, generate a user verification request when the proposed transaction appears to be fraudulent, transmit the user verification request to a user computing device communicatively coupled to the server, receive an approval or a refusal of the proposed transaction based on the user verification request, and process the proposed transaction based on the received approval or refusal of the proposed transaction.

Abstract: Disclosed are systems and methods for mitigation of fraudulent transactions. In some embodiments, a server is communicatively coupled to a user device, and is configured to receive a proposed transaction from a merchant device communicatively coupled to the server, apply a dynamic classification algorithm to the proposed transaction to determine if the proposed transactions appears to be fraudulent, generate a user verification request when the proposed transaction appears to be fraudulent, transmit the user verification request to a user computing device communicatively coupled to the server, receive an approval or a refusal of the proposed transaction based on the user verification request, and process the proposed transaction based on the received approval or refusal of the proposed transaction.