Artikel

Estimation of maximum potential losses for digital banking transaction risks using the extreme value-at-risks method

The application of industry 4.0 in banking presents many challenges, with several operational risks related to downtime and timeout services due to system failures. One of the operational risk management steps is to estimate the value of the maximum potential losses. The purpose of this study is to estimate the maximum potential losses for digital banking transaction risks. The method used for estimating risks is the EVaR method. There are several steps in this study. The first step is to resample the data using MEBoot. This process is a simulation of the operational risk loss data of digital banking. Next, the threshold value is determined to obtain the extreme data value. Then, a Kolmogorov-Smirnov test is conducted to fit the data with the GPD. Afterward, the GPD parameter is estimated. Then, EVaR is calculated using a portfolio approach to obtain a combination of risk values as maximum potential losses. The analysis results show that the maximum potential loss is IDR144,357,528,750.94. The research results imply that the banks need to pay attention to the maximum potential losses of digital financial transactions as a reference for risk management. Therefore, banks can anticipate the adequacy of reserve funds for these potential risks.

Sprache
Englisch

Erschienen in
Journal: Risks ; ISSN: 2227-9091 ; Volume: 10 ; Year: 2022 ; Issue: 1 ; Pages: 1-18 ; Basel: MDPI

Klassifikation
Wirtschaft
Thema
digital banking
digital transaction system risks
risk management
maximum potential losses
EVaR method
portfolio approach

Ereignis
Geistige Schöpfung
(wer)
Saputra, Moch Panji Agung
Sukono
Chaerani, Diah
Ereignis
Veröffentlichung
(wer)
MDPI
(wo)
Basel
(wann)
2022

DOI
doi:10.3390/risks10010010
Handle
Letzte Aktualisierung
10.03.2025, 11:43 MEZ

Datenpartner

Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.

Objekttyp

  • Artikel

Beteiligte

  • Saputra, Moch Panji Agung
  • Sukono
  • Chaerani, Diah
  • MDPI

Entstanden

  • 2022

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