Abstract: A computer based method and system for advanced scenario based alert generation and processing is presented, with the specific ability to broker and investor activities that put either at risk. Advanced scenarios that describe such broker and investor activities are specifically defined. By applying these scenarios to transactional data from a variety of financial institutions, broker and investor activities causing unacceptable amounts of risk can be detected on an automated basis.

Abstract: A method of analyzing customer behavior, where customers are engaged in customer-to-customer transactions in a third-party network, includes a transformation of data representing the customer-to-customer transactions from a data representation to a network representation, and then analyzing the network representation. The network representation includes a set of nodes and a set of links where each node represents a customer and each link represents a transaction between two of the customers.

Abstract: A method of analyzing customer behavior, where customers are engaged in customer-to-customer transactions in the third-party network, includes the transformation of data representing the customer-to-customer transactions from a data representation to a network representation, and then analyzing the network representation. The network representation includes a set of nodes and a set of links where each node represents a customer and each link represents a transaction between two of the customers.

Abstract: A method of analyzing customer behavior, where customers are engaged in customer-to-customer transactions in the third-party network, includes the transformation of data representing the customer-to-customer transactions from a data representation to a network representation, and then analyzing the network representation. The network representation includes a set of nodes and a set of links where each node represents a customer and each link represents a transaction between two of the customers.

Abstract: A computer based method and system for advanced scenario based alert generation and processing is presented, with the specific ability to broker and investor activities that put either at risk. Advanced scenarios that describe such broker and investor activities are specifically defined. By applying these scenarios to transactional data from a variety of financial institutions, broker and investor activities causing unacceptable amounts of risk can be detected on an automated basis.

Abstract: A computer based method and system for advanced scenario based alert generation and processing is presented, with the specific ability to broker and investor activities that put either at risk. Advanced scenarios that describe such broker and investor activities are specifically defined. By applying these scenarios to transactional data from a variety of financial institutions, broker and investor activities causing unacceptable amounts of risk can be detected on an automated basis.

Abstract: A method of analyzing customer behavior, where customers are engaged in customer-to-customer transactions in the third-party network, includes the transformation of data representing the customer-to-customer transactions from a data representation to a network representation, and then analyzing the network representation. The network representation includes a set of nodes and a set of links where each node represents a customer and each link represents a transaction between two of the customers.

Abstract: A method of analyzing customer behavior, where customers are engaged in customer-to-customer transactions in the third-party network, includes the transformation of data representing the customer-to-customer transactions from a data representation to a network representation, and then analyzing the network representation. The network representation includes a set of nodes and a set of links where each node represents a customer and each link represents a transaction between two of the customers.

Abstract: A computer based method and system generates alerts based on the detection of an advanced scenario in a data set. The system and method may take data related to events and entities, transform the data, and apply advanced scenarios to the data to produce matches that reflect the occurrence of an advanced scenario and the behavior of interest. The advanced scenarios can be defined to cover specific product lines and services, lines of businesses, and combinations thereof. The advanced scenarios can be defined to be indicative of a behavior class, or a specific behavior which is part of a behavior class. Alerts produced by the system can be grouped, prioritized and routed such that the appropriate users are notified in a timely manner. The system and method can be applied to a variety of industries including financial and health care, and can detect both illicit and licit behaviors of interest.

Abstract: A computer based method and system for advanced scenario based alert generation and processing is presented, with the specific ability to identify trading compliance violations in fixed income securities trading. Advanced scenarios that describe such trading compliance violations are specifically defined. By applying these scenarios to fixed income security transaction data from a variety of financial institutions, trading compliance violations can be detected on an automated basis.

Abstract: A computer based method and system generates alerts based on the detection of an advanced scenario in a data set. The system and method may take data related to events and entities, transform the data, and apply advanced scenarios to the data to produce matches that reflect the occurrence of an advanced scenario and the behavior of interest. The advanced scenarios can be defined to cover specific product lines and services, lines of businesses, and combinations thereof. The advanced scenarios can be defined to be indicative of a behavior class, or a specific behavior which is part of a behavior class. Alerts produced by the system can be grouped, prioritized and routed such that the appropriate users are notified in a timely manner. The system and method can be applied to a variety of industries including financial and health care, and can detect both illicit and licit behaviors of interest.

Abstract: A method of analyzing customer behavior, where customers are engaged in customer-to-customer transactions in the third-party network, includes the transformation of data representing the customer-to-customer transactions from a data representation to a network representation, and then analyzing the network representation. The network representation includes a set of nodes and a set of links where each node represents a customer and each link represents a transaction between two of the customers.