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
Risk disclosures in annual reports: the role of nonfinancial companies listed on the Athens stock exchange
This study analyzes the risks disclosed by all nonfinancial companies listed on the Athens stock exchange by undertaking content analysis of their annual reports during the period 2005–11.
Nonhomogeneous bivariate compound Poisson process with short-term periodicity
This paper presents new results on the nonhomogeneous bivariate compound Poisson process with a short-term periodic intensity function.
Ex-intrusion corporate cyber risk: evidence from internet protocol networks
This study examines IP address footprints as a proxy for cyber risks in public firms.
Key impact deep dive (KIDD)
This paper proposes a KIDD (key impact deep dive) approach for assessing extreme risks based on assessing key impact types.
On modeling contagion in the formation of operational risk loss
This paper models an overall operational risk loss caused by the accumulation of intermediate losses incurred at each process via a mechanism of network contagion across distinct processes within the boundary of a bank.
An approach to simultaneously assess operational risk and maturity levels in information technology management
The aim of this paper is to investigate the operational risk and maturity level of IT in an anonymized financial institution, based on the American Productivity and Quality Center benchmark and control objectives for information and related technologies.
Risk governance, market competition and operational risk disclosure quality: a study of the ASEAN-5 banking sector
This paper investigates the impact of risk governance and market competition on banks' operational risk disclosure (ORD) quality (total and voluntary) in the Association of Southeast Asian Nations (ASEAN-5) banking sector
The economic cost of a fat finger mistake: a comparative case study from Samsung Securities’s ghost stock blunder
This paper quantifies the economic cost of Samsung Securities’s ghost stock blunder using the synthetic control method.
The impact of culture upon operational risk management guidelines in the banking sector of selected Asian countries
The central banks of different countries regulate ORM according to the specificities of their national banking industry. This paper tests the hypothesis that such regulatory openness results in legal texts that are highly influenced by the culture of the…
Measurement of operational risk regulatory capital in the banking sector: developed countries versus emerging markets
This paper addresses operational risk as a fundamental risk type faced by banks in emerging and developed economies.
Bank supervision: lessons from the post-2008 banking crisis
This paper considers the learning points from official third-party reports produced in the wake of supervisory failures that can be applied to the management of front-line bank supervisors.
Regulatory arbitrage in the use of insurance in the new standardized approach for operational risk capital
Basel’s new standardized approach (SA) for operational risk capital may allow for regulatory arbitrage through the use of insurance. Under the SA, banks will likely have an incentive to insure recurring losses. Such insurance can meaningfully reduce…
Critical variables in the implementation of a risk-based internal audit: a theoretical and empirical investigation of Greek companies
This paper investigates the critical variables for the implementation of RBIA in Greek companies and examines the relationship between the above variables and RBIA implementation using data collected by 105 internal auditors, external auditors, directors…
The spillover effect of the Bangladesh Bank cyber heist on banks’ cyber risk disclosures in Bangladesh
This study examines the spillover effect of that cyber heist on the cyber risk disclosures of the banking sector in Bangladesh.
Detection of financial fraud risk: implications for financial stability
This introduction to the Journal of Operational Risk special issue shines a light on the relationship between financial fraud risks and financial stability.
The strange case of the Jet Airways bankruptcy: a financial structure analysis
The authors investigate the financial structure of Jet Airways, with the aim of understanding whether financial turbulence for an airline company can constitute an antecedent for predicting the risk of bankruptcy.
Ten laws of operational risk
This paper sets out ten laws that govern the behavior of operational risk relating to the occurrence and detection/duration of events; the rapidity with which firms suffer losses; the lags in crystallization of losses; and internal and external drivers…
Quantification of regulatory capital for management of operational risk in banks: study from an emerging market economy
This paper studies the various methodologies used by an Indian bank in its operational risk management activities: these include loss database analysis, risk control self-assessment and key risk indicator (KRI) identification.
Evaluating cyclic risk propagation through an organization
Many large organizations have risk that propagates because of the dependencies between their various major organizational components. This paper addresses when cycles of dependencies exist in an organization or system of systems.
Does the source of information influence depositors’ withdrawal intentions during operational events?
The objective of this paper is to identify whether depositors’ intentions to withdraw funds during operational risk events differ based on the source of information.