Abstract: A machine learning engine for fraud detection related to cross-location online transaction processing may be trained using artificial intelligence techniques and used according to techniques discussed herein. An account may be used to electronically process a transaction for an item in a foreign location, such as a new city or country. The transaction may be identified as potentially fraudulent based on the item and/or location of purchase. A service provider may identify a vertical, such as an item type, for the transaction, and may determine the account's propensity to purchase within that vertical in the new location and the merchant's propensity to sell within that vertical to the account's location or shipping address. Based on the propensities, the service provider may utilize one or more risk rules with a risk assessment engine to determine transaction processing risk and whether to proceed with transaction processing.

Abstract: A machine learning engine for fraud detection related to cross-location online transaction processing may be trained using artificial intelligence techniques and used according to techniques discussed herein. An account may be used to electronically process a transaction for an item in a foreign location, such as a new city or country. The transaction may be identified as potentially fraudulent based on the item and/or location of purchase. A service provider may identify a vertical, such as an item type, for the transaction, and may determine the account's propensity to purchase within that vertical in the new location and the merchant's propensity to sell within that vertical to the account's location or shipping address. Based on the propensities, the service provider may utilize one or more risk rules with a risk assessment engine to determine transaction processing risk and whether to proceed with transaction processing.

Abstract: A machine learning engine for fraud detection related to cross-location online transaction processing may be trained using artificial intelligence techniques and used according to techniques discussed herein. An account may be used to electronically process a transaction for an item in a foreign location, such as a new city or country. The transaction may be identified as potentially fraudulent based on the item and/or location of purchase. A service provider may identify a vertical, such as an item type, for the transaction, and may determine the account's propensity to purchase within that vertical in the new location and the merchant's propensity to sell within that vertical to the account's location or shipping address. Based on the propensities, the service provider may utilize one or more risk rules with a risk assessment engine to determine transaction processing risk and whether to proceed with transaction processing.

Abstract: A machine learning engine for identification of related vertical groupings may be trained using artificial intelligence and machine techniques and used according to techniques discussed herein. A consumer account may be used to process transactions electronically with merchants. The consumer account may therefore be linked to a transaction history, which may be processed to identify the consumer's vertical transaction list for verticals of previous transactions. This may be aggregated for a merchant used by the consumer, and may be weighted before sending back to the consumer. Multiple iterations of aggregating and weighing the merchant and consumer lists may be applied to determine highest ranked verticals for consumers and merchants based on multiple degrees of separation between certain merchants and consumers. Using the weighted lists, verticals may be identified for consumers that the consumer may not have previously transacted within, which may be used to provide a recommendation.

Abstract: Aspects of the present disclosure involve systems, methods, devices, and the like for augmented media intelligence using Artificial Intelligence (AI), Machine Learning (ML), Natural Language Processing (NLP), data analytics and data visualization. In one embodiment, a system is introduced that can retrieve real-time data from social media platforms to perform augmented media intelligence analysis and take real time actions if necessary. In another embodiment, the augmented media intelligence is design to use the machine learning and natural language processing capabilities to determine a resilience measure for determining how to respond to a media event.