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Title:Uporaba posplošenih linearnih modelov pri analizi zavarovalniških podatkov
Authors:ID Navotnik, Tjaša (Author)
ID Jakovac, Marko (Mentor) More about this mentor... New window
ID Pisanec, Mihael (Comentor)
Files:.pdf MAG_Navotnik_Tjasa_2020.pdf (1,29 MB)
MD5: 7AB76BFC4352E58486C4293FA0499A7F
PID: 20.500.12556/dkum/ccfbe995-e47b-4b29-8b3e-d662950e8396
 
Language:Slovenian
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FNM - Faculty of Natural Sciences and Mathematics
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 rizičnost 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:posplošeni linearni modeli, avtomobilsko zavarovanje, prekinitve življenjskih zavarovanj, modeliranje v R
Place of publishing:Maribor
Publisher:[T. Navotnik]
Year of publishing:2020
PID:20.500.12556/DKUM-76371 New window
UDC:519.22(043.2)
COBISS.SI-ID:23866371 New window
NUK URN:URN:SI:UM:DK:KCOAFQWM
Publication date in DKUM:30.07.2020
Views:1367
Downloads:131
Metadata:XML DC-XML DC-RDF
Categories:FNM
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Licences

License:CC BY-NC-ND 4.0, Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International
Link:http://creativecommons.org/licenses/by-nc-nd/4.0/
Description:The most restrictive Creative Commons license. This only allows people to download and share the work for no commercial gain and for no other purposes.
Licensing start date:15.05.2020

Secondary language

Language:English
Title:Applying generalized linear models to insurance data analysis
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.
Keywords:generalized linear models, motor insurance, termination of life insurance policies, modeling in R


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