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REINSURANCE WITH R: PRICING, RESERVING, SOLVENCY AND PORTFOLIO ANALYSIS

Authors

  • Q. C. Chukwudum Department of Insurance and Risk Management, University of Uyo, Akwa Ibom State, Nigeria.
  • M. Ekanem Department of Insurance and Risk Management, University of Uyo, Akwa Ibom State, Nigeria.

DOI:

https://doi.org/10.52417/ojms.v3i2.392

Keywords:

Aggregate claims; Reinsurer’s risk; Pareto distribution; Frequency-severity; Nigerian reinsurance sector.

Abstract

The lack of education and training has been highlighted as one of the highest factors stifling the growth of the re/insurance industry in Africa. Although reinsurance is offered as a course in the insurance/actuarial undergraduate and postgraduate study programs, many higher institutions of learning in Nigeria lack the sufficient mathematical and technical faculty expertise required to thoroughly deliver the reinsurance subject matter particularly at the masters and doctorate levels. As a result of the general absence of the required expertise in the re/insurance field of study, only a couple of universities offer postgraduate programs in insurance within Nigeria. The ripple effect of this gap is consequently felt in the re/insurance sector.  This paper, therefore, is meant to serve as a teaching aid to boost the postgraduate teaching and classroom experience in reinsurance and to strengthen the technical capacity of researchers in this field. First, contributions to literature from the Nigerian academic landscape is reviewed and then the computational aspect is implemented. The study aims to bridge the gap between theory and application. Both simulated and real data are used to illustrate the different concepts in reinsurance with techniques ranging from Monte Carlo simulations to various statistical distributions. The R language has been adopted because of its ease of use.

Published

2022-07-28

How to Cite

Chukwudum, Q. C., & Ekanem, M. (2022). REINSURANCE WITH R: PRICING, RESERVING, SOLVENCY AND PORTFOLIO ANALYSIS. Open Journal of Management Science (ISSN: 2734-2107), 3(2), 1-20. https://doi.org/10.52417/ojms.v3i2.392