Pay-As-You-Drive Insurance Pricing Model
DOI:
https://doi.org/10.47672/ajsas.442Keywords:
Cox Process, Martingales, Aggregate Risk Models, PAYD, Actuarial Mathematics.Abstract
Purpose: Every time drivers take to the road, and with each mile that they drive, exposes themselves and others to the risk of an accident. Insurance premiums are only weakly linked to mileage, however, and have lump-sum characteristics largely. The result is too much driving, and too many accidents. The purpose of carrying out this research was to determine a model for calculating the premiums for Pay-As-You-Drive in Automobile insurances.
Methodology: To price Pay-As-You-Drvie auto insurance, we define a discounted collective risk model while the total number of claim has non-homogeneous Poisson distribution. By applying non-homogeneous Poisson distribution we can enter the mileage to the discounted collective risk model to the premiums for Pay-As-You-Drive in Automobile insurances. We apply the double Double Stochastic Poisson Process for modeling the the DCRM. The Double Stochastic Poisson Process provides flexibility by letting the intensity not only depend on time but also by allowing it to be a stochastic process.
Findings: By applying the doubly stochastic Poisson process to viewe the driver's milege in the model, we find the distribution of discounted collective risk model and present the expected value of total loss for calculating the premiums.
Policy recommendation: The current auto insurance pricing systems are inequitable because low-mileage drivers subsidize insurance costs for high-mileage drivers, and low-income people drive fewer miles on average. The study recommends a more efficient pricing systems model to find a good model for calculating the fair auto insurance premiumDownloads
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Copyright (c) 2020 Safoora Zarei, Alireza Fallahi
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