As part of business analytics, the Predictive Modeling process is a search for explanatory values. It starts with the identification of a problem that needs to be solved: real estate appraisers want to predict selling price; executives want to predict sales; life insurance carriers want to predict mortality. Uncovering relevant relationships between the variable you are interested in predicting, and independent variables that influence its result, starts with statistical analysis. A mathematical model is then developed using a modeling technique like regression analysis that defines the relationship between the dependent variable and many independent (explanatory) variables. This can then be used to predict the value of the dependent variable based on changes in the independent variables.
Modeling has seen expanded use outside of the domain of actuarial departments. Underwriting departments and industry laboratories have also used modeling to help improve underwriting decisions and improve efficiency.
Modeling and “triage”
Emergency rooms triage incoming patients by sorting out treatment priority based on severity of health condition. In underwriting departments this means figuring out which applications need closer attention and which may be spared additional requirements and may move more quickly to approval and issue. Finding ways to do this with reasonable accuracy requires the analysis of data from past experience and the application of what has been learned to future underwriting. Modeling can help sort this out. Doing this well ensures better placement of resources and better efficiency.
Modeling and quick issue