Journal of Operational Risk
ISSN:
1744-6740 (print)
1755-2710 (online)
Editor-in-chief: Marcelo Cruz
About this journal
Of the main areas of risk management, operational risk has the shortest history, with the industry beginning to give it serious consideration only 25 years ago. In that time, the industry has made great strides in both the definition and quantification of operational risk. The Journal of Operational Risk has been publishing papers at the forefront of this development since its inception.
On the quantification side, significant progress has been made, with major banks disclosing their operational risk exposures on a yearly basis. For many financial institutions their operational risk exposure is higher than that of market and credit risks. One large operational risk event can be lethal to a financial firm. Operational risk is thus a key concern for the industry as well as for the regulators that supervise financial institutions.
On the definition side, the industry has recently introduced the concept of “Non-Financial Risk” encompassing not just the early definition of operational risk but other risks like strategic, people, cyber, IT, etc. A broader view of operational risk would also consider Enterprise Risk Management, Cyber Risk Management, Information Technology Risks, Data Quality Risks amongst others. The introduction of new technologies like machine learning, artificial intelligence alongside new quantification ideas makes operational risk an intriguing risk domain with a green field for development and implementation of new ideas and theories.
With that in mind, The Journal of Operational Risk welcomes papers on non-financial 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, e.g., 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 management;
- IT risk management (how systems errors/fails impact an organization and change their risk profile);
- Big data applications to non-financial risk;
- Artificial intelligence and machine learning applications to risk management;
- Qualitative analysis of non-financial risks.
Journal Metrics:
Journal Impact Factor: 0.645
5-Year Impact Factor: 0.488
CiteScore: 0.8
Latest papers
Maximum likelihood estimation error and operational value-at-risk stability
The aim of this paper is to systematically investigate the stability of operational value-at-risk (OpVaR) models when fitting heavy-tailed distributions to the relatively small sample sizes found in operational loss data.
An alternative approach for the operational risk assessment of a new product
The aim of this paper is to provide a new operational risk management framework to identify and mitigate the operational risk exposure arising from a new product.
Operational risk measurement: a loss distribution approach with segmented dependence
This paper proposes an approach, called the loss distribution approach with segmented dependence (LDA-SD), which can model the different dependencies of HFLI and LFHI losses in the framework of LDA.
A review of the state of the art in quantifying operational risk
In this paper, the authors provide a comprehensive review of the different approaches developed to model operational risk, specifically focusing on the actuarial approach.
Global perspectives on operational risk management and practice: a survey by the Institute of Operational Risk (IOR) and the Center for Financial Professionals (CeFPro)
This paper presents survey results which represent comprehensive perspectives on operational risk practice, obtained from practitioners in a wide range of countries and sectors.
Is operational risk regulation forward looking and sensitive to current risks?
This paper evaluates the operational risk capital requirements of large US banks to determine whether they are forward looking, sensitive to banks’ current exposures and designed to allow for risk mitigation.
Predictive fraud analytics: B-tests
In this paper, the authors look at B-tests: methods by which it is possible to identify internal fraud among employees and partners of the bank at an early stage.
Forward-looking and incentive-compatible operational risk capital framework
This paper proposes an alternative framework for setting banks’ operational risk capital, which allows for forward-looking assessments and limits gaming opportunities by relying on an incentive-compatible mechanism.
Modeling operational risk depending on covariates: an empirical investigation
In this paper, the authors apply a dynamic extreme value theory (EVT) model based on a nonhomogeneous Poisson process incorporating covariates to estimate frequency, severity and risk measures for operational risk.
Risk monitoring through better knowledge-based risk processes
The aim of this paper is to propose a model that describes the integration of knowledge-based risks (via the processes of knowledge-based risk identification, analysis, evaluation and education) and knowledge-based risk repositories to support risk…
Operational risk: a forgotten case study
This paper is a historical case study of the GAS scandal and is the first to analyze it from the perspective of operational risk.
Operational risk measurement beyond the loss distribution approach: an exposure-based methodology
In this paper, the authors present an alternative quantification technique, so-called exposure-based operational risk (EBOR) models, which aim to replace historical severity curves by measures of current exposures and use event frequencies based on…
Distortion risk measures for nonnegative multivariate risks
In this paper, the authors present a way to address multivariate distortion risk measures and give some examples of distortion functions and distributions where the final expression has a closed form.
An operational risk capital model based on the loss distribution approach
In this paper, the author constructs a capital model for operational risk based on the observation that operational losses can, under a certain dimensional transformation, converge into a single, universal distribution.
Modeling very large losses
In this paper, the author presents a simple probabilistic model for aggregating very large losses into a loss collection.
Bridging networks, systems and controls frameworks for cybersecurity curriculums and standards development
This paper proposes a risk management framework designed to facilitate the alignment, integration and streamlining of professional practice standards and computer science/cybersecurity educational curriculums by bridging NPNATFs, SNIFs and RMCPFs.
Tail dependence in small samples: from theory to practice
In this paper, the authors study tail dependence by defining the conditions required for all the methods used to perform and to quantify their efficiency and accuracy.
Shapley allocation, diversification and services in operational risk
In this paper, the authors propose a method of allocating operational risk regulatory capital using a closed-form Shapley method, applicable to a large number of business units (BUs).
Modeling catastrophic operational risk using a compound Neyman–Scott clustering model
In this paper, the authors discuss the hazard generated by OpRisk driven by natural and human-made disasters, and argue the position of the LDA as the most-fitted statistical approach to deal with it.
Standardized measurement approach extension to integrate insurance deduction into operational risk capital requirement
The SMA proposed in BCBS (2016) presents several issues: in particular, its two components are not sufficient to discriminate banking institutions by risk profile, thus penalizing the more virtuous ones. This paper describes a possible solution to extend…