Assessing Consumer Credit Applications by a Genetic Programming Approach
Created by W.Langdon from
gp-bibliography.bib Revision:1.7964
- @InCollection{series/sci/RamponeFL13,
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author = "Salvatore Rampone and Franco Frattolillo and
Federica Landolfi",
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title = "Assessing Consumer Credit Applications by a Genetic
Programming Approach",
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bibdate = "2013-01-18",
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bibsource = "DBLP,
http://dblp.uni-trier.de/db/series/sci/sci448.html#RamponeFL13",
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booktitle = "Advanced Dynamic Modeling of Economic and Social
Systems",
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publisher = "Springer",
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year = "2013",
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volume = "448",
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editor = "Araceli N. Proto and Massimo Squillante and
Janusz Kacprzyk",
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keywords = "genetic algorithms, genetic programming",
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isbn13 = "978-3-642-32902-9",
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series = "Studies in Computational Intelligence",
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pages = "79--89",
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URL = "http://dx.doi.org/10.1007/978-3-642-32903-6_7",
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DOI = "doi:10.1007/978-3-642-32903-6_7",
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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