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Computational Intelligence and Neuroscience
Volume 2016, Article ID 9139380, 7 pages
http://dx.doi.org/10.1155/2016/9139380
Research Article

An Artificial Intelligence System to Predict Quality of Service in Banking Organizations

1NOVA IMS, Universidade Nova de Lisboa, Rua de Campolide, 1070-312 Lisboa, Portugal
2DISCo, Università degli Studi di Milano-Bicocca, Viale Sarca 336, 20126 Milan, Italy
3Faculty of Economics, University of Ljubljana, Kardeljeva Ploscad 17, 1000 Ljubljana, Slovenia

Received 1 December 2015; Accepted 26 April 2016

Academic Editor: Saeid Sanei

Copyright © 2016 Mauro Castelli et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Quality of service, that is, the waiting time that customers must endure in order to receive a service, is a critical performance aspect in private and public service organizations. Providing good service quality is particularly important in highly competitive sectors where similar services exist. In this paper, focusing on banking sector, we propose an artificial intelligence system for building a model for the prediction of service quality. While the traditional approach used for building analytical models relies on theories and assumptions about the problem at hand, we propose a novel approach for learning models from actual data. Thus, the proposed approach is not biased by the knowledge that experts may have about the problem, but it is completely based on the available data. The system is based on a recently defined variant of genetic programming that allows practitioners to include the concept of semantics in the search process. This will have beneficial effects on the search process and will produce analytical models that are based only on the data and not on domain-dependent knowledge.