The expected loss due to online fraud for the year 2008 is ;In this study, we test models that account for misclassification error in credit card transactions, with a goal of assessing the performance of standard and modified binary choice models that include misclassification error parameters. We estimate models and the misclassification error parameters for two sample credit card transaction datasets. We found that the inclusion of omission error parameter in the modified model shifted the probability of fraud upwards, while as expected commission error was zero. The overall model adequacy measured by the percentage correct classification was similar for the standard and modified logit models.;This study is based on real-life credit card transactions dataset from an international credit card operation. This dataset has all credit card transactions during 13 months, from January 2006 to January 2007, of about 50 million transactions (49,858,600 transactions) on about one million (1,167,757 credit cards) credit cards from a single country.
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