Using Genetic Programming Systems as Early Warning to Prevent Bank Failure

Using Genetic Programming Systems as Early Warning to Prevent Bank Failure

Alma Lilia Garcia Almanza, Serafín Martínez Jaramillo, Biliana Alexandrova-Kabadjova, Edward Tsang
ISBN13: 9781613501627|ISBN10: 1613501625|EISBN13: 9781613501634
DOI: 10.4018/978-1-61350-162-7.ch014
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MLA

Almanza, Alma Lilia Garcia, et al. "Using Genetic Programming Systems as Early Warning to Prevent Bank Failure." Information Systems for Global Financial Markets: Emerging Developments and Effects, edited by Alexander Y. Yap, IGI Global, 2012, pp. 369-382. https://doi.org/10.4018/978-1-61350-162-7.ch014

APA

Almanza, A. L., Jaramillo, S. M., Alexandrova-Kabadjova, B., & Tsang, E. (2012). Using Genetic Programming Systems as Early Warning to Prevent Bank Failure. In A. Yap (Ed.), Information Systems for Global Financial Markets: Emerging Developments and Effects (pp. 369-382). IGI Global. https://doi.org/10.4018/978-1-61350-162-7.ch014

Chicago

Almanza, Alma Lilia Garcia, et al. "Using Genetic Programming Systems as Early Warning to Prevent Bank Failure." In Information Systems for Global Financial Markets: Emerging Developments and Effects, edited by Alexander Y. Yap, 369-382. Hershey, PA: IGI Global, 2012. https://doi.org/10.4018/978-1-61350-162-7.ch014

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Abstract

The main advantage of creating understandable rules is that users are able to interpret and identify the events that may trigger bankruptcy. By using the method that we propose in this work, it is possible to identify when certain financial indicators are getting close to specific thresholds, something that can turn into an undesirable situation. This is particularly relevant if the companies we are referring to are banks. The contribution of this chapter is to improve the prediction by means of a multi-population approach. The experimental results were evaluated using the Receiver Operating Characteristic (ROC) described in Fawcett and Provost (1997). We show that our approach could improve the Area Under the ROC Curve in 5% with respect to the same method proposed in Garcia et al. (2010). Additionally, a series of experiments were performed in order to find out the reasons of success of the EDR.

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