FINANCIAL LOSS RISK MODELING DUE TO TECTONIC EARTHQUAKES USING AN EARTHQUAKE CATASTROPHE (CAT) MODEL: CASE STUDY OF RESIDENTIAL BUILDINGS IN KABUPATEN MIMIKA

• Main Author: Ferer Christian W., Vincensius
• Format: Final Project
• Language: Indonesia
• Online Access: https://digilib.itb.ac.id/gdl/view/73038
• Institution: Institut Teknologi Bandung

Indonesia is located at the meeting point of four major tectonic plates in the world, namely the Indo-Australian, the Eurasian, the Pacific, and the Philippine Sea Plates, which result in Indonesia experiencing many earthquakes. Besides causing many fatalities, earthquakes could also result in financial losses due to damages they caused to properties and infrastructures. According to the Indonesia Ministry of Finance, the economic losses in Indonesia due to earthquakes, on average, is IDR 7.56 trillion per year. As a result, a mechanism is needed to minimize the risk of financial losses due to an earthquake catastrophe event; one of which is through an earthquake insurance. In this Undergraduate Final Project, an Earthquake Catastrophe (CAT) Model is discussed. The Earthquake CAT Model is used to model the risk of financial losses due to tectonic earthquakes, which can then be used to determine the earthquake insurance premium. There are four modules in the Earthquake CAT Model, namely the Hazard, the Inventory, the Vulnerability, and the Loss Modules. In the Loss Module, an Event Loss Table (ELT) is constructed based on past tectonic earthquake events (historical earthquakes) or based on tectonic earthquake events in the synthetic earthquake catalogue. In this Undergraduate Final Project, ELT is built using the collective risk model for financial losses experienced by residential properties (buildings) in Kabupaten Mimika (Mimika District), Central Papua Province, due to historical subduction (megathrust) tectonic earthquakes. Multi-scenarios of the ELT are built based on the distribution of the moment magnitude of the tectonic earthquakes mainshocks using Monte-Carlo simulations. The probability distribution of the ELT could then be determined which is then used to determine the Value-at-Risk and Tail Value-at-Risk of the ELT.