{"title":"Capital assessment of operational risk for the solvency of health insurance companies","authors":"Rafael Hernández Barros, M. I. M. Torre-Enciso","doi":"10.21314/JOP.2012.107","DOIUrl":"https://doi.org/10.21314/JOP.2012.107","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"37 1","pages":"43-65"},"PeriodicalIF":0.5,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74939711","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":"Legal risk and compliance for banks operating in a common law legal system","authors":"J. R. Terblanché","doi":"10.21314/JOP.2012.105","DOIUrl":"https://doi.org/10.21314/JOP.2012.105","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"12 1","pages":"67-79"},"PeriodicalIF":0.5,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74610375","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":"A combination model for operational risk estimation in a Chinese banking industry case","authors":"Jichuang Feng, Jianping Li, Lijun Gao, Zhongsheng Hua","doi":"10.21314/JOP.2012.106","DOIUrl":"https://doi.org/10.21314/JOP.2012.106","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"5 1","pages":"17-39"},"PeriodicalIF":0.5,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83770740","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}
Sometimes it is not possible to obtain a single parametric density with the desired tail behavior to fit a given data set. Splicing two different parametric densities is a useful process in such cases. Since the two parts depend on local data, a question arises over how best to assemble the two parts so that the properties of the whole data set are taken into account. We propose an application of the method of maximum entropy in the mean to splice the two parts together in such a way that the resulting global density has the first two moments of the full data set.
{"title":"Reconstructing heavy-tailed distributions by splicing with maximum entropy in the mean","authors":"Santiago Carrillo, H. Gzyl, A. Tagliani","doi":"10.21314/JOP.2012.108","DOIUrl":"https://doi.org/10.21314/JOP.2012.108","url":null,"abstract":"Sometimes it is not possible to obtain a single parametric density with the desired tail behavior to fit a given data set. Splicing two different parametric densities is a useful process in such cases. Since the two parts depend on local data, a question arises over how best to assemble the two parts so that the properties of the whole data set are taken into account. We propose an application of the method of maximum entropy in the mean to splice the two parts together in such a way that the resulting global density has the first two moments of the full data set.","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"1 1","pages":"3-15"},"PeriodicalIF":0.5,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90854549","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}
May 2011 was a very bad month for UK banks. In the previous month, a long running legal case was resolved when the UK High Court ruled against the British Banking Association (BBA) which had petitioned for a judicial review of regulatory action concerning mis-selling of Payment Protection Insurance (PPI) products. Following the ruling, the four major UK banks announced provisions totaling over £6 billion to cover restitution to buyers of their PPI products. Some of the banks also decided to exit the PPI business.At first glance, PPI appears to be standard insurance product. For an up-front or monthly premium, an insurer will sell protection to a borrower against being unable to make loan repayments, as a result of, for example, illness or unemployment. Before the market collapsed, the main distributors/arrangers of PPI contracts were the largest UK banks, often using their affiliated insurance subsidiary as the insurer.The underlying problems that generated the so-called PPI Scandal should not have come as a complete surprise to the banks. For several years prior to the ruling, consumer advocacy groups had been complaining loudly about banks selling PPI products to customers who did not fully understand the policies and, in many cases, did not need the protection provided. Yet, having seemingly taken on a life of its own, the practice of selling PPI policies continued and grew rapidly in all major banks. Various official inquiries found that the 'people' involved, from front line bank staff, lending managers to insurers just did not do the full due diligence necessary to check the suitability of PPI for many customers. Prudence seems to have been diluted/abandoned in a chase for increased product volume across the whole UK retail-banking sector. This paper argues that the losses incurred as a result of the PPI scandal were, in most part, precipitated by Systemic Operational Risk, in particular, People-related Risks. Using examples from official inquiries, the paper identifies some of the People Risks that went unmanaged in this part of the UK Retail banking sector system, until the PPI market seized up in 2011. The paper then suggests proactive approaches to People Risk Management that should help detect and minimize the impact of similar scandals in future. This topic is important as the demographic shift towards longer periods of retirement and the prevalence of the 'universal banking model', means that non-traditional banking products such insurance, pensions and investments, will be increasingly sold through banks, raising the specter of further mis-selling scandals in future.
