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Komparativna Analiza Modela Kreditnog Skoringa: Konvencijalni Vs Modeli Bazirani Na Mašinskom I Dubokom Učenju

Author

Listed:
  • Milovan Rankov

Abstract

Ovaj istraživački rad predstavlja komparativnu analizu različitih modela kreditnog skoringa, fokusirajući se na poređenje logističke regresije sa naprednim modelima mašinskog i dubokog učenja. Kao indikatori performansi modela i osnova za poređenje njihove efikasnosti biće korišćeni tačnost, preciznost, F1, opoziv, Gini i AUC. Jedan od osnovnih ciljeva ovog rada jeste da na transparentan način prikaže efikasnost različitih model i ukaže na njihove prednosti odnosno nedostatke. Za emprijsku analizu biće korišćena „Kaggle” baza podataka o ponašanju dužnika, a samo modeliranje će biti rađeno u razvojnom okruženju PyCharm koristeći Python programski jezik. Jedan od osnovnih rezultata istraživanja jeste da su modeli bazirani na dubokom učenju daleko efikasniji od ostalih modela, posmatrano kroz prizmu pomenutih indikatora performansi.

Suggested Citation

  • Milovan Rankov, 2025. "Komparativna Analiza Modela Kreditnog Skoringa: Konvencijalni Vs Modeli Bazirani Na Mašinskom I Dubokom Učenju," Ekonomske ideje i praksa, Faculty of Economics and Business, University of Belgrade, issue 57, pages 29-45, June.
    • Handle: RePEc:beo:ekidpr:y:2025:i:57:p:29-45
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    More about this item

    Keywords

    modeli kreditnog skoringa; logistička regresija; mašinsko učenje; duboko učenje;
    All these keywords.

    JEL classification:

    • C45 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Neural Networks and Related Topics
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • G32 - Financial Economics - - Corporate Finance and Governance - - - Financing Policy; Financial Risk and Risk Management; Capital and Ownership Structure; Value of Firms; Goodwill

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