{"title":"Systemic Operational Risk - The Libor Manipulation Scandal","authors":"P. Mcconnell","doi":"10.21314/JOP.2013.127","DOIUrl":null,"url":null,"abstract":"The manipulation of LIBOR rates was not a localized event. Unscrupulous traders and managers in some of the largest banks around the world deliberately and systematically manipulated borrowing rates. It was not the work of isolated 'rogue traders' but part of business-as-usual in the international money markets. This paper describes the LIBOR Scandal and argues that it is an example of Systemic Operational Risk, in particular People Risk. The paper first describes the LIBOR setting process. The explosive growth over the past 25 years in the use of Interest Rate Swaps (IRS) and the process of resetting rates on IRS, which ultimately led to the unethical manipulation of the underlying LIBOR rates, is then described. The paper then looks at official inquiries into manipulation of LIBOR at three banks: Barclays, UBS and RBS to identify examples of Operational Risk. The transcripts of conversations unearthed by these investigations show rampant illicit activities that were apparently a normal part of doing business, as traders, LIBOR submitters and brokers colluded to manipulate LIBOR for their own interests. Finally, the paper makes some suggestions as to how the management of Systemic Operational Risks may be addressed by banks and regulators.","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"15 1","pages":"59-99"},"PeriodicalIF":0.4000,"publicationDate":"2013-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"39","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Operational Risk","FirstCategoryId":"96","ListUrlMain":"https://doi.org/10.21314/JOP.2013.127","RegionNum":4,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 39
Abstract
The manipulation of LIBOR rates was not a localized event. Unscrupulous traders and managers in some of the largest banks around the world deliberately and systematically manipulated borrowing rates. It was not the work of isolated 'rogue traders' but part of business-as-usual in the international money markets. This paper describes the LIBOR Scandal and argues that it is an example of Systemic Operational Risk, in particular People Risk. The paper first describes the LIBOR setting process. The explosive growth over the past 25 years in the use of Interest Rate Swaps (IRS) and the process of resetting rates on IRS, which ultimately led to the unethical manipulation of the underlying LIBOR rates, is then described. The paper then looks at official inquiries into manipulation of LIBOR at three banks: Barclays, UBS and RBS to identify examples of Operational Risk. The transcripts of conversations unearthed by these investigations show rampant illicit activities that were apparently a normal part of doing business, as traders, LIBOR submitters and brokers colluded to manipulate LIBOR for their own interests. Finally, the paper makes some suggestions as to how the management of Systemic Operational Risks may be addressed by banks and regulators.
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.