MODELING SHANKER-GAMMA CLAIM RISK AND BAYES PREMIUM CALCULATION

• Main Author: Kadek Darma Arnawa, I
• Format: Theses
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/83069
• Institution: Institut Teknologi Bandung

Accurate claims risk modeling is essential in actuarial science for predicting the size or severity of future claims that insurance companies might encounter. The severity of these claims is influenced by the risk profiles of policyholders, necessitating a flexible statistical model to represent these variations accurately. This study introduces the Shanker-gamma (S-G) type II mixture model to address this requirement. Two types of mixture distributions are explored: type I, which combines two distributions with a specified mixing weight, and type II, which employs conditional random variables with parameters treated as random variables. Additionally, a premium calculation model is developed based on the S-G loss model, using expectations (pure premium) and standard deviation (SDPP). These premium values are then compared with the Bayes premium value, which provides a precise assessment of the policyholder’s risk profile by incorporating non-constant parameters in the loss model. By utilizing these advanced statistical methods, financial management in insurance can be significantly improved, offering a more accurate approach to predicting and managing future claims.