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The purpose of this paper is to examine the determinants of operational losses in insurance companies.

By using most common estimates of frequency and severity of losses that affected business‐lines during 2009, the paper integrates a quantitative aspect that reflects the mode of organization in the insurance company. In this paper, it would be more appropriate to focus on the frequency and severity of losses estimated by insurers and which are related to each category of operational risk events that took place in 2009.

The paper finds that the frequency of operational losses is positively related to the Market Share (MARKSHARE) and the Rate of Geographic Location (RAGELOC). However, the occurrence of loss is negatively related to the Variety of Insurance Activities (VARIACT). The paper also found a decrease in the frequency of losses associated with a large number of employees. Therefore, there is a significant relationship between the Human Factor (HF) and the occurrence of operational losses. In terms of severity, the empirical study has shown that the probability of zero intensity of operational losses is negatively influenced by the Market Share (MARKSHARE) and the Rate of Geographic Location (RAGELOC). In the same framework, the Variety of Insurance Activities (VARIACT) has a negative effect on the probability of high operational loss severity.

Despite the absence of the quantitative data of operational risk, this article will discover a new research perspective to estimate the frequency and severity of operational losses in the insurance sector in Tunisia.

The problem in alleviating homeowner mortgage distress through refinance is how to achieve meaningful alleviation without prospectively harming the financier. The problem revolves around two parameters from real estate finance – the probability that the distress leads to foreclosure and resulting foreclosure loss severity for the financier if foreclosure does occur. Previous analysis focuses on reducing the probability that homeowner distress leads to foreclosure. By contrast, the purpose of this paper is to focus on reducing foreclosure loss severity.

The study develops a new intuitive formula for foreclosure loss severity to quantify its dependence on transaction costs. The study shows that foreclosure loss severity reduction is feasible by introducing a new refinancing instrument that lowers foreclosure transaction costs and applying property law to derive the structure of the refinancing instrument.

Foreclosure loss severity reduction can subsidize concessions on scheduled payments for homeowners with arbitrarily poor credit without prospective harm to the financier.

Quantification of mortgage distress relief is limited to distressed mortgages described by representative parameter values from various government studies.

For most distressed homeowners, payment and principal reductions could exceed those available from the recent government programs.

Implementation should significantly enlarge the pool of homeowners eligible for mortgage distress relief.

The mortgage refinance is qualitatively different from that available under existing government refinance programs because it is based on an arms-length exchange of property rights that makes market sense regardless of whether the refinancing results in subsequent homeowner default.

The purpose of this paper is to study the relationship between reporting a loss and changes in board quality. Low quality corporate governance is associated with adverse accounting outcomes and is characterised by the lack of non-executive and independent directors on the board. Changes in these board quality indicators in response to the reporting of a loss and conditioned by the severity of the loss are examined.

This study uses four years of board information spanning the report of an initial loss for companies listed on the UK stock exchange. An industry and size matched control sample is used in a difference-in-difference analysis to isolate the impact of the loss from underlying changes in board quality.

Overall the results indicate that more severe initial loss events precipitate improvements in board quality over and above the control sample as well as less severe loss events.

Although unambiguous, the reporting of a loss is only one measure of underperformance. Also the board quality indicators used in this study are two from several individual corporate governance variables and amalgamations used in the extent literature.

The findings demonstrate that the relationship between corporate governance and performance is endogenous and that the majority of any improvement in board quality actually anticipates the reporting of the loss. Any celebration of improvements in governance need to be tempered by an understanding of the precariousness of the firms at which these improvements are made.

This study contributes to a research stream that examines negative shocks, and losses in particular, as an event likely to precipitate firm-level changes in board quality, i.e. firms tend not to make improvements to board quality without the impetus to do so.

Cargo loss has been a major issue in logistics management. However, few studies have tackled the issue of cargo loss severity via business analytics. Hence, the purpose of this paper is to provide guidance about how to retrieve valuable information from logistics data and to develop cargo loss mitigation strategies for logistics risk management.

This study proposes a research design of business analytics to scrutinize the causes of cargo loss severity.

The empirical results of the decision tree analytics reveal that transit types, product categories, and shipping destinations are key factors behind cargo loss severity. Furthermore, strategies for cargo loss prevention were developed.

The proposed framework of cargo loss analytics provides a research foundation for logistics risk management.

Companies with logistics data can utilize the proposed business analytics to identify cargo loss factors, while companies without logistics data can employ the proposed cargo loss mitigation strategies in their logistics systems.

This pioneer empirical study scrutinizes the critical cargo loss issues of cargo damage, cargo theft, and cargo liability insurance through exploiting real cargo loss data.

