An Artificial Intelligence System to Predict Quality of Service in Banking Organizations.
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.
NOVA IMS, Universidade Nova de Lisboa, Rua de Campolide, 1070-312 Lisboa, Portugal.
Mauro
0000-0002-8793-1451
M
Castelli
DISCo, Università degli Studi di Milano-Bicocca, Viale Sarca 336, 20126 Milan, Italy.
Luca
0000-0001-6312-7728
L
Manzoni
NOVA IMS, Universidade Nova de Lisboa, Rua de Campolide, 1070-312 Lisboa, Portugal; Faculty of Economics, University of Ljubljana, Kardeljeva Ploscad 17, 1000 Ljubljana, Slovenia.
Aleš
A
Popovič
D001185:Artificial Intelligence; D000067012:Banking, Personal; D003198:Computer Simulation; D019992:Databases as Topic; D005069:Evaluation Studies as Topic; D006801:Humans; D011237:Predictive Value of Tests; D012660:Semantics