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Pregled bibliografske jedinice broj: 259040

Modeling Small Business Credit Scoring Using Logistic Regression, Neural Networks, and Decision Trees


Benšić, Mirta; Šarlija, Nataša; Zekić-Sušac, Marijana
Modeling Small Business Credit Scoring Using Logistic Regression, Neural Networks, and Decision Trees // Intelligent Systems in Accounting, Finance and Management, 13 (2005), 3; 133 - 150 (podatak o recenziji nije dostupan, članak, znanstveni)


CROSBI ID: 259040 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Modeling Small Business Credit Scoring Using Logistic Regression, Neural Networks, and Decision Trees

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

Izvornik
Intelligent Systems in Accounting, Finance and Management (1055-615X) 13 (2005), 3; 133 - 150

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
CART decision trees; credit scoring modelling; logistic regression; neural networks; small business loans

Sažetak
Previous research on credit scoring that used statistical and intelligent methods was mostly focused on commercial and consumer lending. The main purpose of this paper is to extract important features for credit scoring in small business lending on a dataset with specific transitional economic conditions using relatively small data set. To do this we compare the accuracy of best models extracted by different methodologies, such as logistic regression, neural networks, and CART decision trees. Four different neural network algorithms are tested, including backpropagation, radial basis function network, probabilistic and learning vector quantization, using forward nonlinear variable selection strategy. Although the test of differences in proportion and McNemar’ s test do not show statistically significant difference in the tested models, the probabilistic NN model produces the highest hit rate and the lowest type I error. According to the measures of association the best NN model also shows the highest degree of association with the data, and it yields the lowest total relative cost of misclassification for all examined scenarios. The best model extracts a set of important features for small business credit scoring for the observed sample, emphasizing credit program characteristics, as well as entrepreneur's personal and business characteristics as the most important.

Izvorni jezik
Engleski

Znanstvena područja
Ekonomija, Informacijske i komunikacijske znanosti



POVEZANOST RADA


Projekti:
0235002

Ustanove:
Ekonomski fakultet, Osijek,
Sveučilište u Osijeku, Odjel za matematiku


Citiraj ovu publikaciju:

Benšić, Mirta; Šarlija, Nataša; Zekić-Sušac, Marijana
Modeling Small Business Credit Scoring Using Logistic Regression, Neural Networks, and Decision Trees // Intelligent Systems in Accounting, Finance and Management, 13 (2005), 3; 133 - 150 (podatak o recenziji nije dostupan, članak, znanstveni)
Benšić, M., Šarlija, N. & Zekić-Sušac, M. (2005) Modeling Small Business Credit Scoring Using Logistic Regression, Neural Networks, and Decision Trees. Intelligent Systems in Accounting, Finance and Management, 13 (3), 133 - 150.
@article{article, year = {2005}, pages = {133 - 150}, keywords = {CART decision trees, credit scoring modelling, logistic regression, neural networks, small business loans}, journal = {Intelligent Systems in Accounting, Finance and Management}, volume = {13}, number = {3}, issn = {1055-615X}, title = {Modeling Small Business Credit Scoring Using Logistic Regression, Neural Networks, and Decision Trees}, keyword = {CART decision trees, credit scoring modelling, logistic regression, neural networks, small business loans} }
@article{article, year = {2005}, pages = {133 - 150}, keywords = {CART decision trees, credit scoring modelling, logistic regression, neural networks, small business loans}, journal = {Intelligent Systems in Accounting, Finance and Management}, volume = {13}, number = {3}, issn = {1055-615X}, title = {Modeling Small Business Credit Scoring Using Logistic Regression, Neural Networks, and Decision Trees}, keyword = {CART decision trees, credit scoring modelling, logistic regression, neural networks, small business loans} }

Časopis indeksira:


  • Web of Science Core Collection (WoSCC)
    • Emerging Sources Citation Index (ESCI)


Uključenost u ostale bibliografske baze podataka::


  • The INSPEC Science Abstracts series





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