Abstract: A classification system includes a processor and a memory that stores an initial dataset, an analyzed dataset, a model rules database, and instructions. The instructions, in response to receiving first interaction data corresponding to a first interaction, store the first interaction data in the initial dataset as a first entry. The instructions include, at a predetermined time, selecting a set of entries from the initial dataset including the first entry and obtaining a set of analysis rules from the model rules database. The instructions include, for each selected set of entries, calculating an additional parameter based on the obtained set of analysis rules and generating a first analyzed dataset corresponding to the obtained set of analysis rules. The instructions include storing the first analyzed dataset and providing the first analyzed dataset to determine a recommendation using the first analyzed dataset and displaying the recommendation on a user interface.

Abstract: A classification system includes a processor and a memory that stores an initial dataset, an analyzed dataset, a model rules database, and instructions. The instructions, in response to receiving first interaction data corresponding to a first interaction, store the first interaction data in the initial dataset as a first entry. The instructions include, at a predetermined time, selecting a set of entries from the initial dataset including the first entry and obtaining a set of analysis rules from the model rules database. The instructions include, for each selected set of entries, calculating an additional parameter based on the obtained set of analysis rules and generating a first analyzed dataset corresponding to the obtained set of analysis rules. The instructions include storing the first analyzed dataset and providing the first analyzed dataset to determine a recommendation using the first analyzed dataset and displaying the recommendation on a user interface.

Abstract: A model management system for validating models for predicting a client behavior event includes a model validation system configured to execute each of multiple stages of a selected model, which includes calculating a respective output based on a respective input of each of the stages. The model validation system is configured to separately verify, based on the respective outputs, each of the stages. The model validation system is configured to generate and store model data corresponding to the respective outputs of each of the stages. The model data includes a first set of model data and a second set of model data different from the first set of model data. A user interface module is configured to receive an indication of credentials of a user and selectively retrieve and display one of the first set of model data and the second set of model data based on the indication.

Abstract: A system for validating models for predicting a client behavior event includes a development module and a validation module. The development module is configured to receive a use case corresponding to the client behavior event and select a subset of variables correlated to the client behavior event. The validation module is configured to select a first model from models that predict client behavior event using the selected subset of variables. The development module selects the first model based on a predicted lift of the first model. The validation module applies the first model to client data acquired subsequent to the selection of the first model. The validation module compares the predicted lift of the first model to an actual lift of the first model as applied to the client data. The validation module selects one of the first model and a different model in response to the comparison.