Financial technology (fintech) has driven a profound transformation in the finance industry, and the application of various new technologies in the financial sector has brought about changes in the operating environment faced by commercial banks. To assess the impact of fintech on commercial banks, we selected Chinese commercial banks as sample data, calculated the fintech application index at the individual bank level using text mining methods and principal component analysis, and conducted empirical tests using fixed-effect panel regression models. Our results indicate that the application of fintech can effectively increase a bank’s revenue. In terms of risk, using binned groups analysis we found that the development of fintech has a nonlinear, roughly L-shaped relationship with the risk of commercial banks. Further, we also considered the characteristics of the Chinese banking industry for further analysis of the impact of bank-type heterogeneity and to control for sample differences. In addition, we enhanced the robustness of the empirical results using substitution variables, instrumental variable methods and propensity score matching. In conclusion, starting from a new perspective on fintech, using the Chinese banking industry as an example, we offer suggestions for developing the fintech capabilities of banks in developing countries.
{"title":"How does fintech affect the revenue and risk of commercial banks? Evidence from China","authors":"Lixia Yu, Zhenghan Li, Liujue Li","doi":"10.21314/jop.2023.008","DOIUrl":"https://doi.org/10.21314/jop.2023.008","url":null,"abstract":"Financial technology (fintech) has driven a profound transformation in the finance industry, and the application of various new technologies in the financial sector has brought about changes in the operating environment faced by commercial banks. To assess the impact of fintech on commercial banks, we selected Chinese commercial banks as sample data, calculated the fintech application index at the individual bank level using text mining methods and principal component analysis, and conducted empirical tests using fixed-effect panel regression models. Our results indicate that the application of fintech can effectively increase a bank’s revenue. In terms of risk, using binned groups analysis we found that the development of fintech has a nonlinear, roughly L-shaped relationship with the risk of commercial banks. Further, we also considered the characteristics of the Chinese banking industry for further analysis of the impact of bank-type heterogeneity and to control for sample differences. In addition, we enhanced the robustness of the empirical results using substitution variables, instrumental variable methods and propensity score matching. In conclusion, starting from a new perspective on fintech, using the Chinese banking industry as an example, we offer suggestions for developing the fintech capabilities of banks in developing countries.","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"90 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135506064","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Xiaoqian Zhu, Yinghui Wang, Mingxi Liu, Jianping Li
{"title":"How to choose the dependence types in operational risk measurement? A method considering strength, sensitivity and simplicity","authors":"Xiaoqian Zhu, Yinghui Wang, Mingxi Liu, Jianping Li","doi":"10.21314/jop.2023.002","DOIUrl":"https://doi.org/10.21314/jop.2023.002","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"11 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88582651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Filippo Curti, Jeffrey R. Gerlach, Sophia Kazinnik, Michael Lee, Atanas Mihov
: Cyber risk is undeniably one of the most critical emerging risks to the financial industry. However, even though cyber risk is recognized as a significant threat to financial institutions and, more generally, to financial stability, the quantification and analysis of cyber risk has not yet matured to the point where it can be consistently measured and managed against corporate risk appetites. This impedes efforts to effectively measure and manage such risk, diminishing institutions’ individual and collective readiness to handle system-level cyber threats. This paper aims to address this gap by providing a preliminary cyber risk definition and classification of cyber risk for risk management purposes. As such, the proposed definition and classification would ensure that adopting institutions are utilizing common language and allowing consistent data collection and sharing. We provide a deeper dive into the reasoning behind the variables we propose to collect and demonstrate how some of the existing cybersecurity events map into our proposed scheme.
