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Case Study in Banking Using Neural Networks

In: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Kotor, Montengero, 10-11 September 2015

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  • Bilal Zorić, Alisa

Abstract

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.

Suggested Citation

  • Bilal Zorić, Alisa, 2015. "Case Study in Banking Using Neural Networks," Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference (2015), Kotor, Montengero, in: Proceedings of the ENTRENOVA - ENTerprise REsearch InNOVAtion Conference, Kotor, Montengero, 10-11 September 2015, pages 251-257, IRENET - Society for Advancing Innovation and Research in Economy, Zagreb.
    • Handle: RePEc:zbw:entr15:183656
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    References listed on IDEAS

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    1. Van den Poel, Dirk & Lariviere, Bart, 2004. "Customer attrition analysis for financial services using proportional hazard models," European Journal of Operational Research, Elsevier, vol. 157(1), pages 196-217, August.
    2. Baesens, Bart & Viaene, Stijn & Van den Poel, Dirk & Vanthienen, Jan & Dedene, Guido, 2002. "Bayesian neural network learning for repeat purchase modelling in direct marketing," European Journal of Operational Research, Elsevier, vol. 138(1), pages 191-211, April.
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    More about this item

    Keywords

    data mining; neural network; banking; alyuda;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics

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