• Medientyp: E-Artikel
  • Titel: A dynamic credit risk assessment model with data mining techniques: Evidence from Iranian banks
  • Beteiligte: Moradi, Somayeh [VerfasserIn]; Mokhatab Rafiei, Farimah [VerfasserIn]
  • Erschienen: Heidelberg: Springer, 2019
  • Sprache: Englisch
  • DOI: https://doi.org/10.1186/s40854-019-0121-9
  • ISSN: 2199-4730
  • Schlagwörter: Non-performing loan ; FIS ; ANFIS ; Credit risk ; Dynamism ; Fuzzy clustering
  • Entstehung:
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  • Beschreibung: Giving loans and issuing credit cards are two of the main concerns of banks in that they include the risks of non-payment. According to the Basel 2 guidelines, banks need to develop their own credit risk assessment systems. Some banks have such systems; nevertheless they have lost a large amount of money simply because the models they used failed to accurately predict customers' defaults. Traditionally, banks have used static models with demographic or static factors to model credit risk patterns. However, economic factors are not independent of political fluctuations, and as the political environment changes, the economic environment evolves with it.
  • Zugangsstatus: Freier Zugang
  • Rechte-/Nutzungshinweise: Namensnennung (CC BY)