Abstract: This disclosure relates to detecting fraudulent transactions in a multi-user account based on multimodal data that reflects the actions of multiple users of the account. A system and process may receive transaction requests associated with the multi-user account from multiple users at multiple user-interactive computers. A server receives the transaction requests from the user-interactive computers. The server may also receive multimodal data, such as audio, video, biometric, and other data that provides information about the actions of at least two of the users. The server analyzes the transaction requests and multimodal data to detect correlations between the user's actions and transaction requests that may be indicative of an unauthorized or fraudulent transaction.

Abstract: This disclosure relates to protecting data in a distributed network. Data may be maintained across multiple endpoint devices, where different logical or geographical branches of the network have different data classification ratings that indicate different capabilities and limitations on data transfer and storage. Computer processes provide data governance in the distributed network to manage and transfer data through the network efficiently, provide predictive processing, and prevent unauthorized access to the data through sanitization and manipulation of the data. Artificial intelligence models may be leveraged to monitor data flow in the network and autonomously modify the network or data to enable multiple restricted data sources to be used together in a common workflow efficiently and securely.

Abstract: This disclosure relates to protecting data in a distributed network. Data may be maintained across multiple endpoint devices, where different logical or geographical branches of the network have different data classification ratings that indicate different capabilities and limitations on data transfer and storage. Computer processes provide data governance in the distributed network to manage and transfer data through the network efficiently, provide predictive processing, and prevent unauthorized access to the data through sanitization and manipulation of the data. Artificial intelligence models may be leveraged to monitor data flow in the network and autonomously modify the network or data to enable multiple restricted data sources to be used together in a common workflow efficiently and securely.

Abstract: This disclosure relates to protecting data in a distributed network. Data may be maintained across multiple endpoint devices, where different logical or geographical branches of the network have different data classification ratings that indicate different capabilities and limitations on data transfer and storage. Computer processes provide data governance in the distributed network to manage and transfer data through the network efficiently, provide predictive processing, and prevent unauthorized access to the data through sanitization and manipulation of the data. Artificial intelligence models may be leveraged to monitor data flow in the network and autonomously modify the network or data to enable multiple restricted data sources to be used together in a common workflow efficiently and securely.