- author = "Alma Lilia {Garcia Almanza} and Serafin {Martinez Jaramillo} and Biliana Alexandrova-Kabadjova and Edward Tsang",
- title = "Using Genetic Programming Systems as Early Warning to Prevent Bank Failure",
- booktitle = "Information Systems for Global Financial Markets: Emerging Developments and Effects",
- publisher = "IGI global",
- year = "2011",
- editor = "Alexander Y. Yap",
- chapter = "14",
- pages = "369--382",
- month = nov,
- keywords = "genetic algorithms, genetic programming",
- ISBN = "1-61350-162-5",
-
URL = "
http://www.amazon.com/Information-Systems-Global-Financial-Markets/dp/1613501625",
-
DOI = "
doi:10.4018/978-1-61350-162-7.ch014",
-
abstract = "Corporate bankruptcy has been always an active area of
financial research. Furthermore, after the Lehman
Brothers' default and its consequences on the global
financial system, this topic has attracted even more
attention from regulators and researchers. This event
has brought an imperious urge to change the regulatory
framework regardless of whether this is good or bad.
Consequently, the need for timely signals for
supervisory actions and the development of tools that
help to determine which financial information is more
relevant to predict distress is very important.
During crisis periods the bankruptcy of a bank or a group of banks can make things far worse if contagion effects are transmitted first to other participants of the financial system and then to the real economy. In a previous work, developed by Garcia et al. (2010), an evolutionary technique named Evolving Decision Rules (EDR) was used to identify patterns in data from the Federal Deposit Insurance Corporation (FDIC) for generating a set of comprehensible rules, which were able to predict bank bankruptcy. The major contribution of that work was to show a series of decision rules constituted by simple financial ratios, despite that the method is not restricted to the use of such type of information.
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 5percent 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",
