The event of a default for low-default portfolios, such as sovereign debt or banks, have received much attention as a result of the increasing instabilities in financial markets. The lack of sufficient default information on low-default portfolios complicates the protection of such portfolios. Default protections have typically, in the past, relied on extreme value theory and reporting the value at risk. The focus here, is the application of an engineering concept, accelerated test techniques, to the problem of insufficient data on low-default portfolios. In the application, high-default portfolios serve as stressed cases of low-default portfolios. Since high-default portfolios have more data available, viewing it as a stressed case of a low-default portfolio enables us to extrapolate the data to the low-default portfolio environment, and do estimation such as estimating the default probability for a low-default portfolio. The flexible framework through which the above is achieved, is provided. / Dissertation (MSc)--University of Pretoria, 2016. / Statistics / MSc / Unrestricted