Assessing Consumer Credit Applications by a Genetic Programming Approach

Created by W.Langdon from gp-bibliography.bib Revision:1.8010

@InCollection{series/sci/RamponeFL13,

• author = "Salvatore Rampone and Franco Frattolillo and Federica Landolfi",
• title = "Assessing Consumer Credit Applications by a Genetic Programming Approach",
• bibdate = "2013-01-18",
• bibsource = "DBLP, http://dblp.uni-trier.de/db/series/sci/sci448.html#RamponeFL13",
• booktitle = "Advanced Dynamic Modeling of Economic and Social Systems",
• publisher = "Springer",
• year = "2013",
• volume = "448",
• editor = "Araceli N. Proto and Massimo Squillante and Janusz Kacprzyk",
• keywords = "genetic algorithms, genetic programming",
• isbn13 = "978-3-642-32902-9",
• series = "Studies in Computational Intelligence",
• pages = "79--89",
• URL = "http://dx.doi.org/10.1007/978-3-642-32903-6_7",
• DOI = "doi:10.1007/978-3-642-32903-6_7",
• abstract = "Credit scoring is the assessment of the risk associated with lending to an organisation or an individual. Genetic Programming is an evolutionary computational technique that enables computers to solve problems without being explicitly programmed. This paper proposes a genetic programming approach for risk assessment. In particular, the study is set in order to predict, on a collection of real loan data, whether a credit request has to be approved or rejected. The task is to use existing data to develop rules for placing new observations into one of a set of discrete groups. The automation of such decision-making processes can lead to savings in time and money by relieving the load of work on an expert who would otherwise consider each new case individually. The proposed model provides good performance in terms of accuracy and error rate.",

}

Genetic Programming entries for Salvatore Rampone Franco Frattolillo Federica Landolfi

Citations