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Journals / Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler / 2019 / Cilt: 7 - Sayı: 2

SOME COMPOSITE MODELS AND THEIR APPLICATION TO TURKISH MOTOR INSURANCE DATA

Ayten YİĞİTER
Yasemin GENÇTÜRK
Canan HAMURKAROĞLU
Pages
121–132
Publication Date
2019-08-23
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

From the results obtained, it is concluded that the composite Weibull-Pareto model provides better fit to Turkish Motor Insurance claim data than the all other models considered.

📌 3 Key Takeaways

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Objective & Hypothesis:It is important for an insurance company to predict the future claims in order to evaluate premiums, to determine the reserve necessary to meet its obligation and probabilities of ruin, etc. as the claim data is highly positively skewed and has heavy tail, no standard parametric model seems to provide an acceptable fit to both small and large losses.
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Key Findings & Data:Composite models that use one standard distribution up to a threshold and other standard distribution thereafter are developed and it is seen that these composite models provide better fit than the standard models when claim data involve small and high claims.
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Conclusion & Impact:From the results obtained, it is concluded that the composite Weibull-Pareto model provides better fit to Turkish Motor Insurance claim data than the all other models considered.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Composite models · Standard parametric models · Turkish motor insurance loss data

Abstract

It is important for an insurance company to predict the future claims in order to evaluate premiums, to determine the reserve necessary to meet its obligation and probabilities of ruin, etc. as the claim data is highly positively skewed and has heavy tail, no standard parametric model seems to provide an acceptable fit to both small and large losses. Composite models that use one standard distribution up to a threshold and other standard distribution thereafter are developed and it is seen that these composite models provide better fit than the standard models when claim data involve small and high claims. The aim of this study is to investigate the use of the composite models namely Exponential-Pareto, Weibull-Pareto and Lognormal-Pareto to model the Turkish Motor Insurance claim data. From the results obtained, it is concluded that the composite Weibull-Pareto model provides better fit to Turkish Motor Insurance claim data than the all other models considered.

Özet

It is important for an insurance company to predict the future claims in order to evaluate premiums, to determine the reserve necessary to meet its obligation and probabilities of ruin, etc. as the claim data is highly positively skewed and has heavy tail, no standard parametric model seems to provide an acceptable fit to both small and large losses. Composite models that use one standard distribution up to a threshold and other standard distribution thereafter are developed and it is seen that these composite models provide better fit than the standard models when claim data involve small and high claims. The aim of this study is to investigate the use of the composite models namely Exponential-Pareto, Weibull-Pareto and Lognormal-Pareto to model the Turkish Motor Insurance claim data. From the results obtained, it is concluded that the composite Weibull-Pareto model provides better fit to Turkish Motor Insurance claim data than the all other models considered.

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Cite This Article

YİĞİTER, A., GENÇTÜRK, Y., HAMURKAROĞLU, C. (2019). SOME COMPOSITE MODELS AND THEIR APPLICATION TO TURKISH MOTOR INSURANCE DATA. Eskişehir Teknik Üniversitesi Bilim ve Teknoloji Dergisi B - Teorik Bilimler, Cilt: 7 - Sayı: 2, 121–132. https://ajindex.com/articles/253890

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