Abstract: Systems and methods for processing peer-to-peer financial product markup language agency notices are disclosed. According to one embodiment, in an information processing apparatus, a computer-implemented method for processing peer-to-peer financial product markup language agency notices may include: (1) receiving a FpML notice from a sender to a receiver; (2) obtaining a sender unique identifier for the sender and a receiver unique identifier for the receiver; (3) generating a FpML message body for a transaction associated with the notice; (4) generating FpML data comprising the unique identifiers and the FpML message body; (5) generating an electronic message comprising the FpML data; and (6) sending the electronic message FpML data to the receiver.

Abstract: Systems and methods for processing peer-to-peer financial product markup language agency notices are disclosed. According to one embodiment, in an information processing apparatus, a computer-implemented method for processing peer-to-peer financial product markup language agency notices may include: (1) receiving a FpML notice from a sender to a receiver; (2) obtaining a sender unique identifier for the sender and a receiver unique identifier for the receiver; (3) generating a FpML message body for a transaction associated with the notice; (4) generating FpML data comprising the unique identifiers and the FpML message body; (5) generating an electronic message comprising the FpML data; and (6) sending the electronic message FpML data to the receiver.

Abstract: Systems and methods for processing peer-to-peer financial product markup language agency notices are disclosed. According to one embodiment, in an information processing apparatus, a computer-implemented method for processing peer-to-peer financial product markup language agency notices may include: (1) receiving a FpML notice from a sender to a receiver; (2) obtaining a sender unique identifier for the sender and a receiver unique identifier for the receiver; (3) generating a FpML message body for a transaction associated with the notice; (4) generating FpML data comprising the unique identifiers and the FpML message body; (5) generating an electronic message comprising the FpML data; and (6) sending the electronic message FpML data to the receiver.

Abstract: Systems and methods for processing peer-to-peer financial product markup language agency notices are disclosed. According to one embodiment, in an information processing apparatus, a computer-implemented method for processing peer-to-peer financial product markup language agency notices may include: (1) receiving a FpML notice from a sender to a receiver; (2) obtaining a sender unique identifier for the sender and a receiver unique identifier for the receiver; (3) generating a FpML message body for a transaction associated with the notice; (4) generating FpML data comprising the unique identifiers and the FpML message body; (5) generating an electronic message comprising the FpML data; and (6) sending the electronic message FpML data to the receiver.

Abstract: A method and system for managing and executing business formulas using a single platform includes a storage function for storing a plurality of business formulas in a single repository, where each business formula is defined using multi-dimensional data. The multi-dimensional data is accessible by employee-users of the business through a server communicatively connected to the repository. The employee-user may alter the multi-dimensional data of a business formula to incorporate modifications, as well as to create new business formulas. The server functions to execute business formulas contained within the repository. By allowing employee-users to modify existing business formulas and to input new business formulas directly into the system without requiring a programmer to write new software code, the efficiency of executing business formulas and implementing modifications is increased.

Abstract: A system and method for performing Value at Risk (VaR) analysis at a large volume scale. The system employs two basic types of elements in its architecture: controllers and brokers. Controllers are engines that perform actual processing of data, while brokers manage the access to and from the data resources. Controllers of the present invention have three main components, an input queue, a manager and workers. The controllers retrieve units of work from the incoming queue, process the units, and place the result onto an outgoing queue. The outgoing queue of one controller is shared with the next element in the processing chain. Brokers are responsible for maintaining pool of common resources and providing access to those resources to a requestor (i.e., a controller). In the preferred embodiment, the resource is a data source, such as a database containing market pricing data. The broker accesses the data source though an adapter.