Credit Screening System Selection
نویسندگان
چکیده
منابع مشابه
Feature Selection in Big Data by Using the enhancement of Mahalanobis–Taguchi System; Case Study, Identifiying Bad Credit clients of a Private Bank of Islamic Republic of Iran
The Mahalanobis-Taguchi System (MTS) is a relatively new collection of methods proposed for diagnosis and forecasting using multivariate data. It consists of two main parts: Part 1, the selection of useful variables in order to reduce the complexity of multi-dimensional systems and part 2, diagnosis and prediction, which are used to predict the abnormal group according to the remaining us...
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This note presents a simple model of competitive screening in a credit market with adverse selection, where firms use interest and collateral as instruments for screening borrowers’ risk type. While the basic ideas appear in Bester (1985,1987), this version of the model is far more useful pedagogically, also (arguably) when compared with models that are more conventionally employed for this pur...
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We develop a model that derives “screening” and “incentive” effects of credit information systems that mitigate problems of adverse selection and moral hazard in credit markets. We also derive a “credit expansion” effect in which borrowers with clean credit records receive larger and more favorable equilibrium loan contracts. The credit expansion effect increases default rates, but does not ove...
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Inappropriate management in some fields such as credit allocation has imposed too many losses to financial institutions and even has forced some of them to go bankrupt. Moreover, large volume data sets collected by credit departments has necessitated utilizing highly accurate models with less complexities. Credit scoring models with classification and forecasting customers into two groups good ...
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تاریخ انتشار 2001