American Express Travel Related Services

System, method, and computer program product embodiments detect misinformation based on received inferencing data that includes textual or media content. A data vector is derived from one or more samples of the inferencing data. Quantum computing hardware is commanded to select a plurality of features of the data vector using a quantum approximate optimization algorithm (QAOA). Quantum computing hardware is commanded to classify the inferencing data as one of misinformation or genuine information using a quantum support vector machine (QSVM) provided with the selected plurality of features of the data vector. A signal based on the classification is received, and based on the signal indicating that the classification made by the QSVM is indicative that the content includes misinformation, a notification or alert to a human user or an automated system is generated, warning that the content includes misinformation.

Disclosed herein are system, method, and computer program product embodiments for generating and customizing micro agents. An embodiment comprises receiving, from a user device, a request to customize template agents. The embodiment further comprises selecting a set of template agents, receiving a selection of at least at template agent, personalizing the a least the template agent to obtain a micro agent, receiving from the user device a request to complete one or more tasks associated with a service provider system, transmitting using the micro agent, a command to the service provider system to perform the one or more tasks, and transmitting, to the user device, a notification indicating that the one or more tasks are completed.

Disclosed are various approaches for configuring and issuing a temporary instrument derivative to a primary account. A computing device can be configured to receive a request to designate a temporary user for a primary instrument (129), where the request identifying temporary user data (136). Next, the computing device can determine one or more provisioning rules (123) for a temporary instrument (119) based at least in part on the request and send an authentication request (133) to the temporary user based at least in part on the temporary user data (136). After receiving an authentication response based at least in part on the authentication request, the computing device can issue the temporary instrument (119) to the temporary user.

Disclosed are various approaches for language model based options selections. In one example, a service (122) can generate a user interface (167) that identifies user interactions received from a client device (106) to register transaction instruments. Transaction facilitation websites (152) can be scraped to identify transaction instrument terms for the registered transaction instruments (173). An option selection language model (126) can be generated and trained to select a subset of the registered transaction instruments (173). The option selection language model (126), the transaction instrument data (172), and the transaction instrument terms (156) can be transmitted to the client device (106).

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