EARTHQUAKE INSURANCE CLAIM RESERVING BY APPLICATING NEURO-FUZZY INFERENCE SYSTEM: STOCHASTIC GRADIENT DESCENT METHOD
An earthquake insurance business is a long-tail insurance business. In determining the outstanding claims liability of a long-tail insurance business, the Basic Chain Ladder method is commonly used because it is simple and distribution free. In this Final Project, a method to predict the outstand...
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| Format: | Final Project |
| Language: | Indonesia |
| Online Access: | https://digilib.itb.ac.id/gdl/view/39295 |
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| Institution: | Institut Teknologi Bandung |
| Language: | Indonesia |
| Summary: | An earthquake insurance business is a long-tail insurance business. In determining
the outstanding claims liability of a long-tail insurance business, the Basic Chain
Ladder method is commonly used because it is simple and distribution free. In
this Final Project, a method to predict the outstanding claims liability using a
Neuro Fuzzy Inference System with the Stochastic Gradient Descent optimization
method is discussed. The architecture of the Neuro Fuzzy Inference System is
modified to determine the development factors of the resulting runoff triangles of
the claims data which are based on four characteristics of the claims data. Those
characteristics of the underlying earthquakes are: moment magnitude; depth;
latitude and longitude. The resulting chain ladder prediction is then compared
with the Basic Chain Ladder prediction when the claims characteristics are not
taken into account. Initially, it is assumed that the clustering will be based on the
earthquakes cresta zones. However, the results of the analysis showed that the
clustering is based on the depths of the earthquakes hypocenters. |
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