Ventsislav Vasilev and Radka Vasileva
The study explores some methods used to assess risk and determine optimal retention levels in motor casco insurance, specifically focusing on comparing the three statistical techniques: Chebyshev’s Inequality, the Monte Carlo Simulation, and Normal Distribution. By utilizing historical claims data from the Bulgarian insurance market published by the Financial Supervision Commission, the study investigates the probability of the claim exceeding retention thresholds and compares the accuracy and precision of each method. While Chebyshev’s inequality provides a conservative estimate, the Monte Carlo simulation offers a probabilistic approach that models various outcomes, whereas normal distribution assumes a symmetrical loss pattern. The research aims to identify which method offers the most reliable estimation for setting retention levels in motor casco insurance. By evaluating the accuracy of each technique against real claims data, the study aims to inform insurers about the approach which optimizes their risk management decisions best. The research shows that the Monte Carlo simulation offers the most accurate and reliable estimates for motor casco retention decisions due to its flexibility in modelling various loss scenarios.