Pregled bibliografske jedinice broj: 1238057
Credit rating prediction using machine learning techniques: A bibliometric analysis
Credit rating prediction using machine learning techniques: A bibliometric analysis // Proceedings of the 90th International Scientific Conference on Economic and Social Development – "Building Resilient Society: National and Corporate Security" / Kopal, Robert ; Samodol, Ante ; Buccella, Domenico (ur.).
Zagreb, 2022. str. 264-272 (predavanje, recenziran, cjeloviti rad (in extenso), znanstveni)
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Naslov
Credit rating prediction using machine learning
techniques: A bibliometric analysis
Autori
Šebalj, Dario
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of the 90th International Scientific Conference on Economic and Social Development – "Building Resilient Society: National and Corporate Security"
/ Kopal, Robert ; Samodol, Ante ; Buccella, Domenico - Zagreb, 2022, 264-272
Skup
90th International Scientific Conference on Economic and Social Development: "Building Resilient Society: National and Corporate Security"
Mjesto i datum
Zagreb, Hrvatska, 16.12.2022. - 17.12.2022
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Recenziran
Ključne riječi
Bibliometric analysis ; Credit rating ; Machine learning ; Forecast ; Prediction
Sažetak
Credit rating is the assessment of the financial situation of a state, a company or an individual, i.e. it is a criterion for granting credit. Advanced prediction methods, such as machine learning methods, are increasingly used to predict credit ratings due to their high accuracy. In this paper, a bibliometric analysis of papers dealing with machine learning methods for credit rating prediction is performed. The data used for the analysis is retrived from the two most relevant scientific databases, Web of Science Core Collection (WoSCC) and Scopus. As part of the bibliometric analysis, the authors used several analysis techniques: citation analysis, cocitation analysis, co-authorship analysis and keywords analysis. Keyword analysis shows that all articles mainly deal with 3 machine learning techniques - support vector machines, neural networks and decision trees. The main conclusion is that the research area of machine learning for credit rating prediction is still under- researched, as there is a relatively small number of articles dealing with this topic. Moreover, the observed papers are not so frequently cited and have a low number of mutual links, which shows that their importance is not so high.
Izvorni jezik
Engleski
Znanstvena područja
Ekonomija, Informacijske i komunikacijske znanosti
Citiraj ovu publikaciju:
Časopis indeksira:
- HeinOnline
