Applying Classification and Regression Trees to manage financial risk


Applying Classification and Regression Trees to manage financial risk

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dc.contributor.advisor Scott, James Gordon
dc.creator Martin, Stephen Fredrick 2012-08-16T14:46:20Z 2012-08-16T14:46:20Z 2012-05 2012-08-16 May 2012
dc.description.abstract This goal of this project is to develop a set of business rules to mitigate risk related to a specific financial decision within the prepaid debit card industry. Under certain circumstances issuers of prepaid debit cards may need to decide if funds on hold can be released early for use by card holders prior to the final transaction settlement. After a brief introduction to the prepaid card industry and the financial risk associated with the early release of funds on hold, the paper presents the motivation to apply the CART (Classification and Regression Trees) method. The paper provides a tutorial of the CART algorithms formally developed by Breiman, Friedman, Olshen and Stone in the monograph Classification and Regression Trees (1984), as well as, a detailed explanation of the R programming code to implement the RPART function. (Therneau 2010) Special attention is given to parameter selection and the process of finding an optimal solution that balances complexity against predictive classification accuracy when measured against an independent data set through a cross validation process. Lastly, the paper presents an analysis of the financial risk mitigation based on the resulting business rules.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subject CART
dc.subject Classification and Regression Trees
dc.subject Breiman
dc.subject Risk
dc.subject Prepaid
dc.subject Debit cards
dc.subject Rollback
dc.subject R
dc.subject RPART
dc.subject Cross validation
dc.title Applying Classification and Regression Trees to manage financial risk 2012-08-16T14:46:30Z
dc.identifier.slug 2152/ETD-UT-2012-05-5428
dc.contributor.committeeMember Carvalho, Carlos M.
dc.contributor.committeeMember Marti, Nathan C.
dc.description.department Mathematics
dc.type.genre thesis
dc.type.material text Mathematics Statistics University of Texas at Austin Masters Master of Science in Statistics

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