Abstract: A computer-implemented rules based decision management system which is cross-platform, cross-industry and cross-function. The decision management system has a software architecture which includes a common code layer, a processing platform layer and a data architecture layer. The common code layer includes a common code kernel simultaneously operable on first and second hardware platforms which are different from each other, and provides software processing to interpret and apply the strategies. The processing platform layer includes a first software module supporting a processing mode for the first hardware platform, and a second software module supporting a processing mode for the second hardware platform. The data architecture layer includes a first data module supporting data storage and access by the first software module, and a second data module supporting data storage and access by the second software module.

Abstract: A computer-implemented decision management system which provides qualitative client assessment via point in time simulation. More specifically, the decision management system (a) simulates the effect of a strategy by applying the strategy to client data, and (b) tracks what type of client traveled through a respective decision point in the strategy during the simulation. Simulation parameters can be selected without technical intervention via, for example, a GUI and a relational data model. Such parameters can include which customers and which client data sample will be used for the simulation, and which inbound events will trigger the strategy. Moreover, detailed and aggregate results can be consolidated to determine expected results from the simulated strategies, and traditional and OLAP reporting facilities can be applied to analyze/view the consolidated results.

Abstract: A computer-implemented decision management system which provides qualitative client assessment via point in time simulation. More specifically, the decision management system (a) simulates the effect of a strategy by applying the strategy to client data, and (b) tracks what type of client traveled through a respective decision point in the strategy during the simulation. Simulation parameters can be selected without technical intervention via, for example, a GUI and a relational data model. Such parameters can include which customers and which client data sample will be used for the simulation, and which inbound events will trigger the strategy. Moreover, detailed and aggregate results can be consolidated to determine expected results from the simulated strategies, and traditional and OLAP reporting facilities can be applied to analyze/view the consolidated results.

Abstract: A computer-implemented rules based decision management system which is cross-platform, cross-industry and cross-function. The decision management system has a software architecture which includes a common code layer, a processing platform layer and a data architecture layer. The common code layer includes a common code kernel simultaneously operable on first and second hardware platforms which are different from each other, and provides software processing to interpret and apply the strategies. The processing platform layer includes a first software module supporting a processing mode for the first hardware platform, and a second software module supporting a processing mode for the second hardware platform. The data architecture layer includes a first data module supporting data storage and access by the first software module, and a second data module supporting data storage and access by the second software module.

Abstract: A computer-implemented rules based decision management system which is cross-platform, cross-industry and cross-function. The decision management system has a software architecture which includes a common code layer, a processing platform layer and a data architecture layer. The common code layer includes a common code kernel simultaneously operable on first and second hardware platforms which are different from each other, and provides software processing to interpret and apply the strategies. The processing platform layer includes a first software module supporting a processing mode for the first hardware platform, and a second software module supporting a processing mode for the second hardware platform. The data architecture layer includes a first data module supporting data storage and access by the first software module, and a second data module supporting data storage and access by the second software module.

Abstract: A computer-implemented decision management system which provides qualitative client assessment via point in time simulation. More specifically, the decision management system (a) simulates the effect of a strategy by applying the strategy to client data, and (b) tracks what type of client traveled through a respective decision point in the strategy during the simulation. Simulation parameters can be selected without technical intervention via, for example, a GUI and a relational data model. Such parameters can include which customers and which client data sample will be used for the simulation, and which inbound events will trigger the strategy. Moreover, detailed and aggregate results can be consolidated to determine expected results from the simulated strategies, and traditional and OLAP reporting facilities can be applied to analyze/view the consolidated results.

Abstract: A computer-implemented decision management system which provides qualitative client assessment via point in time simulation. More specifically, the decision management system (a) simulates the effect of a strategy by applying the strategy to client data, and (b) tracks what type of client traveled through a respective decision point in the strategy during the simulation. Simulation parameters can be selected without technical intervention via, for example, a GUI and a relational data model. Such parameters can include which customers and which client data sample will be used for the simulation, and which inbound events will trigger the strategy. Moreover, detailed and aggregate results can be consolidated to determine expected results from the simulated strategies, and traditional and OLAP reporting facilities can be applied to analyze/view the consolidated results.