PREDICTING DEBT REPAYMENT PATTERNS IN SOUTH AFRICA

dc.contributor.authorBrodkin, Michael
dc.date.accessioned2011-03-22T13:02:49Z
dc.date.available2011-03-22T13:02:49Z
dc.date.issued2011-03-22
dc.descriptionMBA - WBSen_US
dc.description.abstractDebt recovery agencies and attorneys specializing in high volume debt recovery have in the past either used judgmental systems or standard credit bureau scores to prioritise recovery efforts and to make decisions on how to allocate scarce resources. Both of these methods are insufficient and inferior to statistical credit scoring methodologies that are tailored specifically for the debt recovery function. The purpose of this research is to apply credit scoring methodologies to the South African debt recovery environment and to discover which variables are the most predictive in identifying the re-payment patterns of written-off, post legal, credit card debt in South Africa. Bivariate analysis was used to distil six variables which were then subjected to logistic regression to produce a scorecard which was then tested on a holdout sample of debtors that were not used in the development of the model. The research concludes that just six variables produce a scorecard that predicts repayment significantly better than chance. The research also concludes that standard credit bureau scores are very poor predictors of re-payment of written-off, post legal, credit card debt in South Africa. The relevance of the findings are firstly, that just six variables are necessary to predict debt repayment patterns in South Africa and secondly, collection agencies and collections attorneys should not rely on standard credit bureau scores to assess the best re-payment prospects or to optimise the allocation of scarce resources. Instead, collections agencies and collection attorneys should develop scoring models that are specific to the debt recovery function as well as the specific type of debt being worked on.en_US
dc.identifier.urihttp://hdl.handle.net/10539/9198
dc.language.isoenen_US
dc.subjectDebt repayment patternsen_US
dc.subjectDebt recoveryen_US
dc.titlePREDICTING DEBT REPAYMENT PATTERNS IN SOUTH AFRICAen_US
dc.typeThesisen_US
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