Naslov
Small business credit scoring: A comparison of logistic regression, neural network and decision tree models

Autori
Zekić-Sušac, Marijana ; Šarlija, Nataša ; Benšić, Mirta

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Proceedings of the 26th International Conference on Information Tehnology Interfaces / Lužar-Stiffler, Vesna - Zagreb : Sveučilišni računski centar Sveučilišta u Zagrebu (Srce), 2004, 265-270

Skup
International Conference on Information Technology Interfaces (ITI) 2004

Mjesto i datum
Dubrovnik, Hrvatska; Cavtat, Hrvatska, 07.06.2004. - 10.06.2004

Vrsta sudjelovanja
Predavanje

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
credit scoring modeling; decision trees; logistic regression; neural network; small business

Sažetak
The paper compares the models for small business credit scoring developed by logistic regression, neural networks, and CART decision trees on a Croatian bank dataset. The models obtained by all three methodologies were estimated ; then validated on the same hold-out sample, and their performance is compared. There is an evident significant difference among the best neural network model, decision tree model, and logistic regression model. The most successful neural network model was obtained by the probabilistic algorithm. The best model extracted the most important features for small business credit scoring from the observed data.

Izvorni jezik
Engleski

Znanstvena područja
Ekonomija

POVEZANOST RADA