This thesis is backed up by an internship in SIFA' (Società Italiana Flotte Aziendali). The thesis starts by providing an overview of the automotive market, with a focus on the Italian one, then covering the definition and the particularities of the long-term car rental and the differences with the other main car rental modalities. Then, it is analyzed the specificity of the services and of the companies that provide services, considering the different approaches adopted when constructing the price. After looking into the SIFA' company, its dynamics and processes, it is reported the project done during the internship. The project aim is to help the company by: Analyzing the costs relative to the maintenance and introducing the age of the vehicles as a key data to determine real maintenance costs in time, creating a simple forecast model in order to estimate the above-mentioned costs for the next year. Categorize the different vehicles in their classes of belonging and estimate the cost of every category, in order to help to identify the right tariff to apply in new contracts of the same category. Analyze the cost of claims, and how to retarget the tariffs for the penalties for virtuous customer and high frequency claims customers.
Pricing Evaluations in the Long-Term Car Rental Sector: The Sifà Case
2020
Abstract
This thesis is backed up by an internship in SIFA' (Società Italiana Flotte Aziendali). The thesis starts by providing an overview of the automotive market, with a focus on the Italian one, then covering the definition and the particularities of the long-term car rental and the differences with the other main car rental modalities. Then, it is analyzed the specificity of the services and of the companies that provide services, considering the different approaches adopted when constructing the price. After looking into the SIFA' company, its dynamics and processes, it is reported the project done during the internship. The project aim is to help the company by: Analyzing the costs relative to the maintenance and introducing the age of the vehicles as a key data to determine real maintenance costs in time, creating a simple forecast model in order to estimate the above-mentioned costs for the next year. Categorize the different vehicles in their classes of belonging and estimate the cost of every category, in order to help to identify the right tariff to apply in new contracts of the same category. Analyze the cost of claims, and how to retarget the tariffs for the penalties for virtuous customer and high frequency claims customers.| File | Dimensione | Formato | |
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https://hdl.handle.net/20.500.14242/301074
URN:NBN:IT:UNIMORE-301074