PL EN


2010 | 1(45) | 138-152
Article title

A NEURAL NETWORK APPROACH FOR BANK CREDIT DECISIONS (Podejmowanie decyzji kredytowych w oparciu o sztuczne sieci neuronowe)

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Title variants
Languages of publication
PL
Abstracts
EN
To grant a bank credit or not is very important for effective bank management. A standard approach of computer decision support systems is based on spread sheets. The artificial neural network approach gives more possibilities to analyze credit decisions, to classify entities applying for credits according to their credibility, including different groups of risk. In this work, the authoress presents a review of various neural network topologies appliance and net trained using various algorithms for dichotomous and polytomic classification. Classification errors were compared and the most effective net was determined. Advantages and disadvantages of described method were shown, which indicate the right appliance of artificial neural networks for the analysis of loan debtors. The usage of artificial networks can rationalize and speed up the process of granting credits, as well as provide a basis for a secondary verification of refused applications.
Year
Issue
Pages
138-152
Physical description
Document type
ARTICLE
Contributors
  • Beata Rubin, Uniwersytet w Bialymstoku, Wydzial Ekonomii i Zarzadzania, ul. Warszawska 63, 15-062 Bialystok, Poland
References
Document Type
Publication order reference
Identifiers
CEJSH db identifier
10PLAAAA08609
YADDA identifier
bwmeta1.element.52318b23-b3bb-3c4d-97be-26801c5e3f5c
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