Indeterminate values of target variable in development of credit scoring models

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F13%3A00069259" target="_blank" >RIV/00216224:14310/13:00069259 - isvavai.cz</a>

Výsledek na webu

<a href="http://dx.doi.org/10.11118/actaun201361072709" target="_blank" >http://dx.doi.org/10.11118/actaun201361072709</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.11118/actaun201361072709" target="_blank" >10.11118/actaun201361072709</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Indeterminate values of target variable in development of credit scoring models

Popis výsledku v původním jazyce

In the beginning of every modelling procedure, the first question to ask is what we are trying to predict by the model. In credit scoring the most frequent case is modelling of probability of default; however other situations, such as fraud, revolving ofthe credit or success of collections could be predicted as well. Nevertheless, the first step is always to define the target variable. The target variable is generally an ?output? of the model. It contains the information on the available data that we want to predict in future data. In credit scoring it is commonly called good/bad definition. In this paper we study the effect of use of indeterminate value of target variable in development of credit scoring models. We explain the basic principles of logistic regression modelling and selection of target variable. Next, the focus is given to introduction of some of the widely used statistics for model assessment.

Název v anglickém jazyce

Indeterminate values of target variable in development of credit scoring models

Popis výsledku anglicky

In the beginning of every modelling procedure, the first question to ask is what we are trying to predict by the model. In credit scoring the most frequent case is modelling of probability of default; however other situations, such as fraud, revolving ofthe credit or success of collections could be predicted as well. Nevertheless, the first step is always to define the target variable. The target variable is generally an ?output? of the model. It contains the information on the available data that we want to predict in future data. In credit scoring it is commonly called good/bad definition. In this paper we study the effect of use of indeterminate value of target variable in development of credit scoring models. We explain the basic principles of logistic regression modelling and selection of target variable. Next, the focus is given to introduction of some of the widely used statistics for model assessment.

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BB - Aplikovaná statistika, operační výzkum

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2013

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Acta universitatis agriculturae et silviculturae Mendelianae Brunensis

ISSN

1211-8516

e-ISSN

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Svazek periodika

61

Číslo periodika v rámci svazku

7

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

8

Strana od-do

2709-2716

Kód UT WoS článku

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EID výsledku v databázi Scopus

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