Modeling premiums of non-life insurance companies in India
Kartik Sethi, Siddhartha P. Chakrabarty
TL;DR
This paper empirically analyzes non-life insurance premiums in India, finding that the Generalized Extreme Value distribution best models the data across ten companies.
Contribution
It introduces an empirical approach comparing multiple distributions to model insurance premiums, identifying the most suitable distribution for Indian non-life insurance data.
Findings
GEV distribution fits best for all ten companies
Lognormal and GPD distributions are less suitable
Provides insights into premium modeling for Indian insurers
Abstract
We undertake an empirical analysis for the premium data of non-life insurance companies operating in India, in the paradigm of fitting the data for the parametric distribution of Lognormal and the extreme value based distributions of Generalized Extreme Value and Generalized Pareto. The best fit to the data for ten companies considered, is obtained for the Generalized Extreme Value distribution.
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Taxonomy
TopicsInsurance and Financial Risk Management · Insurance, Mortality, Demography, Risk Management · Financial Risk and Volatility Modeling