Influence of variable interactions versus segmentation in credit scoring: a case study

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F12%3A00060319" target="_blank" >RIV/00216224:14310/12:00060319 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.sas.com/events/analytics/europe/pres/rezac.pdf" target="_blank" >http://www.sas.com/events/analytics/europe/pres/rezac.pdf</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Influence of variable interactions versus segmentation in credit scoring: a case study

Popis výsledku v původním jazyce

Credit scoring is a set of predictive models and their underlying techniques that aid financial institutions in the granting of credit. These techniques decide who will get credit, how much credit they should get, and what further strategies will enhancethe profitability of borrowers to lenders. The industry standard for modeling the probability of client default is the logistic regression. However, details such as inclusion of interactions of predictors or segmentation of given data sample may determine the success. The paper will present the influence of inclusion of variable interactions versus segmentation on quality of a credit scoring model.

Název v anglickém jazyce

Influence of variable interactions versus segmentation in credit scoring: a case study

Popis výsledku anglicky

Credit scoring is a set of predictive models and their underlying techniques that aid financial institutions in the granting of credit. These techniques decide who will get credit, how much credit they should get, and what further strategies will enhancethe profitability of borrowers to lenders. The industry standard for modeling the probability of client default is the logistic regression. However, details such as inclusion of interactions of predictors or segmentation of given data sample may determine the success. The paper will present the influence of inclusion of variable interactions versus segmentation on quality of a credit scoring model.

Druh

O - Ostatní výsledky

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

2012

Kód důvěrnosti údajů

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