na študijskem programu 2. stopnje Matematika
Tjaša Navotnik (Author), Marko Jakovac (Mentor), Mihael Pisanec (Co-mentor)

Abstract

V magistrskem delu je predstavljena teorija posplošenih linearnih modelov (GLM) in uporaba le-teh v zavarovalništvu. Na realnih zavarovalniških podatkih izbrane zavarovalnice s pomočjo modelov GLM segmentiramo zavarovance glede na tveganje, in s tem določimo premijo za zavarovanje avtomobilske odgovornosti, ki je prilagojena posamezniku. S pomočjo logistične regresije analiziramo prekinitve življenjskih zavarovanj in zgradimo klasifikacijski model, ki razvrsti zavarovance v dve skupini; na tiste, ki so oz.\ niso nagnjeni k prekinitvi.

Keywords

magistrska dela;posplošeni linearni modeli;avtomobilsko zavarovanje;prekinitve življenjskih zavarovanj;modeliranje v R;

Data

Language: Slovenian
Year of publishing:
Typology: 2.09 - Master's Thesis
Organization: UM FNM - Faculty of Natural Sciences and Mathematics
Publisher: [T. Navotnik]
UDC: 519.22(043.2)
COBISS: 23866371 Link will open in a new window
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Downloads: 62
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Other data

Secondary language: English
Secondary title: Applying generalized linear models to insurance data analysis
Secondary abstract: The master's thesis presents the theory of generalized linear models (GLM) and their application in the insurance industry. Based on the real insurance data of the selected insurance company, we use the GLM models to segment insured persons according to risk, thus determining the premium for individual motor third party liability insurance. We use logistic regression to analyze the termination of life insurance policies and we build a classification model that classifies policyholders into two groups; to those who are and who are not prone to lapse.
Secondary keywords: master theses;generalized linear models;motor insurance;termination of life insurance;policies;modeling in R;
Type (COBISS): Master's thesis/paper
Thesis comment: Univ. v Mariboru, Fak. za naravoslovje in matematiko, Oddelek za matematiko in računalništvo
Pages: 61 f.
ID: 11681195