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Please use this identifier to cite or link to this item: http://hdl.handle.net/123456789/10089

Title: Stochastic Analysis of General Insurance Claims Using Markov Chain Monte Carlo Method
Authors: Ossei Kofi, Tuffuor
Issue Date: 20-Jan-2017
Abstract: Motor insurance companies need to utilize past and current claim amounts in predicting future liabilities. It is therefore necessary that, motor insurance com- panies develop actuarial models using Bayesian and Markov Chain and Monte Carlo procedures. This thesis focuses on developing stochastic models for insur- ance claim amounts using Bayesian statistics. Motor insurance claim numbers usually follow compound Poisson distribution. This research work, however ex- amines the claim amount distributions. The methodology requires intensive use of Bayesian and Markov Chain Monte Carlo techniques through a software called WinBUGS. Two distributions usually tted to claim amounts are examined and the issues encountered when using Bayesian and Markov Chain Monte Carlo techniques in this context are investigated.
Description: A thesis submitted to the Department of Mathematics, Kwame Nkrumah University of Science and Technology in partial fulfillment of the requirement for the Degree of Master of Science in Actuarial Science, 2016
URI: http://hdl.handle.net/123456789/10089
Appears in Collections:College of Science

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