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dc.contributor.authorTong, L. I.en_US
dc.contributor.authorWei, W. Y.en_US
dc.contributor.authorWu, P. Y.en_US
dc.date.accessioned2014-12-08T15:29:42Z-
dc.date.available2014-12-08T15:29:42Z-
dc.date.issued2012en_US
dc.identifier.isbn978-0-9763486-8-9en_US
dc.identifier.urihttp://hdl.handle.net/11536/21330-
dc.description.abstractThe global economic environment is changing rapidly. Consequently, the financial risks of banks or financial institutions are also increased. Banks or financial institutions often utilize various classification methods to construct risk assessment models to determine whether to grant loans to a corporation or an individual. It is often found that the data used to construct a risk assessment model are imbalanced. That is, the number of default is significantly smaller than the number of non-default. In this case, most classification methods fail to construct an accurate risk assessment model since the classification methods are subjected to the imbalanced data. The try-and-error method is often utilized to balance the sample sizes for default and non-default classes. However, the try-and error method is costly and the sampling strategy determined by the try-and-error method may not effectively classify the imbalanced data. Therefore, this study aims to develop an optimal re-sampling strategy using design of experiments (DOE) and dual response surface methodology (DRS). The proposed method can be employed for any classification method to develop a risk assessment model. The effectiveness of the proposed procedure is verified using a real case from a Taiwanese financial institution.en_US
dc.language.isoen_USen_US
dc.subjectRisk assessmenten_US
dc.subjectRe-sampling strategyen_US
dc.subjectImbalanced dataen_US
dc.subjectDesign of Experimentsen_US
dc.subjectDual Response Surface Methodologyen_US
dc.titleThe Optimal Re-sampling Strategy for a Risk Assessment Modelen_US
dc.typeProceedings Paperen_US
dc.identifier.journalPROCEEDINGS 18TH ISSAT INTERNATIONAL CONFERENCE ON RELIABILITY & QUALITY IN DESIGNen_US
dc.citation.spage293en_US
dc.citation.epage295en_US
dc.contributor.department工業工程與管理學系zh_TW
dc.contributor.departmentDepartment of Industrial Engineering and Managementen_US
dc.identifier.wosnumberWOS:000316157500058-
Appears in Collections:Conferences Paper