Abstract: A data processing framework for financial services that supports the automated development and delivery of financial service products to a plurality of customers.

Abstract: An automated method and system (100) for the development and delivery of value impact risk transfer products and programs.

Abstract: A method and system (100) for identifying, measuring and managing the risk associated with a portfolio of securities.

Abstract: A system (100), method and media for an entity centric computer that develops, entity context by layer before analyzing, applying, distributing, maintaining, replicating and/or synchronizing the knowledge developed using said context as required and/or requested.

Abstract: An automated method and system (100) for enhancing the operational effectiveness and optimizing the tangible financial impact of one or more enterprise processes on a continual basis.

Abstract: An automated system (100) and methods for defining and measuring the real options of a commercial enterprise on a specified valuation date. The real options are evaluated on the basis of the relative strength of the elements of value of the enterprise. The performance of the elements of value are first summarized using composite variables. The elements strength of the cause change in enterprise stock price are then determined. The relative strength of the causal elements of value for the enterprise vis a vis its competitors are then calculated. The relative ranking of the enterprise causal elements of value is then used in determining the discount rate to be used in real option valuation. The real options are then valued.

Abstract: An automated system (100) and method for optimizing purchasing activity from the perspective of the buyer. The purchasing activity features and resources are defined using purchasing system data. The suppliers and deliverables are then mapped to one or more frames within the Market Value Matrix™ System for the Buyer. The system then identifies the mix of features and resources that maximize the expected value from purchasing activity from the different Buyer frames.

Abstract: An automated system (100) and method for analyzing, modeling and valuing elements of a business enterprise on a specified valuation date. The performance of the elements are analyzed using search algorithms and induction algorithms to determine the value drivers associated with each element. The induction algorithms are also used to create composite variables that relate element performance to enterprise revenue, expenses and changes in capital. Predictive models are then used to determine the correlation between the value drivers and the enterprise revenue, expenses and changes in capital. The correlation percentages for each value driver are then multiplied by capitalized value of future revenue, expenses and changes in capital, the resulting numbers for each value driver associated with each element are then added together to calculate a value for each element.

Abstract: A method of and system for creating an organization risk matrix and an organization value matrix and using said matrices to support the optimization of one or more aspects of organization risk and value.

Abstract: An automated system and method for measuring the performance of elements of a business enterprise and for valuing said elements on a specified valuation date. The performance of the elements are calculated using composite variables. Predictive models are then used to determine the correlation between the element performance and the enterprise value drivers, revenue, expenses and changes in capital. The element correlation percentages are then multiplied by capitalized value of future revenue, expenses and changes in capital, the three resulting numbers are then added together to calculate a value for each element. Finally, the relationship between the market value of the business and the calculated business value is optionally calculated for use in forecasting future equity prices.

Abstract: An automated system (100) and method for evaluating the probable impact of user-specified or system generated changes in business value drivers on the other value drivers, the financial performance and the future value of a commercial enterprise. Value drivers are identified using search algorithms and induction algorithms that define the value drivers associated with each element of the enterprise. After identifying enterprise value drivers the system completes a detailed valuation of the firm using predictive models to determine the relative impact of each value driver on the overall valuation. The detailed valuation results are then used to define a financial simulation model such as a Markov Chain Monte Carlo model. The financial simulation model then analyzes the impact of user specified changes in value drivers on financial performance or generates a list of recommended changes to value drivers that achieve a user specified financial goal.

Abstract: In a computer based inventory control method and system, feasible profit maximizing sets of requisitions are created. System processing starts with the creation of detailed, multi-dimensional forecasts of sales and cash receipts using stored algorithms and data preferentially extracted from a basic financial system and the adjustment of the forecasts to match the controlling forecast specified by the user. The adjustment of the forecasts is facilitated by the use of a calculated variable that defines the magnitude of the relative adjustment for each forecast element. All forecasts are adjusted to exactly match a controlling forecast which is either a multivalent combination of the previously generated forecasts or the user specified controlling forecast. The adjusted forecast of sales by item is then used in calculating a requisition set that satisfies expected demand while meeting user specified service level targets.