Credit scoring by logistic regression

dc.contributor.advisorPärna, Kalev, juhendaja
dc.contributor.authorTabagari, Salome
dc.contributor.otherTartu Ülikool. Matemaatika-informaatikateaduskondet
dc.contributor.otherTartu Ülikool. Matemaatilise statistika instituutet
dc.date.accessioned2015-07-08T12:06:03Z
dc.date.available2015-07-08T12:06:03Z
dc.date.issued2015
dc.description.abstractToday banking business’ most successful products are loans and credits given to the clients. In order to make a decision whether to accept or reject a loan application banks gather information from applicants. In the past, decision was made by individual bank’s expert. It was not efficient way for banks, because competition was growing, thus they introduced better method – credit scoring. Credit scoring is one of the most effective and successful methods in finance and banking. With help of credit scoring methodology it is easier to make correct and fast decisions. An overview of the credit scoring is given in the following thesis. A real data set is used to demonstrate how to calculate applicants’ scores. For this purpose one of the most frequently used statistical method- logistic regression – is used.et
dc.identifier.urihttp://hdl.handle.net/10062/47572
dc.language.isoenet
dc.publisherTartu Ülikoolet
dc.subjectlaenutaotluste hindamineet
dc.subjectlogistiline regressioonet
dc.subject.othermagistritöödet
dc.subject.othercredit scoringen
dc.subject.otherlogistic regressionen
dc.titleCredit scoring by logistic regressionet
dc.typeThesiset

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