DEVELOPMENT OF ENTERPRISE CREDIT RISK ASSESSMENT MODEL FOR LITHUANIAN CREDIT UNIONS

被引：0

作者：

Spicas, Renatas ^{[1
]}

Kanapickiene, Rasa ^{[2
]}

Vijunas, Mindaugas ^{[1
]}

Kirka, Robertas ^{[3
]}

机构：

[1] Vilnius Univ, Kaunas Fac, Dept Finance & Accounting, Muitines Str 12, LT-44280 Kaunas, Lithuania

[2] Vilnius Univ, Fac Econ, Dept Finance, Sauletekio Av 9, LT-10222 Vilnius, Lithuania

[3] Vilnius Univ, Fac Math & Informat, Dept Math Stat, Naugarduko Str 24, LT-03225 Vilnius, Lithuania

来源：

TRANSFORMATIONS IN BUSINESS & ECONOMICS | 2018年 / 17卷 / 01期

关键词：

credit risk assessment; logistic regression; credit unions; Lithuania; FEATURE-SELECTION METHODS; SUPPORT VECTOR MACHINES; BANKRUPTCY PREDICTION; NEURAL-NETWORKS; SCORING MODELS; FINANCIAL RATIOS; HYBRID APPROACH; CLASSIFICATION; PROBABILITY; ALGORITHMS;

D O I：

暂无

中图分类号：

F [经济];

学科分类号：

02 ;

摘要：

As credit unions expand the expert credit risk assessment methods are becoming ineffective. It becomes essential to apply quantitative risk assessment methods by employing objective analytical information. Credit unions should apply statistical credit risk assessment models to assess credit risk of potential loan recipients as accurately as possible. However, current credit risk assessment models are usually adapted to the banking sector. Thus, the aim of this article is to form a logistic regression model of enterprise credit risk assessment for Lithuanian credit unions. Definitions of "good" and "bad" debtor are reconsidered when developing the model; financial and nonfinancial ratios able to best describe the probability of default are researched Model development methodology has been improved and original logistic regression model of enterprise credit risk has been provided

引用

页码：152 / 177

页数：26

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