DETERMINING CRITICAL ILLNESS PREMIUM USING FOURSTATE MARKOV CHAIN MODEL

• Main Author: Rahma Yanti, Aulia
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/43009
• Institution: Institut Teknologi Bandung

Critical Illness Insurance is an insurance product with lump sum benefit or cash payment if the policy holder is diagnosed with critical illness in insurance contract. Health state change process can be observed and modeled by multi-state Markov chain with time continuous parameter. The change process of individual status is modeled by four-states Markov chain; healthy, critically ill, dead due to critical illness and dead due to other causes. Based on this model, the transition probability and transition intensity will be calculated according to the four-states model using a modification from Mortality Table. Patient cancer data from RS Borromeus Bandung will be used to calculate the transition probability and transition intensity. This model application goal is determining premium value of Critical Illness Insurance by compute the transition probability and transition intensity value to create Stand Alone Policy and Accelerated Benefit model. Based on the result of this analysis, the amount of premium for each patients age is different due to the dissimilarity of the transition probability. The premium for Stand Alone and Accelerated Benefit models will be higher at certain ages with high transition probability and transition intensity.