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What is Trait Recognition

Handbook of Research on Financial and Banking Crisis Prediction through Early Warning Systems
An early warning system that splits each predictive variable into different segments and calculates different interactions of these segments for one or more variables. In the financial arena, the trait recognition provides the best combination of variables to predict banking failures.
Published in Chapter:
Using Self Organizing Maps for Banking Oversight: The Case of Spanish Savings Banks
Felix Lopez-Iturriaga (University of Valladolid, Spain) and Iván Pastor-Sanz (University of Valladolid, Spain)
DOI: 10.4018/978-1-4666-9484-2.ch006
Abstract
This chapter combines two methods based on neural networks (trait recognition and self-organizing maps) to develop a model of bankruptcy prediction. The authors apply the method to the Spanish savings banks, most of them rescued by the Government between 2008 and 2013 in a costly massive process. First, the authors detect the combinations of variables (performance, asset structure, and capitalization) that best describe the profile of the rescued savings banks. Then, the authors use these combinations on a yearly basis to generate bi-dimensional maps in which banks are placed according to their risk and similarities. This method provides a visual tool that can improve the oversight of policy makers on the whole financial system and enable time pertinent answers to some threatens to the country financial stability. The maps are useful means to detect and understand how the financial threats emerge over time too.
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