The regulatory loss cut-off level: Does it undervalue the operational capital at risk?

Jiménez-Rodríguez, Enrique; Feria-Domínguez, José Manuel; Martín-Marín, José Luis

doi:10.1016/j.srfe.2011.09.003

Cited by 2 publications

(6 citation statements)

References 10 publications

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“…LDA has evolved in many ways to ensure suitability with loss data having different characteristics, such as fat-tail and data truncation. For instance, Jiménez-Rodríguez et al ( 2011 ) applied LDA to assess the operational risk of banks based on left-truncated data. Li et al ( 2009 ) and Wang et al ( 2012 ) proposed a PSD-LDA that combines a parameter form for ordinary losses, and a GPD for extreme losses, and then estimated the operational risk by LDA using a Monte Carlo simulation.…”

Section: Methodsmentioning

confidence: 99%

“…The losses range from 0.0001 yuan to 65.89 million yuan. However, there is a consensus that the operational risk losses collected from public media may be biased, which makes the number of small losses look lesser than the actual data (Chen 2019 ; Jiménez-Rodríguez et al 2011 ; Shevchenko and Temnov 2009 ). The unwanted biases affect the accuracy of the operational capital charge (Jiménez-Rodríguez et al 2011 ).…”

Section: Database Construction and Characteristic Analysismentioning

confidence: 99%

“…However, there is a consensus that the operational risk losses collected from public media may be biased, which makes the number of small losses look lesser than the actual data (Chen 2019 ; Jiménez-Rodríguez et al 2011 ; Shevchenko and Temnov 2009 ). The unwanted biases affect the accuracy of the operational capital charge (Jiménez-Rodríguez et al 2011 ). A higher threshold can better avoid data biases and increase the statistical significance; hence, we assume a relatively large value at 0.1 million yuan as the data collecting threshold, that is, the left-truncated point.…”

Section: Database Construction and Characteristic Analysismentioning

confidence: 99%

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Operational risk assessment of third-party payment platforms: a case study of China

Yao

2022

Financ Innov

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Operational risk events have severely impacted the development of third-party payment (TPP) platforms, and have even led to a discussion on the operational risk capital charge settlement by relevant international regulators. However, prior studies have mostly focused on qualitative mechanism analysis, and have rarely examined quantitative risk assessment based on actual operational risk events. Therefore, this study attempts to assess the operational risk on TPP platforms in China by constructing a systematic framework incorporating database construction and risk modeling. First, the operational risk database that covers 202 events between Q1, 2014, and Q2, 2020 is constructed. Then, specific causes are clarified, and the characteristics are analyzed from both the trend and loss severity perspectives. Finally, the piecewise-defined severity distribution based-Loss Distribution Approach (PSD-LDA) with double truncation is utilized to assess the operational risk. Two main conclusions are drawn from the empirical analysis. First, legal risk and external fraud risk are the two main causes of operational risk. Second, the yearly Value at Risk and Expected Shortfall are 724.46 million yuan and 1081.98 million yuan under the 99.9% significance level, respectively. Our results are beneficial for both TPP platform operators and regulators in managing and controlling operational risk.

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Section: Methodsmentioning

confidence: 99%

Section: Database Construction and Characteristic Analysismentioning

confidence: 99%

Section: Database Construction and Characteristic Analysismentioning

confidence: 99%

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Operational risk assessment of third-party payment platforms: a case study of China

Yao

2022

Financ Innov

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“…They validated the method on synthetic time series and emphesesized that the method could be used for the practical implementation in a mid or small sized bank, since it contains a small effect on the organizational structure of a bank and needs an investment in human resources, which is limited to the computational area. Jiménez-Rodríguez et al (2011) explain that Basel II generates a minimum threshold of 10,000 Euros for operational losses when estimating regulatory capital for financial firms. However, this recommendation is not obligatory for the bank industry and banks are permitted to use internal thresholds discretionally.…”

Section: Introductionmentioning

confidence: 99%

“…However, this recommendation is not obligatory for the bank industry and banks are permitted to use internal thresholds discretionally. Therefore, Jiménez-Rodríguez et al (2011) analyzed the potential effect that the selection of a specific threshold could possibly have on the final estimation of the capital charge for covering operational risk, adopting a critical perspective. They used the internal operational losses database (IOLD) provided by a Spanish Saving Bank to calculate the loss distribution approach (LDA) for various modeling thresholds.…”

Section: Introductionmentioning

confidence: 99%

An empirical study to measure the effects of various factors on operating loss

Valahzaghard¹,

Araghi²,

Papkiyadeh³

et al. 2012

MSL

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In this paper, we present an empirical investigation to measure the effects of various factors on operating loss in one of major Iranian banks called Bank Mellat. The proposed study of this paper uses a standard questionnaire and distributes it among 57 people who are mainly in top management levels. The questions are categorized into five groups including events related to the processes and methods, events outside the organization, related events within the organization and business disruptions and system failure. The results of our survey confirm that the loss associated with events related to the processes and methods increases operating risk meaningfully, the loss associated with business disruptions and system failure increases operating risk meaningfully and the loss associated with related events within the organization increases operating risk meaningfully. However, our survey do not confirm that the loss associated with events outside the organization increase operating, risk meaningfully. Finally, the preliminary survey of our analysis shows that there is not enough evidence to believe that the effects of business disruption and internal affairs are significantly different from the other event.

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The regulatory loss cut-off level: Does it undervalue the operational capital at risk?

Cited by 2 publications

References 10 publications

Operational risk assessment of third-party payment platforms: a case study of China

Operational risk assessment of third-party payment platforms: a case study of China

An empirical study to measure the effects of various factors on operating loss

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