title: Modern claim frequency and claim severity models: An application to the Russian motor own damage insurance market
metadata.name: dc.contributor.author
metadata.value: Gilenko, Evgenii
metadata.lang: -
metadata.name: dc.contributor.author
metadata.value: Mironova, Elena
metadata.lang: -
metadata.name: dc.date.accessioned
metadata.value: 2017-05-06T10:40:57Z
metadata.lang: -
metadata.name: dc.date.available
metadata.value: 2017-05-06T10:40:57Z
metadata.lang: -
metadata.name: dc.date.issued
metadata.value: 2017-04-04
metadata.lang: -
metadata.name: dc.identifier.citation
metadata.value: Cogent Economics & Finance
metadata.lang: en_GB
metadata.name: dc.identifier.issn
metadata.value: 2332-2039
metadata.lang: -
metadata.name: dc.identifier.uri
metadata.value: http://hdl.handle.net/11701/6220
metadata.lang: -
metadata.name: dc.description.abstract
metadata.value:  During 2012–2015, the motor insurance in Russia received considerable
  attention both from the parts of the Russian government and from the insurance
  business. This was caused, in particular, by significant losses from the side of insurance
  companies that occurred during 2012–2013. Experts explain these losses not
  only by the effects of inflation or by the changes in Russian insurance legislation,
  but also by the incomplete set of factors that has been used by insurance companies
  for tariff calculation. This research analyses the factors that influence claim
  frequency and claim severity in the Russian motor own damage (MOD) insurance to
  assess the efficiency of the existing set of factors used for MOD insurance tariff calculations.
  To this end, we employ the appropriate claim frequency and claim severity
  models on the data provided by one of the leading St. Petersburg (Russia) insurance
  companies for the period of 2012–2013. The results of our calculations, organized
  within a resampling framework, show that additional factors may indeed be worth
  taking into account in the MOD insurance tariff calculation.
metadata.lang: en_GB
metadata.name: dc.language.iso
metadata.value: en
metadata.lang: en_GB
metadata.name: dc.publisher
metadata.value: Taylor & Francis Online
metadata.lang: en_GB
metadata.name: dc.relation.ispartofseries
metadata.value: Vol. 5;Iss. 1
metadata.lang: -
metadata.name: dc.subject
metadata.value: generalized linear models; hurdle model; gamma-distribution; motor insurance; claim frequency; claim severity
metadata.lang: en_GB
metadata.name: dc.title
metadata.value: Modern claim frequency and claim severity models: An application to the Russian motor own damage insurance market
metadata.lang: en_GB
metadata.name: dc.type
metadata.value: Article
metadata.lang: en_GB
resources.filename: Modern claim frequency and claim severity models An application to the Russian motor own damage insurance market.pdf
resources.url: https://dspace.spbu.ru/bitstream/11701/6220/1/Modern%20claim%20frequency%20and%20claim%20severity%20models%20An%20application%20to%20the%20Russian%20motor%20own%20damage%20insurance%20market.pdf
resources.format: Adobe PDF
resources.size: 1,44 MB