{"title":"Systemic Operational Risk the UK Payment Protection Insurance Scandal","authors":"P. Mcconnell, K. Blacker","doi":"10.21314/JOP.2012.104","DOIUrl":"https://doi.org/10.21314/JOP.2012.104","url":null,"abstract":"May 2011 was a very bad month for UK banks. In the previous month, a long running legal case was resolved when the UK High Court ruled against the British Banking Association (BBA) which had petitioned for a judicial review of regulatory action concerning mis-selling of Payment Protection Insurance (PPI) products. Following the ruling, the four major UK banks announced provisions totaling over £6 billion to cover restitution to buyers of their PPI products. Some of the banks also decided to exit the PPI business.At first glance, PPI appears to be standard insurance product. For an up-front or monthly premium, an insurer will sell protection to a borrower against being unable to make loan repayments, as a result of, for example, illness or unemployment. Before the market collapsed, the main distributors/arrangers of PPI contracts were the largest UK banks, often using their affiliated insurance subsidiary as the insurer.The underlying problems that generated the so-called PPI Scandal should not have come as a complete surprise to the banks. For several years prior to the ruling, consumer advocacy groups had been complaining loudly about banks selling PPI products to customers who did not fully understand the policies and, in many cases, did not need the protection provided. Yet, having seemingly taken on a life of its own, the practice of selling PPI policies continued and grew rapidly in all major banks. Various official inquiries found that the 'people' involved, from front line bank staff, lending managers to insurers just did not do the full due diligence necessary to check the suitability of PPI for many customers. Prudence seems to have been diluted/abandoned in a chase for increased product volume across the whole UK retail-banking sector. This paper argues that the losses incurred as a result of the PPI scandal were, in most part, precipitated by Systemic Operational Risk, in particular, People-related Risks. Using examples from official inquiries, the paper identifies some of the People Risks that went unmanaged in this part of the UK Retail banking sector system, until the PPI market seized up in 2011. The paper then suggests proactive approaches to People Risk Management that should help detect and minimize the impact of similar scandals in future. This topic is important as the demographic shift towards longer periods of retirement and the prevalence of the 'universal banking model', means that non-traditional banking products such insurance, pensions and investments, will be increasingly sold through banks, raising the specter of further mis-selling scandals in future.","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"38 1","pages":"79-139"},"PeriodicalIF":0.5,"publicationDate":"2012-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84400487","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":"Combining scenario analysis with loss data in operational risk quantification","authors":"Eric Cope","doi":"10.21314/JOP.2012.102","DOIUrl":"https://doi.org/10.21314/JOP.2012.102","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"31 1","pages":"39-56"},"PeriodicalIF":0.5,"publicationDate":"2012-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73087071","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":"A nonparametric approach to analyzing operational risk with an application to insurance fraud","authors":"Catalina Bolancé, M. Ayuso, Montserrat Guillén","doi":"10.21314/JOP.2012.103","DOIUrl":"https://doi.org/10.21314/JOP.2012.103","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"105 1","pages":"57-75"},"PeriodicalIF":0.5,"publicationDate":"2012-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75664718","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":"A framework for the analysis of reputational risk","authors":"S. Scandizzo","doi":"10.21314/JOP.2011.094","DOIUrl":"https://doi.org/10.21314/JOP.2011.094","url":null,"abstract":"","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"14 1","pages":"41-63"},"PeriodicalIF":0.5,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78682443","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}
An important problem in the field of insurance and operational risk is the determination of the distribution function when a compound loss model is used for the total loss. A large variety of methods have been developed for this purpose. Here we explore some mathematical aspects of a method consisting of the reconstruction of the cumulative distribution function or the probability density of the compound loss, based on the knowledge of the Laplace transform of the compound loss, or, equivalently, based on the knowledge of the moments of the exponential of the compound loss. This is particularly useful when analytical models exist for the individual severities and for the frequency of events. In this case the moments are the values of the Laplace transform of the compound severity at integer points.
{"title":"Determining the total loss distribution from the moments of the exponential of the compound loss","authors":"H. Gzyl","doi":"10.21314/JOP.2011.096","DOIUrl":"https://doi.org/10.21314/JOP.2011.096","url":null,"abstract":"An important problem in the field of insurance and operational risk is the determination of the distribution function when a compound loss model is used for the total loss. A large variety of methods have been developed for this purpose. Here we explore some mathematical aspects of a method consisting of the reconstruction of the cumulative distribution function or the probability density of the compound loss, based on the knowledge of the Laplace transform of the compound loss, or, equivalently, based on the knowledge of the moments of the exponential of the compound loss. This is particularly useful when analytical models exist for the individual severities and for the frequency of events. In this case the moments are the values of the Laplace transform of the compound severity at integer points.","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"54 1","pages":"3-13"},"PeriodicalIF":0.5,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78288506","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}
A copula-based simulation model for supply portfolio risk in the presence of dependent breaches of contracts is introduced in this paper. We demonstrate our method for a supply-chain contract portfolio of commodity metals traded at the London Metal Exchange (LME). The analysis of spot price data on six LME com- modity metals leads us to use a t-copula dependence structure with t-marginals and generalized hyperbolic marginals for the log returns. We also provide effi- cient simulation algorithms using importance sampling for the normal and t- copula dependence structure to quantify risk measures, supply-at-risk and condi- tional supply-at-risk. Numerical examples on a portfolio of six commodity metals demonstrate that our proposed method succeeds in decreasing the variance of the simulations. A numerical sensitivity analysis for the choice of the copula function is also provided. To the best of our knowledge, this is the first paper proposing efficient simulation algorithms on a supply-chain contract portfolio that has a copula-based dependence structure with generalized hyperbolic marginals.
{"title":"A copula-based simulation model for supply portfolio risk","authors":"Halis Sak, Ç. Haksöz","doi":"10.21314/JOP.2011.093","DOIUrl":"https://doi.org/10.21314/JOP.2011.093","url":null,"abstract":"A copula-based simulation model for supply portfolio risk in the presence of dependent breaches of contracts is introduced in this paper. We demonstrate our method for a supply-chain contract portfolio of commodity metals traded at the London Metal Exchange (LME). The analysis of spot price data on six LME com- modity metals leads us to use a t-copula dependence structure with t-marginals and generalized hyperbolic marginals for the log returns. We also provide effi- cient simulation algorithms using importance sampling for the normal and t- copula dependence structure to quantify risk measures, supply-at-risk and condi- tional supply-at-risk. Numerical examples on a portfolio of six commodity metals demonstrate that our proposed method succeeds in decreasing the variance of the simulations. A numerical sensitivity analysis for the choice of the copula function is also provided. To the best of our knowledge, this is the first paper proposing efficient simulation algorithms on a supply-chain contract portfolio that has a copula-based dependence structure with generalized hyperbolic marginals.","PeriodicalId":54030,"journal":{"name":"Journal of Operational Risk","volume":"31 1","pages":"15-38"},"PeriodicalIF":0.5,"publicationDate":"2011-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87063961","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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