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Prediction of Banks Financial Distress

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dc.contributor.author SirElkhatim , Mohammed A.
dc.contributor.author Salim , Naomie
dc.date.accessioned 2017-04-25T07:24:33Z
dc.date.available 2017-04-25T07:24:33Z
dc.date.issued 2015
dc.identifier.citation SirElkhatim , Mohammed A. . Prediction of Banks Financial Distress Naomie Salim A. , Mohammed A. SirElkhatim .- Journal of Engineering and Computer Sciences (ECS) .- vol 16 , no1.- 2015.- article en_US
dc.identifier.issn ISSN 1605-427X
dc.identifier.uri http://repository.sustech.edu/handle/123456789/16609
dc.description article en_US
dc.description.abstract In this research we are conducting a comprehensive review on the existing literature of prediction techniques that have been used to assist on prediction of the bank distress. We categorized the review results on the groups depending on the prediction techniques method, our categorization started by firstly using time factors of the founded literature, so we mark the literature founded in the period (1990-2010) as history of prediction techniques, and after this period until 2013 as recent prediction techniques and then present the strengths and weaknesses of both. We come out by the fact that there is no specific type fit with all bank distress issue although we found that intelligent hybrid techniques consider the most candidates methods in term of accuracy and reputation. en_US
dc.description.sponsorship Sudan University of Science and Technology en_US
dc.language.iso en_US en_US
dc.publisher Sudan University of Science and Technology en_US
dc.subject Bank Distress , Banks Factors , Prediction techniques ,Text Mining, Data Mining. en_US
dc.title Prediction of Banks Financial Distress en_US
dc.type Article en_US


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