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Estimation of the Optimal Threshold Using Kernel Estimate and ROC Curve Approaches

Credit Line Analysis plays a very important role in the housing market, especially with the situation of large number of frozen loans during the current financial crisis. In this thesis, we apply the methods of kernel estimate and the Receiver Operating Characteristic (ROC) curve in the credit loan application process in order to help banks select the optimal threshold to differentiate good customers from bad customers. Better choice of the threshold is essential for banks to prevent loss and maximize profit from loans. One of the main advantages of our study is that the method does not require us to specify the distribution of the latent risk score. We apply bootstrap method to construct the confidence interval for the estimate.

Identiferoai:union.ndltd.org:GEORGIA/oai:digitalarchive.gsu.edu:math_theses-1108
Date23 May 2011
CreatorsZhu, Zi
PublisherDigital Archive @ GSU
Source SetsGeorgia State University
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMathematics Theses

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