Operational or event risk is not a new phenomenon for financial services companies. However, its measurement, as part of integrated risk management programs, has been the subject of recent focus. Property and casualty insurers have measured components of this risk class as part of the pricing and underwriting process. Although all financial services firms are exposed to direct and indirect (e.g., reputational) costs of operational risk events, few financial services firms actually measure “operational risk.” This article explores ways in which this may be done in practice.

This study aims to investigate hazards in theater venues on the performance day by combining operational risk theory with a service blueprint method.

Interviews and Delphi method are applied to find the hazards, then a survey and ANOVA are followed. The study explores a profile of hazards using data from theater venues in Taiwan and examines whether employee characteristics (i.e. professional tasks, experience and working location) affect risk perception.

The study suggests a new framework represented by a 5 (types of loss events) × 6 (service systems) matrix to check operational risks. The analyses indicate two types of hazards: risk perception about performance and operations by performers and crew (RPPOPC) and audience behaviors and safety (RPABS). RPPOPC is related to the core show, but not all employees possess high RPPOPC. Seniors have relatively low RPPOPC, and frontend house employees possess insufficient RPABS. Further, front house employees, seniors and those working in municipal cities show relatively high RPPOPC in high-loss situations.

Managers can use the analytic framework to effectively identify operational risks in the core show operations and audience service offerings. They can promote risk perception considering employee differences and loss severity. However, the framework does not discuss the cause-and-effect relationship. Incorporating a large amount of loss experience into a risk information system would help clarify this complex relationship.

This study contributes to hazard mitigation in the performing arts sector, both in the peripheral services for customers and in the core show services.

Given the continuing growth in both the complexity and severity of cyber risk, a fundamental rethink of cyber risk management has become an issue of paramount importance, particularly as insurance firms are now providing both cyber risk management services and cyber risk insurance coverage. In this study, we set out to provide analyses of the prevailing cyber risk levels in various industries using the “Chronology of Data Breaches” database and then go on to assess the overall benefits of cyber risk insurance coverage. Our results reveal that compared to other industries, insurance firms exhibit superior cyber risk management. Regardless of internal and external cyber risk, insurance companies retain the lowest cyber losses. We further provide evidence to show that cyber risk insurance policies alone cannot effectively cover the potentially extreme cyber risk losses for most industries. However, the situation can be improved by implementing cyber risk management services provided by insurance firms. Insurance firms may need to provide an efficient cyber risk management system to lower the frequency and severity of extreme events.

Amid increased size and complexity of the banking industry, operational risk has a greater potential to occur in more harmful ways than many other sources of risk. This paper seeks to provide a succinct overview of the current regulatory framework of operational risk under the New Basel Accord with a view to inform a critical debate about the influence of data collection, loss reporting, and model specification on the consistency of risk‐sensitive capital rules.

The paper's approach is to investigate the regulatory implications of varying characteristics of operational risk and different methods to identify operational risk exposure.

The findings reveal that effective operational risk measurement hinges on how the reporting of operational risk losses and the model sensitivity of quantitative methods affect the generation of consistent risk estimates.

The presented findings offer tractable recommendations for a more coherent and consistent regulation of operational risk.

This study proposes a novel method to improve the accuracy of overall equipment effectiveness (OEE) estimation in the metallurgical industry. This is achieved by modeling the frequency and severity of stoppage events as random variables.

An analysis of 80,000 datasets from a metal-mechanical firm (2020–2022) was performed using the loss distribution approach (LDA) and Monte Carlo simulation (MCS). The data were further adjusted with a product price index to account for inflation.

The variance analysis revealed supporting colleagues (59.8% of variance contribution), food breaks (29.8%) and refreshments (9.0%) as the events with the strongest influence on operating losses.

This study provides a more rigorous approach to operational risk management and OEE measurement in the metal-mechanical sector. The developed algorithm supports the establishment of risk management guidelines and facilitates targeted OEE improvement efforts.

This research introduces a novel OEE estimation method specifically for the metallurgical industry, utilizing LDA and MCS to improve accuracy compared to existing techniques.

Financial firms announcing large operational losses have empirically been shown to cause significant negative spillover effects in other non-announcing firms in case of the banking and insurance industry. The purpose of this paper is 1) to model such spillover effects in a network from a portfolio perspective and 2) to holistically assess operational risk, reputational risk and the risk of spillover effects, taking into account the dependencies between these risk types.

The authors propose different approaches to model spillover effects with different complexity, including stochasticity and influencing factors within the industry network. They then calibrate the model based on information from previous empirical literature.

The results emphasize that spillover effects can represent a considerable (non-diversifiable) risk, especially in portfolios, and that neglecting them may lead to a severe underestimation of the actual impact of single operational loss events.

This study is relevant not only for a firm’s risk management strategy but also for investors holding a portfolio of firms potentially subject to spillover effects.