THESIS
2015
Abstract
With the boost of vehicle industry in China, automobile insurance has become
an important pillar of China's insurance industry. However, this industry was
once hindered by the governments excessive regulations and the cut-throat competitions in the market, which turns the scientific ratemaking problem into an
urgent issue. How to set a reasonable premium which can win the customers and
make profits at the same time is crucial to the business of automobile insurance.
In this thesis, with real data from an insurance company in China, we develop
a risk-based pricing system called R-Pricing for ratemaking of the automobile
insurance. This system mainly apply the theory of generalized linear models,
which is one of the most popular statistical models used in automobile insurance
pri...[
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With the boost of vehicle industry in China, automobile insurance has become
an important pillar of China's insurance industry. However, this industry was
once hindered by the governments excessive regulations and the cut-throat competitions in the market, which turns the scientific ratemaking problem into an
urgent issue. How to set a reasonable premium which can win the customers and
make profits at the same time is crucial to the business of automobile insurance.
In this thesis, with real data from an insurance company in China, we develop
a risk-based pricing system called R-Pricing for ratemaking of the automobile
insurance. This system mainly apply the theory of generalized linear models,
which is one of the most popular statistical models used in automobile insurance
pricing.
We will briefly introduce the theory of GLMs and then focus on the design of our
system R-Pricing. Finally, we evaluate our system from both the model angle
and the business angle. And the results demonstrate that R-Pricing has a good
performance close to a commercial pricing system.
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