Net premium estimation on term-health insurance based on Markov chain

Abstract

Health insurance is a part of life insurance with life as an object and product that provides some sum assured if the insured is exposed to certain illness or disability. This research aims to estimate net premium based on trend movement on every possible entry age and probability of being exposed to diabetes mellitus, chronic kidney disease, and hemodialysis on every age. Net premium estimation is based on multistate model using Markov chain to determine transition probability on a case study of 5 status, namely healthy, diabetes mellitus, chronic kidney disease, hemodialysis, and death. Specified case study is conducted on a 56-year-old man taking 20 years of insurance protection, paying premium for 5 years with sum insured of one billion IDR on 4 benefit categories. Calculation on every entry age shows that the older someone, the higher annual net premium that must be paid as the transition probability towards high severity disease increases.