Building intelligent credit scoring systems using decision tables
Building intelligent credit scoring systems using decision tables
Accuracy and comprehensibility are two important criteria when developing decision support systems for credit scoring. In this paper, we focus on the second criterion and propose the use of decision tables as an alternative knowledge visualization formalism which lends itself very well to build intelligent and user-friendly credit scoring systems. Starting from a set of propositional if-then rules extracted by a neural network rule extraction algorithm, we develop decision tables and demonstrate their efficiency and user-friendliness for 2 real-life credit scoring cases.
Baesens, Bart
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Mues, Christophe
07438e46-bad6-48ba-8f56-f945bc2ff934
Setiono, Rudy
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De Backer, Manu
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Vanthienen, Jan
6f3d818f-0fce-46fa-966b-160e645caf6d
2003
Baesens, Bart
f7c6496b-aa7f-4026-8616-ca61d9e216f0
Mues, Christophe
07438e46-bad6-48ba-8f56-f945bc2ff934
Setiono, Rudy
98ca7376-c02e-4f65-a2df-bb09cc0c6e6b
De Backer, Manu
9c56870f-a34a-4eba-87ef-137fec532349
Vanthienen, Jan
6f3d818f-0fce-46fa-966b-160e645caf6d
Baesens, Bart, Mues, Christophe, Setiono, Rudy, De Backer, Manu and Vanthienen, Jan
(2003)
Building intelligent credit scoring systems using decision tables.
Camp, O., Filipe, J.B., Hammoudi, S. and Piattini, M.G.
(eds.)
In Enterprise Information Systems V.
Springer..
Record type:
Conference or Workshop Item
(Paper)
Abstract
Accuracy and comprehensibility are two important criteria when developing decision support systems for credit scoring. In this paper, we focus on the second criterion and propose the use of decision tables as an alternative knowledge visualization formalism which lends itself very well to build intelligent and user-friendly credit scoring systems. Starting from a set of propositional if-then rules extracted by a neural network rule extraction algorithm, we develop decision tables and demonstrate their efficiency and user-friendliness for 2 real-life credit scoring cases.
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More information
Published date: 2003
Venue - Dates:
5th International Conference on Enterprise Information Systems (ICEIS'2003), 2003-01-01
Identifiers
Local EPrints ID: 36170
URI: http://eprints.soton.ac.uk/id/eprint/36170
PURE UUID: 8bb45c7b-3356-4c7e-8e6a-14ea103a8b0c
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Date deposited: 24 May 2006
Last modified: 08 Apr 2022 01:38
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Contributors
Author:
Rudy Setiono
Author:
Manu De Backer
Author:
Jan Vanthienen
Editor:
O. Camp
Editor:
J.B. Filipe
Editor:
S. Hammoudi
Editor:
M.G. Piattini
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