Standardized Modeling Suite

A computer-assisted method comprising:

• collecting data from a plurality of data sources, wherein the collected data includes data related to a plurality of independent variables;
• storing the collected data in a datastore associated with the computer;
• using a processor associated with the computer, performing a plurality of checks on the collected data, wherein the plurality of checks include replacing missing values in the collected data with a median value of one of the plurality of independent variables, removing outlier values that are below a 0.5 percentile or above a 99.5 percentile for each of the plurality of independent variables in the collected data, and normalizing each of the plurality of independent variables;
• using the processor, analyzing the checked data to identify a subset of the plurality of independent variables for inclusion in a model for a dependent variable, wherein the analysis includes transforming categorical variables into numerical variables;
• and
• using the processor, generating the model using the identified subset of independent variables.

An apparatus comprising:

• a data collection module configured to collect data from a plurality of sources, wherein the collected data includes data related to a plurality of independent variables;
• a data checking module configured to perform a plurality of checks on the collected data, wherein the plurality of checks include filling in missing values in the collected data with a median value of one of the plurality of independent variables, removing outlier values, removing highly correlated independent variables, and normalizing at least one of the plurality of independent variables;
• a data analysis module configured to identify a first subset of the plurality of independent variables for inclusion in a model for a dependent variable by correlating at least one of the plurality of independent variables with the dependent variable through a plurality of statistics, wherein the data analysis module is further configure to transform categorical variables into numerical variables;
• a data reduction module configured to identify a second subset of strongest independent variables from the first subset by boot screening the first subset of the plurality of independent variables;
• and
• a modeling module configured to estimate the model based on the identified second subset of strongest independent variables.