{"title":"Cyber risk definition and classification for financial risk management","authors":"Filippo Curti, Jeffrey R. Gerlach, Sophia Kazinnik, Michael Lee, Atanas Mihov","doi":"10.21314/jop.2022.036","DOIUrl":"https://doi.org/10.21314/jop.2022.036","url":null,"abstract":": Cyber risk is undeniably one of the most critical emerging risks to the financial industry. However, even though cyber risk is recognized as a significant threat to financial institutions and, more generally, to financial stability, the quantification and analysis of cyber risk has not yet matured to the point where it can be consistently measured and managed against corporate risk appetites. This impedes efforts to effectively measure and manage such risk, diminishing institutions’ individual and collective readiness to handle system-level cyber threats. This paper aims to address this gap by providing a preliminary cyber risk definition and classification of cyber risk for risk management purposes. As such, the proposed definition and classification would ensure that adopting institutions are utilizing common language and allowing consistent data collection and sharing. We provide a deeper dive into the reasoning behind the variables we propose to collect and demonstrate how some of the existing cybersecurity events map into our proposed scheme.","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"195 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76949164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Zuzhen Ji, Xuhai Duan, D. Pons, Yong Chen, Zhi Pei
{"title":"Integrating text mining and analytic hierarchy process risk assessment with knowledge graphs for operational risk analysis","authors":"Zuzhen Ji, Xuhai Duan, D. Pons, Yong Chen, Zhi Pei","doi":"10.21314/jop.2023.004","DOIUrl":"https://doi.org/10.21314/jop.2023.004","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"31 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75382870","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Some value-at-risk (VaR) calculations yield extremely large results, which are often rejected on the grounds that they are inconsistent with the operational loss profile of the organization concerned. Therefore, an informal limit has effectively been placed on VaR. Hitherto, the concept of a “maximum” VaR has rarely been considered. In this paper, we propose an objective and simple process to determine whether or not a calculated VaR is “too large”, and thereby give a precise definition of “too large” in this context. A simple decision process, using a constant multiplier of the annualized sum of losses, is proposed to reject distributions that produce extremely high VaR values. This decision process works in conjunction with a bootstrap to also reject distributions that produce very low VaR values. Together, they determine whether or not a calculated VaR value is “credible”. A practical guide to using the combined procedures is given, along with a discussion of potential problems and viable solutions to those problems.
{"title":"Credible value-at-risk","authors":"Peter Mitic","doi":"10.21314/jop.2023.005","DOIUrl":"https://doi.org/10.21314/jop.2023.005","url":null,"abstract":"Some value-at-risk (VaR) calculations yield extremely large results, which are often rejected on the grounds that they are inconsistent with the operational loss profile of the organization concerned. Therefore, an informal limit has effectively been placed on VaR. Hitherto, the concept of a “maximum” VaR has rarely been considered. In this paper, we propose an objective and simple process to determine whether or not a calculated VaR is “too large”, and thereby give a precise definition of “too large” in this context. A simple decision process, using a constant multiplier of the annualized sum of losses, is proposed to reject distributions that produce extremely high VaR values. This decision process works in conjunction with a bootstrap to also reject distributions that produce very low VaR values. Together, they determine whether or not a calculated VaR value is “credible”. A practical guide to using the combined procedures is given, along with a discussion of potential problems and viable solutions to those problems.","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135659821","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Mansoureh Rasouli, M. A. Fariborzi Araghi, T. Damercheli
{"title":"Application of the radial basis function in solving an operational risk management model: investigating the probability of bank survival with risk reserves","authors":"Mansoureh Rasouli, M. A. Fariborzi Araghi, T. Damercheli","doi":"10.21314/jop.2022.034","DOIUrl":"https://doi.org/10.21314/jop.2022.034","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"12 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81042779","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Operational risk and regulatory capital: do public and private banks differ?","authors":"Tarika Singh Sikarwar, Harshita Mathur, Vandana Lothi, Aarti Tomar","doi":"10.21314/jop.2023.001","DOIUrl":"https://doi.org/10.21314/jop.2023.001","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"32 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76155386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Haitham Nobanee, Maryam Alhajjar, Mehroz Nida Dilshad, Maitha Sultan Al Kuwaiti, Anoud Abdulla Al Kaabi
{"title":"Operational risk: a global examination based on bibliometric analysis","authors":"Haitham Nobanee, Maryam Alhajjar, Mehroz Nida Dilshad, Maitha Sultan Al Kuwaiti, Anoud Abdulla Al Kaabi","doi":"10.21314/jop.2022.031","DOIUrl":"https://doi.org/10.21314/jop.2022.031","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"12 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85209480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Michail Pazarskis, Andreas G. Koutupis, Maria I. Kyriakou, Stergios Galanis
{"title":"A risk-based internal audit methodology for Greek local government organizations","authors":"Michail Pazarskis, Andreas G. Koutupis, Maria I. Kyriakou, Stergios Galanis","doi":"10.21314/jop.2022.029","DOIUrl":"https://doi.org/10.21314/jop.2022.029","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"37 1","pages":""},"PeriodicalIF":0.5,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73306345","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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