Konferenzbeitrag
Case Study in Banking Using Neural Networks
Data Mining represents a Business Intelligence (BI) methodology which provides an insight into the 'hidden' information about its operations thus improving the process of making strategic business decisions based on a clear and understandable interpretation of existing results. Data mining can help to resolve banking problems by finding some regularity, causality and correlation to business information which are not visible at first sight because they are hidden in large amounts of data. The goal of this paper is to present a case study of usage of operations research methods in knowledge discovery from databases in the banking industry. Neural network method was used within the software package Alyuda.
- Language
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Englisch
- Bibliographic citation
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In: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Kotor, Montengero, 10-11 September 2015 ; Year: 2015 ; Pages: 251-257 ; Zagreb: IRENET - Society for Advancing Innovation and Research in Economy
- Classification
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Wirtschaft
Neural Networks and Related Topics
- Subject
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data mining
neural network
banking
alyuda
- Event
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Geistige Schöpfung
- (who)
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Bilal Zorić, Alisa
- Event
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Veröffentlichung
- (who)
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IRENET - Society for Advancing Innovation and Research in Economy
- (where)
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Zagreb
- (when)
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2015
- Handle
- Last update
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10.03.2025, 11:45 AM CET
Data provider
This object is provided by:
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ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.
Object type
- Konferenzbeitrag
Associated
- Bilal Zorić, Alisa
- IRENET - Society for Advancing Innovation and Research in Economy
Time of origin
- 2015
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