Journal of Operational Risk
ISSN:
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: 0.4
5-Year Impact Factor: 0.6
CiteScore: 0.8
Latest papers
Do bank complexities increase the risks? Insights from four Asian countries
Focussing on China, Malaysia, Pakistan and Qatar, the authors investigate how bank complexity impacts bank risk.
The role of banks’ digital transformation in operational risk management: evidence from China
The authors investigate the impact of banks' digital transformation on operational risk, finding that in most cases, this reduces operational risk,
Risk measures associated with insurance losses in Ghana
The authors investigate VaR and TVaR comprehensive motor insurance claims paid by an insurance company in Ghana and compare the estimates obtained by these risk measures.
The future of risk and insurability in the era of systemic disruption, unpredictability and artificial intelligence
The authors demonstrate the fragile nature of traditional risk management techniques in the face of frequent high-impact shocks and advocate for a new approach that treats disruption as systemic rather than episodic.
Enhancing organizational sustainability through human resource analytics: examining the moderating effect of organizational culture
Focussing on information-technology-based organizations, the authors investigate links between human resources analytics and organizational sustainability, finding HR analytics to enhance organizational sustainability.
Operational risk, capital regulation and model risk
The author proposes seven basic properties for operational risk modelling to form an operational risk management framework.
The robot-labeling phenomenon: robot-ready modern operational risk management
The author highlights misuse of the term "robot" in banking practice and the literature, proposes the robot-labelling phenomenon and recommends a shift in approaches to operational risk management to address challenges of the synthetic era.
Navigating risk horizons: a comprehensive bibliometric analysis of corporate risk management
The authors conduct a bibliometric analysis of 100 research papers to identify trends within corporate risk management.
Operational risk modeling under the loss distribution approach: estimation of operational risk capital by business line versus risk category
The authors apply the loss distribution approach to operational risk data, contributing to understandings of the composition and distribution of operational risk data across risk classes and the corresponding operational risk capital requirements
Operational risk and non-life insurers’ performance
The authors assess operational risk in the non-life-insurance sector, finding operational lapses and the cost–income ratio to have negative effects on premium growth and financial performance.
Operational risks: trends and challenges
The authors carry out a systematic literature review of operational risk research to determine the current state of operational risk research in financial institutions.
Determination of the fraction of losses and their probabilities by type of risk and business line from aggregate loss data
This paper proposes a novel means to derive the individual loss severities and the frequency of these losses per business line and risk type.
Unraveling Lebanon’s financial crisis: the path from promise to peril, delving into a risk strategist’s own experience
The author investigates the causes of Lebanon's financial crisis which began in 2019 and puts forward suggestions with which to restore trust and stability.
Cyber risk assessment model for information assets: a tailored approach for the financial and banking sector
The authors present a novel model risk assessment model designed specifically for cyber risks and information assets.
Artificial intelligence in crisis management: a bibliometric analysis
The authors carry out a bibliometric analysis of academic papers in the field of artificial intelligence applications in crisis management and propose potential new directions for researchers in this field.
A qualitative study of operational resilience in financial institutions
The authors analyze data from a qualitative survey of senior G-SIB employees to identify recommendations for organisations looking to improve their operational resilience.
How is risk culture conceptualized in organizations? The pan-industry risk culture (PIRC) model
This paper puts forward a pan-industry risk culture as a framework through which to proactively manage risk culture.
Natural language processing-based detection of systematic anomalies among the narratives of consumer complaints
The authors develop a means to detect nonmeritorious consumer complaints using natural language processing.
Do government audits raise the risk awareness of management? An investigation from the perspective of cost variability
The authors investigate the impact of government audits on state-owned enterprises, finding they increase cost variability in these enterprises.
Integrating internal and external loss data via an equivalence principle
The authors put forward a means address data scarcity in operational risk modelling by supplementing internal loss data with external loss data.
