Abstract: A fraud detection and protection method and system are disclosed. The method and system utilize a fraud detection and protection server to monitor online commercial transactions between a webserver and a client computer, and generate a risk assessment of a user associated with the client computer. The system and method further utilize a number of beacon servers geographically dispersed in an area. Each beacon server is configured to receive packet header information associated with the online commercial transactions, analyze the packet header information for authenticating information, and send the authenticating information to the fraud detection and protection server for the risk assessment.

Abstract: A method for detecting likely fraud is described. The method includes obtaining from a first financial organization first information relating to a first financial account indicative of financial performance for the first financial account, obtaining from a second financial organization independent of the first financial organization second information relating to a second financial account indicative of financial performance for the second financial account, and determining if the first financial account and the second financial account relate to a common customer, and if they do, analyzing the first information and the second information to determine a likelihood of fraud in one of the accounts.

Abstract: A system and method for protecting identity fraud are disclosed. A system includes a detection subsystem to identify applications and/or accounts at risk of identity fraud, and a disposition subsystem to process data provided by the detection system and to determine whether identity fraud exists in the applications and/or accounts. According to an implementation, one or more neural network models are defined, each neural network model being configured to handle a class of cases related to the subject and a specific data configuration describing a case of the class. The one or more neural network models are run to generate data requests about the subject's identity, and the data requests are passed to a detection system that monitor transactions associated with the subject. Additional data associated with the transactions is requested until a threshold certainty is achieved or until available data or models are exhausted.