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: In computer-implemented methods, systems and program products for estimating financial modeling outcomes, financial data are segmented into a number of categories and scenario data for a set of model scenarios are processed to obtain an estimated model outcome distribution. The categories are mutually exclusive and collectively exhaustive of the financial data while the model may be developed by learning from the data. Multiple model tests are performed with samples of the financial data until a cumulative model outcome distribution is within a pre-determined acceptable tolerance limit from a distribution of fully assessed model outcomes obtainable by performing a single test of the scenarios using all of the financial data.

Abstract: An automated method, computer program product and system for using artificial intelligence based cognitive learning methods to identify, measure and manage risks for a commercial enterprise on a continual basis. The elements of value, external factors, components of value and categories of value of the enterprise are analyzed and modeled using predictive models that are developed by learning from the data associated with said enterprise. Scenarios of both normal and extreme situations are also developed by learning from the data. The scenarios are then used to drive simulations of the predictive models. The output from these simulations are then used to measure a plurality of risks and complete optimization analyses that identify the optimal mix of risk reduction activities for the enterprise. The optimal mix of risk reduction activities is then presented to the user for optional editing, rejection or acceptance.

Abstract: An automated system, method and media for optimizing the impact of a subset of an organization such as purchasing on the financial performance of said organization.

Abstract: A method of and system for transforming data from a plurality of systems into models of each of the segments of organization value and using said models to support the analysis, measurement and optimization of one or more aspects of organization risk and value.

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: 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 management and optimization of one or more aspects of organization risk and value, the development and optimized delivery of standard and customized risk transfer products for one or more organizations, and the development, valuation and sale of securities for one or more organizations.

Abstract: A method of and system for creating a performance management platform for an organization and using said platform to support analysis, management, optimization, reporting and simulation for any part of the organization.

Abstract: A method of and system for flexibly integrating organization related data, information, knowledge and systems into a market value matrix and using said matrix to support the optimization one or more aspects of organization risk, return and value.

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: 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 system (100), method and media for an entity centric computer that develops, entity knowledge before analyzing, applying, distributing, maintaining, replicating and/or synchronizing said knowledge as required and/or requested.

Abstract: An automated method and system (100) for identifying, measuring and enhancing categories of value for the different levels of a value chain on a continual basis. The categories of value are analyzed at each level in the value chain using predictive models and vector creation algorithms to define the enterprise and element vectors before valuing the organization, each enterprise in the organization and the elements of value in each enterprise. The relative strengths of the intangible elements of value are used in evaluating the real options of each enterprise and in determining the allocation of industry real options to the enterprise and the organization before summary reports are prepared, displayed and optionally printed. The system then generates potential value improvements which the user (20) optionally accepts, rejects or modifies before simulations are completed to analyze the value impact of the enhancements.

Abstract: An automated system (100) for integrating narrowly focused management systems in to a financial measurement and optimization system for a multi-enterprise commercial organization. A matrix of market value is developed for each enterprise in the organization. The matrices of market value are then used to guide the integration of narrow systems in to the organization's financial system. Value and risk are analyzed by element of value on the system date as required to complete and display the matrix of market value for the organization by enterprise. A series of scenarios under both normal and extreme conditions are then developed. The information from these scenarios is then combined with market value matrix information to determine the optimal mode for financial management. The information on the optimal mode of organization operation is then communicated to the integrated narrow systems for implementation.

Abstract: An automated system (100) and method for knowledge based performance management for an organization. After extracting data from existing narrowly focused systems, mission measures and organization levels are defined for one or more organizations. The elements, factors and risks that contribute to mission measure performance by organization level and organization are systematically defined and stored in a ContextBase using up to six context layers. ContextBase information is extracted for specified combinations of context layers, organization levels and organizations as required to produce complete context frames. The complete context frames are then used by a series of applications for reviewing, analyzing, forecasting, planning and optimizing organization performance.

Abstract: A method, system and media for learning, analyzing, managing and/or optimizing one or more aspects of organization value, risk and return (VARR) directly and indirectly through the use of narrow systems.

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 components of value, revenue, expense and capital change, of a commercial enterprise. Value drivers are identified using predictive models that define the value drivers associated with each element of the enterprise. After the causal value drivers are identified using causal models, the system completes a detailed valuation of the firm using predictive models to determine the relative impact of each causal value driver on the overall valuation. The detailed valuation results are then used to define a probabilistic 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 the components of value performance and optionally generates a list of recommended changes to value drivers that achieve a user specified financial goal.

Abstract: An automated system (100) and method for developing Complete Context™ Bots (30) for an organization. After extracting data from existing narrowly focused systems, mission measures and organization levels are defined for one or more organizations. The elements, factors and risks that contribute to mission measure performance by organization level and organization are systematically defined and stored in a ContextBase (60) using up to six context layers. ContextBase (60) information is extracted for specified combinations of context layers, organization levels and organizations as required to produce complete context frames that are used to support simulations of bot performance under a variety of scenarios. The program instructions that will maximize bot performance under the forecast scenarios are identified. After this programming is transferred to the Complete Context™ Bot (30), it is activated.

Abstract: An automated method and system (100) for the collaborative, on-line development and delivery of customized risk transfer programs. A profile of risk, liquidity and foreign exchange is obtained from each customer via a network connection. A series of scenarios under both normal and extreme situations are then developed in order to provide a complete picture of the risks facing the customer base. Information from external sources and internals systems is then combined with the scenarios to drive simulations that identify the optimal mix of risk transfer for each customer and the required pricing for risk transfer transactions. The optimal mix is then presented to the risk exchange system operator (21) for optional editing, rejection or acceptance. After the optimal mix has been determined, asset sales and purchases are completed as required to bring the asset mix in line with the specified mix. The information regarding the proposed risk transfers is reviewed by the customer (20) and optionally accepted.