Expert system design for long term care underwriting

Abstract

The project presents a mathematical model created to determine a risk score for applicants for long term care insurance. We developed software to assist in the implementation and testing of the model. We analyze the suitability of our model, including the sensitivity of scores to the model's parameters. We formulate methods which could help train the model, including numerical regression to solve for model parameters and pair-wise comparisons between applicants to verify consistency of parameters and risk factors