Reinsurance Pricing of Large Motor Insurance Claims in Nigeria: An Extreme Value Analysis

Queensley C. Chukwudum

International Journal of Statistics and Probability, 2019, vol. 8, issue 4, 1-12

Abstract: Reinsurance is of utmost importance to insurers because it enables insurance companies cover risks that they, under normal circumstances, would not be able to cover on their own. An insurer needs to be able to evaluate his solvency probability and consequently, adjust his retention levels appropriately because the insurer’s retention level plays a vital role in determining the premiums he will pay to the reinsurer. To illustrate how Extreme Value theory can be applied, this study delves into modelling the probabilistic behaviour of the frequency and severity of large motor claims from the Nigerian insurance sector (2013-2016) using the Negative Binomial-Generalized Pareto distribution (NB-GPD). The annual loss distribution is simulated using the Monte Carlo method and it is used to predict the expected annual total claims and estimate the capital requirement for a year. Pricing of the Excess-of-loss (XL) reinsurance is also examined to aid insurers in optimizing their risk management decision in regards to the choice of their risk transfer position.

Keywords: extreme value theory; generalized Pareto distribution; risk management; XL reinsurance; negative binomial (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.ccsenet.org/journal/index.php/ijsp/article/download/0/0/39750/40682 (application/pdf)
http://www.ccsenet.org/journal/index.php/ijsp/article/view/0/39750 (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ibn:ijspjl:v:8:y:2019:i:4:p:1

Access Statistics for this article

More articles in International Journal of Statistics and Probability from Canadian Center of Science and Education Contact information at EDIRC.
Bibliographic data for series maintained by Canadian Center of Science and Education ().