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Author: Zhang Zenglian

Affiliation: School of Economics and Management and University of Science and Technology Beijing, China

Keyword(s): Commercial bank, Personal loan, Credit risk evaluation, Apriori.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Guard against financial risks, reduce bad loans, increase the ability to identity risk of commercial banks, the key is risk warning. In view of the increasing proportion of personal loans in banking business, it is particularly important to warning personal loans credit risk. Commercial bank lending itself is a complex nonlinear system, using general linear theory is difficult to objectively reflect the laws of this, this paper uses association rule. Personal loan credit index first constructed, and then use apriori algorithm to extract rules. Results showed that apriori algorithm plays an important role in identifying risk in personal loans.

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Paper citation in several formats:
Zenglian, Z. (2011). RESEARCH OF CREDIT RISK OF COMMERCIAL BANK PERSONAL LOAN BASED ON ASSOCIATION RULE. In Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-8425-53-9; ISSN 2184-4992, SciTePress, pages 129-134. DOI: 10.5220/0003413101290134

@conference{iceis11,
author={Zhang Zenglian.},
title={RESEARCH OF CREDIT RISK OF COMMERCIAL BANK PERSONAL LOAN BASED ON ASSOCIATION RULE},
booktitle={Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2011},
pages={129-134},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003413101290134},
isbn={978-989-8425-53-9},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 13th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - RESEARCH OF CREDIT RISK OF COMMERCIAL BANK PERSONAL LOAN BASED ON ASSOCIATION RULE
SN - 978-989-8425-53-9
IS - 2184-4992
AU - Zenglian, Z.
PY - 2011
SP - 129
EP - 134
DO - 10.5220/0003413101290134
PB - SciTePress