LOGISTIC REGRESSION AND MULTICRITERIA DECISION MAKING IN CREDIT SCORING

被引：0

作者：

Sarlija, Natasa ^{[1
]}

Soric, Kristina ^{[2
]}

Vlah, Silvija ^{[2
]}

Rosenzweig, Visnja Vojvodic ^{[2
]}

机构：

[1] Univ JJ Strossmayer Osijek, Fac Econ Osijek, Gajev Trg 7, Osijek, Croatia

[2] Univ Zagreb, Fac Econ, Zagreb, Croatia

来源：

PROCEEDINGS OF THE 10TH INTERNATIONAL SYMPOSIUM ON OPERATIONAL RESEARCH SOR 09 | 2009年

关键词：

credit scoring; logistic regression; multicriteria decision making; NEURAL-NETWORKS; SUPPORT; MODELS;

D O I：

暂无

中图分类号：

C93 [管理学]; O22 [运筹学];

学科分类号：

070105 ; 12 ; 1201 ; 1202 ; 120202 ;

摘要：

The paper aims to develop models for evaluating credit risk of small companies for one Croatian bank using two different methodologies - logistic regression and multicriteria decision making. The first method's result is the probability of default while the second method's result is the classification of the firms regarding predefined criteria for credit scoring. The paper gives the hints how to combine these two methods in order to construct an efficient strategy for achieving high performance.

引用

页码：175 / +

页数：3

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