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Modelling of Claim Frequency and Claim Size in Non-Life Insurance

Student: Makovei Daria

Supervisor: Marina V. Polyakova

Faculty: Faculty of Economic Sciences

Educational Programme: Statistical Modelling and Actuarial Science (Master)

Year of Graduation: 2019

In the study, conducted on the auto insurance data, methods for predicting number and size of claims in non-life insurance were studied. In the empirical part of the work analysis of the portfolio with contacts from 2012 to 2018 was conducted within which the main factors that could influence the frequency and severity were identified. Based on the GLM model, the cost of claims for the insurance portfolio under review was predicted. Comparison with factual values ​​showed that the method demonstrated high accuracy and also gave consistent results whithin portfolio segments. In addition, a hurdle model was built to predict the number of claims.

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