FUZZY NEURAL NETWORK APPLICATION IN LONG TAIL BUSINESS CLAIM RESERVING: ELBOW METHOD FOR DETERMINING NUMBER OF OPTIMAL CLUSTERS

The development in information technology causes a large number of receiving and recording data, including earthquake insurance data. With the existence of this technology, claim data with various claim characteristics can be recorded more quickly and more accurately. In this Thesis, a system tha...

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Main Author: Imanuella Rachman, Joanne
Format: Theses
Language:Indonesia
Online Access:https://digilib.itb.ac.id/gdl/view/39042
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Institution: Institut Teknologi Bandung
Language: Indonesia
id id-itb.:39042
spelling id-itb.:390422019-06-21T11:03:56ZFUZZY NEURAL NETWORK APPLICATION IN LONG TAIL BUSINESS CLAIM RESERVING: ELBOW METHOD FOR DETERMINING NUMBER OF OPTIMAL CLUSTERS Imanuella Rachman, Joanne Indonesia Theses earthquake insurance, claim reserve, chain ladder method, fuzzy neural network. INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/39042 The development in information technology causes a large number of receiving and recording data, including earthquake insurance data. With the existence of this technology, claim data with various claim characteristics can be recorded more quickly and more accurately. In this Thesis, a system that can recognize the characteristics of claim data is used, namely Fuzzy Neural Network. This system is then applied to determine the estimated claim reserve for an earthquake insurance claim data in Indonesia. The amount of claim reserve is an important component for insurance companies in ensuring the security of the assets of policyholders. Therefore, it is expected that the estimation of claims reserves using the Fuzzy Neural Network system produces more precise results compared to other methods, the Chain Ladder method. text
institution Institut Teknologi Bandung
building Institut Teknologi Bandung Library
continent Asia
country Indonesia
Indonesia
content_provider Institut Teknologi Bandung
collection Digital ITB
language Indonesia
description The development in information technology causes a large number of receiving and recording data, including earthquake insurance data. With the existence of this technology, claim data with various claim characteristics can be recorded more quickly and more accurately. In this Thesis, a system that can recognize the characteristics of claim data is used, namely Fuzzy Neural Network. This system is then applied to determine the estimated claim reserve for an earthquake insurance claim data in Indonesia. The amount of claim reserve is an important component for insurance companies in ensuring the security of the assets of policyholders. Therefore, it is expected that the estimation of claims reserves using the Fuzzy Neural Network system produces more precise results compared to other methods, the Chain Ladder method.
format Theses
author Imanuella Rachman, Joanne
spellingShingle Imanuella Rachman, Joanne
FUZZY NEURAL NETWORK APPLICATION IN LONG TAIL BUSINESS CLAIM RESERVING: ELBOW METHOD FOR DETERMINING NUMBER OF OPTIMAL CLUSTERS
author_facet Imanuella Rachman, Joanne
author_sort Imanuella Rachman, Joanne
title FUZZY NEURAL NETWORK APPLICATION IN LONG TAIL BUSINESS CLAIM RESERVING: ELBOW METHOD FOR DETERMINING NUMBER OF OPTIMAL CLUSTERS
title_short FUZZY NEURAL NETWORK APPLICATION IN LONG TAIL BUSINESS CLAIM RESERVING: ELBOW METHOD FOR DETERMINING NUMBER OF OPTIMAL CLUSTERS
title_full FUZZY NEURAL NETWORK APPLICATION IN LONG TAIL BUSINESS CLAIM RESERVING: ELBOW METHOD FOR DETERMINING NUMBER OF OPTIMAL CLUSTERS
title_fullStr FUZZY NEURAL NETWORK APPLICATION IN LONG TAIL BUSINESS CLAIM RESERVING: ELBOW METHOD FOR DETERMINING NUMBER OF OPTIMAL CLUSTERS
title_full_unstemmed FUZZY NEURAL NETWORK APPLICATION IN LONG TAIL BUSINESS CLAIM RESERVING: ELBOW METHOD FOR DETERMINING NUMBER OF OPTIMAL CLUSTERS
title_sort fuzzy neural network application in long tail business claim reserving: elbow method for determining number of optimal clusters
url https://digilib.itb.ac.id/gdl/view/39042
_version_ 1822925177558663168