Changes in operational risk and its determinants under Covid-19

IF 0.4 4区经济学 Q4 BUSINESS, FINANCE

Journal of Operational Risk Pub Date : 2022-01-01 DOI:10.21314/jop.2022.018

Zongrun Wang, Haiqin Fu, Ling Zhou

引用次数: 0

Abstract

This examines the direct impact of the Covid-19 pandemic on the operational risk of Chinese commercial banks and the moderating effect of bank size, business diversification and regulatory records. To address the lack of data in operational risk studies, we gather financial statements on operational risk to obtain empirical proxy variables. We conduct an empirical study using 639 financial statements from 20 listed commercial banks in China from 2011 Q4 to 2021 Q3 and find that the Covid-19 pandemic has increased the operational risk of commercial banks. Moreover, business diversification, bank size and poor regulatory record significantly increase the operational risk effects of the pandemic. Finally, we test the robustness of our results, supporting our conclusions and providing new insights into the interaction between the Covid-19 pandemic and banks’ operational risk. © 2022 Infopro Digital Risk (IP) Limited.

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Covid-19下操作风险及其决定因素的变化

本研究考察了新冠肺炎疫情对中国商业银行操作风险的直接影响，以及银行规模、业务多样化和监管记录的调节作用。为了解决操作风险研究中数据不足的问题，我们收集了有关操作风险的财务报表，以获得经验代理变量。我们对中国20家上市商业银行2011年第四季度至2021年第三季度的639份财务报表进行了实证研究，发现新冠肺炎疫情增加了商业银行的操作风险。此外，业务多样化、银行规模和糟糕的监管记录大大增加了疫情对操作风险的影响。最后，我们测试了结果的稳健性，支持了我们的结论，并为Covid-19大流行与银行操作风险之间的相互作用提供了新的见解。©2022 Infopro Digital Risk (IP) Limited。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Journal of Operational Risk BUSINESS, FINANCE-

CiteScore

1.00

自引率

40.00%

发文量

期刊介绍： In December 2017, the Basel Committee published the final version of its standardized measurement approach (SMA) methodology, which will replace the approaches set out in Basel II (ie, the simpler standardized approaches and advanced measurement approach (AMA) that allowed use of internal models) from January 1, 2022. Independently of the Basel III rules, in order to manage and mitigate risks, they still need to be measurable by anyone. The operational risk industry needs to keep that in mind. While the purpose of the now defunct AMA was to find out the level of regulatory capital to protect a firm against operational risks, we still can – and should – use models to estimate operational risk economic capital. Without these, the task of managing and mitigating capital would be incredibly difficult. These internal models are now unshackled from regulatory requirements and can be optimized for managing the daily risks to which financial institutions are exposed. In addition, operational risk models can and should be used for stress tests and Comprehensive Capital Analysis and Review (CCAR). The Journal of Operational Risk also welcomes papers on nonfinancial risks as well as topics including, but not limited to, the following. The modeling and management of operational risk. Recent advances in techniques used to model operational risk, eg, copulas, correlation, aggregate loss distributions, Bayesian methods and extreme value theory. The pricing and hedging of operational risk and/or any risk transfer techniques. Data modeling external loss data, business control factors and scenario analysis. Models used to aggregate different types of data. Causal models that link key risk indicators and macroeconomic factors to operational losses. Regulatory issues, such as Basel II or any other local regulatory issue. Enterprise risk management. Cyber risk. Big data.