Expert System Design for Long Term Care Underwriting 1

Long-term Care Insurance underwriters analyze all of the data provided in an application to assess the risk associated with the applicant. The work described here focuses on the applicant’s medical conditions and computes a numerical risk score based on these conditions. The model uses a least squares approach to determine how the risk points for several independent medical conditions will accumulate. It includes an additional penalty for comorbid medical conditions. The model has the advantage of objectivity; two applicants with the same set of medical conditions will always receive the same risk score. Results from testing with simulated data show that the model is efficient and eliminates error quickly when the sources of error can be isolated.