Actuarial Applications of Hierarchical Modeling to Health Insurance Claims

dc.contributor.authorAtta-Mensah, Michael
dc.date.accessioned2016-09-30T13:39:56Z
dc.date.accessioned2023-04-21T02:42:10Z
dc.date.available2016-09-30T13:39:56Z
dc.date.available2023-04-21T02:42:10Z
dc.date.issuedOctober 22, 2015
dc.descriptionA thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirement for the Degree of M.Phil. Actuarial Science.en_US
dc.description.abstractThis study demonstrates actuarial applications that can be performed on the Health insurance claims in the country. To achieve this, data from the CPC scheme in Accra of the NHIA in the year 2013 was employed for the study. this consisted of facility type, number of claims submitted(in-patient and out-patient) and amount submitted (in-patient,out-patient,drugs and services charges). A hierarchical model allowing for frequency, claim type and severity amount to be jointly modeled was used. Based on this hierarchical model, we proceeded to estimate premium values under various conditions, however due to lack of information from the insurer most of these estimates could not be stated categorically. Applications of the study was also made to the Value-at-Risk theory. This fact not withstanding, a case has been made for the consideration of the hierarchical modeling approach to be considered as the means of analyzing health insurance claims since this model takes into consideration not only the loss (severity) amount submitted but also considers most especially factors integral to the planning and budgeting of the insurer, and these are, the frequency and type of claim. The hierarchical modeling approach thus provided further insight which previously was overlooked.en_US
dc.description.sponsorshipKNUSTen_US
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/9013
dc.language.isoenen_US
dc.titleActuarial Applications of Hierarchical Modeling to Health Insurance Claimsen_US
dc.typeThesisen_US
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