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Division of Actuarial Science

Estimating the risks in defined benefit pension funds under the constraints of PF117

Abstract

dc:description.abstract

With the issuing of Pension Funds circular PF117 in 2004 in South Africa, regulation required valuation assumptions for defined benefit pension funds to be on a best-estimate basis. Allowance for prudence was to be made through explicit contingency reserves, in order to increase reporting transparency. These reserves for prudence, however, were not permitted to put the fund into deficit (the no-deficit clause). Analysis is conducted to understand the risk that PF117 poses to pension fund sponsors and members under two key measures: contribution rate risk and solvency risk. A stochastic model of a typical South African defined benefit fund is constructed with simulations run to determine the impact of the PF117 requirements. Findings show that a best-estimate funding basis, coupled with the no-deficit clause, results in significant risk under both contribution rate and solvency risk measures, particularly in the short-term. To mitigate these risks, alternative ways of introducing conservatism into the funding basis are required, with possible options including incorporating margins into investment return assumptions or the removal of the no-deficit clause.

Degree

thesis:*
Grantor dc:publisher.institution
Division of Actuarial Science
Year dc:date.issued
2017

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Mahmood, Ra'ees
Advisors dc:contributor.advisor
  • Kendal, Shannon
  • Dorrington, Rob

Rights

Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11427/27342
OAI identifier oai:identifier
oai:open.uct.ac.za:11427/27342

Chain of custody

source
Harvested from
University of Cape Town
Base URL
open.uct.ac.za/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
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citation

Mahmood, Ra'ees. Estimating the risks in defined benefit pension funds under the constraints of PF117. Division of Actuarial Science, 2017. http://hdl.handle.net/11427/27342