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Most lending institutions are aware of the importance of having a well-performing credit scoring model or scorecard and know that, in order to remain competitive in the credit industry, it is necessary to continuously improve their scorecards. This is because better scorecards result in substantial monetary savings that can be stated in terms of millions of dollars. Thus, there has been increasing interest in the application of new classifiers in credit scoring from both practitioners and researchers in the last few decades. Most of the recent work in this field has focused on the use of new and innovative techniques to classify applicants as either 'credit-worthy' or 'non-credit-worthy', with the aim of improving scorecard performance. In this thesis, we investigate the suitability of intelligent systems techniques for credit scoring. In particular, intelligent systems that use immunological metaphors are examined and used to build a learning and evolutionary classification algorithm. Our model, named Simple Artificial Immune System (SAIS), is based on the concepts of the natural immune system. The model uses applicants' credit details to classify them as either 'credit-worthy' or 'non-credit-worthy'. As part of the model development, we also investigate several techniques for selecting variables from the applicants' credit details. Variable selection is important as choosing the best set of variables can have a significant effect on the performance of scorecards. Interestingly, our results demonstrate that the traditional stepwise regression variable selection technique seems to perform better than many of the more recent techniques. A further contribution offered by this thesis is a detailed description of the scorecard development process. A detailed explanation of this process is not readily available in the literature and our description of the process is based on our own experiences and discussions with industry credit risk practitioners. We evaluate our model using both publicly available datasets as well as a very large set of real-world consumer credit scoring data obtained from a leading Australian bank. The evaluation results reveal that SAIS is a competitive classifier and is appropriate for developing scorecards which require a class decision as an outcome. Another conclusion reached is one confirmed by the existing literature, that even though more sophisticated scorecard development techniques, including SAIS, perform well compared to the traditional statistical methods, their performances are not statistically significantly different from the statistical methods. As with other intelligent systems techniques, SAIS is not explicitly designed to develop practical scorecards which require the generation of a score that represents the degree of confidence that an applicant will belong to a particular group. However, it is comparable to other intelligent systems techniques which are outperformed by statistical techniques for generating p ractical scorecards. Our final remark on this research is that even though SAIS does not seem to be quite suitable for developing practical scorecards, we still believe that there is room for improvement and that the natural immune system of the body has a number of avenues yet to be explored which could assist with the development of practical scorecards.

Fowlpox viruses (FPV) are attractive platform vaccine vector candidates because their capacity for insertion of multiple heterologous genes makes them favourable for genetic modification. They also have strong adjuvant activity in their own right. As FPV does not replicate in mammalian cells, there is significantly less opposition associated with their clinical application, with a number already in use. However, a thorough understanding of the immunological relationship between FPV and the mammalian immune system is still lacking. The aim of this thesis was to construct a series of recombinant FPV vectors that co-expressed the nominal antigen chicken ovalbumin (OVA), (FPV[subscript]OVA), and/or murine interleukin-4 (mIL-4). These constructs were used for the characterisation of the relationship between FPV and the mammalian immune system and how this is altered by the co-expression of mIL-4. Immunisation with FPV[subscript]OVA resulted in rapid and highly localized OVA expression which induced strong CD8⁺ cytotoxic T cell (CTL) activity but only weak CD4⁺ T helper and antibody responses. In addition, presentation of FPV-derived antigen and the priming of antigen-specific CTL responses required a permissive bone marrow (BM)-derived cell as the antigen presenting cell (APC). Co-administration with FPV[subscript]mIL-4 resulted in a dramatic reduction in CTL activity that remained largely non-functional throughout the infection and a skewing of the T helper (Th) response towards Th2 with a reduction in interferon (IFN)-γ production by OVA-specific Th cells. These findings provide a sound basis for further characterization of how FPV interacts with the innate and adaptive arms of the immune system, how these can be manipulated via the co-administration of cytokines, and discovering if future rationally designed modifications result in FPV vectored vaccines that induce durable cellular and humoral immunity. / http://proxy.library.adelaide.edu.au/login?url= http://library.adelaide.edu.au/cgi-bin/Pwebrecon.cgi?BBID=1352466 / Thesis (M.Med.Sc.) - University of Adelaide, School of Medicine, 2009

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Thesis (PhD)--University of Stellenbosch, 2005. / Bibliography. Also available via the Internet.

Thesis (Ph. D.)--University of Texas at Austin, 2007. / Vita. Includes bibliographical references.